Mathematics : Publications since January 2023
List all publications in the database. :chronological alphabetical by author listing:
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@article{fds376060,
Author = {Chew, J and Hirn, M and Krishnaswamy, S and Needell, D and Perlmutter,
M and Steach, H and Viswanath, S and Wu, HT},
Title = {Geometric scattering on measure spaces},
Journal = {Applied and Computational Harmonic Analysis},
Volume = {70},
Year = {2024},
Month = {May},
url = {http://dx.doi.org/10.1016/j.acha.2024.101635},
Abstract = {The scattering transform is a multilayered, wavelet-based
transform initially introduced as a mathematical model of
convolutional neural networks (CNNs) that has played a
foundational role in our understanding of these networks'
stability and invariance properties. In subsequent years,
there has been widespread interest in extending the success
of CNNs to data sets with non-Euclidean structure, such as
graphs and manifolds, leading to the emerging field of
geometric deep learning. In order to improve our
understanding of the architectures used in this new field,
several papers have proposed generalizations of the
scattering transform for non-Euclidean data structures such
as undirected graphs and compact Riemannian manifolds
without boundary. Analogous to the original scattering
transform, these works prove that these variants of the
scattering transform have desirable stability and invariance
properties and aim to improve our understanding of the
neural networks used in geometric deep learning. In this
paper, we introduce a general, unified model for geometric
scattering on measure spaces. Our proposed framework
includes previous work on compact Riemannian manifolds
without boundary and undirected graphs as special cases but
also applies to more general settings such as directed
graphs, signed graphs, and manifolds with boundary. We
propose a new criterion that identifies to which groups a
useful representation should be invariant and show that this
criterion is sufficient to guarantee that the scattering
transform has desirable stability and invariance properties.
Additionally, we consider finite measure spaces that are
obtained from randomly sampling an unknown manifold. We
propose two methods for constructing a data-driven graph on
which the associated graph scattering transform approximates
the scattering transform on the underlying manifold.
Moreover, we use a diffusion-maps based approach to prove
quantitative estimates on the rate of convergence of one of
these approximations as the number of sample points tends to
infinity. Lastly, we showcase the utility of our method on
spherical images, a directed graph stochastic block model,
and on high-dimensional single-cell data.},
Doi = {10.1016/j.acha.2024.101635},
Key = {fds376060}
}
@article{fds376241,
Author = {Ji, H and Witelski, TP},
Title = {Coarsening of Thin Films with Weak Condensation},
Journal = {SIAM Journal on Applied Mathematics},
Volume = {84},
Number = {2},
Pages = {362-386},
Publisher = {Society for Industrial & Applied Mathematics
(SIAM)},
Year = {2024},
Month = {April},
url = {http://dx.doi.org/10.1137/23m1559336},
Doi = {10.1137/23m1559336},
Key = {fds376241}
}
@article{fds374862,
Author = {Feng, Y and Li, L and Liu, JG and Xu, X},
Title = {EXISTENCE OF WEAK SOLUTIONS TO p-NAVIER-STOKES
EQUATIONS},
Journal = {Discrete and Continuous Dynamical Systems - Series
B},
Volume = {29},
Number = {4},
Pages = {1868-1890},
Publisher = {American Institute of Mathematical Sciences
(AIMS)},
Year = {2024},
Month = {April},
url = {http://dx.doi.org/10.3934/dcdsb.2023159},
Abstract = {We study the existence of weak solutions to the
p-Navier-Stokes equations with a symmetric p-Laplacian on
bounded domains. We construct a particular Schauder basis in
W01, p(Ω) with divergence free constraint and prove
existence of weak solutions using the Galerkin approximation
via this basis. Meanwhile, in the proof, we establish a
chain rule for the Lp integral of the weak solutions, which
fixes a gap in our previous work. The equality of energy
dissipation is also established for the weak solutions
considered.},
Doi = {10.3934/dcdsb.2023159},
Key = {fds374862}
}
@article{fds376686,
Author = {Blekherman, G and Raymond, A and Wei, F},
Title = {Undecidability of polynomial inequalities in weighted graph
homomorphism densities},
Journal = {Forum of Mathematics, Sigma},
Volume = {12},
Year = {2024},
Month = {March},
url = {http://dx.doi.org/10.1017/fms.2024.19},
Abstract = {Many problems and conjectures in extremal combinatorics
concern polynomial inequalities between homomorphism
densities of graphs where we allow edges to have real
weights. Using the theory of graph limits, we can
equivalently evaluate polynomial expressions in homomorphism
densities on kernels W, that is, symmetric, bounded and
measurable functions W from. In 2011, Hatami and Norin
proved a fundamental result that it is undecidable to
determine the validity of polynomial inequalities in
homomorphism densities for graphons (i.e., the case where
the range of W is, which corresponds to unweighted graphs
or, equivalently, to graphs with edge weights between and).
The corresponding problem for more general sets of kernels,
for example, for all kernels or for kernels with range,
remains open. For any 0$ ]]>, we show undecidability of
polynomial inequalities for any set of kernels which
contains all kernels with range. This result also answers a
question raised by Lovász about finding computationally
effective certificates for the validity of homomorphism
density inequalities in kernels.},
Doi = {10.1017/fms.2024.19},
Key = {fds376686}
}
@article{fds376265,
Author = {Chidyagwai, SG and Kaplan, MS and Jensen, CW and Chen, JS and Chamberlain, RC and Hill, KD and Barker, PCA and Slesnick, TC and Randles, A},
Title = {Surgical Modulation of Pulmonary Artery Shear Stress: A
Patient-Specific CFD Analysis of the Norwood
Procedure.},
Journal = {Cardiovasc Eng Technol},
Year = {2024},
Month = {March},
url = {http://dx.doi.org/10.1007/s13239-024-00724-3},
Abstract = {PURPOSR: This study created 3D CFD models of the Norwood
procedure for hypoplastic left heart syndrome (HLHS) using
standard angiography and echocardiogram data to investigate
the impact of shunt characteristics on pulmonary artery (PA)
hemodynamics. Leveraging routine clinical data offers
advantages such as availability and cost-effectiveness
without subjecting patients to additional invasive
procedures. METHODS: Patient-specific geometries of the
intrathoracic arteries of two Norwood patients were
generated from biplane cineangiograms. "Virtual surgery" was
then performed to simulate the hemodynamics of alternative
PA shunt configurations, including shunt type (modified
Blalock-Thomas-Taussig shunt (mBTTS) vs. right
ventricle-to-pulmonary artery shunt (RVPAS)), shunt
diameter, and pulmonary artery anastomosis angle. Left-right
pulmonary flow differential, Qp/Qs, time-averaged wall shear
stress (TAWSS), and oscillatory shear index (OSI) were
evaluated. RESULTS: There was strong agreement between
clinically measured data and CFD model output throughout the
patient-specific models. Geometries with a RVPAS tended
toward more balanced left-right pulmonary flow, lower Qp/Qs,
and greater TAWSS and OSI than models with a mBTTS. For both
shunt types, larger shunts resulted in a higher Qp/Qs and
higher TAWSS, with minimal effect on OSI. Low TAWSS areas
correlated with regions of low flow and changing the
PA-shunt anastomosis angle to face toward low TAWSS regions
increased TAWSS. CONCLUSION: Excellent correlation between
clinically measured and CFD model data shows that 3D CFD
models of HLHS Norwood can be developed using standard
angiography and echocardiographic data. The CFD analysis
also revealed consistent changes in PA TAWSS, flow
differential, and OSI as a function of shunt
characteristics.},
Doi = {10.1007/s13239-024-00724-3},
Key = {fds376265}
}
@article{fds372258,
Author = {Kirveslahti, H and Mukherjee, S},
Title = {Representing fields without correspondences: the lifted
Euler characteristic transform},
Journal = {Journal of Applied and Computational Topology},
Volume = {8},
Number = {1},
Pages = {1-34},
Year = {2024},
Month = {March},
url = {http://dx.doi.org/10.1007/s41468-023-00133-w},
Abstract = {Topological transforms have been very useful in statistical
analysis of shapes or surfaces without restrictions that the
shapes are diffeomorphic and requiring the estimation of
correspondence maps. In this paper we introduce two
topological transforms that generalize from shapes to
fields, f:R3→R. Both transforms take a field and associate
to each direction v∈Sd-1 a summary obtained by scanning
the field in the direction v. The transforms we introduce
are of interest for both applications as well as their
theoretical properties. The topological transforms for
shapes are based on an Euler calculus on sets. A key insight
in this paper is that via a lifting argument one can develop
an Euler calculus on real valued functions from the standard
Euler calculus on sets, this idea is at the heart of the two
transforms we introduce. We prove the transforms are
injective maps. We show for particular moduli spaces of
functions we can upper bound the number of directions needed
determine any particular function.},
Doi = {10.1007/s41468-023-00133-w},
Key = {fds372258}
}
@article{fds374249,
Author = {Chung, YM and Huang, WK and Wu, HT},
Title = {Topological data analysis assisted automated sleep stage
scoring using airflow signals},
Journal = {Biomedical Signal Processing and Control},
Volume = {89},
Pages = {105760-105760},
Publisher = {Elsevier BV},
Year = {2024},
Month = {March},
url = {http://dx.doi.org/10.1016/j.bspc.2023.105760},
Abstract = {Objective: Breathing pattern variability (BPV), as a
universal physiological feature, encodes rich health
information. We aim to show that, a high-quality automatic
sleep stage scoring based on a proper quantification of BPV
extracting from the single airflow signal can be achieved.
Methods: Topological data analysis (TDA) is applied to
characterize BPV from the intrinsically nonstationary
airflow signal. The extracted features from TDA are utilized
to train an automatic sleep stage scoring model using the
XGBoost learner. Additionally, the noise and artifacts that
are typically present in the air flow signal are leveraged
to improve the performance of the trained system. To
evaluate the effectiveness of the proposed approach, a
state-of-the-art method is implemented for comparison
purposes. Results: A leave-one-subject-out cross-validation
was conducted on a dataset comprising 30 whole-night
polysomnogram signals with standard annotations. The results
show that the proposed features outperform those considered
in the state-of-the-art work in terms of overall accuracy
(78.8% ± 8.7% vs. 75.0% ± 9.6%) and Cohen's kappa (0.56 ±
0.15 vs. 0.50 ± 0.15) for automatically scoring wake, rapid
eye movement (REM), and non-REM (NREM) stages. An external
validation conducted on a dataset comprising 80 whole-night
polysomnogram signals with standard annotations shows a
result of overall accuracy 74.1%±11.6% and Cohen's kappa
0.42±0.15, which again outperforms the state-of-the-art
work. Furthermore, the analysis of feature importance
reveals that the TDA features provide complementary
information to the traditional features commonly used in the
literature, and the respiratory quality index is identified
as an essential component. Conclusion: The proposed
TDA-assisted automatic annotation system can accurately
distinguish wake, REM and NREM from the airflow signal.
Significance: The utilization of a single air flow channel
and the universality of BPV suggest the potential of
TDA-assisted signal processing in addressing various
biomedical signals and homecare issues beyond sleep stage
annotation.},
Doi = {10.1016/j.bspc.2023.105760},
Key = {fds374249}
}
@article{fds375271,
Author = {Liu, T-C and Chen, Y-C and Chen, P-L and Tu, P-H and Yeh, C-H and Yeap,
M-C and Wu, Y-H and Chen, C-C and Wu, H-T},
Title = {Removal of electrical stimulus artifact in local field
potential recorded from subthalamic nucleus by using
manifold denoising.},
Journal = {Journal of neuroscience methods},
Volume = {403},
Pages = {110038},
Year = {2024},
Month = {March},
url = {http://dx.doi.org/10.1016/j.jneumeth.2023.110038},
Abstract = {<h4>Background</h4>Deep brain stimulation (DBS) is an
effective treatment for movement disorders such as
Parkinson's disease (PD). However, local field potentials
(LFPs) recorded through lead externalization during
high-frequency stimulation (HFS) are contaminated by
stimulus artifacts, which require to be removed before
further analysis.<h4>New method</h4>In this study, a novel
stimulus artifact removal algorithm based on manifold
denoising, termed Shrinkage and Manifold-based Artifact
Removal using Template Adaptation (SMARTA), was proposed to
remove artifacts by deriving a template for each stimulus
artifact and subtracting it from the signal. Under a
low-dimensional manifold assumption, a matrix denoising
technique called optimal shrinkage was applied to design a
similarity metric such that the template for stimulus
artifacts could be accurately recovered.<h4>Result</h4>SMARTA
was evaluated using semirealistic signals, which were the
combination of semirealistic stimulus artifacts recorded in
an agar brain model and LFPs of PD patients with no
stimulation, and realistic LFP signals recorded in patients
with PD during HFS. The results indicated that SMARTA
removes stimulus artifacts with a modest distortion in LFP
estimates.<h4>Comparison with existing methods</h4>SMARTA
was compared with moving-average subtraction,
sample-and-interpolate technique, and Hampel
filtering.<h4>Conclusion</h4>The proposed SMARTA algorithm
helps the exploration of the neurophysiological mechanisms
of DBS effects.},
Doi = {10.1016/j.jneumeth.2023.110038},
Key = {fds375271}
}
@article{fds375222,
Author = {Ding, X and Wu, HT},
Title = {How do kernel-based sensor fusion algorithms behave under
high-dimensional noise?},
Journal = {Information and Inference},
Volume = {13},
Number = {1},
Publisher = {Oxford University Press (OUP)},
Year = {2024},
Month = {March},
url = {http://dx.doi.org/10.1093/imaiai/iaad051},
Abstract = {We study the behavior of two kernel based sensor fusion
algorithms, nonparametric canonical correlation analysis
(NCCA) and alternating diffusion (AD), under the nonnull
setting that the clean datasets collected from two sensors
are modeled by a common low-dimensional manifold embedded in
a high-dimensional Euclidean space and the datasets are
corrupted by high-dimensional noise. We establish the
asymptotic limits and convergence rates for the eigenvalues
of the associated kernel matrices assuming that the sample
dimension and sample size are comparably large, where NCCA
and AD are conducted using the Gaussian kernel. It turns out
that both the asymptotic limits and convergence rates depend
on the signal-to-noise ratio (SNR) of each sensor and
selected bandwidths. On one hand, we show that if NCCA and
AD are directly applied to the noisy point clouds without
any sanity check, it may generate artificial information
that misleads scientists' interpretation. On the other hand,
we prove that if the bandwidths are selected adequately,
both NCCA and AD can be made robust to high-dimensional
noise when the SNRs are relatively large.},
Doi = {10.1093/imaiai/iaad051},
Key = {fds375222}
}
@article{fds376235,
Author = {Ciocanel, M-V and Ding, L and Mastromatteo, L and Reichheld, S and Cabral, S and Mowry, K and Sandstede, B},
Title = {Parameter Identifiability in PDE Models of Fluorescence
Recovery After Photobleaching.},
Journal = {Bulletin of mathematical biology},
Volume = {86},
Number = {4},
Pages = {36},
Year = {2024},
Month = {March},
url = {http://dx.doi.org/10.1007/s11538-024-01266-4},
Abstract = {Identifying unique parameters for mathematical models
describing biological data can be challenging and often
impossible. Parameter identifiability for partial
differential equations models in cell biology is especially
difficult given that many established in vivo measurements
of protein dynamics average out the spatial dimensions.
Here, we are motivated by recent experiments on the binding
dynamics of the RNA-binding protein PTBP3 in RNP granules of
frog oocytes based on fluorescence recovery after
photobleaching (FRAP) measurements. FRAP is a widely-used
experimental technique for probing protein dynamics in
living cells, and is often modeled using simple
reaction-diffusion models of the protein dynamics. We show
that current methods of structural and practical parameter
identifiability provide limited insights into
identifiability of kinetic parameters for these PDE models
and spatially-averaged FRAP data. We thus propose a pipeline
for assessing parameter identifiability and for learning
parameter combinations based on re-parametrization and
profile likelihoods analysis. We show that this method is
able to recover parameter combinations for synthetic FRAP
datasets and investigate its application to real
experimental data.},
Doi = {10.1007/s11538-024-01266-4},
Key = {fds376235}
}
@article{fds372447,
Author = {YU, J and LAI, R and LI, W and OSHER, S},
Title = {A FAST PROXIMAL GRADIENT METHOD AND CONVERGENCE ANALYSIS FOR
DYNAMIC MEAN FIELD PLANNING},
Journal = {Mathematics of Computation},
Volume = {93},
Number = {346},
Pages = {603-642},
Publisher = {American Mathematical Society (AMS)},
Year = {2024},
Month = {March},
url = {http://dx.doi.org/10.1090/mcom/3879},
Abstract = {In this paper, we propose an efficient and flexible
algorithm to solve dynamic mean-field planning problems
based on an accelerated proximal gradient method. Besides an
easy-to-implement gradient descent step in this algorithm, a
crucial projection step becomes solving an elliptic equation
whose solution can be obtained by conventional methods
efficiently. By induction on iterations used in the
algorithm, we theoretically show that the proposed discrete
solution converges to the underlying continuous solution as
the grid becomes finer. Furthermore, we generalize our
algorithm to meanfield game problems and accelerate it using
multilevel and multigrid strategies. We conduct
comprehensive numerical experiments to confirm the
convergence analysis of the proposed algorithm, to show its
efficiency and mass preservation property by comparing it
with state-of-the-art methods, and to illustrate its
flexibility for handling various mean-field variational
problems.},
Doi = {10.1090/mcom/3879},
Key = {fds372447}
}
@article{fds375300,
Author = {Mémoli, F and Stefanou, A and Zhou, L},
Title = {Persistent cup product structures and related
invariants},
Journal = {Journal of Applied and Computational Topology},
Volume = {8},
Number = {1},
Pages = {93-148},
Publisher = {Springer Science and Business Media LLC},
Year = {2024},
Month = {March},
url = {http://dx.doi.org/10.1007/s41468-023-00138-5},
Abstract = {<jats:title>Abstract</jats:title><jats:p>One-dimensional
persistent homology is arguably the most important and
heavily used computational tool in topological data
analysis. Additional information can be extracted from
datasets by studying multi-dimensional persistence modules
and by utilizing cohomological ideas, e.g. the
cohomological cup product. In this work, given a single
parameter filtration, we investigate a certain 2-dimensional
persistence module structure associated with persistent
cohomology, where one parameter is the cup-length
<jats:inline-formula><jats:alternatives><jats:tex-math>$$\ell
\ge 0$$</jats:tex-math>?? <mml:mrow> <mml:mi>ℓ</mml:mi>
<mml:mo>≥</mml:mo> <mml:mn>0</mml:mn> </mml:mrow>
</mml:math></jats:alternatives></jats:inline-formula> and
the other is the filtration parameter. This new persistence
structure, called the <jats:italic>persistent cup
module</jats:italic>, is induced by the cohomological cup
product and adapted to the persistence setting. Furthermore,
we show that this persistence structure is stable. By fixing
the cup-length parameter <jats:inline-formula><jats:alternatives><jats:tex-math>$$\ell
$$</jats:tex-math>?? <mml:mi>ℓ</mml:mi>
</mml:math></jats:alternatives></jats:inline-formula>, we
obtain a 1-dimensional persistence module, called the
persistent <jats:inline-formula><jats:alternatives><jats:tex-math>$$\ell
$$</jats:tex-math>?? <mml:mi>ℓ</mml:mi>
</mml:math></jats:alternatives></jats:inline-formula>-cup
module, and again show it is stable in the interleaving
distance sense, and study their associated generalized
persistence diagrams. In addition, we consider a generalized
notion of a <jats:italic>persistent invariant</jats:italic>,
which extends both the <jats:italic>rank
invariant</jats:italic> (also referred to as
<jats:italic>persistent Betti number</jats:italic>),
Puuska’s rank invariant induced by epi-mono-preserving
invariants of abelian categories, and the recently-defined
<jats:italic>persistent cup-length invariant</jats:italic>,
and we establish their stability. This generalized notion of
persistent invariant also enables us to lift the
Lyusternik-Schnirelmann (LS) category of topological spaces
to a novel stable persistent invariant of filtrations,
called the <jats:italic>persistent LS-category
invariant</jats:italic>.</jats:p>},
Doi = {10.1007/s41468-023-00138-5},
Key = {fds375300}
}
@article{fds372954,
Author = {Agarwal, PK and Katz, MJ and Sharir, M},
Title = {On reverse shortest paths in geometric proximity
graphs},
Journal = {Computational Geometry: Theory and Applications},
Volume = {117},
Year = {2024},
Month = {February},
url = {http://dx.doi.org/10.1016/j.comgeo.2023.102053},
Abstract = {Let S be a set of n geometric objects of constant complexity
(e.g., points, line segments, disks, ellipses) in R2, and
let ϱ:S×S→R≥0 be a distance function on S. For a
parameter r≥0, we define the proximity graph G(r)=(S,E)
where E={(e1,e2)∈S×S|e1≠e2,ϱ(e1,e2)≤r}. Given S,
s,t∈S, and an integer k≥1, the reverse-shortest-path
(RSP) problem asks for computing the smallest value r⁎≥0
such that G(r⁎) contains a path from s to t of length at
most k. In this paper we present a general randomized
technique that solves the RSP problem efficiently for a
large family of geometric objects and distance functions.
Using standard, and sometimes more involved, semi-algebraic
range-searching techniques, we first give an efficient
algorithm for the decision problem, namely, given a value
r≥0, determine whether G(r) contains a path from s to t of
length at most k. Next, we adapt our decision algorithm and
combine it with a random-sampling method to compute r⁎, by
efficiently performing a binary search over an implicit set
of O(n2) candidate ‘critical’ values that contains r⁎.
We illustrate the versatility of our general technique by
applying it to a variety of geometric proximity graphs. For
example, we obtain (i) an O⁎(n4/3) expected-time
randomized algorithm (where O⁎(⋅) hides polylog(n)
factors) for the case where S is a set of (possibly
intersecting) line segments in R2 and ϱ(e1,e2)=minx∈e1,y∈e2‖x−y‖
(where ‖⋅‖ is the Euclidean distance), and (ii) an
O⁎(n+m4/3) expected-time randomized algorithm for the case
where S is a set of m points lying on an x-monotone
polygonal chain T with n vertices, and ϱ(p,q), for p,q∈S,
is the smallest value h such that the points p′:=p+(0,h)
and q′:=q+(0,h) are visible to each other, i.e., all
points on the segment p′q′ lie above or on the polygonal
chain T.},
Doi = {10.1016/j.comgeo.2023.102053},
Key = {fds372954}
}
@article{fds376258,
Author = {Huang, J and Morsomme, R and Dunson, D and Xu, J},
Title = {Detecting changes in the transmission rate of a stochastic
epidemic model.},
Journal = {Statistics in medicine},
Year = {2024},
Month = {February},
url = {http://dx.doi.org/10.1002/sim.10050},
Abstract = {Throughout the course of an epidemic, the rate at which
disease spreads varies with behavioral changes, the
emergence of new disease variants, and the introduction of
mitigation policies. Estimating such changes in transmission
rates can help us better model and predict the dynamics of
an epidemic, and provide insight into the efficacy of
control and intervention strategies. We present a method for
likelihood-based estimation of parameters in the stochastic
susceptible-infected-removed model under a
time-inhomogeneous transmission rate comprised of piecewise
constant components. In doing so, our method simultaneously
learns change points in the transmission rate via a Markov
chain Monte Carlo algorithm. The method targets the exact
model posterior in a difficult missing data setting given
only partially observed case counts over time. We validate
performance on simulated data before applying our approach
to data from an Ebola outbreak in Western Africa and
COVID-19 outbreak on a university campus.},
Doi = {10.1002/sim.10050},
Key = {fds376258}
}
@article{fds376051,
Author = {Aquino, W and Rouse, J and Bonnet, M},
Title = {Active design of diffuse acoustic fields in
enclosures.},
Journal = {The Journal of the Acoustical Society of
America},
Volume = {155},
Number = {2},
Pages = {1297-1307},
Year = {2024},
Month = {February},
url = {http://dx.doi.org/10.1121/10.0024770},
Abstract = {This paper presents a numerical framework for designing
diffuse fields in rooms of any shape and size, driven at
arbitrary frequencies. That is, we aim at overcoming the
Schroeder frequency limit for generating diffuse fields in
an enclosed space. We formulate the problem as a Tikhonov
regularized inverse problem and propose a low-rank
approximation of the spatial correlation that results in
significant computational gains. Our approximation is
applicable to arbitrary sets of target points and allows us
to produce an optimal design at a computational cost that
grows only linearly with the (potentially large) number of
target points. We demonstrate the feasibility of our
approach through numerical examples where we approximate
diffuse fields at frequencies well below the Schroeder
limit.},
Doi = {10.1121/10.0024770},
Key = {fds376051}
}
@article{fds374395,
Author = {Li, X and Pura, J and Allen, A and Owzar, K and Lu, J and Harms, M and Xie,
J},
Title = {DYNATE: Localizing rare-variant association regions via
multiple testing embedded in an aggregation
tree.},
Journal = {Genet Epidemiol},
Volume = {48},
Number = {1},
Pages = {42-55},
Year = {2024},
Month = {February},
url = {http://dx.doi.org/10.1002/gepi.22542},
Abstract = {Rare-variants (RVs) genetic association studies enable
researchers to uncover the variation in phenotypic traits
left unexplained by common variation. Traditional
single-variant analysis lacks power; thus, researchers have
developed various methods to aggregate the effects of RVs
across genomic regions to study their collective impact.
Some existing methods utilize a static delineation of
genomic regions, often resulting in suboptimal effect
aggregation, as neutral subregions within the test region
will result in an attenuation of signal. Other methods use
varying windows to search for signals but often result in
long regions containing many neutral RVs. To pinpoint short
genomic regions enriched for disease-associated RVs, we
developed a novel method, DYNamic Aggregation TEsting
(DYNATE). DYNATE dynamically and hierarchically aggregates
smaller genomic regions into larger ones and performs
multiple testing for disease associations with a controlled
weighted false discovery rate. DYNATE's main advantage lies
in its strong ability to identify short genomic regions
highly enriched for disease-associated RVs. Extensive
numerical simulations demonstrate the superior performance
of DYNATE under various scenarios compared with existing
methods. We applied DYNATE to an amyotrophic lateral
sclerosis study and identified a new gene, EPG5, harboring
possibly pathogenic mutations.},
Doi = {10.1002/gepi.22542},
Key = {fds374395}
}
@article{fds375267,
Author = {Gressman, PT and Pierce, LB and Roos, J and Yung,
PL},
Title = {A NEW TYPE OF SUPERORTHOGONALITY},
Journal = {Proceedings of the American Mathematical
Society},
Volume = {152},
Number = {2},
Pages = {665-675},
Year = {2024},
Month = {February},
url = {http://dx.doi.org/10.1090/proc/16631},
Abstract = {We provide a simple criterion on a family of functions that
implies a square function estimate on Lp for every even
integer p ≥ 2. This defines a new type of
superorthogonality that is verified by checking a less
restrictive criterion than any other type of
superorthogonality that is currently known.},
Doi = {10.1090/proc/16631},
Key = {fds375267}
}
@article{fds373972,
Author = {Chiu, N-T and Chuang, B and Anakmeteeprugsa, S and Shelley, KH and Alian, AA and Wu, H-T},
Title = {Signal quality assessment of peripheral venous
pressure.},
Journal = {Journal of clinical monitoring and computing},
Volume = {38},
Number = {1},
Pages = {101-112},
Year = {2024},
Month = {February},
url = {http://dx.doi.org/10.1007/s10877-023-01071-9},
Abstract = {Develop a signal quality index (SQI) for the widely
available peripheral venous pressure waveform (PVP). We
focus on the quality of the cardiac component in PVP. We
model PVP by the adaptive non-harmonic model. When the
cardiac component in PVP is stronger, the PVP is defined to
have a higher quality. This signal quality is quantified by
applying the synchrosqueezing transform to decompose the
cardiac component out of PVP, and the SQI is defined as a
value between 0 and 1. A database collected during the lower
body negative pressure experiment is utilized to validate
the developed SQI. All signals are labeled into categories
of low and high qualities by experts. A support vector
machine (SVM) learning model is trained for practical
purpose. The developed signal quality index coincide with
human experts' labels with the area under the curve 0.95. In
a leave-one-subject-out cross validation (LOSOCV), the SQI
achieves accuracy 0.89 and F1 0.88, which is consistently
higher than other commonly used signal qualities, including
entropy, power and mean venous pressure. The trained SVM
model trained with SQI, entropy, power and mean venous
pressure could achieve an accuracy 0.92 and F1 0.91 under
LOSOCV. An exterior validation of SQI achieves accuracy 0.87
and F1 0.92; an exterior validation of the SVM model
achieves accuracy 0.95 and F1 0.96. The developed SQI has a
convincing potential to help identify high quality PVP
segments for further hemodynamic study. This is the first
work aiming to quantify the signal quality of the widely
applied PVP waveform.},
Doi = {10.1007/s10877-023-01071-9},
Key = {fds373972}
}
@article{fds374250,
Author = {Li, X and Pura, J and Allen, A and Owzar, K and Lu, J and Harms, M and Xie,
J},
Title = {DYNATE: Localizing rare-variant association regions via
multiple testing embedded in an aggregation
tree.},
Journal = {Genet Epidemiol},
Volume = {48},
Number = {1},
Pages = {42-55},
Year = {2024},
Month = {February},
url = {http://dx.doi.org/10.1002/gepi.22542},
Abstract = {Rare-variants (RVs) genetic association studies enable
researchers to uncover the variation in phenotypic traits
left unexplained by common variation. Traditional
single-variant analysis lacks power; thus, researchers have
developed various methods to aggregate the effects of RVs
across genomic regions to study their collective impact.
Some existing methods utilize a static delineation of
genomic regions, often resulting in suboptimal effect
aggregation, as neutral subregions within the test region
will result in an attenuation of signal. Other methods use
varying windows to search for signals but often result in
long regions containing many neutral RVs. To pinpoint short
genomic regions enriched for disease-associated RVs, we
developed a novel method, DYNamic Aggregation TEsting
(DYNATE). DYNATE dynamically and hierarchically aggregates
smaller genomic regions into larger ones and performs
multiple testing for disease associations with a controlled
weighted false discovery rate. DYNATE's main advantage lies
in its strong ability to identify short genomic regions
highly enriched for disease-associated RVs. Extensive
numerical simulations demonstrate the superior performance
of DYNATE under various scenarios compared with existing
methods. We applied DYNATE to an amyotrophic lateral
sclerosis study and identified a new gene, EPG5, harboring
possibly pathogenic mutations.},
Doi = {10.1002/gepi.22542},
Key = {fds374250}
}
@article{fds375372,
Author = {Bryant, R},
Title = {The generality of closed G_2 solitons},
Journal = {Pure and Applied Mathematics Quarterly},
Volume = {19},
Number = {6},
Pages = {2827-2840},
Publisher = {International Press},
Editor = {Cheng, S-Y and Lima-Filho, P and Yau, SS-T and Yau,
S-T},
Year = {2024},
Month = {January},
Abstract = {The local generality of the space of solitons for the
Laplacian flow of closed G2-structures is analyzed, and it
is shown that the germs of such structures depend, up to
diffeomorphism, on 16 functions of 6 variables (in the sense
of É. Cartan). The method is to construct a natural
exterior differential system whose integral manifolds
describe such solitons and to show that it is involutive in
Cartan’s sense, so that Cartan-Kähler theory can be
applied. Meanwhile, it turns out that, for the more special
case of gradient solitons, the natural exterior differential
system is not involutive, and the generality of these
structures remains a mystery.},
Key = {fds375372}
}
@article{fds375373,
Author = {Bryant, R and Cheeger, J and Lima-Filho, P and Rosenberg, J and White,
B},
Title = {The mathematical work of H. Blaine Lawson,
Jr.},
Journal = {Pure and Applied Mathematics Quarterly},
Volume = {19},
Number = {6},
Pages = {2627-2662},
Publisher = {International Press},
Year = {2024},
Month = {January},
Key = {fds375373}
}
@article{fds375395,
Author = {Stevens, JB and Riley, BA and Je, J and Gao, Y and Wang, C and Mowery, YM and Brizel, DM and Yin, F-F and Liu, J-G and Lafata, KJ},
Title = {Radiomics on spatial-temporal manifolds via Fokker-Planck
dynamics.},
Journal = {Med Phys},
Year = {2024},
Month = {January},
url = {http://dx.doi.org/10.1002/mp.16905},
Abstract = {BACKGROUND: Delta radiomics is a high-throughput
computational technique used to describe quantitative
changes in serial, time-series imaging by considering the
relative change in radiomic features of images extracted at
two distinct time points. Recent work has demonstrated a
lack of prognostic signal of radiomic features extracted
using this technique. We hypothesize that this lack of
signal is due to the fundamental assumptions made when
extracting features via delta radiomics, and that other
methods should be investigated. PURPOSE: The purpose of this
work was to show a proof-of-concept of a new radiomics
paradigm for sparse, time-series imaging data, where
features are extracted from a spatial-temporal manifold
modeling the time evolution between images, and to assess
the prognostic value on patients with oropharyngeal cancer
(OPC). METHODS: To accomplish this, we developed an
algorithm to mathematically describe the relationship
between two images acquired at time t = 0 $t = 0$ and t > 0
$t > 0$ . These images serve as boundary conditions of a
partial differential equation describing the transition from
one image to the other. To solve this equation, we propagate
the position and momentum of each voxel according to
Fokker-Planck dynamics (i.e., a technique common in
statistical mechanics). This transformation is driven by an
underlying potential force uniquely determined by the
equilibrium image. The solution generates a spatial-temporal
manifold (3 spatial dimensions + time) from which we define
dynamic radiomic features. First, our approach was
numerically verified by stochastically sampling dynamic
Gaussian processes of monotonically decreasing noise. The
transformation from high to low noise was compared between
our Fokker-Planck estimation and simulated ground-truth. To
demonstrate feasibility and clinical impact, we applied our
approach to 18 F-FDG-PET images to estimate early metabolic
response of patients (n = 57) undergoing definitive
(chemo)radiation for OPC. Images were acquired pre-treatment
and 2-weeks intra-treatment (after 20 Gy). Dynamic radiomic
features capturing changes in texture and morphology were
then extracted. Patients were partitioned into two groups
based on similar dynamic radiomic feature expression via
k-means clustering and compared by Kaplan-Meier analyses
with log-rank tests (p < 0.05). These results were
compared to conventional delta radiomics to test the added
value of our approach. RESULTS: Numerical results confirmed
our technique can recover image noise characteristics given
sparse input data as boundary conditions. Our technique was
able to model tumor shrinkage and metabolic response. While
no delta radiomics features proved prognostic, Kaplan-Meier
analyses identified nine significant dynamic radiomic
features. The most significant feature was
Gray-Level-Size-Zone-Matrix gray-level variance
(p = 0.011), which demonstrated prognostic improvement
over its corresponding delta radiomic feature (p = 0.722).
CONCLUSIONS: We developed, verified, and demonstrated the
prognostic value of a novel, physics-based radiomics
approach over conventional delta radiomics via data
assimilation of quantitative imaging and differential
equations.},
Doi = {10.1002/mp.16905},
Key = {fds375395}
}
@article{fds375396,
Author = {Nguyen, DL and Shelley Hwang and E and Ryser, MD and Grimm,
LJ},
Title = {Imaging Changes and Outcomes of Patients Undergoing Active
Monitoring for Ductal Carcinoma In Situ: Seven-Year
Follow-up Study.},
Journal = {Acad Radiol},
Year = {2024},
Month = {January},
url = {http://dx.doi.org/10.1016/j.acra.2023.12.021},
Abstract = {RATIONALE AND OBJECTIVES: To determine the imaging changes
and their associated positive predictive value (PPV) for
invasive breast cancer in women undergoing active monitoring
for ductal carcinoma in situ (DCIS). MATERIALS AND METHODS:
In this seven-year follow-up retrospective IRB-exempted
cohort study, we reviewed patients diagnosed with DCIS who
elected active monitoring between 2003 and 2022 at a single
academic institution. Imaging characteristics,
histopathology at initial diagnosis, and subsequent
follow-up were recorded. Low-risk DCIS was defined as low or
intermediate grade and hormone receptor (HR) positive
(estrogen and/or progesterone receptor positive) disease
diagnosed in women at least 40 years of age. Progression was
defined as subsequent ipsilateral invasive breast cancer
diagnosis. RESULTS: There were 39 patients with a median age
of 58.4 years (IQR: 51.1-69.6 years) and a median follow-up
of 4.3 years (range: 0.6-16.4 years). Nearly two thirds of
patients (64%, 25/39) had stable imaging (range: 0.6-16.4
years) and remained progression-free during active
monitoring. Among the remaining 14 patients (36%), there
were 24 imaging findings which prompted 22 subsequent core
needle biopsies (range: 1-3 biopsies per patient) and two
surgical biopsies. The PPV of invasive cancer was 29%
(7/24) overall and 38% (3/8) for masses, 33% (3/9) for
calcifications, 17% (1/6) for non-mass enhancement, and 0%
(0/1) for architectural distortion. CONCLUSION: Of the
radiographic changes prompting an additional biopsy,
development of a new mass (38%) and new calcifications (33%)
had the highest PPV for invasive progression. Close imaging
follow-up should be a critical component for patients
undergoing monitoring for DCIS.},
Doi = {10.1016/j.acra.2023.12.021},
Key = {fds375396}
}
@article{fds361709,
Author = {Earle, G and Mattingly, JC},
Title = {Convergence of stratified MCMC sampling of non-reversible
dynamics},
Journal = {Stochastics and Partial Differential Equations: Analysis and
Computations},
Year = {2024},
Month = {January},
url = {http://dx.doi.org/10.1007/s40072-024-00325-0},
Abstract = {We present a form of stratified MCMC algorithm built with
non-reversible stochastic dynamics in mind. It can also be
viewed as a generalization of the exact milestoning method
or form of NEUS. We prove the convergence of the method
under certain assumptions, with expressions for the
convergence rate in terms of the process’s behavior within
each stratum and large-scale behavior between strata. We
show that the algorithm has a unique fixed point which
corresponds to the invariant measure of the process without
stratification. We will show how the convergence speeds of
two versions of the algorithm, one with an extra eigenvalue
problem step and one without, related to the mixing rate of
a discrete process on the strata, and the mixing probability
of the process being sampled within each stratum. The
eigenvalue problem version also relates to local and global
perturbation results of discrete Markov chains, such as
those given by Van Koten, Weare et. al.},
Doi = {10.1007/s40072-024-00325-0},
Key = {fds361709}
}
@article{fds374408,
Author = {Melikechi, O and Dunson, DB},
Title = {Ellipsoid fitting with the Cayley transform.},
Journal = {IEEE transactions on signal processing : a publication of
the IEEE Signal Processing Society},
Volume = {72},
Pages = {70-83},
Year = {2024},
Month = {January},
url = {http://dx.doi.org/10.1109/tsp.2023.3332560},
Abstract = {We introduce Cayley transform ellipsoid fitting (CTEF), an
algorithm that uses the Cayley transform to fit ellipsoids
to noisy data in any dimension. Unlike many ellipsoid
fitting methods, CTEF is ellipsoid specific, meaning it
always returns elliptic solutions, and can fit arbitrary
ellipsoids. It also significantly outperforms other fitting
methods when data are not uniformly distributed over the
surface of an ellipsoid. Inspired by growing calls for
interpretable and reproducible methods in machine learning,
we apply CTEF to dimension reduction, data visualization,
and clustering in the context of cell cycle and circadian
rhythm data and several classical toy examples. Since CTEF
captures global curvature, it extracts nonlinear features in
data that other machine learning methods fail to identify.
For example, on the clustering examples CTEF outperforms 10
popular algorithms.},
Doi = {10.1109/tsp.2023.3332560},
Key = {fds374408}
}
@article{fds376095,
Author = {Datta, J and Banerjee, S and Dunson, DB},
Title = {Nonparametric Bayes multiresolution testing for
high-dimensional rare events},
Journal = {Journal of Nonparametric Statistics},
Year = {2024},
Month = {January},
url = {http://dx.doi.org/10.1080/10485252.2024.2309978},
Abstract = {In a variety of application areas, there is interest in
assessing evidence of differences in the intensity of event
realizations between groups. For example, in cancer genomic
studies collecting data on rare variants, the focus is on
assessing whether and how the variant profile changes with
the disease subtype. Motivated by this application, we
develop multiresolution nonparametric Bayes tests for
differential mutation rates across groups. The
multiresolution approach yields fast and accurate detection
of spatial clusters of rare variants, and our nonparametric
Bayes framework provides great flexibility for modelling the
intensities of rare variants. Some theoretical properties
are also assessed, including weak consistency of our
Dirichlet Process-Poisson-Gamma mixture over multiple
resolutions. Simulation studies illustrate excellent small
sample properties relative to competitors, and we apply the
method to detect rare variants related to common variable
immunodeficiency from whole exome sequencing data on 215
patients and over 60,027 control subjects.},
Doi = {10.1080/10485252.2024.2309978},
Key = {fds376095}
}
@article{fds376122,
Author = {Solomon, YE and Bendich, P},
Title = {Convolutional persistence transforms},
Journal = {Journal of Applied and Computational Topology},
Year = {2024},
Month = {January},
url = {http://dx.doi.org/10.1007/s41468-024-00164-x},
Abstract = {In this paper, we consider topological featurizations of
data defined over simplicial complexes, like images and
labeled graphs, obtained by convolving this data with
various filters before computing persistence. Viewing a
convolution filter as a local motif, the persistence diagram
of the resulting convolution describes the way the motif is
distributed across the simplicial complex. This pipeline,
which we call convolutional persistence, extends the
capacity of topology to observe patterns in such data.
Moreover, we prove that (generically speaking) for any two
labeled complexes one can find some filter for which they
produce different persistence diagrams, so that the
collection of all possible convolutional persistence
diagrams is an injective invariant. This is proven by
showing convolutional persistence to be a special case of
another topological invariant, the Persistent Homology
Transform. Other advantages of convolutional persistence are
improved stability, greater flexibility for data-dependent
vectorizations, and reduced computational complexity for
certain data types. Additionally, we have a suite of
experiments showing that convolutions greatly improve the
predictive power of persistence on a host of classification
tasks, even if one uses random filters and vectorizes the
resulting diagrams by recording only their total
persistences.},
Doi = {10.1007/s41468-024-00164-x},
Key = {fds376122}
}
@article{fds374555,
Author = {Duprez, F and Crombin, M and Daubechies, I and Devries, N and Durant, V and El Khalil and M and Audag, N},
Title = {[Update on manual bronchial clearance techniques (adults and
adolescents)].},
Journal = {Revue des maladies respiratoires},
Volume = {41},
Number = {1},
Pages = {43-50},
Year = {2024},
Month = {January},
url = {http://dx.doi.org/10.1016/j.rmr.2023.10.006},
Abstract = {In adults and teenagers, airway clearance physiotherapy
techniques (ACPT) are various and numerous. However, they
for still awaiting scientific validation. Among ACPTs, Slow
Expiration with the Glottis Opened in the Lateral Posture
(ELTGOL), Autogenic Drainage (DA), and Active Cycling
Breathing Technique (ACBT) present a Grade B level of
evidence with weak recommendations. Even though these
maneuvers are widely applied, precise description of chest
physiotherapy (CP) is largely absent from the scientific
literature; it is difficult to standardize its
implementation and reproduce the results; scientific
validation and faithful execution of the techniques are
consequently problematic. In this paper, the authors aim to
depict each of the three CP techniques as precisely as
possible; with this in mind, graphic modeling of the
different respiratory exercises is presented in such a way
that they can be easily learned, applied and reproduced by
physiotherapists.},
Doi = {10.1016/j.rmr.2023.10.006},
Key = {fds374555}
}
@article{fds374248,
Author = {Jing, Y and Chen, J and Li, L and Lu, J},
Title = {A Machine Learning Framework for Geodesics Under Spherical
Wasserstein–Fisher–Rao Metric and Its Application for
Weighted Sample Generation},
Journal = {Journal of Scientific Computing},
Volume = {98},
Number = {1},
Year = {2024},
Month = {January},
url = {http://dx.doi.org/10.1007/s10915-023-02396-y},
Abstract = {Wasserstein–Fisher–Rao (WFR) distance is a family of
metrics to gauge the discrepancy of two Radon measures,
which takes into account both transportation and weight
change. Spherical WFR distance is a projected version of WFR
distance for probability measures so that the space of Radon
measures equipped with WFR can be viewed as metric cone over
the space of probability measures with spherical WFR.
Compared to the case for Wasserstein distance, the
understanding of geodesics under the spherical WFR is less
clear and still an ongoing research focus. In this paper, we
develop a deep learning framework to compute the geodesics
under the spherical WFR metric, and the learned geodesics
can be adopted to generate weighted samples. Our approach is
based on a Benamou–Brenier type dynamic formulation for
spherical WFR. To overcome the difficulty in enforcing the
boundary constraint brought by the weight change, a
Kullback–Leibler divergence term based on the inverse map
is introduced into the cost function. Moreover, a new
regularization term using the particle velocity is
introduced as a substitute for the Hamilton–Jacobi
equation for the potential in dynamic formula. When used for
sample generation, our framework can be beneficial for
applications with given weighted samples, especially in the
Bayesian inference, compared to sample generation with
previous flow models.},
Doi = {10.1007/s10915-023-02396-y},
Key = {fds374248}
}
@article{fds373608,
Author = {Shnitzer, T and Wu, HT and Talmon, R},
Title = {Spatiotemporal analysis using Riemannian composition of
diffusion operators},
Journal = {Applied and Computational Harmonic Analysis},
Volume = {68},
Year = {2024},
Month = {January},
url = {http://dx.doi.org/10.1016/j.acha.2023.101583},
Abstract = {Multivariate time-series have become abundant in recent
years, as many data-acquisition systems record information
through multiple sensors simultaneously. In this paper, we
assume the variables pertain to some geometry and present an
operator-based approach for spatiotemporal analysis. Our
approach combines three components that are often considered
separately: (i) manifold learning for building operators
representing the geometry of the variables, (ii) Riemannian
geometry of symmetric positive-definite matrices for
multiscale composition of operators corresponding to
different time samples, and (iii) spectral analysis of the
composite operators for extracting different dynamic modes.
We propose a method that is analogous to the classical
wavelet analysis, which we term Riemannian multi-resolution
analysis (RMRA). We provide some theoretical results on the
spectral analysis of the composite operators, and we
demonstrate the proposed method on simulations and on real
data.},
Doi = {10.1016/j.acha.2023.101583},
Key = {fds373608}
}
@article{fds376687,
Author = {Ruotolo, J and Wang, K and Wei, F},
Title = {An Asymptotically Sharp Bound on the Maximum Number of
Independent Transversals},
Journal = {Electronic Journal of Combinatorics},
Volume = {31},
Number = {1},
Year = {2024},
Month = {January},
url = {http://dx.doi.org/10.37236/11670},
Abstract = {Let G be a multipartite graph with partition V1, V2, …, Vk
of V (G). Let di,j denote the edge density of the pair (Vi,
Vj). An independent transversal is an independent set of G
with exactly one vertex in each Vi . In this paper, we prove
an asymptotically sharp upper bound on the maximum number of
independent transversals given the di,j ’s.},
Doi = {10.37236/11670},
Key = {fds376687}
}
@article{fds375344,
Author = {Franz, L and Viljoen, M and Askew, S and Brown, M and Dawson, G and Di
Martino, JM and Sapiro, G and Sebolai, K and Seris, N and Shabalala, N and Stahmer, A and Turner, EL and de Vries, PJ},
Title = {Autism Caregiver Coaching in Africa (ACACIA): Protocol for a
type 1-hybrid effectiveness-implementation
trial.},
Journal = {PLoS One},
Volume = {19},
Number = {1},
Pages = {e0291883},
Year = {2024},
url = {http://dx.doi.org/10.1371/journal.pone.0291883},
Abstract = {BACKGROUND: While early autism intervention can
significantly improve outcomes, gaps in implementation exist
globally. These gaps are clearest in Africa, where forty
percent of the world's children will live by 2050.
Task-sharing early intervention to non-specialists is a key
implementation strategy, given the lack of specialists in
Africa. Naturalistic Developmental Behavioral Interventions
(NDBI) are a class of early autism intervention that can be
delivered by caregivers. As a foundational step to address
the early autism intervention gap, we adapted a
non-specialist delivered caregiver coaching NDBI for the
South African context, and pre-piloted this cascaded
task-sharing approach in an existing system of care.
OBJECTIVES: First, we will test the effectiveness of the
caregiver coaching NDBI compared to usual care. Second, we
will describe coaching implementation factors within the
Western Cape Department of Education in South Africa.
METHODS: This is a type 1 effectiveness-implementation
hybrid design; assessor-blinded, group randomized controlled
trial. Participants include 150 autistic children (18-72
months) and their caregivers who live in Cape Town, South
Africa, and those involved in intervention implementation.
Early Childhood Development practitioners, employed by the
Department of Education, will deliver 12, one hour, coaching
sessions to the intervention group. The control group will
receive usual care. Distal co-primary outcomes include the
Communication Domain Standard Score (Vineland Adaptive
Behavior Scales, Third Edition) and the Language and
Communication Developmental Quotient (Griffiths Scales of
Child Development, Third Edition). Proximal secondary
outcome include caregiver strategies measured by the sum of
five items from the Joint Engagement Rating Inventory. We
will describe key implementation determinants. RESULTS:
Participant enrolment started in April 2023. Estimated
primary completion date is March 2027. CONCLUSION: The
ACACIA trial will determine whether a cascaded task-sharing
intervention delivered in an educational setting leads to
meaningful improvements in communication abilities of
autistic children, and identify implementation barriers and
facilitators. TRIAL REGISTRATION: NCT05551728 in Clinical
Trial Registry (https://clinicaltrials.gov).},
Doi = {10.1371/journal.pone.0291883},
Key = {fds375344}
}
@article{fds374859,
Author = {Gao, Y and Liu, J-G},
Title = {A Selection Principle for Weak KAM Solutions via
Freidlin–Wentzell Large Deviation Principle of Invariant
Measures},
Journal = {SIAM Journal on Mathematical Analysis},
Volume = {55},
Number = {6},
Pages = {6457-6495},
Publisher = {Society for Industrial & Applied Mathematics
(SIAM)},
Year = {2023},
Month = {December},
url = {http://dx.doi.org/10.1137/22m1519717},
Doi = {10.1137/22m1519717},
Key = {fds374859}
}
@article{fds374860,
Author = {Gao, Y and Liu, J-G},
Title = {Large Deviation Principle and Thermodynamic Limit of
Chemical Master Equation via Nonlinear Semigroup},
Journal = {Multiscale Modeling & Simulation},
Volume = {21},
Number = {4},
Pages = {1534-1569},
Publisher = {Society for Industrial & Applied Mathematics
(SIAM)},
Year = {2023},
Month = {December},
url = {http://dx.doi.org/10.1137/22m1505633},
Doi = {10.1137/22m1505633},
Key = {fds374860}
}
@article{fds373953,
Author = {Cruikshank, A and Nijhout, HF and Best, J and Reed,
M},
Title = {Dynamical questions in volume transmission.},
Journal = {Journal of biological dynamics},
Volume = {17},
Number = {1},
Pages = {2269986},
Year = {2023},
Month = {December},
url = {http://dx.doi.org/10.1080/17513758.2023.2269986},
Abstract = {In volume transmission (or neuromodulation) neurons do not
make one-to-one connections to other neurons, but instead
simply release neurotransmitter into the extracellular space
from numerous varicosities. Many well-known
neurotransmitters including serotonin (5HT), dopamine (DA),
histamine (HA), Gamma-Aminobutyric Acid (GABA) and
acetylcholine (ACh) participate in volume transmission.
Typically, the cell bodies are in one volume and the axons
project to a distant volume in the brain releasing the
neurotransmitter there. We introduce volume transmission and
describe mathematically two natural homeostatic mechanisms.
In some brain regions several neurotransmitters in the
extracellular space affect each other's release. We
investigate the dynamics created by this comodulation in two
different cases: serotonin and histamine; and the
comodulation of 4 neurotransmitters in the striatum and we
compare to experimental data. This kind of comodulation
poses new dynamical questions as well as the question of how
these biochemical networks influence the
electrophysiological networks in the brain.},
Doi = {10.1080/17513758.2023.2269986},
Key = {fds373953}
}
@article{fds374394,
Author = {Witt, CE and Mena, S and Holmes, J and Hersey, M and Buchanan, AM and Parke, B and Saylor, R and Honan, LE and Berger, SN and Lumbreras, S and Nijhout, FH and Reed, MC and Best, J and Fadel, J and Schloss, P and Lau,
T and Hashemi, P},
Title = {Serotonin is a common thread linking different classes of
antidepressants.},
Journal = {Cell chemical biology},
Volume = {30},
Number = {12},
Pages = {1557-1570.e6},
Year = {2023},
Month = {December},
url = {http://dx.doi.org/10.1016/j.chembiol.2023.10.009},
Abstract = {Depression pathology remains elusive. The monoamine
hypothesis has placed much focus on serotonin, but due to
the variable clinical efficacy of monoamine reuptake
inhibitors, the community is looking for alternative
therapies such as ketamine (neurogenesis theory of
antidepressant action). There is evidence that different
classes of antidepressants may affect serotonin levels; a
notion we test here. We measure hippocampal serotonin in
mice with voltammetry and study the effects of acute
challenges of escitalopram, fluoxetine, reboxetine, and
ketamine. We find that pseudo-equivalent doses of these
drugs similarly raise ambient serotonin levels, despite
their differing pharmacodynamics because of differences in
Uptake 1 and 2, rapid SERT trafficking, and modulation of
serotonin by histamine. These antidepressants have different
pharmacodynamics but have strikingly similar effects on
extracellular serotonin. Our findings suggest that serotonin
is a common thread that links clinically effective
antidepressants, synergizing different theories of
depression (synaptic plasticity, neurogenesis, and the
monoamine hypothesis).},
Doi = {10.1016/j.chembiol.2023.10.009},
Key = {fds374394}
}
@article{fds371873,
Author = {Buch, DA and Johndrow, JE and Dunson, DB},
Title = {Explaining transmission rate variations and forecasting
epidemic spread in multiple regions with a semiparametric
mixed effects SIR model.},
Journal = {Biometrics},
Volume = {79},
Number = {4},
Pages = {2987-2997},
Year = {2023},
Month = {December},
url = {http://dx.doi.org/10.1111/biom.13901},
Abstract = {The transmission rate is a central parameter in mathematical
models of infectious disease. Its pivotal role in outbreak
dynamics makes estimating the current transmission rate and
uncovering its dependence on relevant covariates a core
challenge in epidemiological research as well as public
health policy evaluation. Here, we develop a method for
flexibly inferring a time-varying transmission rate
parameter, modeled as a function of covariates and a smooth
Gaussian process (GP). The transmission rate model is
further embedded in a hierarchy to allow information
borrowing across parallel streams of regional incidence
data. Crucially, the method makes use of optional
vaccination data as a first step toward modeling of endemic
infectious diseases. Computational techniques borrowed from
the Bayesian spatial analysis literature enable fast and
reliable posterior computation. Simulation studies reveal
that the method recovers true covariate effects at nominal
coverage levels. We analyze data from the COVID-19 pandemic
and validate forecast intervals on held-out data.
User-friendly software is provided to enable practitioners
to easily deploy the method in public health research.},
Doi = {10.1111/biom.13901},
Key = {fds371873}
}
@article{fds374279,
Author = {Nazaret, A and Tonekaboni, S and Darnell, G and Ren, SY and Sapiro, G and Miller, AC},
Title = {Modeling personalized heart rate response to exercise and
environmental factors with wearables data},
Journal = {npj Digital Medicine},
Volume = {6},
Number = {1},
Year = {2023},
Month = {December},
url = {http://dx.doi.org/10.1038/s41746-023-00926-4},
Abstract = {Heart rate (HR) response to workout intensity reflects
fitness and cardiorespiratory health. Physiological models
have been developed to describe such heart rate dynamics and
characterize cardiorespiratory fitness. However, these
models have been limited to small studies in controlled lab
environments and are challenging to apply to noisy—but
ubiquitous—data from wearables. We propose a hybrid
approach that combines a physiological model with flexible
neural network components to learn a personalized,
multidimensional representation of fitness. The
physiological model describes the evolution of heart rate
during exercise using ordinary differential equations
(ODEs). ODE parameters are dynamically derived via a neural
network connecting personalized representations to external
environmental factors, from area topography to weather and
instantaneous workout intensity. Our approach efficiently
fits the hybrid model to a large set of 270,707 workouts
collected from wearables of 7465 users from the Apple Heart
and Movement Study. The resulting model produces fitness
representations that accurately predict full HR response to
exercise intensity in future workouts, with a per-workout
median error of 6.1 BPM [4.4–8.8 IQR]. We further
demonstrate that the learned representations correlate with
traditional metrics of cardiorespiratory fitness, such as
VO2 max (explained variance 0.81 ± 0.003). Lastly, we
illustrate how our model is naturally interpretable and
explicitly describes the effects of environmental factors
such as temperature and humidity on heart rate, e.g., high
temperatures can increase heart rate by 10%. Combining
physiological ODEs with flexible neural networks can yield
interpretable, robust, and expressive models for health
applications.},
Doi = {10.1038/s41746-023-00926-4},
Key = {fds374279}
}
@article{fds375268,
Author = {Chu, R and Pierce, LB},
Title = {Generalizations of the Schrödinger maximal operator:
building arithmetic counterexamples},
Journal = {Journal d'Analyse Mathematique},
Volume = {151},
Number = {1},
Pages = {59-114},
Year = {2023},
Month = {December},
url = {http://dx.doi.org/10.1007/s11854-023-0335-7},
Abstract = {Let TtP2f(x) denote the solution to the linear Schrödinger
equation at time t, with initial value function f, where P
2(ξ) = ∣ξ∣2. In 1980, Carleson asked for the minimal
regularity of f that is required for the pointwise a.e.
convergence of TtP2f(x) to f(x) as t → 0. This was
recently resolved by work of Bourgain, and Du and Zhang.
This paper considers more general dispersive equations, and
constructs counterexamples to pointwise a.e. convergence for
a new class of real polynomial symbols P of arbitrary
degree, motivated by a broad question: what occurs for
symbols lying in a generic class? We construct the
counterexamples using number-theoretic methods, in
particular the Weil bound for exponential sums, and the
theory of Dwork-regular forms. This is the first case in
which counterexamples are constructed for indecomposable
forms, moving beyond special regimes where P has some
diagonal structure.},
Doi = {10.1007/s11854-023-0335-7},
Key = {fds375268}
}
@article{fds374353,
Author = {Deng, H and Robles, C},
Title = {Completion of two-parameter period maps by nilpotent
orbits},
Year = {2023},
Month = {December},
Abstract = {We show that every two-parameter period map admits a
Kato--Nakayama--Usui completion to a morphism of log
manifolds.},
Key = {fds374353}
}
@article{fds374414,
Author = {Nan, J and Roychowdhury, S and Randles, A},
Title = {Investigating the Influence of Heterogeneity Within Cell
Types on Microvessel Network Transport.},
Journal = {Cellular and molecular bioengineering},
Volume = {16},
Number = {5-6},
Pages = {497-507},
Year = {2023},
Month = {December},
url = {http://dx.doi.org/10.1007/s12195-023-00790-y},
Abstract = {<h4>Background</h4>Current research on the biophysics of
circulating tumor cells often overlooks the heterogeneity of
cell populations, focusing instead on average cellular
properties. This study aims to address the gap by
considering the diversity of cell biophysical
characteristics and their implications on cancer
spread.<h4>Methods</h4>We utilized computer simulations to
assess the influence of variations in cell size and membrane
elasticity on the behavior of cells within fluid
environments. The study controlled cell and fluid properties
to systematically investigate the transport of tumor cells
through a simulated network of branching
channels.<h4>Results</h4>The simulations revealed that even
minor differences in cellular properties, such as slight
changes in cell radius or shear elastic modulus, lead to
significant changes in the fluid conditions that cells
experience, including velocity and wall shear stress
(p < 0.001).<h4>Conclusion</h4>The findings underscore
the importance of considering cell heterogeneity in
biophysical studies and suggest that small variations in
cellular characteristics can profoundly impact the dynamics
of tumor cell circulation. This has potential implications
for understanding the mechanisms of cancer metastasis and
the development of therapeutic strategies.},
Doi = {10.1007/s12195-023-00790-y},
Key = {fds374414}
}
@article{fds374493,
Author = {Gong, Y and Kiselev, A},
Title = {A simple reaction-diffusion system as a possible model for
the origin of chemotaxis.},
Journal = {Journal of biological dynamics},
Volume = {17},
Number = {1},
Pages = {2260833},
Year = {2023},
Month = {December},
url = {http://dx.doi.org/10.1080/17513758.2023.2260833},
Abstract = {Chemotaxis is a directed cell movement in response to
external chemical stimuli. In this paper, we propose a
simple model for the origin of chemotaxis - namely how a
directed movement in response to an external chemical signal
may occur based on purely reaction-diffusion equations
reflecting inner working of the cells. The model is inspired
by the well-studied role of the rho-GTPase Cdc42 regulator
of cell polarity, in particular in yeast cells. We analyse
several versions of the model to better understand its
analytic properties and prove global regularity in one and
two dimensions. Using computer simulations, we demonstrate
that in the framework of this model, at least in certain
parameter regimes, the speed of the directed movement
appears to be proportional to the size of the gradient of
signalling chemical. This coincides with the form of the
chemical drift in the most studied mean field model of
chemotaxis, the Keller-Segel equation.},
Doi = {10.1080/17513758.2023.2260833},
Key = {fds374493}
}
@article{fds371626,
Author = {Wang, S-C and Ting, C-K and Chen, C-Y and Liu, C and Lin, N-C and Loong,
C-C and Wu, H-T and Lin, Y-T},
Title = {Arterial blood pressure waveform in liver transplant surgery
possesses variability of morphology reflecting recipients'
acuity and predicting short term outcomes.},
Journal = {Journal of clinical monitoring and computing},
Volume = {37},
Number = {6},
Pages = {1521-1531},
Year = {2023},
Month = {December},
url = {http://dx.doi.org/10.1007/s10877-023-01047-9},
Abstract = {We investigated clinical information underneath the
beat-to-beat fluctuation of the arterial blood pressure
(ABP) waveform morphology. We proposed the Dynamical
Diffusion Map algorithm (DDMap) to quantify the variability
of morphology. The underlying physiology could be the
compensatory mechanisms involving complex interactions
between various physiological mechanisms to regulate the
cardiovascular system. As a liver transplant surgery
contains distinct periods, we investigated its clinical
behavior in different surgical steps. Our study used DDmap
algorithm, based on unsupervised manifold learning, to
obtain a quantitative index for the beat-to-beat variability
of morphology. We examined the correlation between the
variability of ABP morphology and disease acuity as
indicated by Model for End-Stage Liver Disease (MELD)
scores, the postoperative laboratory data, and 4 early
allograft failure (EAF) scores. Among the 85 enrolled
patients, the variability of morphology obtained during the
presurgical phase was best correlated with MELD-Na scores.
The neohepatic phase variability of morphology was
associated with EAF scores as well as postoperative
bilirubin levels, international normalized ratio, aspartate
aminotransferase levels, and platelet count. Furthermore,
variability of morphology presents more associations with
the above clinical conditions than the common BP measures
and their BP variability indices. The variability of
morphology obtained during the presurgical phase is
indicative of patient acuity, whereas those during the
neohepatic phase are indicative of short-term surgical
outcomes.},
Doi = {10.1007/s10877-023-01047-9},
Key = {fds371626}
}
@article{fds374285,
Author = {Topaz, CM and Ning, S and Ciocanel, MV and Bushway,
S},
Title = {Federal criminal sentencing: race-based disparate impact and
differential treatment in judicial districts},
Journal = {Humanities and Social Sciences Communications},
Volume = {10},
Number = {1},
Year = {2023},
Month = {December},
url = {http://dx.doi.org/10.1057/s41599-023-01879-5},
Abstract = {Race-based inequity in federal criminal sentencing is widely
acknowledged, and yet our understanding of it is far from
complete. Inequity may arise from several sources, including
direct bias of courtroom actors and structural bias that
produces racially disparate impacts. Irrespective of these
sources, inequity may also originate from different loci
within the federal system. We bring together the questions
of the sources and loci of inequity. The purpose of our
study is to quantify race-based disparate impact and
differential treatment at the national level and at the
level of individual federal judicial districts. We analyze
over one-half million sentencing records publicly available
from the United States Sentencing Commission database,
spanning the years 2006 to 2020. At the system-wide level,
Black and Hispanic defendants receive average sentences that
are approximately 19 months longer and 5 months longer,
respectively. Demographic factors and sentencing guideline
elements account for nearly 17 of the 19 months for Black
defendants and all five of the months for Hispanic
defendants, demonstrating the disparate impact of the system
at the national level. At the individual district level,
even after controlling for each district’s unique
demographics and implementation of sentencing factors, 14
districts show significant differences for minoritized
defendants as compared to white ones. These unexplained
differences are evidence of possible differential treatment
by judges, prosecutors, and defense attorneys.},
Doi = {10.1057/s41599-023-01879-5},
Key = {fds374285}
}
@article{fds368358,
Author = {Drivas, TD and Elgindi, TM and La, J},
Title = {Propagation of singularities by Osgood vector fields and for
2D inviscid incompressible fluids},
Journal = {Mathematische Annalen},
Volume = {387},
Number = {3-4},
Pages = {1691-1718},
Year = {2023},
Month = {December},
url = {http://dx.doi.org/10.1007/s00208-022-02498-2},
Abstract = {We show that certain singular structures (Hölderian cusps
and mild divergences) are transported by the flow of
homeomorphisms generated by an Osgood velocity field. The
structure of these singularities is related to the modulus
of continuity of the velocity and the results are shown to
be sharp in the sense that slightly more singular structures
cannot generally be propagated. For the 2D Euler equation,
we prove that certain singular structures are preserved by
the motion, e.g. a system of log log +(1 / | x|) vortices
(and those that are slightly less singular) travel with the
fluid in a nonlinear fashion, up to bounded perturbations.
We also give stability results for weak Euler solutions away
from their singular set.},
Doi = {10.1007/s00208-022-02498-2},
Key = {fds368358}
}
@article{fds370528,
Author = {Moris, D and Barfield, R and Chan, C and Chasse, S and Stempora, L and Xie,
J and Plichta, JK and Thacker, J and Harpole, DH and Purves, T and Lagoo-Deenadayalan, S and Hwang, E-SS and Kirk,
AD},
Title = {Immune Phenotype and Postoperative Complications After
Elective Surgery.},
Journal = {Ann Surg},
Volume = {278},
Number = {6},
Pages = {873-882},
Year = {2023},
Month = {December},
url = {http://dx.doi.org/10.1097/SLA.0000000000005864},
Abstract = {OBJECTIVES: To characterize and quantify accumulating
immunologic alterations, pre and postoperatively in patients
undergoing elective surgical procedures. BACKGROUND:
Elective surgery is an anticipatable, controlled human
injury. Although the human response to injury is generally
stereotyped, individual variability exists. This makes
surgical outcomes less predictable, even after standardized
procedures, and may provoke complications in patients unable
to compensate for their injury. One potential source of
variation is found in immune cell maturation, with
phenotypic changes dependent on an individual's unique,
lifelong response to environmental antigens. METHODS: We
enrolled 248 patients in a prospective trial facilitating
comprehensive biospecimen and clinical data collection in
patients scheduled to undergo elective surgery. Peripheral
blood was collected preoperatively, and immediately on
return to the postanesthesia care unit. Postoperative
complications that occurred within 30 days after surgery
were captured. RESULTS: As this was an elective surgical
cohort, outcomes were generally favorable. With a median
follow-up of 6 months, the overall survival at 30 days was
100%. However, 20.5% of the cohort experienced a
postoperative complication (infection, readmission, or
system dysfunction). We identified substantial heterogeneity
of immune senescence and terminal differentiation phenotypes
in surgical patients. More importantly, phenotypes
indicating increased T-cell maturation and senescence were
associated with postoperative complications and were evident
preoperatively. CONCLUSIONS: The baseline immune repertoire
may define an immune signature of resilience to surgical
injury and help predict risk for surgical
complications.},
Doi = {10.1097/SLA.0000000000005864},
Key = {fds370528}
}
@article{fds374556,
Author = {Deng, H and Robles, C},
Title = {Completion of two-parameter period maps by nilpotent
orbits},
Year = {2023},
Month = {December},
Abstract = {We show that every two-parameter period map admits a
Kato--Nakayama--Usui completion to a morphism of log
manifolds.},
Key = {fds374556}
}
@article{fds374391,
Author = {Falcinelli, SD and Cooper-Volkheimer, AD and Semenova, L and Wu, E and Richardson, A and Ashokkumar, M and Margolis, DM and Archin, NM and Rudin, CD and Murdoch, D and Browne, EP},
Title = {Impact of Cannabis Use on Immune Cell Populations and the
Viral Reservoir in People With HIV on Suppressive
Antiretroviral Therapy.},
Journal = {J Infect Dis},
Volume = {228},
Number = {11},
Pages = {1600-1609},
Year = {2023},
Month = {November},
url = {http://dx.doi.org/10.1093/infdis/jiad364},
Abstract = {BACKGROUND: Human immunodeficiency virus (HIV) infection
remains incurable due to the persistence of a viral
reservoir despite antiretroviral therapy (ART). Cannabis
(CB) use is prevalent amongst people with HIV (PWH), but the
impact of CB on the latent HIV reservoir has not been
investigated. METHODS: Peripheral blood cells from a cohort
of PWH who use CB and a matched cohort of PWH who do not use
CB on ART were evaluated for expression of
maturation/activation markers, HIV-specific T-cell
responses, and intact proviral DNA. RESULTS: CB use was
associated with increased abundance of naive T cells,
reduced effector T cells, and reduced expression of
activation markers. CB use was also associated with reduced
levels of exhausted and senescent T cells compared to
nonusing controls. HIV-specific T-cell responses were
unaffected by CB use. CB use was not associated with intact
or total HIV DNA frequency in CD4 T cells. CONCLUSIONS: This
analysis is consistent with the hypothesis that CB use
reduces activation, exhaustion, and senescence in the T
cells of PWH, and does not impair HIV-specific CD8 T-cell
responses. Longitudinal and interventional studies with
evaluation of CB exposure are needed to fully evaluate the
impact of CB use on the HIV reservoir.},
Doi = {10.1093/infdis/jiad364},
Key = {fds374391}
}
@article{fds372445,
Author = {Bezemek, Z and Heldman, M},
Title = {Importance Sampling for the Empirical Measure of Weakly
Interacting Diffusions},
Journal = {Applied Mathematics and Optimization},
Volume = {89},
Publisher = {Springer},
Year = {2023},
Month = {November},
Key = {fds372445}
}
@article{fds374019,
Author = {Martin, A and Liu, G and Ladd, W and Lee, S and Gounley, J and Vetter, J and Patel, S and Rizzi, S and Mateevitsi, V and Insley, J and Randles,
A},
Title = {Performance Evaluation of Heterogeneous GPU Programming
Frameworks for Hemodynamic Simulations},
Journal = {ACM International Conference Proceeding Series},
Pages = {1126-1137},
Publisher = {ACM},
Year = {2023},
Month = {November},
ISBN = {9798400707858},
url = {http://dx.doi.org/10.1145/3624062.3624188},
Abstract = {Preparing for the deployment of large scientific and
engineering codes on upcoming exascale systems with
GPU-dense nodes is made challenging by the unprecedented
diversity of device architectures and heterogeneous
programming models. In this work, we evaluate the process of
porting a massively parallel, fluid dynamics code written in
CUDA to SYCL, HIP, and Kokkos with a range of backends,
using a combination of automated tools and manual tuning. We
use a proxy application along with a custom performance
model to inform the results and identify additional
optimization strategies. At scale performance of the
programming model implementations are evaluated on
pre-production GPU node architectures for Frontier and
Aurora, as well as on current NVIDIA device-based systems
Summit and Polaris. Real-world workloads representing 3D
blood flow calculations in complex vasculature are assessed.
Our analysis highlights critical trade-offs between code
performance, portability, and development
time.},
Doi = {10.1145/3624062.3624188},
Key = {fds374019}
}
@article{fds374020,
Author = {Valero-Lara, P and Vetter, J and Gounley, J and Randles,
A},
Title = {Moment Representation of Regularized Lattice Boltzmann
Methods on NVIDIA and AMD GPUs},
Journal = {ACM International Conference Proceeding Series},
Pages = {1697-1704},
Publisher = {ACM},
Year = {2023},
Month = {November},
ISBN = {9798400707858},
url = {http://dx.doi.org/10.1145/3624062.3624250},
Abstract = {The lattice Boltzmann method is a highly scalable
Navier-Stokes solver that has been applied to flow problems
in a wide array of domains. However, the method is
bandwidth-bound on modern GPU accelerators and has a large
memory footprint. In this paper, we present new 2D and 3D
GPU implementations of two different regularized lattice
Boltzmann methods, which are not only able to achieve an
acceleration of ~1.4 × w.r.t. reference lattice Boltzmann
implementations but also reduce the memory requirements by
up to 35% and 47% in 2D and 3D simulations respectively.
These new approaches are evaluated on NVIDIA and AMD GPU
architectures.},
Doi = {10.1145/3624062.3624250},
Key = {fds374020}
}
@article{fds374021,
Author = {Tanade, C and Rakestraw, E and Ladd, W and Draeger, E and Randles,
A},
Title = {Cloud Computing to Enable Wearable-Driven Longitudinal
Hemodynamic Maps},
Journal = {Proceedings of the International Conference for High
Performance Computing, Networking, Storage and Analysis, SC
2023},
Publisher = {ACM},
Year = {2023},
Month = {November},
ISBN = {9798400701092},
url = {http://dx.doi.org/10.1145/3581784.3607101},
Abstract = {Tracking hemodynamic responses to treatment and stimuli over
long periods remains a grand challenge. Moving from
established single-heartbeat technology to longitudinal
profiles would require continuous data describing how the
patient's state evolves, new methods to extend the temporal
domain over which flow is sampled, and high-throughput
computing resources. While personalized digital twins can
accurately measure 3D hemodynamics over several heartbeats,
state-of-the-art methods would require hundreds of years of
wallclock time on leadership scale systems to simulate one
day of activity. To address these challenges, we propose a
cloud-based, parallel-in-time framework leveraging
continuous data from wearable devices to capture the first
3D patient-specific, longitudinal hemodynamic maps. We
demonstrate the validity of our method by establishing
ground truth data for 750 beats and comparing the results.
Our cloud-based framework is based on an initial fixed set
of simulations to enable the wearable-informed creation of
personalized longitudinal hemodynamic maps.},
Doi = {10.1145/3581784.3607101},
Key = {fds374021}
}
@article{fds374482,
Author = {Pierce, L and Chu, R},
Title = {Generalizations of the Schrödinger maximal operator:
building arithmetic counterexamples},
Booktitle = {https://arxiv.org/abs/2309.05872},
Year = {2023},
Month = {November},
Key = {fds374482}
}
@article{fds371622,
Author = {Chapman, SJ and Dallaston, MC and Kalliadasis, S and Trinh, PH and Witelski, TP},
Title = {The role of exponential asymptotics and complex
singularities in self-similarity, transitions, and branch
merging of nonlinear dynamics},
Journal = {Physica D: Nonlinear Phenomena},
Volume = {453},
Year = {2023},
Month = {November},
url = {http://dx.doi.org/10.1016/j.physd.2023.133802},
Abstract = {We study a prototypical example in nonlinear dynamics where
transition to self-similarity in a singular limit is
fundamentally changed as a parameter is varied. Here, we
focus on the complicated dynamics that occur in a
generalised unstable thin-film equation that yields
finite-time rupture. A parameter, n, is introduced to model
more general disjoining pressures. For the standard case of
van der Waals intermolecular forces, n=3, it was previously
established that a countably infinite number of self-similar
solutions exist leading to rupture. Each solution can be
indexed by a parameter, ϵ=ϵ1>ϵ2>⋯>0, and the prediction
of the discrete set of solutions requires examination of
terms beyond-all-orders in ϵ. However, recent numerical
results have demonstrated the surprising complexity that
exists for general values of n. In particular, the
bifurcation structure of self-similar solutions now exhibits
branch merging as n is varied. In this work, we shall
present key ideas of how branch merging can be interpreted
via exponential asymptotics.},
Doi = {10.1016/j.physd.2023.133802},
Key = {fds371622}
}
@article{fds374205,
Author = {Wang, Z and Zhang, Z and Lu, J and Li, Y},
Title = {Coordinate Descent Full Configuration Interaction for
Excited States.},
Journal = {Journal of chemical theory and computation},
Volume = {19},
Number = {21},
Pages = {7731-7739},
Year = {2023},
Month = {November},
url = {http://dx.doi.org/10.1021/acs.jctc.3c00452},
Abstract = {An efficient excited state method, named xCDFCI, in the
configuration interaction framework is proposed. xCDFCI
extends the unconstrained nonconvex optimization problem in
coordinate descent full configuration interaction (CDFCI) to
a multicolumn version for low-lying excited states
computation. The optimization problem is addressed via a
tailored coordinate descent method. In each iteration, a
determinant is selected based on an approximated gradient,
and coefficients of all states associated with the selected
determinant are updated. A deterministic compression is
applied to limit memory usage. We test xCDFCI applied to
H<sub>2</sub>O and N<sub>2</sub> molecules under the cc-pVDZ
basis set. For both systems, five low-lying excited states
in the same symmetry sector are calculated, together with
the ground state. xCDFCI also produces accurate binding
curves of the carbon dimer in the cc-pVDZ basis with
chemical accuracy, where the ground state and four excited
states in the same symmetry sector are benchmarked.},
Doi = {10.1021/acs.jctc.3c00452},
Key = {fds374205}
}
@article{fds374022,
Author = {Roychowdhury, S and Balogh, P and Mahmud, ST and Puleri, DF and Martin,
A and Gounley, J and Draeger, EW and Randles, A},
Title = {Enhancing Adaptive Physics Refinement Simulations Through
the Addition of Realistic Red Blood Cell
Counts.},
Journal = {International Conference for High Performance Computing,
Networking, Storage and Analysis : [proceedings]. SC
(Conference : Supercomputing)},
Volume = {2023},
Pages = {41},
Publisher = {ACM},
Year = {2023},
Month = {November},
ISBN = {9798400701092},
url = {http://dx.doi.org/10.1145/3581784.3607105},
Abstract = {Simulations of cancer cell transport require accurately
modeling mm-scale and longer trajectories through a
circulatory system containing trillions of deformable red
blood cells, whose intercellular interactions require
submicron fidelity. Using a hybrid CPU-GPU approach, we
extend the advanced physics refinement (APR) method to
couple a finely-resolved region of explicitly-modeled red
blood cells to a coarsely-resolved bulk fluid domain. We
further develop algorithms that: capture the dynamics at the
interface of differing viscosities, maintain hematocrit
within the cell-filled volume, and move the finely-resolved
region and encapsulated cells while tracking an individual
cancer cell. Comparison to a fully-resolved fluid-structure
interaction model is presented for verification. Finally, we
use the advanced APR method to simulate cancer cell
transport over a mm-scale distance while maintaining a local
region of RBCs, using a fraction of the computational power
required to run a fully-resolved model.},
Doi = {10.1145/3581784.3607105},
Key = {fds374022}
}
@article{fds374290,
Author = {Repasky, M and Cheng, X and Xie, Y},
Title = {Neural Stein Critics with Staged L2-Regularization},
Journal = {IEEE Transactions on Information Theory},
Volume = {69},
Number = {11},
Pages = {7246-7275},
Year = {2023},
Month = {November},
url = {http://dx.doi.org/10.1109/TIT.2023.3299258},
Abstract = {Learning to differentiate model distributions from observed
data is a fundamental problem in statistics and machine
learning, and high-dimensional data remains a challenging
setting for such problems. Metrics that quantify the
disparity in probability distributions, such as the Stein
discrepancy, play an important role in high-dimensional
statistical testing. In this paper, we investigate the role
of L2 regularization in training a neural network Stein
critic so as to distinguish between data sampled from an
unknown probability distribution and a nominal model
distribution. Making a connection to the Neural Tangent
Kernel (NTK) theory, we develop a novel staging procedure
for the weight of regularization over training time, which
leverages the advantages of highly-regularized training at
early times. Theoretically, we prove the approximation of
the training dynamic by the kernel optimization, namely the
'lazy training', when the L2 regularization weight is large,
and training on n samples converge at a rate of O(n-1/2) up
to a log factor. The result guarantees learning the optimal
critic assuming sufficient alignment with the leading
eigen-modes of the zero-time NTK. The benefit of the staged
L2 regularization is demonstrated on simulated high
dimensional data and an application to evaluating generative
models of image data.},
Doi = {10.1109/TIT.2023.3299258},
Key = {fds374290}
}
@article{fds374488,
Author = {An, J and Henderson, C and Ryzhik, L},
Title = {Voting models and semilinear parabolic equations},
Journal = {Nonlinearity},
Volume = {36},
Number = {11},
Year = {2023},
Month = {November},
url = {http://dx.doi.org/10.1088/1361-6544/ad001c},
Abstract = {We present probabilistic interpretations of solutions to
semi-linear parabolic equations with polynomial
nonlinearities in terms of the voting models on the
genealogical trees of branching Brownian motion (BBM). These
extend McKean’s connection between the Fisher-KPP equation
and BBM (McKean 1975 Commun. Pure Appl. Math. 28 323-31). In
particular, we present ‘random outcome’ and ‘random
threshold’ voting models that yield any polynomial
nonlinearity f satisfying f ( 0 ) = f ( 1 ) = 0 and a
‘recursive up the tree’ model that allows to go beyond
this restriction on f. We compute several examples of
particular interest; for example, we obtain a curious
interpretation of the heat equation in terms of a nontrivial
voting model and a ‘group-based’ voting rule that leads
to a probabilistic view of the pushed-pulled transition for
a class of nonlinearities introduced by Ebert and van
Saarloos.},
Doi = {10.1088/1361-6544/ad001c},
Key = {fds374488}
}
@article{fds371968,
Author = {Dunlap, A and Gu, Y and Komorowski, T},
Title = {Fluctuation exponents of the KPZ equation on a large
torus},
Journal = {Communications on Pure and Applied Mathematics},
Volume = {76},
Number = {11},
Pages = {3104-3149},
Publisher = {Wiley},
Year = {2023},
Month = {November},
url = {http://dx.doi.org/10.1002/cpa.22110},
Abstract = {We study the one‐dimensional KPZ equation on a large
torus, started at equilibrium. The main results are optimal
variance bounds in the super‐relaxation regime and part of
the relaxation regime.},
Doi = {10.1002/cpa.22110},
Key = {fds371968}
}
@article{fds372375,
Author = {An, D and Fang, D and Jordan, S and Liu, J-P and Low, GH and Wang,
J},
Title = {Efficient quantum algorithm for nonlinear reaction-diffusion
equations and energy estimation},
Journal = {Commun. Math. Phys.},
Volume = {404},
Pages = {963-1020},
Booktitle = {arXiv 2205.01141},
Year = {2023},
Month = {October},
url = {http://dx.doi.org/10.48550/arXiv.2205.01141},
Doi = {10.48550/arXiv.2205.01141},
Key = {fds372375}
}
@article{fds373607,
Author = {Schmitz, RSJM and van den Belt-Dusebout, AW and Clements, K and Ren,
Y and Cresta, C and Timbres, J and Liu, Y-H and Byng, D and Lynch, T and Menegaz, BA and Collyar, D and Hyslop, T and Thomas, S and Love, JK and Schaapveld, M and Bhattacharjee, P and Ryser, MD and Sawyer, E and Hwang, ES and Thompson, A and Wesseling, J and Lips, EH and Schmidt, MK and Grand Challenge PRECISION consortium},
Title = {Association of DCIS size and margin status with risk of
developing breast cancer post-treatment: multinational,
pooled cohort study.},
Journal = {BMJ},
Volume = {383},
Pages = {e076022},
Year = {2023},
Month = {October},
url = {http://dx.doi.org/10.1136/bmj-2023-076022},
Abstract = {OBJECTIVE: To examine the association between size and
margin status of ductal carcinoma in situ (DCIS) and risk of
developing ipsilateral invasive breast cancer and
ipsilateral DCIS after treatment, and stage and subtype of
ipsilateral invasive breast cancer. DESIGN: Multinational,
pooled cohort study. SETTING: Four large international
cohorts. PARTICIPANTS: Patient level data on 47 695 women
with a diagnosis of pure, primary DCIS between 1999 and 2017
in the Netherlands, UK, and US who underwent surgery, either
breast conserving or mastectomy, often followed by
radiotherapy or endocrine treatment, or both. MAIN OUTCOME
MEASURES: The main outcomes were 10 year cumulative
incidence of ipsilateral invasive breast cancer and
ipsilateral DCIS estimated in relation to DCIS size and
margin status, and adjusted hazard ratios and 95% confidence
intervals, estimated using multivariable Cox proportional
hazards analyses with multiple imputed data RESULTS: The 10
year cumulative incidence of ipsilateral invasive breast
cancer was 3.2%. In women who underwent breast conserving
surgery with or without radiotherapy, only adjusted risks
for ipsilateral DCIS were significantly increased for larger
DCIS (20-49 mm) compared with DCIS <20 mm (hazard ratio
1.38, 95% confidence interval 1.11 to 1.72). Risks for both
ipsilateral invasive breast cancer and ipsilateral DCIS were
significantly higher with involved compared with clear
margins (invasive breast cancer 1.40, 1.07 to 1.83; DCIS
1.39, 1.04 to 1.87). Use of adjuvant endocrine treatment was
not significantly associated with a lower risk of
ipsilateral invasive breast cancer compared to treatment
with breast conserving surgery only (0.86, 0.62 to 1.21). In
women who received breast conserving treatment with or
without radiotherapy, higher DCIS grade was not
significantly associated with ipsilateral invasive breast
cancer, only with a higher risk of ipsilateral DCIS (grade
1: 1.42, 1.08 to 1.87; grade 3: 2.17, 1.66 to 2.83). Higher
age at diagnosis was associated with lower risk (per year)
of ipsilateral DCIS (0.98, 0.97 to 0.99) but not ipsilateral
invasive breast cancer (1.00, 0.99 to 1.00). Women with
large DCIS (≥50 mm) more often developed stage III and IV
ipsilateral invasive breast cancer compared to women with
DCIS <20 mm. No such association was found between involved
margins and higher stage of ipsilateral invasive breast
cancer. Associations between larger DCIS and hormone
receptor negative and human epidermal growth factor receptor
2 positive ipsilateral invasive breast cancer and involved
margins and hormone receptor negative ipsilateral invasive
breast cancer were found. CONCLUSIONS: The association of
DCIS size and margin status with ipsilateral invasive breast
cancer and ipsilateral DCIS was small. When these two
factors were added to other known risk factors in
multivariable models, clinicopathological risk factors alone
were found to be limited in discriminating between low and
high risk DCIS.},
Doi = {10.1136/bmj-2023-076022},
Key = {fds373607}
}
@article{fds373482,
Author = {Getz, J and Hsu, C-H and Leslie, S},
Title = {Harmonic analysis on certain spherical varieties},
Journal = {Journal of the European Mathematical Society},
Publisher = {EMS Press},
Year = {2023},
Month = {October},
url = {http://dx.doi.org/10.4171/JEMS/1381},
Doi = {10.4171/JEMS/1381},
Key = {fds373482}
}
@article{fds373473,
Author = {Getz, J and Hsu, C-H and Leslie, S},
Title = {Harmonic analysis on certain spherical varieties},
Journal = {Journal of the European Mathematical Society},
Publisher = {EMS Press},
Year = {2023},
Month = {October},
url = {http://dx.doi.org/10.4171/JEMS/1381},
Doi = {10.4171/JEMS/1381},
Key = {fds373473}
}
@article{fds374286,
Author = {Nelson, AC and Rolls, MM and Ciocanel, M-V and McKinley,
SA},
Title = {Minimal Mechanisms of Microtubule Length Regulation in
Living Cells},
Year = {2023},
Month = {October},
Key = {fds374286}
}
@article{fds373668,
Author = {Ryser, MD and Greenwald, MA and Sorribes, IC and King, LM and Hall, A and Geradts, J and Weaver, DL and Mallo, D and Holloway, S and Monyak, D and Gumbert, G and Vaez-Ghaemi, S and Wu, E and Murgas, K and Grimm, LJ and Maley, CC and Marks, JR and Shibata, D and Hwang,
ES},
Title = {Growth Dynamics of Ductal Carcinoma in Situ Recapitulate
Normal Breast Development.},
Journal = {bioRxiv},
Year = {2023},
Month = {October},
url = {http://dx.doi.org/10.1101/2023.10.01.560370},
Abstract = {Ductal carcinoma in situ (DCIS) and invasive breast cancer
share many morphologic, proteomic, and genomic alterations.
Yet in contrast to invasive cancer, many DCIS tumors do not
progress and may remain indolent over decades. To better
understand the heterogenous nature of this disease, we
reconstructed the growth dynamics of 18 DCIS tumors based on
the geo-spatial distribution of their somatic mutations. The
somatic mutation topographies revealed that DCIS is
multiclonal and consists of spatially discontinuous
subclonal lesions. Here we show that this pattern of spread
is consistent with a new 'Comet' model of DCIS
tumorigenesis, whereby multiple subclones arise early and
nucleate the buds of the growing tumor. The discontinuous,
multiclonal growth of the Comet model is analogous to the
branching morphogenesis of normal breast development that
governs the rapid expansion of the mammary epithelium during
puberty. The branching morphogenesis-like dynamics of the
proposed Comet model diverges from the canonical model of
clonal evolution, and better explains observed genomic
spatial data. Importantly, the Comet model allows for the
clinically relevant scenario of extensive DCIS spread,
without being subjected to the selective pressures of
subclone competition that promote the emergence of
increasingly invasive phenotypes. As such, the normal cell
movement inferred during DCIS growth provides a new
explanation for the limited risk of progression in DCIS and
adds biologic rationale for ongoing clinical efforts to
reduce DCIS overtreatment.},
Doi = {10.1101/2023.10.01.560370},
Key = {fds373668}
}
@article{fds371236,
Author = {Agarwal, PK and Geft, T and Halperin, D and Taylor,
E},
Title = {Multi-robot motion planning for unit discs with revolving
areas},
Journal = {Computational Geometry: Theory and Applications},
Volume = {114},
Year = {2023},
Month = {October},
url = {http://dx.doi.org/10.1016/j.comgeo.2023.102019},
Abstract = {We study the problem of motion planning for a collection of
n labeled unit disc robots in a polygonal environment. We
assume that the robots have revolving areas around their
start and final positions: that each start and each final is
contained in a radius 2 disc lying in the free space, not
necessarily concentric with the start or final position,
which is free from other start or final positions. This
assumption allows a weakly-monotone motion plan, in which
robots move according to an ordering as follows: during the
turn of a robot R in the ordering, it moves fully from its
start to final position, while other robots do not leave
their revolving areas. As R passes through a revolving area,
a robot R′ that is inside this area may move within the
revolving area to avoid a collision. Notwithstanding the
existence of a motion plan, we show that minimizing the
total traveled distance in this setting, specifically even
when the motion plan is restricted to be weakly-monotone, is
APX-hard, ruling out any polynomial-time
(1+ε)-approximation algorithm. On the positive side, we
present the first constant-factor approximation algorithm
for computing a feasible weakly-monotone motion plan. The
total distance traveled by the robots is within an O(1)
factor of that of the optimal motion plan, which need not be
weakly monotone. Our algorithm extends to an online setting
in which the polygonal environment is fixed but the initial
and final positions of robots are specified in an online
manner. Finally, we observe that the overhead in the overall
cost that we add while editing the paths to avoid
robot-robot collision can vary significantly depending on
the ordering we chose. Finding the best ordering in this
respect is known to be NP-hard, and we provide a polynomial
time O(lognloglogn)-approximation algorithm for
this problem.},
Doi = {10.1016/j.comgeo.2023.102019},
Key = {fds371236}
}
@article{fds373536,
Author = {Qi, D and Liu, J-G},
Title = {High-order moment closure models with random batch method
for efficient computation of multiscale turbulent
systems.},
Journal = {Chaos (Woodbury, N.Y.)},
Volume = {33},
Number = {10},
Pages = {103133},
Year = {2023},
Month = {October},
url = {http://dx.doi.org/10.1063/5.0160057},
Abstract = {We propose a high-order stochastic-statistical moment
closure model for efficient ensemble prediction of
leading-order statistical moments and probability density
functions in multiscale complex turbulent systems. The
statistical moment equations are closed by a precise
calibration of the high-order feedbacks using ensemble
solutions of the consistent stochastic equations, suitable
for modeling complex phenomena including non-Gaussian
statistics and extreme events. To address challenges
associated with closely coupled spatiotemporal scales in
turbulent states and expensive large ensemble simulation for
high-dimensional systems, we introduce efficient
computational strategies using the random batch method
(RBM). This approach significantly reduces the required
ensemble size while accurately capturing essential
high-order structures. Only a small batch of small-scale
fluctuation modes is used for each time update of the
samples, and exact convergence to the full model statistics
is ensured through frequent resampling of the batches during
time evolution. Furthermore, we develop a reduced-order
model to handle systems with really high dimensions by
linking the large number of small-scale fluctuation modes to
ensemble samples of dominant leading modes. The
effectiveness of the proposed models is validated by
numerical experiments on the one-layer and two-layer Lorenz
'96 systems, which exhibit representative chaotic features
and various statistical regimes. The full and reduced-order
RBM models demonstrate uniformly high skill in capturing the
time evolution of crucial leading-order statistics,
non-Gaussian probability distributions, while achieving
significantly lower computational cost compared to direct
Monte-Carlo approaches. The models provide effective tools
for a wide range of real-world applications in prediction,
uncertainty quantification, and data assimilation.},
Doi = {10.1063/5.0160057},
Key = {fds373536}
}
@article{fds373425,
Author = {Baek, Y and Aquino, W and Mukherjee, S},
Title = {Generalized Bayes approach to inverse problems with model
misspecification.},
Journal = {Inverse problems},
Volume = {39},
Number = {10},
Pages = {105011},
Year = {2023},
Month = {October},
url = {http://dx.doi.org/10.1088/1361-6420/acf51c},
Abstract = {We propose a general framework for obtaining probabilistic
solutions to PDE-based inverse problems. Bayesian methods
are attractive for uncertainty quantification but assume
knowledge of the likelihood model or data generation
process. This assumption is difficult to justify in many
inverse problems, where the specification of the data
generation process is not obvious. We adopt a Gibbs
posterior framework that directly posits a regularized
variational problem on the space of probability
distributions of the parameter. We propose a novel model
comparison framework that evaluates the optimality of a
given loss based on its "predictive performance". We provide
cross-validation procedures to calibrate the regularization
parameter of the variational objective and compare multiple
loss functions. Some novel theoretical properties of Gibbs
posteriors are also presented. We illustrate the utility of
our framework via a simulated example, motivated by
dispersion-based wave models used to characterize arterial
vessels in ultrasound vibrometry.},
Doi = {10.1088/1361-6420/acf51c},
Key = {fds373425}
}
@article{fds373966,
Author = {Schlesinger, O and Kundu, R and Goetz, S and Sapiro, G and Peterchev,
AV and Di Martino and JM},
Title = {Automatic Neurocranial Landmarks Detection from Visible
Facial Landmarks Leveraging 3D Head Priors.},
Journal = {Clin Image Based Proced Fairness AI Med Imaging Ethical
Philos Issues Med Imaging (2023)},
Volume = {14242},
Pages = {12-20},
Year = {2023},
Month = {October},
ISBN = {9783031452482},
url = {http://dx.doi.org/10.1007/978-3-031-45249-9_2},
Abstract = {The localization and tracking of neurocranial landmarks is
essential in modern medical procedures, e.g., transcranial
magnetic stimulation (TMS). However, state-of-the-art
treatments still rely on the manual identification of head
targets and require setting retroreflective markers for
tracking. This limits the applicability and scalability of
TMS approaches, making them time-consuming, dependent on
expensive hardware, and prone to errors when retroreflective
markers drift from their initial position. To overcome these
limitations, we propose a scalable method capable of
inferring the position of points of interest on the scalp,
e.g., the International 10-20 System's neurocranial
landmarks. In contrast with existing approaches, our method
does not require human intervention or markers; head
landmarks are estimated leveraging visible facial landmarks,
optional head size measurements, and statistical head model
priors. We validate the proposed approach on ground truth
data from 1,150 subjects, for which facial 3D and head
information is available; our technique achieves a
localization RMSE of 2.56 mm on average, which is of the
same order as reported by high-end techniques in TMS. Our
implementation is available at https://github.com/odedsc/ANLD.},
Doi = {10.1007/978-3-031-45249-9_2},
Key = {fds373966}
}
@article{fds373329,
Author = {Perochon, S and Di Martino and JM and Carpenter, KLH and Compton, S and Davis, N and Eichner, B and Espinosa, S and Franz, L and Krishnappa
Babu, PR and Sapiro, G and Dawson, G},
Title = {Early detection of autism using digital behavioral
phenotyping.},
Journal = {Nat Med},
Volume = {29},
Number = {10},
Pages = {2489-2497},
Year = {2023},
Month = {October},
url = {http://dx.doi.org/10.1038/s41591-023-02574-3},
Abstract = {Early detection of autism, a neurodevelopmental condition
associated with challenges in social communication, ensures
timely access to intervention. Autism screening
questionnaires have been shown to have lower accuracy when
used in real-world settings, such as primary care, as
compared to research studies, particularly for children of
color and girls. Here we report findings from a multiclinic,
prospective study assessing the accuracy of an autism
screening digital application (app) administered during a
pediatric well-child visit to 475 (17-36 months old)
children (269 boys and 206 girls), of which 49 were
diagnosed with autism and 98 were diagnosed with
developmental delay without autism. The app displayed
stimuli that elicited behavioral signs of autism, quantified
using computer vision and machine learning. An algorithm
combining multiple digital phenotypes showed high diagnostic
accuracy with the area under the receiver operating
characteristic curve = 0.90, sensitivity = 87.8%,
specificity = 80.8%, negative predictive
value = 97.8% and positive predictive value = 40.6%.
The algorithm had similar sensitivity performance across
subgroups as defined by sex, race and ethnicity. These
results demonstrate the potential for digital phenotyping to
provide an objective, scalable approach to autism screening
in real-world settings. Moreover, combining results from
digital phenotyping and caregiver questionnaires may
increase autism screening accuracy and help reduce
disparities in access to diagnosis and intervention.},
Doi = {10.1038/s41591-023-02574-3},
Key = {fds373329}
}
@article{fds372698,
Author = {Cao, Y and Lu, J and Wang, L},
Title = {On Explicit L2 -Convergence Rate Estimate for
Underdamped Langevin Dynamics},
Journal = {Archive for Rational Mechanics and Analysis},
Volume = {247},
Number = {5},
Year = {2023},
Month = {October},
url = {http://dx.doi.org/10.1007/s00205-023-01922-4},
Abstract = {We provide a refined explicit estimate of the exponential
decay rate of underdamped Langevin dynamics in the L2
distance, based on a framework developed in Albritton et al.
(Variational methods for the kinetic Fokker–Planck
equation, arXiv arXiv:1902.04037 , 2019). To achieve this,
we first prove a Poincaré-type inequality with a Gibbs
measure in space and a Gaussian measure in momentum. Our
estimate provides a more explicit and simpler expression of
the decay rate; moreover, when the potential is convex with
a Poincaré constant m≪ 1 , our estimate shows the decay
rate of O(m) after optimizing the choice of the friction
coefficient, which is much faster than m for the overdamped
Langevin dynamics.},
Doi = {10.1007/s00205-023-01922-4},
Key = {fds372698}
}
@article{fds373363,
Author = {Garrett, BL and Rudin, C},
Title = {Interpretable algorithmic forensics.},
Journal = {Proceedings of the National Academy of Sciences of the
United States of America},
Volume = {120},
Number = {41},
Pages = {e2301842120},
Year = {2023},
Month = {October},
url = {http://dx.doi.org/10.1073/pnas.2301842120},
Abstract = {One of the most troubling trends in criminal investigations
is the growing use of "black box" technology, in which law
enforcement rely on artificial intelligence (AI) models or
algorithms that are either too complex for people to
understand or they simply conceal how it functions. In
criminal cases, black box systems have proliferated in
forensic areas such as DNA mixture interpretation, facial
recognition, and recidivism risk assessments. The champions
and critics of AI argue, mistakenly, that we face a catch
22: While black box AI is not understandable by people, they
assume that it produces more accurate forensic evidence. In
this Article, we question this assertion, which has so
powerfully affected judges, policymakers, and academics. We
describe a mature body of computer science research showing
how "glass box" AI-designed to be interpretable-can be more
accurate than black box alternatives. Indeed, black box AI
performs predictably <i>worse</i> in settings like the
criminal system. Debunking the black box performance myth
has implications for forensic evidence, constitutional
criminal procedure rights, and legislative policy. Absent
some compelling-or even credible-government interest in
keeping AI as a black box, and given the constitutional
rights and public safety interests at stake, we argue that a
substantial burden rests on the government to justify black
box AI in criminal cases. We conclude by calling for
judicial rulings and legislation to safeguard a right to
interpretable forensic AI.},
Doi = {10.1073/pnas.2301842120},
Key = {fds373363}
}
@article{fds374489,
Author = {An, J and Henderson, C and Ryzhik, L},
Title = {Quantitative Steepness, Semi-FKPP Reactions, and
Pushmi-Pullyu Fronts},
Journal = {Archive for Rational Mechanics and Analysis},
Volume = {247},
Number = {5},
Year = {2023},
Month = {October},
url = {http://dx.doi.org/10.1007/s00205-023-01924-2},
Abstract = {We uncover a seemingly previously unnoticed algebraic
structure of a large class of reaction–diffusion equations
and use it to study the long time behavior of the solutions
and their convergence to traveling waves in the pulled and
pushed regimes, as well as at the pushmi-pullyu boundary.
One such new object introduced in this paper is the shape
defect function, which, indirectly, measures the difference
between the profiles of the solution and the traveling wave.
While one can recast the classical notion of ‘steepness’
in terms of the positivity of the shape defect function, its
positivity can, surprisingly, be used in numerous
quantitative ways. In particular, the positivity is used in
a new weighted Hopf-Cole transform and in a relative entropy
approach that play a key role in the stability arguments.
The shape defect function also gives a new connection
between reaction–diffusion equations and reaction
conservation laws at the pulled-pushed transition. Other
simple but seemingly new algebraic constructions in the
present paper supply various unexpected inequalities
sprinkled throughout the paper. Of note is a new variational
formulation that applies equally to pulled and pushed
fronts, opening the door to an as-yet-elusive variational
analysis in the pulled case.},
Doi = {10.1007/s00205-023-01924-2},
Key = {fds374489}
}
@article{fds374292,
Author = {Landa, B and Cheng, X},
Title = {Robust Inference of Manifold Density and Geometry by Doubly
Stochastic Scaling},
Journal = {SIAM Journal on Mathematics of Data Science},
Volume = {5},
Number = {3},
Pages = {589-614},
Publisher = {Society for Industrial & Applied Mathematics
(SIAM)},
Year = {2023},
Month = {September},
url = {http://dx.doi.org/10.1137/22m1516968},
Doi = {10.1137/22m1516968},
Key = {fds374292}
}
@article{fds373376,
Author = {Hughes, J},
Title = {Weave-realizability for D–type},
Journal = {Algebraic & Geometric Topology},
Volume = {23},
Number = {6},
Pages = {2735-2776},
Publisher = {Mathematical Sciences Publishers},
Year = {2023},
Month = {September},
url = {http://dx.doi.org/10.2140/agt.2023.23.2735},
Doi = {10.2140/agt.2023.23.2735},
Key = {fds373376}
}
@article{fds374287,
Author = {Ciocanel, M-V and Goldrosen, N and Topaz, C},
Title = {Quantifying Federal Sentence Disparities with Inferred
Sentencing Records},
Journal = {SIAM News Blogs},
Year = {2023},
Month = {September},
Key = {fds374287}
}
@article{fds374498,
Author = {Akin, V and Bookman, J and Braley, E},
Title = {Modeling Active Learning in Professional Development for
Teaching},
Journal = {The journal of faculty development},
Volume = {37},
Number = {3},
Pages = {28-39},
Publisher = {Magna Publications},
Year = {2023},
Month = {September},
Key = {fds374498}
}
@article{fds370378,
Author = {Xu, J and Li, Y and Yang, H and Dunson, D and Daubechies,
I},
Title = {PiPs: A kernel-based optimization scheme for analyzing
non-stationary 1D signals},
Journal = {Applied and Computational Harmonic Analysis},
Volume = {66},
Pages = {1-17},
Year = {2023},
Month = {September},
url = {http://dx.doi.org/10.1016/j.acha.2023.04.002},
Abstract = {This paper proposes a novel kernel-based optimization scheme
to handle tasks in the analysis, e.g., signal spectral
estimation and single-channel source separation of 1D
non-stationary oscillatory data. The key insight of our
optimization scheme for reconstructing the time-frequency
information is that when a nonparametric regression is
applied on some input values, the output regressed points
would lie near the oscillatory pattern of the oscillatory 1D
signal only if these input values are a good approximation
of the ground-truth phase function. In this work, Gaussian
Process (GP) is chosen to conduct this nonparametric
regression: the oscillatory pattern is encoded as the
Pattern-inducing Points (PiPs) which act as the training
data points in the GP regression; while the targeted phase
function is fed in to compute the correlation kernels,
acting as the testing input. Better approximated phase
function generates more precise kernels, thus resulting in
smaller optimization loss error when comparing the
kernel-based regression output with the original signals. To
the best of our knowledge, this is the first algorithm that
can satisfactorily handle fully non-stationary oscillatory
data, close and crossover frequencies, and general
oscillatory patterns. Even in the example of a signal
produced by slow variation in the parameters of a
trigonometric expansion, we show that PiPs admits
competitive or better performance in terms of accuracy and
robustness than existing state-of-the-art
algorithms.},
Doi = {10.1016/j.acha.2023.04.002},
Key = {fds370378}
}
@article{fds372678,
Author = {Rigon, T and Herring, AH and Dunson, DB},
Title = {A generalized Bayes framework for probabilistic
clustering},
Journal = {Biometrika},
Volume = {110},
Number = {3},
Pages = {559-578},
Year = {2023},
Month = {September},
url = {http://dx.doi.org/10.1093/biomet/asad004},
Abstract = {Loss-based clustering methods, such as k-means clustering
and its variants, are standard tools for finding groups in
data. However, the lack of quantification of uncertainty in
the estimated clusters is a disadvantage. Model-based
clustering based on mixture models provides an alternative
approach, but such methods face computational problems and
are highly sensitive to the choice of kernel. In this
article we propose a generalized Bayes framework that
bridges between these paradigms through the use of Gibbs
posteriors. In conducting Bayesian updating, the
loglikelihood is replaced by a loss function for clustering,
leading to a rich family of clustering methods. The Gibbs
posterior represents a coherent updating of Bayesian beliefs
without needing to specify a likelihood for the data, and
can be used for characterizing uncertainty in clustering. We
consider losses based on Bregman divergence and pairwise
similarities, and develop efficient deterministic algorithms
for point estimation along with sampling algorithms for
uncertainty quantification. Several existing clustering
algorithms, including k-means, can be interpreted as
generalized Bayes estimators in our framework, and thus we
provide a method of uncertainty quantification for these
approaches, allowing, for example, calculation of the
probability that a data point is well clustered.},
Doi = {10.1093/biomet/asad004},
Key = {fds372678}
}
@article{fds370363,
Author = {Xu, J and Li, Y and Yang, H and Dunson, D and Daubechies,
I},
Title = {PiPs: A kernel-based optimization scheme for analyzing
non-stationary 1D signals},
Journal = {Applied and Computational Harmonic Analysis},
Volume = {66},
Pages = {1-17},
Year = {2023},
Month = {September},
url = {http://dx.doi.org/10.1016/j.acha.2023.04.002},
Abstract = {This paper proposes a novel kernel-based optimization scheme
to handle tasks in the analysis, e.g., signal spectral
estimation and single-channel source separation of 1D
non-stationary oscillatory data. The key insight of our
optimization scheme for reconstructing the time-frequency
information is that when a nonparametric regression is
applied on some input values, the output regressed points
would lie near the oscillatory pattern of the oscillatory 1D
signal only if these input values are a good approximation
of the ground-truth phase function. In this work, Gaussian
Process (GP) is chosen to conduct this nonparametric
regression: the oscillatory pattern is encoded as the
Pattern-inducing Points (PiPs) which act as the training
data points in the GP regression; while the targeted phase
function is fed in to compute the correlation kernels,
acting as the testing input. Better approximated phase
function generates more precise kernels, thus resulting in
smaller optimization loss error when comparing the
kernel-based regression output with the original signals. To
the best of our knowledge, this is the first algorithm that
can satisfactorily handle fully non-stationary oscillatory
data, close and crossover frequencies, and general
oscillatory patterns. Even in the example of a signal
produced by slow variation in the parameters of a
trigonometric expansion, we show that PiPs admits
competitive or better performance in terms of accuracy and
robustness than existing state-of-the-art
algorithms.},
Doi = {10.1016/j.acha.2023.04.002},
Key = {fds370363}
}
@article{fds372370,
Author = {Balmaceda, JM and Clemens, CH and Daubechies, I and Pineda, AR and Rusu,
G and Waldschmidt, M},
Title = {Graduate Assistantships in Developing Countries (GRAID)
Supporting Mathematics Graduate Students in the Countries
that Need it Most},
Journal = {Notices of the American Mathematical Society},
Volume = {70},
Number = {8},
Pages = {1281-1284},
Year = {2023},
Month = {September},
url = {http://dx.doi.org/10.1090/noti2749},
Doi = {10.1090/noti2749},
Key = {fds372370}
}
@article{fds373965,
Author = {Nazaret, A and Sapiro, G},
Title = {A large-scale observational study of the causal effects of a
behavioral health nudge.},
Journal = {Science advances},
Volume = {9},
Number = {38},
Pages = {eadi1752},
Year = {2023},
Month = {September},
url = {http://dx.doi.org/10.1126/sciadv.adi1752},
Abstract = {Nudges are interventions promoting healthy behavior without
forbidding options or substantial incentives; the Apple
Watch, for example, encourages users to stand by delivering
a notification if they have been sitting for the first 50
minutes of an hour. On the basis of 76 billion minutes of
observational standing data from 160,000 subjects in the
public Apple Heart and Movement Study, we estimate the
causal effect of this notification using a regression
discontinuity design for time series data with time-varying
treatment. We show that the nudge increases the probability
of standing by up to 43.9% and remains effective with time.
The nudge's effectiveness increases with age and is
independent of gender. Closing Apple Watch Activity Rings, a
visualization of participants' daily progress in Move,
Exercise, and Stand, further increases the nudge's impact.
This work demonstrates the effectiveness of behavioral
health interventions and introduces tools for investigating
their causal effect from large-scale observations.},
Doi = {10.1126/sciadv.adi1752},
Key = {fds373965}
}
@article{fds374499,
Author = {Akin, V and Viel, S},
Title = {Equity in Grading Systems: Moving Away From “Fair”
Towards Transparency and Inclusion in Coordinated Calculus
Courses},
Volume = {96},
Booktitle = {Justice through the lens of calculus: Framing new
possibilities for diversity, equity, and
inclusion.},
Publisher = {MAA Press},
Editor = {Voigt, M and Hagaman, J and Gehrtz, J and Ratliff, B and Alexander, N and Levy, R},
Year = {2023},
Month = {September},
Key = {fds374499}
}
@article{fds374500,
Author = {Akin, V and Bookman, J and Braley, E},
Title = {Modeling Active Learning in Professional Development for
Teaching},
Journal = {The journal of faculty development},
Volume = {37},
Number = {3},
Pages = {28-39},
Publisher = {Magna Publications},
Year = {2023},
Month = {September},
Key = {fds374500}
}
@article{fds374501,
Author = {Akin, V and Viel, S},
Title = {Equity in Grading Systems: Moving Away From “Fair”
Towards Transparency and Inclusion in Coordinated Calculus
Courses},
Volume = {96},
Booktitle = {Justice through the lens of calculus: Framing new
possibilities for diversity, equity, and
inclusion.},
Publisher = {MAA Press},
Editor = {Voigt, M and Hagaman, J and Gehrtz, J and Ratliff, B and Alexander, N and Levy, R},
Year = {2023},
Month = {September},
Key = {fds374501}
}
@article{fds372441,
Author = {Bachmann, T and Wickelgren, K},
Title = {On quadratically enriched excess and residual
intersections},
Journal = {Journal fur die Reine und Angewandte Mathematik},
Volume = {2023},
Number = {802},
Pages = {77-123},
Year = {2023},
Month = {September},
url = {http://dx.doi.org/10.1515/crelle-2023-0041},
Abstract = {We use recent duality results of Eisenbud and Ulrich to give
tools to study quadratically enriched residual intersections
when there is no excess bundle. We use this to prove a
formula for the Witt-valued Euler number of an almost
complete intersection. We give example computations of
quadratically enriched excess and residual
intersections.},
Doi = {10.1515/crelle-2023-0041},
Key = {fds372441}
}
@article{fds372277,
Author = {Drivas, TD and Dunlap, A and Graham, C and La, J and Ryzhik,
L},
Title = {Invariant measures for stochastic conservation laws on the
line},
Journal = {Nonlinearity},
Volume = {36},
Number = {9},
Pages = {4553-4594},
Year = {2023},
Month = {September},
url = {http://dx.doi.org/10.1088/1361-6544/acdb3a},
Abstract = {We consider a stochastic conservation law on the line with
solution-dependent diffusivity, a super-linear,
sub-quadratic Hamiltonian, and smooth, spatially-homogeneous
kick-type random forcing. We show that this Markov process
admits a unique ergodic spatially-homogeneous invariant
measure for each mean in a non-explicit unbounded set. This
generalises previous work on the stochastic Burgers
equation.},
Doi = {10.1088/1361-6544/acdb3a},
Key = {fds372277}
}
@article{fds372446,
Author = {Huang, H and Yu, J and Chen, J and Lai, R},
Title = {Bridging mean-field games and normalizing flows with
trajectory regularization},
Journal = {Journal of Computational Physics},
Volume = {487},
Pages = {112155-112155},
Publisher = {Elsevier BV},
Year = {2023},
Month = {August},
url = {http://dx.doi.org/10.1016/j.jcp.2023.112155},
Abstract = {Mean-field games (MFGs) are a modeling framework for systems
with a large number of interacting agents. They have
applications in economics, finance, and game theory.
Normalizing flows (NFs) are a family of deep generative
models that compute data likelihoods by using an invertible
mapping typically parameterized by neural networks. They are
useful for density modeling and data generation. While
active research has been conducted on both models, few noted
the relationship between the two. In this work, we unravel
the connections between MFGs and NFs by contextualizing the
training of an NF as solving the MFG. This is achieved by
reformulating the MFG problem in terms of agent trajectories
and parameterizing a discretization of the resulting MFG
with flow architectures. With this connection, we explore
two research directions. First, we employ expressive NF
architectures to accurately solve high-dimensional MFGs,
sidestepping the curse of dimensionality in traditional
numerical methods. Compared with other deep learning
approaches, our trajectory-based formulation encodes the
continuity equation in the network architecture to better
approximate population dynamics. Second, we regularize the
training of NFs with transport costs and show the
effectiveness on controlling the model's Lipschitz bound,
resulting in better generalization performance. We
demonstrate numerical results through comprehensive
experiments on a variety of synthetic and real-life
datasets.},
Doi = {10.1016/j.jcp.2023.112155},
Key = {fds372446}
}
@article{fds372809,
Author = {Hahn, S and Zhu, R and Mak, S and Rudin, C and Jiang,
Y},
Title = {An Interpretable, Flexible, and Interactive Probabilistic
Framework for Melody Generation},
Journal = {Proceedings of the ACM SIGKDD International Conference on
Knowledge Discovery and Data Mining},
Pages = {4089-4099},
Year = {2023},
Month = {August},
ISBN = {9798400701030},
url = {http://dx.doi.org/10.1145/3580305.3599772},
Abstract = {The fast-growing demand for algorithmic music generation is
found throughout entertainment, art, education, etc.
Unfortunately, most recent models are practically impossible
to interpret or musically fine-tune, as they use deep neural
networks with thousands of parameters. We introduce an
interpretable, flexible, and interactive model,
SchenkComposer, for melody generation that empowers users to
be creative in all aspects of the music generation pipeline
and allows them to learn from the process. We divide the
task of melody generation into steps based on the process
that a human composer using music-theoretical domain
knowledge might use. First, the model determines phrase
structure based on form analysis and identifies an
appropriate number of measures. Using concepts from
Schenkerian analysis, the model then finds a fitting
harmonic rhythm, middleground harmonic progression,
foreground rhythm, and melody in a hierarchical, scaffolded
approach using a probabilistic context-free grammar based on
musical contours. By incorporating theories of musical form
and harmonic structure, our model produces music with
long-term structural coherence. In extensive human
experiments, we find that music generated with our approach
successfully passes a Turing test in human experiments while
current state-of-the-art approaches fail, and we further
demonstrate superior performance and preference for our
melodies compared to existing melody generation methods.
Additionally, we developed and deployed a public website for
SchenkComposer, and conducted preliminary user surveys.
Through analysis, we show the strong viability and
enjoyability of SchenkComposer.},
Doi = {10.1145/3580305.3599772},
Key = {fds372809}
}
@article{fds372520,
Author = {Gao, Q and Ji, Z and Wang, L and Owzar, K and Li, Q-J and Chan, C and Xie,
J},
Title = {SifiNet: A robust and accurate method to identify feature
gene sets and annotate cells.},
Journal = {bioRxiv},
Year = {2023},
Month = {August},
url = {http://dx.doi.org/10.1101/2023.05.24.541352},
Abstract = {SifiNet is a robust and accurate computational pipeline for
identifying distinct gene sets, extracting and annotating
cellular subpopulations, and elucidating intrinsic
relationships among these subpopulations. Uniquely, SifiNet
bypasses the cell clustering stage, commonly integrated into
other cellular annotation pipelines, thereby circumventing
potential inaccuracies in clustering that may compromise
subsequent analyses. Consequently, SifiNet has demonstrated
superior performance in multiple experimental datasets
compared with other state-of-the-art methods. SifiNet can
analyze both single-cell RNA and ATAC sequencing data,
thereby rendering comprehensive multiomic cellular profiles.
It is conveniently available as an open-source R
package.},
Doi = {10.1101/2023.05.24.541352},
Key = {fds372520}
}
@article{fds371623,
Author = {Autry, E and Carter, D and Herschlag, GJ and Hunter, Z and Mattingly,
JC},
Title = {METROPOLIZED FOREST RECOMBINATION FOR MONTE CARLO SAMPLING
OF GRAPH PARTITIONS},
Journal = {SIAM Journal on Applied Mathematics},
Volume = {83},
Number = {4},
Pages = {1366-1391},
Publisher = {Society for Industrial & Applied Mathematics
(SIAM)},
Year = {2023},
Month = {August},
url = {http://dx.doi.org/10.1137/21M1418010},
Abstract = {We develop a new Markov chain on graph partitions that makes
relatively global moves yet is computationally feasible to
be used as the proposal in the Metropolis-Hastings method.
Our resulting algorithm is able to sample from a specified
measure on partitions or spanning forests. Being able to
sample from a specified measure is a requirement of what we
consider as the gold standard in quantifying the extent to
which a particular map is a gerrymander. Our proposal chain
modifies the recently developed method called recombination
(ReCom), which draws spanning trees on joined partitions and
then randomly cuts them to repartition. We improve the
computational efficiency by augmenting the statespace from
partitions to spanning forests. The extra information
accelerates the computation of the forward and backward
proposal probabilities which are required for the
Metropolis-Hastings algorithm. We demonstrate this method by
sampling redistricting plans on several measures of interest
and find promising convergence results on several key
observables of interest. We also explore some limitations in
the measures that are efficient to sample from and
investigate the feasibility of using parallel tempering to
extend this space of measures.},
Doi = {10.1137/21M1418010},
Key = {fds371623}
}
@article{fds371472,
Author = {Liu, R and Li, M and Dunson, DB},
Title = {PPA: Principal parcellation analysis for brain connectomes
and multiple traits.},
Journal = {NeuroImage},
Volume = {276},
Pages = {120214},
Year = {2023},
Month = {August},
url = {http://dx.doi.org/10.1016/j.neuroimage.2023.120214},
Abstract = {Our understanding of the structure of the brain and its
relationships with human traits is largely determined by how
we represent the structural connectome. Standard practice
divides the brain into regions of interest (ROIs) and
represents the connectome as an adjacency matrix having
cells measuring connectivity between pairs of ROIs.
Statistical analyses are then heavily driven by the (largely
arbitrary) choice of ROIs. In this article, we propose a
human trait prediction framework utilizing a
tractography-based representation of the brain connectome,
which clusters fiber endpoints to define a data-driven white
matter parcellation targeted to explain variation among
individuals and predict human traits. This leads to
Principal Parcellation Analysis (PPA), representing
individual brain connectomes by compositional vectors
building on a basis system of fiber bundles that captures
the connectivity at the population level. PPA eliminates the
need to choose atlases and ROIs a priori, and provides a
simpler, vector-valued representation that facilitates
easier statistical analysis compared to the complex graph
structures encountered in classical connectome analyses. We
illustrate the proposed approach through applications to
data from the Human Connectome Project (HCP) and show that
PPA connectomes improve power in predicting human traits
over state-of-the-art methods based on classical
connectomes, while dramatically improving parsimony and
maintaining interpretability. Our PPA package is publicly
available on GitHub, and can be implemented routinely for
diffusion image data.},
Doi = {10.1016/j.neuroimage.2023.120214},
Key = {fds371472}
}
@article{fds376096,
Author = {Talbot, A and Dunson, D and Dzirasa, K and Carlson,
D},
Title = {Estimating a brain network predictive of stress and genotype
with supervised autoencoders.},
Journal = {J R Stat Soc Ser C Appl Stat},
Volume = {72},
Number = {4},
Pages = {912-936},
Year = {2023},
Month = {August},
url = {http://dx.doi.org/10.1093/jrsssc/qlad035},
Abstract = {Targeted brain stimulation has the potential to treat mental
illnesses. We develop an approach to help design protocols
by identifying relevant multi-region electrical dynamics.
Our approach models these dynamics as a superposition of
latent networks, where the latent variables predict a
relevant outcome. We use supervised autoencoders (SAEs) to
improve predictive performance in this context, describe the
conditions where SAEs improve predictions, and provide
modelling constraints to ensure biological relevance. We
experimentally validate our approach by finding a network
associated with stress that aligns with a previous
stimulation protocol and characterizing a genotype
associated with bipolar disorder.},
Doi = {10.1093/jrsssc/qlad035},
Key = {fds376096}
}
@article{fds371669,
Author = {Chen, J and Engelhard, M and Henao, R and Berchuck, S and Eichner, B and Perrin, EM and Sapiro, G and Dawson, G},
Title = {Enhancing early autism prediction based on electronic
records using clinical narratives.},
Journal = {J Biomed Inform},
Volume = {144},
Pages = {104390},
Year = {2023},
Month = {August},
url = {http://dx.doi.org/10.1016/j.jbi.2023.104390},
Abstract = {Recent work has shown that predictive models can be applied
to structured electronic health record (EHR) data to
stratify autism likelihood from an early age (<1 year).
Integrating clinical narratives (or notes) with structured
data has been shown to improve prediction performance in
other clinical applications, but the added predictive value
of this information in early autism prediction has not yet
been explored. In this study, we aimed to enhance the
performance of early autism prediction by using both
structured EHR data and clinical narratives. We built models
based on structured data and clinical narratives separately,
and then an ensemble model that integrated both sources of
data. We assessed the predictive value of these models from
Duke University Health System over a 14-year span to
evaluate ensemble models predicting later autism diagnosis
(by age 4 years) from data collected from ages 30 to
360 days. Our sample included 11,750 children above by age
3 years (385 meeting autism diagnostic criteria). The
ensemble model for autism prediction showed superior
performance and at age 30 days achieved 46.8% sensitivity
(95% confidence interval, CI: 22.0%, 52.9%), 28.0% positive
predictive value (PPV) at high (90%) specificity (CI: 2.0%,
33.1%), and AUC4 (with at least 4-year follow-up for
controls) reaching 0.769 (CI: 0.715, 0.811). Prediction by
360 days achieved 44.5% sensitivity (CI: 23.6%, 62.9%),
and 13.7% PPV at high (90%) specificity (CI: 9.6%, 18.9%),
and AUC4 reaching 0.797 (CI: 0.746, 0.840). Results show
that incorporating clinical narratives in early autism
prediction achieved promising accuracy by age 30 days,
outperforming models based on structured data only.
Furthermore, findings suggest that additional features
learned from clinician narratives might be hypothesis
generating for understanding early development in
autism.},
Doi = {10.1016/j.jbi.2023.104390},
Key = {fds371669}
}
@article{fds374487,
Author = {Autry, E and Carter, D and Herschlag, GJ and Hunter, Z and Mattingly,
JC},
Title = {METROPOLIZED FOREST RECOMBINATION FOR MONTE CARLO SAMPLING
OF GRAPH PARTITIONS},
Journal = {SIAM Journal on Applied Mathematics},
Volume = {83},
Number = {4},
Pages = {1366-1391},
Year = {2023},
Month = {August},
url = {http://dx.doi.org/10.1137/21M1418010},
Abstract = {We develop a new Markov chain on graph partitions that makes
relatively global moves yet is computationally feasible to
be used as the proposal in the Metropolis-Hastings method.
Our resulting algorithm is able to sample from a specified
measure on partitions or spanning forests. Being able to
sample from a specified measure is a requirement of what we
consider as the gold standard in quantifying the extent to
which a particular map is a gerrymander. Our proposal chain
modifies the recently developed method called recombination
(ReCom), which draws spanning trees on joined partitions and
then randomly cuts them to repartition. We improve the
computational efficiency by augmenting the statespace from
partitions to spanning forests. The extra information
accelerates the computation of the forward and backward
proposal probabilities which are required for the
Metropolis-Hastings algorithm. We demonstrate this method by
sampling redistricting plans on several measures of interest
and find promising convergence results on several key
observables of interest. We also explore some limitations in
the measures that are efficient to sample from and
investigate the feasibility of using parallel tempering to
extend this space of measures.},
Doi = {10.1137/21M1418010},
Key = {fds374487}
}
@article{fds371244,
Author = {Parikh, H and Hoffman, K and Sun, H and Zafar, SF and Ge, W and Jing, J and Liu, L and Sun, J and Struck, A and Volfovsky, A and Rudin, C and Westover,
MB},
Title = {Effects of epileptiform activity on discharge outcome in
critically ill patients in the USA: a retrospective
cross-sectional study.},
Journal = {The Lancet. Digital health},
Volume = {5},
Number = {8},
Pages = {e495-e502},
Year = {2023},
Month = {August},
url = {http://dx.doi.org/10.1016/s2589-7500(23)00088-2},
Abstract = {<h4>Background</h4>Epileptiform activity is associated with
worse patient outcomes, including increased risk of
disability and death. However, the effect of epileptiform
activity on neurological outcome is confounded by the
feedback between treatment with antiseizure medications and
epileptiform activity burden. We aimed to quantify the
heterogeneous effects of epileptiform activity with an
interpretability-centred approach.<h4>Methods</h4>We did a
retrospective, cross-sectional study of patients in the
intensive care unit who were admitted to Massachusetts
General Hospital (Boston, MA, USA). Participants were aged
18 years or older and had electrographic epileptiform
activity identified by a clinical neurophysiologist or
epileptologist. The outcome was the dichotomised modified
Rankin Scale (mRS) at discharge and the exposure was
epileptiform activity burden defined as mean or maximum
proportion of time spent with epileptiform activity in 6 h
windows in the first 24 h of electroencephalography. We
estimated the change in discharge mRS if everyone in the
dataset had experienced a specific epileptiform activity
burden and were untreated. We combined pharmacological
modelling with an interpretable matching method to account
for confounding and epileptiform activity-antiseizure
medication feedback. The quality of the matched groups was
validated by the neurologists.<h4>Findings</h4>Between Dec
1, 2011, and Oct 14, 2017, 1514 patients were admitted to
Massachusetts General Hospital intensive care unit, 995
(66%) of whom were included in the analysis. Compared with
patients with a maximum epileptiform activity of 0 to less
than 25%, patients with a maximum epileptiform activity
burden of 75% or more when untreated had a mean 22·27% (SD
0·92) increased chance of a poor outcome (severe disability
or death). Moderate but long-lasting epileptiform activity
(mean epileptiform activity burden 2% to <10%) increased the
risk of a poor outcome by mean 13·52% (SD 1·93). The
effect sizes were heterogeneous depending on preadmission
profile-eg, patients with hypoxic-ischaemic encephalopathy
or acquired brain injury were more adversely affected
compared with patients without these conditions.<h4>Interpretation</h4>Our
results suggest that interventions should put a higher
priority on patients with an average epileptiform activity
burden 10% or greater, and treatment should be more
conservative when maximum epileptiform activity burden is
low. Treatment should also be tailored to individual
preadmission profiles because the potential for epileptiform
activity to cause harm depends on age, medical history, and
reason for admission.<h4>Funding</h4>National Institutes of
Health and National Science Foundation.},
Doi = {10.1016/s2589-7500(23)00088-2},
Key = {fds371244}
}
@article{fds371608,
Author = {Peloquin, J and Kirillova, A and Rudin, C and Brinson, LC and Gall,
K},
Title = {Prediction of tensile performance for 3D printed
photopolymer gyroid lattices using structural porosity, base
material properties, and machine learning},
Journal = {Materials and Design},
Volume = {232},
Year = {2023},
Month = {August},
url = {http://dx.doi.org/10.1016/j.matdes.2023.112126},
Abstract = {Advancements in additive manufacturing (AM) technology and
three-dimensional (3D) modeling software have enabled the
fabrication of parts with combinations of properties that
were impossible to achieve with traditional manufacturing
techniques. Porous designs such as truss-based and
sheet-based lattices have gained much attention in recent
years due to their versatility. The multitude of lattice
design possibilities, coupled with a growing list of
available 3D printing materials, has provided a vast range
of 3D printable structures that can be used to achieve
desired performance. However, the process of computationally
or experimentally evaluating many combinations of base
material and lattice design for a given application is
impractical. This research proposes a framework for quickly
predicting key mechanical properties of 3D printed gyroid
lattices using information about the base material and
porosity of the structure. Experimental data was gathered to
train a simple, interpretable, and accurate kernel ridge
regression machine learning model. The performance of the
model was then compared to numerical simulation data and
demonstrated similar accuracy at a fraction of the
computation time. Ultimately, the model development serves
as an advancement in ML-driven mechanical property
prediction that can be used to guide extension of current
and future models.},
Doi = {10.1016/j.matdes.2023.112126},
Key = {fds371608}
}
@article{fds371888,
Author = {Peloquin, J and Kirillova, A and Mathey, E and Rudin, C and Brinson, LC and Gall, K},
Title = {Tensile performance data of 3D printed photopolymer gyroid
lattices.},
Journal = {Data in brief},
Volume = {49},
Pages = {109396},
Year = {2023},
Month = {August},
url = {http://dx.doi.org/10.1016/j.dib.2023.109396},
Abstract = {Additive manufacturing has provided the ability to
manufacture complex structures using a wide variety of
materials and geometries. Structures such as triply periodic
minimal surface (TPMS) lattices have been incorporated into
products across many fields due to their unique combinations
of mechanical, geometric, and physical properties. Yet, the
near limitless possibility of combining geometry and
material into these lattices leaves much to be discovered.
This article provides a dataset of experimentally gathered
tensile stress-strain curves and measured porosity values
for 389 unique gyroid lattice structures manufactured using
vat photopolymerization 3D printing. The lattice samples
were printed from one of twenty different photopolymer
materials available from either Formlabs, LOCTITE AM, or
ETEC that range from strong and brittle to elastic and
ductile and were printed on commercially available 3D
printers, specifically the Formlabs Form2, Prusa SL1, and
ETEC Envision One cDLM Mechanical. The stress-strain curves
were recorded with an MTS Criterion C43.504 mechanical
testing apparatus and following ASTM standards, and the void
fraction or "porosity" of each lattice was measured using a
calibrated scale. This data serves as a valuable resource
for use in the development of novel printing materials and
lattice geometries and provides insight into the influence
of photopolymer material properties on the printability,
geometric accuracy, and mechanical performance of 3D printed
lattice structures. The data described in this article was
used to train a machine learning model capable of predicting
mechanical properties of 3D printed gyroid lattices based on
the base mechanical properties of the printing material and
porosity of the lattice in the research article
[1].},
Doi = {10.1016/j.dib.2023.109396},
Key = {fds371888}
}
@article{fds373056,
Author = {McDonald, SM and Augustine, EK and Lanners, Q and Rudin, C and Catherine
Brinson, L and Becker, ML},
Title = {Applied machine learning as a driver for polymeric
biomaterials design.},
Journal = {Nature communications},
Volume = {14},
Number = {1},
Pages = {4838},
Year = {2023},
Month = {August},
url = {http://dx.doi.org/10.1038/s41467-023-40459-8},
Abstract = {Polymers are ubiquitous to almost every aspect of modern
society and their use in medical products is similarly
pervasive. Despite this, the diversity in commercial
polymers used in medicine is stunningly low. Considerable
time and resources have been extended over the years towards
the development of new polymeric biomaterials which address
unmet needs left by the current generation of medical-grade
polymers. Machine learning (ML) presents an unprecedented
opportunity in this field to bypass the need for
trial-and-error synthesis, thus reducing the time and
resources invested into new discoveries critical for
advancing medical treatments. Current efforts pioneering
applied ML in polymer design have employed combinatorial and
high throughput experimental design to address data
availability concerns. However, the lack of available and
standardized characterization of parameters relevant to
medicine, including degradation time and biocompatibility,
represents a nearly insurmountable obstacle to ML-aided
design of biomaterials. Herein, we identify a gap at the
intersection of applied ML and biomedical polymer design,
highlight current works at this junction more broadly and
provide an outlook on challenges and future
directions.},
Doi = {10.1038/s41467-023-40459-8},
Key = {fds373056}
}
@article{fds374518,
Author = {Li, S and Zhang, C and Zhang, Z and Zhao, H},
Title = {A data-driven and model-based accelerated Hamiltonian Monte
Carlo method for Bayesian elliptic inverse
problems},
Journal = {Statistics and Computing},
Volume = {33},
Number = {4},
Year = {2023},
Month = {August},
url = {http://dx.doi.org/10.1007/s11222-023-10262-y},
Abstract = {In this paper, we consider a Bayesian inverse problem
modeled by elliptic partial differential equations (PDEs).
Specifically, we propose a data-driven and model-based
approach to accelerate the Hamiltonian Monte Carlo (HMC)
method in solving large-scale Bayesian inverse problems. The
key idea is to exploit (model-based) and construct
(data-based) intrinsic approximate low-dimensional structure
of the underlying problem which consists of two
components—a training component that computes a set of
data-driven basis to achieve significant dimension reduction
in the solution space, and a fast solving component that
computes the solution and its derivatives for a newly
sampled elliptic PDE with the constructed data-driven basis.
Hence we develop an effective data and model-based approach
for the Bayesian inverse problem and overcome the typical
computational bottleneck of HMC—repeated evaluation of the
Hamiltonian involving the solution (and its derivatives)
modeled by a complex system, a multiscale elliptic PDE in
our case. Finally, we present numerical examples to
demonstrate the accuracy and efficiency of the proposed
method.},
Doi = {10.1007/s11222-023-10262-y},
Key = {fds374518}
}
@article{fds372525,
Author = {Przybyło, J and Wei, F},
Title = {On the Asymptotic Confirmation of the Faudree–Lehel
Conjecture for General Graphs},
Journal = {Combinatorica},
Volume = {43},
Number = {4},
Pages = {791-826},
Year = {2023},
Month = {August},
url = {http://dx.doi.org/10.1007/s00493-023-00036-5},
Abstract = {Given a simple graph G, the irregularity strength of G,
denoted by s(G), is the least positive integer k such that
there is a weight assignment on edges f: E(G) → { 1 , 2 ,
⋯ , k} attributing distinct weighted degrees: f~ (v) : =
∑ u:{u,v}∈E(G)f({ u, v}) to all vertices v∈ V(G) . It
is straightforward that s(G) ≥ n/ d for every d-regular
graph G on n vertices with d> 1 . In 1987, Faudree and Lehel
conjectured in turn that there is an absolute constant c
such that s(G) ≤ n/ d+ c for all such graphs. Even though
the conjecture has remained open in almost all relevant
cases, it is more generally believed that there exists a
universal constant c such that s(G) ≤ n/ δ+ c for every
graph G on n vertices with minimum degree δ≥ 1 which does
not contain an isolated edge; In this paper we confirm that
the generalized Faudree–Lehel Conjecture holds for graphs
with δ≥ nβ where β is any fixed constant larger than
0.8; Furthermore, we confirm that the conjecture holds in
general asymptotically. That is, we prove that for any ε∈
(0 , 0.25) there exist absolute constants c1, c2 such that
for all graphs G on n vertices with minimum degree δ≥ 1
and without isolated edges, s(G)≤nδ(1+c1δε)+c2 ; We
thereby extend in various aspects and strengthen a recent
result of Przybyło, who showed that s(G)≤nd(1+1lnε/19n)=nd(1+o(1))
for d-regular graphs with d∈ [ln 1+εn, n/ ln εn] . We
also improve the earlier general upper bound: s(G)<6nδ+6 of
Kalkowski, Karoński and Pfender.},
Doi = {10.1007/s00493-023-00036-5},
Key = {fds372525}
}
@article{fds372207,
Author = {Ciocanel, M-V and Ding, L and Mastromatteo, L and Reichheld, S and Cabral, S and Mowry, K and Sandstede, B},
Title = {Parameter identifiability in PDE models of fluorescence
recovery after photobleaching},
Year = {2023},
Month = {July},
Key = {fds372207}
}
@article{fds373378,
Author = {Hughes, J},
Title = {Lagrangian fillings in $A$-type and their Kálmán loop
orbits},
Journal = {Revista Matemática Iberoamericana},
Volume = {39},
Number = {5},
Pages = {1681-1723},
Publisher = {European Mathematical Society - EMS - Publishing House
GmbH},
Year = {2023},
Month = {July},
url = {http://dx.doi.org/10.4171/rmi/1436},
Doi = {10.4171/rmi/1436},
Key = {fds373378}
}
@article{fds371671,
Author = {Feiger, B and Jensen, CW and Bryner, BS and Segars, WP and Randles,
A},
Title = {Modeling the effect of patient size on cerebral perfusion
during veno-arterial extracorporeal membrane
oxygenation.},
Journal = {Perfusion},
Pages = {2676591231187962},
Year = {2023},
Month = {July},
url = {http://dx.doi.org/10.1177/02676591231187962},
Abstract = {INTRODUCTION: A well-known complication of veno-arterial
extracorporeal membrane oxygenation (VA ECMO) is
differential hypoxia, in which poorly-oxygenated blood
ejected from the left ventricle mixes with and displaces
well-oxygenated blood from the circuit, thereby causing
cerebral hypoxia and ischemia. We sought to characterize the
impact of patient size and anatomy on cerebral perfusion
under a range of different VA ECMO flow conditions. METHODS:
We use one-dimensional (1D) flow simulations to investigate
mixing zone location and cerebral perfusion across 10
different levels of VA ECMO support in eight semi-idealized
patient geometries, for a total of 80 scenarios. Measured
outcomes included mixing zone location and cerebral blood
flow (CBF). RESULTS: Depending on patient anatomy, we found
that a VA ECMO support ranging between 67-97% of a patient's
ideal cardiac output was needed to perfuse the brain. In
some cases, VA ECMO flows exceeding 90% of the patient's
ideal cardiac output are needed for adequate cerebral
perfusion. CONCLUSIONS: Individual patient anatomy markedly
affects mixing zone location and cerebral perfusion in VA
ECMO. Future fluid simulations of VA ECMO physiology should
incorporate varied patient sizes and geometries in order to
best provide insights toward reducing neurologic injury and
improved outcomes in this patient population.},
Doi = {10.1177/02676591231187962},
Key = {fds371671}
}
@article{fds371278,
Author = {Coffman, M and Di Martino and JM and Aiello, R and Carpenter, KLH and Chang, Z and Compton, S and Eichner, B and Espinosa, S and Flowers, J and Franz, L and Perochon, S and Krishnappa Babu and PR and Sapiro, G and Dawson, G},
Title = {Relationship between quantitative digital behavioral
features and clinical profiles in young autistic
children.},
Journal = {Autism Res},
Volume = {16},
Number = {7},
Pages = {1360-1374},
Year = {2023},
Month = {July},
url = {http://dx.doi.org/10.1002/aur.2955},
Abstract = {Early behavioral markers for autism include differences in
social attention and orienting in response to one's name
when called, and differences in body movements and motor
abilities. More efficient, scalable, objective, and reliable
measures of these behaviors could improve early screening
for autism. This study evaluated whether objective and
quantitative measures of autism-related behaviors elicited
from an app (SenseToKnow) administered on a smartphone or
tablet and measured via computer vision analysis (CVA) are
correlated with standardized caregiver-report and clinician
administered measures of autism-related behaviors and
cognitive, language, and motor abilities. This is an
essential step in establishing the concurrent validity of a
digital phenotyping approach. In a sample of 485 toddlers,
43 of whom were diagnosed with autism, we found that
CVA-based gaze variables related to social attention were
associated with the level of autism-related behaviors. Two
language-related behaviors measured via the app, attention
to people during a conversation and responding to one's name
being called, were associated with children's language
skills. Finally, performance during a bubble popping game
was associated with fine motor skills. These findings
provide initial support for the concurrent validity of the
SenseToKnow app and its potential utility in identifying
clinical profiles associated with autism. Future research is
needed to determine whether the app can be used as an autism
screening tool, can reliably stratify autism-related
behaviors, and measure changes in autism-related behaviors
over time.},
Doi = {10.1002/aur.2955},
Key = {fds371278}
}
@article{fds371136,
Author = {Roychowdhury, S and Draeger, EW and Randles, A},
Title = {Establishing metrics to quantify spatial similarity in
spherical and red blood cell distributions},
Journal = {Journal of Computational Science},
Volume = {71},
Year = {2023},
Month = {July},
url = {http://dx.doi.org/10.1016/j.jocs.2023.102060},
Abstract = {As computational power increases and systems with millions
of red blood cells can be simulated, it is important to note
that varying spatial distributions of cells may affect
simulation outcomes. Since a single simulation may not
represent the ensemble behavior, many different
configurations may need to be sampled to adequately assess
the entire collection of potential cell arrangements. In
order to determine both the number of distributions needed
and which ones to run, we must first establish methods to
identify well-generated, randomly placed cell distributions
and to quantify distinct cell configurations. We utilize
metrics to assess (1) the presence of any underlying
structure to the initial cell distribution and (2)
similarity between cell configurations. We propose the use
of the radial distribution function to identify long-range
structure in a cell configuration and apply it to a randomly
distributed and structured set of red blood cells. To
quantify spatial similarity between two configurations, we
make use of the Jaccard index, and characterize sets of red
blood cell and sphere initializations. As an extension to
our work submitted to the International Conference on
Computational Science (Roychowdhury et al., 2022), we
significantly increase our data set size from 72 to 1048
cells, include a similar set of studies using spheres,
compare the effects of varying sphere size, and utilize the
Jaccard index distribution to probe sets of extremely
similar configurations. Our results show that the radial
distribution function can be used as a metric to determine
long-range structure in both distributions of spheres and
RBCs. We determine that the ideal case of spheres within a
cube versus bi-concave shaped cells within a cylinder
affects the shape of the Jaccard index distributions, as
well as the range of Jaccard values, showing that both the
shape of particle and the domain may play a role. We also
find that the distribution is able to capture very similar
configurations through Jaccard index values greater than 95%
when appending several nearly identical configurations into
the data set.},
Doi = {10.1016/j.jocs.2023.102060},
Key = {fds371136}
}
@article{fds371517,
Author = {Tanade, C and Putney, S and Randles, A},
Title = {Establishing massively parallel models to examine the
influence of cell heterogeneity on tumor
growth},
Journal = {Journal of Computational Science},
Volume = {71},
Year = {2023},
Month = {July},
url = {http://dx.doi.org/10.1016/j.jocs.2023.102059},
Abstract = {Parallel 3D cellular automaton models of tumor growth can
efficiently capture emergent morphology. We extended a 2D
growth model to 3D to examine the influence of symmetric
division in heterogeneous tumors on growth dynamics. As
extending to 3D severely increased time-to-solution, we
parallelized the model using N-body, lattice halo exchange,
and adaptive communication schemes. Supplementing prior work
from Tanade et al. (2022), we demonstrated over 55x speedup
and evaluated performance on ≤30 nodes of Stampede2. This
work established a framework to parametrically study 3D
growth dynamics, and of the cancer phenotypes we studied,
the parallel model better scaled when tumor boundaries were
radially symmetric.},
Doi = {10.1016/j.jocs.2023.102059},
Key = {fds371517}
}
@article{fds371627,
Author = {Eid, A-M and Elgamal, M and Gonzalez-Fiol, A and Shelley, KH and Wu,
H-T and Alian, AA},
Title = {Using the ear photoplethysmographic waveform as an early
indicator of central hypovolemia in healthy volunteers
utilizing LBNP induced hypovolemia model.},
Journal = {Physiological measurement},
Volume = {44},
Number = {5},
Year = {2023},
Month = {July},
url = {http://dx.doi.org/10.1088/1361-6579/acd165},
Abstract = {<i>Objective</i>. To study the photoplethysmographic (PPG)
waveforms of different locations (ear and finger) during
lower body negative pressure (LBNP) induced hypovolemia.
Then, to determine whether the PPG waveform can be used to
detect hypovolemia during the early stage of
LBNP.<i>Approach</i>. 36 healthy volunteers were recruited
for progressive LBNP induced hypovolemia, with an endpoint
of -60 mmHg or development of hypoperfusion symptoms,
whichever comes first. Subjects tolerating the entire
protocol without symptoms were designated as high tolerance
(HT), while symptomatic subjects were designated as low
tolerance (LT). Subjects were monitored with an
electrocardiogram, continuous noninvasive blood pressure
monitor, and two pulse oximetry probes, one on the ear
(Xhale) and one the finger (Nellcor). Stroke volume was
measured non-invasively utilizing Non-Invasive Cardiac
Output Monitor (NICOM, Cheetah Medical). The waveform
morphology was analyzed using novel PPG waveforms indices,
including phase hemodynamic index (PHI) and amplitude
hemodyamaic index and were evaluated from the ear PPG and
finger PPG at different LBNP stages.<i>Main results</i>. The
PHI, particularly the phase relationship between the second
harmonic and the fundamental component of the ear PPG
denoted as∇φ2,during the early stage of LBNP (-15 mmHg)
in the HT and LT groups is statistically significantly
different (<i>p</i>value = 0.0033) with the area under curve
0.81 (CI: 0.616-0.926). The other indices are not
significantly different. The 5 fold cross validation shows
that∇φ2during the early stage of LBNP (-15 mmHg) as the
single index could predict the tolerance of the subject with
the sensitivity, specificity, accuracy and<i>F</i>1 as 0.771
± 0.192, 0.71 ± 0.107, 0.7 ± 0.1 and 0.771 ± 0.192
respectively.<i>Significance</i>. The ear's PPG PHI which
compares the phases of the fundamental and second harmonic
has the potential to be used as an early predictor of
central hypovolemia.},
Doi = {10.1088/1361-6579/acd165},
Key = {fds371627}
}
@article{fds370318,
Author = {Soloveychik, I and Tarokh, V},
Title = {Region selection in Markov random fields: Gaussian
case},
Journal = {Journal of Multivariate Analysis},
Volume = {196},
Year = {2023},
Month = {July},
url = {http://dx.doi.org/10.1016/j.jmva.2023.105178},
Abstract = {We consider the problem of model selection in Gaussian
Markov fields in the sample deficient scenario. The
benchmark information-theoretic results in the case of
d-regular graphs require the number of samples to be at
least proportional to the logarithm of the number of
vertices to allow consistent graph recovery. When the number
of samples is less than this amount, reliable recovery of
all edges is impossible. In many applications, it is more
important to learn the distribution of the edge (coupling)
parameters over the network than the specific locations of
the edges. Assuming that the entire graph can be partitioned
into a number of spatial regions with similar edge
parameters and reasonably regular boundaries, we develop new
information-theoretic sample complexity bounds and show that
a bounded number of samples can be sufficient to
consistently recover these regions. Finally, we introduce
and analyze an efficient region growing algorithm capable of
recovering the regions with high accuracy. We show that it
is consistent and demonstrate its performance benefits in
synthetic simulations.},
Doi = {10.1016/j.jmva.2023.105178},
Key = {fds370318}
}
@article{fds370311,
Author = {Rotzoll, M and Regan, MH and Husty, ML and Hayes,
MJD},
Title = {Kinematic geometry of spatial RSSR mechanisms},
Journal = {Mechanism and Machine Theory},
Volume = {185},
Year = {2023},
Month = {July},
url = {http://dx.doi.org/10.1016/j.mechmachtheory.2023.105335},
Abstract = {Two different novel methods to derive the input–output
(IO) equation of arbitrary RSSR linkages are described. Both
methods share some common elements, i.e., they use the
standard Denavit–Hartenberg notation to first describe the
linkage as an open kinematic chain, and Study's kinematic
mapping to describe the displacement of the coordinate frame
attached to the end-effector of the chain with respect to
the relatively non-moving base frame. The kinematic closure
equation is obtained in the seven-dimensional projective
kinematic mapping image space by equating the eight Study
soma coordinates to the identity array. Then two methods are
successfully applied to eliminate the intermediate joint
angle parameters leading to the degree four biquadratic
implicit algebraic IO equation: (a) the linear
implicitisation algorithm, which can be applied after
rearranging the closure equation such that the linkage can
be viewed as two serial RS chains, and (b) numerical
elimination theory using pseudowitness sets. Both approaches
lead to the same IO equation. The utility of this algebraic
form of the IO equation is illustrated with three detailed
application examples.},
Doi = {10.1016/j.mechmachtheory.2023.105335},
Key = {fds370311}
}
@article{fds371967,
Author = {Dunlap, A and Gu, Y and Li, L},
Title = {Localization length of the $1+1$ continuum directed random
polymer},
Journal = {Annales Henri Poincaré},
Volume = {24},
Number = {7},
Pages = {2537-2555},
Publisher = {Springer Science and Business Media LLC},
Year = {2023},
Month = {July},
url = {http://dx.doi.org/10.1007/s00023-023-01288-z},
Abstract = {In this paper, we study the localization length of the
continuum directed polymer, defined as the distance between
the endpoints of two paths sampled independently from the
quenched polymer measure. We show that the localization
length converges in distribution in the thermodynamic limit,
and derive an explicit density formula of the limiting
distribution. As a consequence, we prove the $\frac32$-power
law decay of the density, confirming the physics prediction
of Hwa and Fisher (Phys Rev B 49(5):3136, 1994). Our proof
uses the recent result of Das and Zhu (Localization of the
continuum directed random polymer, 2022).},
Doi = {10.1007/s00023-023-01288-z},
Key = {fds371967}
}
@article{fds372448,
Author = {Yu, J and Lai, R and Li, W and Osher, S},
Title = {Computational mean-field games on manifolds},
Journal = {Journal of Computational Physics},
Volume = {484},
Pages = {112070-112070},
Publisher = {Elsevier BV},
Year = {2023},
Month = {July},
url = {http://dx.doi.org/10.1016/j.jcp.2023.112070},
Abstract = {Conventional Mean-field games/control study the behavior of
a large number of rational agents moving in Euclidean
spaces. In this work, we explore the mean-field games on
Riemannian manifolds. We formulate the mean-field game Nash
Equilibrium on manifolds. We also establish the equivalence
between the PDE system and the optimality conditions of the
associated variational form on manifolds. Based on the
triangular mesh representation of two-dimensional manifolds,
we design a proximal gradient method for variational
mean-field games. Our comprehensive numerical experiments on
various manifolds illustrate the effectiveness and
flexibility of the proposed model and numerical
methods.},
Doi = {10.1016/j.jcp.2023.112070},
Key = {fds372448}
}
@article{fds372436,
Author = {Zhang, R and Xin, R and Seltzer, M and Rudin, C},
Title = {Optimal Sparse Regression Trees},
Journal = {Proceedings of the 37th AAAI Conference on Artificial
Intelligence, AAAI 2023},
Volume = {37},
Pages = {11270-11279},
Year = {2023},
Month = {June},
ISBN = {9781577358800},
Abstract = {Regression trees are one of the oldest forms of AI models,
and their predictions can be made without a calculator,
which makes them broadly useful, particularly for
high-stakes applications. Within the large literature on
regression trees, there has been little effort towards full
provable optimization, mainly due to the computational
hardness of the problem. This work proposes a
dynamic-programming-with-bounds approach to the construction
of provably-optimal sparse regression trees. We leverage a
novel lower bound based on an optimal solution to the
k-Means clustering algorithm on one dimensional data. We are
often able to find optimal sparse trees in seconds, even for
challenging datasets that involve large numbers of samples
and highly-correlated features.},
Key = {fds372436}
}
@article{fds374307,
Author = {Hunt, S and Daily, SB and Viel, S and Boyd-Sinkler,
K},
Title = {Examining the Impact of Introductory Mathematics Courses on
Undergraduate Students' Desire to Pursue a STEM
Major},
Journal = {ASEE Annual Conference and Exposition, Conference
Proceedings},
Year = {2023},
Month = {June},
Key = {fds374307}
}
@article{fds374631,
Author = {Iyer, G and Lu, E and Nolen, J},
Title = {Using Bernoulli maps to accelerate mixing of a random walk
on the torus},
Journal = {Quarterly of Applied Mathematics},
Volume = {82},
Number = {2},
Pages = {359-390},
Publisher = {American Mathematical Society (AMS)},
Year = {2023},
Month = {June},
url = {http://dx.doi.org/10.1090/qam/1668},
Abstract = {<p>We study the mixing time of a random walk on the torus,
alternated with a Lebesgue measure preserving Bernoulli map.
Without the Bernoulli map, the mixing time of the random
walk alone is <inline-formula content-type="math/mathml"> ??
<mml:semantics> <mml:mrow> <mml:mi>O</mml:mi> <mml:mo
stretchy="false">(</mml:mo> <mml:mn>1</mml:mn> <mml:mrow
class="MJX-TeXAtom-ORD"> <mml:mo>/</mml:mo> </mml:mrow>
<mml:msup> <mml:mi>ε<!-- ε --></mml:mi> <mml:mn>2</mml:mn>
</mml:msup> <mml:mo stretchy="false">)</mml:mo> </mml:mrow>
<mml:annotation encoding="application/x-tex">O(1/\varepsilon
^2)</mml:annotation> </mml:semantics> </mml:math>
</inline-formula>, where <inline-formula
content-type="math/mathml"> ?? <mml:semantics>
<mml:mi>ε<!-- ε --></mml:mi> <mml:annotation
encoding="application/x-tex">\varepsilon</mml:annotation>
</mml:semantics> </mml:math> </inline-formula> is the step
size. Our main results show that for a class of Bernoulli
maps, when the random walk is alternated with the Bernoulli
map <inline-formula content-type="math/mathml"> ??
<mml:semantics> <mml:mi>φ<!-- φ --></mml:mi>
<mml:annotation encoding="application/x-tex">\varphi</mml:annotation>
</mml:semantics> </mml:math> </inline-formula> the mixing
time becomes <inline-formula content-type="math/mathml"> ??
<mml:semantics> <mml:mrow> <mml:mi>O</mml:mi> <mml:mo
stretchy="false">(</mml:mo> <mml:mo fence="false"
stretchy="false">|<!-- | --></mml:mo> <mml:mi>ln</mml:mi>
<mml:mo><!-- --></mml:mo> <mml:mi>ε<!-- ε
--></mml:mi> <mml:mo fence="false" stretchy="false">|<!-- |
--></mml:mo> <mml:mo stretchy="false">)</mml:mo> </mml:mrow>
<mml:annotation encoding="application/x-tex">O(\lvert \ln
\varepsilon \rvert )</mml:annotation> </mml:semantics>
</mml:math> </inline-formula>. We also study the
<italic>dissipation time</italic> of this process, and
obtain <inline-formula content-type="math/mathml"> ??
<mml:semantics> <mml:mrow> <mml:mi>O</mml:mi> <mml:mo
stretchy="false">(</mml:mo> <mml:mo fence="false"
stretchy="false">|<!-- | --></mml:mo> <mml:mi>ln</mml:mi>
<mml:mo><!-- --></mml:mo> <mml:mi>ε<!-- ε
--></mml:mi> <mml:mo fence="false" stretchy="false">|<!-- |
--></mml:mo> <mml:mo stretchy="false">)</mml:mo> </mml:mrow>
<mml:annotation encoding="application/x-tex">O(\lvert \ln
\varepsilon \rvert )</mml:annotation> </mml:semantics>
</mml:math> </inline-formula> upper and lower bounds with
explicit constants.</p>},
Doi = {10.1090/qam/1668},
Key = {fds374631}
}
@article{fds371293,
Author = {Motta, FC and McGoff, K and Moseley, RC and Cho, C-Y and Kelliher, CM and Smith, LM and Ortiz, MS and Leman, AR and Campione, SA and Devos, N and Chaorattanakawee, S and Uthaimongkol, N and Kuntawunginn, W and Thongpiam, C and Thamnurak, C and Arsanok, M and Wojnarski, M and Vanchayangkul, P and Boonyalai, N and Smith, PL and Spring, MD and Jongsakul, K and Chuang, I and Harer, J and Haase,
SB},
Title = {The parasite intraerythrocytic cycle and human circadian
cycle are coupled during malaria infection.},
Journal = {Proceedings of the National Academy of Sciences of the
United States of America},
Volume = {120},
Number = {24},
Pages = {e2216522120},
Year = {2023},
Month = {June},
url = {http://dx.doi.org/10.1073/pnas.2216522120},
Abstract = {During infections with the malaria parasites <i>Plasmodium
vivax</i>, patients exhibit rhythmic fevers every 48 h.
These fever cycles correspond with the time the parasites
take to traverse the intraerythrocytic cycle (IEC). In other
<i>Plasmodium</i> species that infect either humans or mice,
the IEC is likely guided by a parasite-intrinsic clock
[Rijo-Ferreira<i>et al.</i>, <i>Science</i> <b>368</b>,
746-753 (2020); Smith <i>et al</i>., <i>Science</i>
<b>368</b>, 754-759 (2020)], suggesting that intrinsic clock
mechanisms may be a fundamental feature of malaria
parasites. Moreover, because <i>Plasmodium</i> cycle times
are multiples of 24 h, the IECs may be coordinated with the
host circadian clock(s). Such coordination could explain the
synchronization of the parasite population in the host and
enable alignment of IEC and circadian cycle phases. We
utilized an ex vivo culture of whole blood from patients
infected with <i>P. vivax</i> to examine the dynamics of the
host circadian transcriptome and the parasite IEC
transcriptome. Transcriptome dynamics revealed that the
phases of the host circadian cycle and the parasite IEC are
correlated across multiple patients, showing that the cycles
are phase coupled. In mouse model systems, host-parasite
cycle coupling appears to provide a selective advantage for
the parasite. Thus, understanding how host and parasite
cycles are coupled in humans could enable antimalarial
therapies that disrupt this coupling.},
Doi = {10.1073/pnas.2216522120},
Key = {fds371293}
}
@article{fds369395,
Author = {Mubayi, D and Mukherjee, S},
Title = {Triangles in graphs without bipartite suspensions},
Journal = {Discrete Mathematics},
Volume = {346},
Number = {6},
Year = {2023},
Month = {June},
url = {http://dx.doi.org/10.1016/j.disc.2023.113355},
Abstract = {Given graphs T and H, the generalized Turán number
ex(n,T,H) is the maximum number of copies of T in an
n-vertex graph with no copies of H. Alon and Shikhelman,
using a result of Erdős, determined the asymptotics of
ex(n,K3,H) when the chromatic number of H is greater than
three and proved several results when H is bipartite. We
consider this problem when H has chromatic number three.
Even this special case for the following relatively simple
three chromatic graphs appears to be challenging. The
suspension Hˆ of a graph H is the graph obtained from H by
adding a new vertex adjacent to all vertices of H. We give
new upper and lower bounds on ex(n,K3,Hˆ) when H is a path,
even cycle, or complete bipartite graph. One of the main
tools we use is the triangle removal lemma, but it is
unclear if much stronger statements can be proved without
using the removal lemma.},
Doi = {10.1016/j.disc.2023.113355},
Key = {fds369395}
}
@article{fds369944,
Author = {Shi, A and Berchuck, SI and Jammal, AA and Singh, G and Hunt, S and Roche,
K and Mukherjee, S and Medeiros, FA},
Title = {Identifying Risk Factors for Blindness From Glaucoma at
First Presentation to a Tertiary Clinic.},
Journal = {Am J Ophthalmol},
Volume = {250},
Pages = {130-137},
Year = {2023},
Month = {June},
url = {http://dx.doi.org/10.1016/j.ajo.2023.02.006},
Abstract = {PURPOSE: Glaucoma is the leading cause of irreversible
blindness, a crippling disability resulting in higher risks
of chronic health conditions. To better understand
disparities in blindness risk, we identified risk factors of
blindness on first presentation to a glaucoma clinic using a
large clinical database. DESIGN: Retrospective
cross-sectional study. METHODS: We used electronic health
records of glaucoma patients from the Duke Ophthalmic
Registry. International Classification of Diseases codes
were used to identify glaucoma and exclude concurrent
diseases. Blindness classification was based on the
definition of legal blindness. Risk factors included gender,
race, marital status, age, intraocular pressure, diabetes
history, income level, and education. Odds ratios (ORs) and
95% CIs were calculated for risk factors using univariable
and multivariable logistic regression. RESULTS: Our cohort
consisted of 3753 patients, with 192 (5%) blind on first
presentation. In univariable models, African American /
Black race (OR 2.48, 95% CI 1.83-3.36), single marital
status (1.74, 95% CI 1.25-2.44), prior diabetes diagnosis
(2.23, 95% CI 1.52-3.27), and higher intraocular pressure
(1.29 per 1 SD higher, 95% CI 1.13-1.46) were associated
with increased risk of presenting blind, whereas higher
annual income (0.75, 95% CI 0.65-0.86) and education (0.77,
95% CI 0.69-0.85) were associated with lower risk. These
associations remained significant and in the same direction
in a multivariable model apart from income, which became
insignificant. CONCLUSIONS: Using a large real-world
clinical database, we identified risk factors associated
with presentation with blindness among glaucoma patients.
Our results highlight disparities in health care outcomes
and indicate the importance of targeted education to reduce
disparities in blindness.},
Doi = {10.1016/j.ajo.2023.02.006},
Key = {fds369944}
}
@article{fds368760,
Author = {Wang, Y and Li, X and Konanur, M and Konkel, B and Seyferth, E and Brajer,
N and Liu, J-G and Bashir, MR and Lafata, KJ},
Title = {Towards optimal deep fusion of imaging and clinical data via
a model-based description of fusion quality.},
Journal = {Med Phys},
Volume = {50},
Number = {6},
Pages = {3526-3537},
Year = {2023},
Month = {June},
url = {http://dx.doi.org/10.1002/mp.16181},
Abstract = {BACKGROUND: Due to intrinsic differences in data formatting,
data structure, and underlying semantic information, the
integration of imaging data with clinical data can be
non-trivial. Optimal integration requires robust data
fusion, that is, the process of integrating multiple data
sources to produce more useful information than captured by
individual data sources. Here, we introduce the concept of
fusion quality for deep learning problems involving imaging
and clinical data. We first provide a general theoretical
framework and numerical validation of our technique. To
demonstrate real-world applicability, we then apply our
technique to optimize the fusion of CT imaging and hepatic
blood markers to estimate portal venous hypertension, which
is linked to prognosis in patients with cirrhosis of the
liver. PURPOSE: To develop a measurement method of optimal
data fusion quality deep learning problems utilizing both
imaging data and clinical data. METHODS: Our approach is
based on modeling the fully connected layer (FCL) of a
convolutional neural network (CNN) as a potential function,
whose distribution takes the form of the classical Gibbs
measure. The features of the FCL are then modeled as random
variables governed by state functions, which are interpreted
as the different data sources to be fused. The probability
density of each source, relative to the probability density
of the FCL, represents a quantitative measure of
source-bias. To minimize this source-bias and optimize CNN
performance, we implement a vector-growing encoding scheme
called positional encoding, where low-dimensional clinical
data are transcribed into a rich feature space that
complements high-dimensional imaging features. We first
provide a numerical validation of our approach based on
simulated Gaussian processes. We then applied our approach
to patient data, where we optimized the fusion of CT images
with blood markers to predict portal venous hypertension in
patients with cirrhosis of the liver. This patient study was
based on a modified ResNet-152 model that incorporates both
images and blood markers as input. These two data sources
were processed in parallel, fused into a single FCL, and
optimized based on our fusion quality framework. RESULTS:
Numerical validation of our approach confirmed that the
probability density function of a fused feature space
converges to a source-specific probability density function
when source data are improperly fused. Our numerical results
demonstrate that this phenomenon can be quantified as a
measure of fusion quality. On patient data, the fused model
consisting of both imaging data and positionally encoded
blood markers at the theoretically optimal fusion quality
metric achieved an AUC of 0.74 and an accuracy of 0.71. This
model was statistically better than the imaging-only model
(AUC = 0.60; accuracy = 0.62), the blood marker-only model
(AUC = 0.58; accuracy = 0.60), and a variety of purposely
sub-optimized fusion models (AUC = 0.61-0.70; accuracy =
0.58-0.69). CONCLUSIONS: We introduced the concept of data
fusion quality for multi-source deep learning problems
involving both imaging and clinical data. We provided a
theoretical framework, numerical validation, and real-world
application in abdominal radiology. Our data suggests that
CT imaging and hepatic blood markers provide complementary
diagnostic information when appropriately
fused.},
Doi = {10.1002/mp.16181},
Key = {fds368760}
}
@article{fds372739,
Author = {Lange, J and Zhao, Y and Gogebakan, KC and Olivas-Martinez, A and Ryser,
MD and Gard, CC and Etzioni, R},
Title = {Test sensitivity in a prospective cancer screening program:
A critique of a common proxy measure.},
Journal = {Stat Methods Med Res},
Volume = {32},
Number = {6},
Pages = {1053-1063},
Year = {2023},
Month = {June},
url = {http://dx.doi.org/10.1177/09622802221142529},
Abstract = {The true sensitivity of a cancer screening test, defined as
the frequency with which the test returns a positive result
if the cancer is present, is a key indicator of diagnostic
performance. Given the challenges of directly assessing test
sensitivity in a prospective screening program, proxy
measures for true sensitivity are frequently reported. We
call one such proxy empirical sensitivity, as it is given by
the observed ratio of screen-detected cancers to the sum of
screen-detected and interval cancers. In the setting of the
canonical three-state Markov model for progression from
preclinical onset to clinical diagnosis, we formulate a
mathematical relationship for how empirical sensitivity
varies with the screening interval and the mean preclinical
sojourn time and identify conditions under which empirical
sensitivity exceeds or falls short of true sensitivity. In
particular, when the inter-screening interval is short
relative to the mean sojourn time, empirical sensitivity
tends to exceed true sensitivity, unless true sensitivity is
high. The Breast Cancer Surveillance Consortium (BCSC) has
reported an estimate of 0.87 for the empirical sensitivity
of digital mammography. We show that this corresponds to a
true sensitivity of 0.82 under a mean sojourn time of 3.6
years estimated based on breast cancer screening trials.
However, the BCSC estimate of empirical sensitivity
corresponds to even lower true sensitivity under more
contemporary, longer estimates of mean sojourn time.
Consistently applied nomenclature that distinguishes
empirical sensitivity from true sensitivity is needed to
ensure that published estimates of sensitivity from
prospective screening studies are properly
interpreted.},
Doi = {10.1177/09622802221142529},
Key = {fds372739}
}
@article{fds362970,
Author = {Wang, C and Han, B and Patel, B and Rudin, C},
Title = {In Pursuit of Interpretable, Fair and Accurate Machine
Learning for Criminal Recidivism Prediction},
Journal = {Journal of Quantitative Criminology},
Volume = {39},
Number = {2},
Pages = {519-581},
Year = {2023},
Month = {June},
url = {http://dx.doi.org/10.1007/s10940-022-09545-w},
Abstract = {Objectives: We study interpretable recidivism prediction
using machine learning (ML) models and analyze performance
in terms of prediction ability, sparsity, and fairness.
Unlike previous works, this study trains interpretable
models that output probabilities rather than binary
predictions, and uses quantitative fairness definitions to
assess the models. This study also examines whether models
can generalize across geographic locations. Methods: We
generated black-box and interpretable ML models on two
different criminal recidivism datasets from Florida and
Kentucky. We compared predictive performance and fairness of
these models against two methods that are currently used in
the justice system to predict pretrial recidivism: the
Arnold PSA and COMPAS. We evaluated predictive performance
of all models on predicting six different types of crime
over two time spans. Results: Several interpretable ML
models can predict recidivism as well as black-box ML models
and are more accurate than COMPAS or the Arnold PSA. These
models are potentially useful in practice. Similar to the
Arnold PSA, some of these interpretable models can be
written down as a simple table. Others can be displayed
using a set of visualizations. Our geographic analysis
indicates that ML models should be trained separately for
separate locations and updated over time. We also present a
fairness analysis for the interpretable models. Conclusions:
Interpretable ML models can perform just as well as
non-interpretable methods and currently-used risk assessment
scales, in terms of both prediction accuracy and fairness.
ML models might be more accurate when trained separately for
distinct locations and kept up-to-date.},
Doi = {10.1007/s10940-022-09545-w},
Key = {fds362970}
}
@article{fds374494,
Author = {Kiselev, A and Luo, X},
Title = {Illposedness of C2 Vortex Patches},
Journal = {Archive for Rational Mechanics and Analysis},
Volume = {247},
Number = {3},
Year = {2023},
Month = {June},
url = {http://dx.doi.org/10.1007/s00205-023-01892-7},
Abstract = {It is well known that vortex patches are wellposed in C1,α
if 0 < α< 1 . In this paper, we prove the illposedness of
C2 vortex patches. The setup is to consider the vortex
patches in Sobolev spaces W2,p where the curvature of the
boundary is Lp integrable. In this setting, we show the
persistence of W2,p regularity when 1 < p< ∞ and construct
C2 initial patch data for which the curvature of the patch
boundary becomes unbounded immediately for t> 0 , though it
regains C2 regularity precisely at all integer times without
being time periodic. The key ingredient is the evolution
equation for the curvature, the dominant term in which turns
out to be linear and dispersive.},
Doi = {10.1007/s00205-023-01892-7},
Key = {fds374494}
}
@article{fds370952,
Author = {Kiselev, A and Luo, X},
Title = {Illposedness of C2 Vortex Patches},
Journal = {Archive for Rational Mechanics and Analysis},
Volume = {247},
Number = {3},
Publisher = {Springer Science and Business Media LLC},
Year = {2023},
Month = {June},
url = {http://dx.doi.org/10.1007/s00205-023-01892-7},
Abstract = {It is well known that vortex patches are wellposed in C1,α
if 0 < α< 1 . In this paper, we prove the illposedness of
C2 vortex patches. The setup is to consider the vortex
patches in Sobolev spaces W2,p where the curvature of the
boundary is Lp integrable. In this setting, we show the
persistence of W2,p regularity when 1 < p< ∞ and construct
C2 initial patch data for which the curvature of the patch
boundary becomes unbounded immediately for t> 0 , though it
regains C2 regularity precisely at all integer times without
being time periodic. The key ingredient is the evolution
equation for the curvature, the dominant term in which turns
out to be linear and dispersive.},
Doi = {10.1007/s00205-023-01892-7},
Key = {fds370952}
}
@article{fds370612,
Author = {Poe, JC and Fang, J and Zhang, D and Lee, MR and DiCioccio, RA and Su, H and Qin, X and Zhang, JY and Visentin, J and Bracken, SJ and Ho, VT and Wang,
KS and Rose, JJ and Pavletic, SZ and Hakim, FT and Jia, W and Suthers, AN and Curry-Chisolm, IM and Horwitz, ME and Rizzieri, DA and McManigle, WC and Chao, NJ and Cardones, AR and Xie, J and Owzar, K and Sarantopoulos,
S},
Title = {Single-cell landscape analysis unravels molecular
programming of the human B cell compartment in chronic
GVHD.},
Journal = {JCI insight},
Volume = {8},
Number = {11},
Pages = {e169732},
Year = {2023},
Month = {June},
url = {http://dx.doi.org/10.1172/jci.insight.169732},
Abstract = {Alloreactivity can drive autoimmune syndromes. After
allogeneic hematopoietic stem cell transplantation
(allo-HCT), chronic graft-versus-host disease (cGVHD), a B
cell-associated autoimmune-like syndrome, commonly occurs.
Because donor-derived B cells continually develop under
selective pressure from host alloantigens, aberrant B cell
receptor (BCR) activation and IgG production can emerge and
contribute to cGVHD pathobiology. To better understand
molecular programing of B cells in allo-HCT, we performed
scRNA-Seq analysis on high numbers of purified B cells from
patients. An unsupervised analysis revealed 10 clusters,
distinguishable by signature genes for maturation,
activation, and memory. Within the memory B cell
compartment, we found striking transcriptional differences
in allo-HCT patients compared with healthy or infected
individuals, including potentially pathogenic atypical B
cells (ABCs) that were expanded in active cGVHD. To identify
intrinsic alterations in potentially pathological B cells,
we interrogated all clusters for differentially expressed
genes (DEGs) in active cGVHD versus patients who never had
signs of immune tolerance loss (no cGVHD). Active cGVHD DEGs
occurred in both naive and BCR-activated B cell clusters.
Remarkably, some DEGs occurred across most clusters,
suggesting common molecular programs that may promote B cell
plasticity. Our study of human allo-HCT and cGVHD provides
understanding of altered B cell memory during chronic
alloantigen stimulation.},
Doi = {10.1172/jci.insight.169732},
Key = {fds370612}
}
@article{fds370641,
Author = {Krishnappa Babu and PR and Aikat, V and Di Martino and JM and Chang, Z and Perochon, S and Espinosa, S and Aiello, R and L H Carpenter and K and Compton, S and Davis, N and Eichner, B and Flowers, J and Franz, L and Dawson, G and Sapiro, G},
Title = {Blink rate and facial orientation reveal distinctive
patterns of attentional engagement in autistic toddlers: a
digital phenotyping approach.},
Journal = {Sci Rep},
Volume = {13},
Number = {1},
Pages = {7158},
Year = {2023},
Month = {May},
url = {http://dx.doi.org/10.1038/s41598-023-34293-7},
Abstract = {Differences in social attention are well-documented in
autistic individuals, representing one of the earliest signs
of autism. Spontaneous blink rate has been used to index
attentional engagement, with lower blink rates reflecting
increased engagement. We evaluated novel methods using
computer vision analysis (CVA) for automatically quantifying
patterns of attentional engagement in young autistic
children, based on facial orientation and blink rate, which
were captured via mobile devices. Participants were 474
children (17-36 months old), 43 of whom were diagnosed with
autism. Movies containing social or nonsocial content were
presented via an iPad app, and simultaneously, the device's
camera recorded the children's behavior while they watched
the movies. CVA was used to extract the duration of time the
child oriented towards the screen and their blink rate as
indices of attentional engagement. Overall, autistic
children spent less time facing the screen and had a higher
mean blink rate compared to neurotypical children.
Neurotypical children faced the screen more often and
blinked at a lower rate during the social movies compared to
the nonsocial movies. In contrast, autistic children faced
the screen less often during social movies than during
nonsocial movies and showed no differential blink rate to
social versus nonsocial movies.},
Doi = {10.1038/s41598-023-34293-7},
Key = {fds370641}
}
@article{fds375282,
Author = {Jin, B and Dunson, DB and Rager, JE and Reif, DM and Engel, SM and Herring,
AH},
Title = {Bayesian matrix completion for hypothesis
testing.},
Journal = {Journal of the Royal Statistical Society. Series C, Applied
statistics},
Volume = {72},
Number = {2},
Pages = {254-270},
Year = {2023},
Month = {May},
url = {http://dx.doi.org/10.1093/jrsssc/qlac005},
Abstract = {We aim to infer bioactivity of each chemical by assay
endpoint combination, addressing sparsity of toxicology
data. We propose a Bayesian hierarchical framework which
borrows information across different chemicals and assay
endpoints, facilitates out-of-sample prediction of activity
for chemicals not yet assayed, quantifies uncertainty of
predicted activity, and adjusts for multiplicity in
hypothesis testing. Furthermore, this paper makes a novel
attempt in toxicology to simultaneously model
heteroscedastic errors and a nonparametric mean function,
leading to a broader definition of activity whose need has
been suggested by toxicologists. Real application identifies
chemicals most likely active for neurodevelopmental
disorders and obesity.},
Doi = {10.1093/jrsssc/qlac005},
Key = {fds375282}
}
@article{fds368952,
Author = {Liu, X and Mukherjee, S},
Title = {Stability theorems for some Kruskal–Katona type
results},
Journal = {European Journal of Combinatorics},
Volume = {110},
Year = {2023},
Month = {May},
url = {http://dx.doi.org/10.1016/j.ejc.2022.103666},
Abstract = {The classical Kruskal–Katona theorem gives a tight upper
bound for the size of an r-uniform hypergraph H as a
function of the size of its shadow. Its stability version
was obtained by Keevash who proved that if the size of H is
close to the maximum with respect to the size of its shadow,
then H is structurally close to a complete r-uniform
hypergraph. We prove similar stability results for two
classes of hypergraphs whose extremal properties have been
investigated by many researchers: the cancellative
hypergraphs and hypergraphs without expansion of
cliques.},
Doi = {10.1016/j.ejc.2022.103666},
Key = {fds368952}
}
@article{fds369943,
Author = {Lahkar, R and Mukherjee, S and Roy, S},
Title = {The logit dynamic in supermodular games with a continuum of
strategies: A deterministic approximation
approach},
Journal = {Games and Economic Behavior},
Volume = {139},
Pages = {133-160},
Year = {2023},
Month = {May},
url = {http://dx.doi.org/10.1016/j.geb.2023.02.003},
Abstract = {We consider large population supermodular games with
pairwise interaction and a continuous strategy set. Our
objective is to establish convergence of the logit dynamic
in such games to logit equilibria. For this purpose, we
apply the deterministic approximation approach, which
interprets a deterministic dynamic as an approximation of a
stochastic process. We first establish the closeness of this
dynamic with a step–wise approximation. We then show that
the logit stochastic process is close to the step–wise
logit dynamic in a discrete approximation of the original
game. Combining the two results, we obtain our deterministic
approximation result. We then apply this result to
supermodular games. Over finite but sufficiently long time
horizons, the logit stochastic process converges to logit
equilibria in a discrete approximation of the supermodular
game. By the deterministic approximation approach, so does
the logit dynamic in the continuum supermodular
game.},
Doi = {10.1016/j.geb.2023.02.003},
Key = {fds369943}
}
@article{fds369091,
Author = {Liu, Y and Claus, S and Kerfriden, P and Chen, J and Zhong, P and Dolbow,
JE},
Title = {Model-based simulations of pulsed laser ablation using an
embedded finite element method.},
Journal = {International Journal of Heat and Mass Transfer},
Volume = {204},
Pages = {123843},
Year = {2023},
Month = {May},
url = {http://dx.doi.org/10.1016/j.ijheatmasstransfer.2022.123843},
Abstract = {A model of thermal ablation with application to multi-pulsed
laser lithotripsy is presented. The approach is based on a
one-sided Stefan-Signorini model for thermal ablation, and
relies on a level-set function to represent the moving
interface between the solid phase and a fictitious gas phase
(representing the ablated material). The model is
discretized with an embedded finite element method, wherein
the interface geometry can be arbitrarily located relative
to the background mesh. Nitsche's method is adopted to
impose the Signorini condition on the moving interface. A
bound constraint is also imposed to deal with thermal shocks
that can arise during representative simulations of pulsed
ablation with high-power lasers. We report simulation
results based on experiments for pulsed laser ablation of
wet BegoStone samples treated in air, where Begostone has
been used as a phantom material for kidney stone. The model
is calibrated against experimental measurements by adjusting
the percentage of incoming laser energy absorbed at the
surface of the stone sample. Simulation results are then
validated against experimental observations for the crater
area, volume, and geometry as a function of laser pulse
energy and duration. Our studies illustrate how the
spreading of the laser beam from the laser fiber tip with
concomitantly reduced incident laser irradiance on the
damaged crater surface explains trends in both the
experimental observations and the model-based simulation
results.},
Doi = {10.1016/j.ijheatmasstransfer.2022.123843},
Key = {fds369091}
}
@article{fds370839,
Author = {An, C and Chu, R and Pierce, LB},
Title = {Counterexamples for High-Degree Generalizations of the
Schrödinger Maximal Operator},
Journal = {International Mathematics Research Notices},
Volume = {2023},
Number = {10},
Pages = {8371-8418},
Publisher = {Oxford University Press (OUP)},
Year = {2023},
Month = {May},
url = {http://dx.doi.org/10.1093/imrn/rnac088},
Abstract = {In 1980 Carleson posed a question on the minimal regularity
of an initial data function in a Sobolev space that implies
pointwise convergence for the solution of the linear
Schrödinger equation. After progress by many authors, this
was recently resolved (up to the endpoint) by Bourgain,
whose counterexample construction for the Schrödinger
maximal operator proved a necessary condition on the
regularity, and Du and Zhang, who proved a sufficient
condition. Analogues of Carleson's question remain open for
many other dispersive partial differential equations. We
develop a flexible new method to approach such problems and
prove that for any integer, if a degree generalization of
the Schrödinger maximal operator is bounded from to, then
In dimensions, for every degree, this is the first result
that exceeds a long-standing barrier at. Our methods are
number-theoretic, and in particular apply the Weil bound, a
consequence of the truth of the Riemann Hypothesis over
finite fields.},
Doi = {10.1093/imrn/rnac088},
Key = {fds370839}
}
@article{fds371252,
Author = {Wu, H-T and Harezlak, J},
Title = {Application of de-shape synchrosqueezing to estimate gait
cadence from a single-sensor accelerometer placed in
different body locations.},
Journal = {Physiological measurement},
Volume = {44},
Number = {5},
Year = {2023},
Month = {May},
url = {http://dx.doi.org/10.1088/1361-6579/accefe},
Abstract = {<i>Objective.</i>Commercial and research-grade wearable
devices have become increasingly popular over the past
decade. Information extracted from devices using
accelerometers is frequently summarized as 'number of steps'
(commercial devices) or 'activity counts' (research-grade
devices). Raw accelerometry data that can be easily
extracted from accelerometers used in research, for instance
ActiGraph GT3X+, are frequently discarded.<i>Approach.</i>Our
primary goal is proposing an innovative use of
the<i>de-shape synchrosqueezing transform</i>to analyze the
raw accelerometry data recorded from a single sensor
installed in different body locations, particularly the
wrist, to extract<i>gait cadence</i>when a subject is
walking. The proposed methodology is tested on data
collected in a semi-controlled experiment with 32
participants walking on a one-kilometer predefined course.
Walking was executed on a flat surface as well as on the
stairs (up and down).<i>Main results.</i>The cadences of
walking on a flat surface, ascending stairs, and descending
stairs, determined from the wrist sensor, are 1.98 ± 0.15
Hz, 1.99 ± 0.26 Hz, and 2.03 ± 0.26 Hz respectively. The
cadences are 1.98 ± 0.14 Hz, 1.97 ± 0.25 Hz, and 2.02 ±
0.23 Hz, respectively if determined from the hip sensor,
1.98 ± 0.14 Hz, 1.93 ± 0.22 Hz and 2.06 ± 0.24 Hz,
respectively if determined from the left ankle sensor, and
1.98 ± 0.14 Hz, 1.97 ± 0.22 Hz, and 2.04 ± 0.24 Hz,
respectively if determined from the right ankle sensor. The
difference is statistically significant indicating that the
cadence is fastest while descending stairs and slowest when
ascending stairs. Also, the standard deviation when the
sensor is on the wrist is larger. These findings are in line
with our expectations.<i>Conclusion.</i>We show that our
proposed algorithm can extract the cadence with high
accuracy, even when the sensor is placed on the
wrist.},
Doi = {10.1088/1361-6579/accefe},
Key = {fds371252}
}
@article{fds367062,
Author = {Petkova, I and Wong, B},
Title = {Twisted Mazur Pattern Satellite Knots & Bordered Floer
Theory},
Journal = {Michigan Mathematical Journal},
Volume = {73},
Number = {2},
Pages = {255-304},
Publisher = {Michigan Mathematical Journal},
Year = {2023},
Month = {May},
url = {http://dx.doi.org/10.1307/mmj/20205927},
Abstract = {We use bordered Floer theory to study properties of twisted
Mazur pattern satellite knots Qn(K). We prove that Qn(K) is
not Floer homologically thin, with two exceptions. We
calculate the 3-genus of Qn(K) in terms of the twisting
parameter n and the 3-genus of the companion K, and we
determine when Qn(K) is fibered. As an application to our
results on Floer thickness and 3-genus, we verify the
Cosmetic Surgery Conjecture for many of these satellite
knots.},
Doi = {10.1307/mmj/20205927},
Key = {fds367062}
}
@article{fds372372,
Author = {Huang, H-Y and Tong, Y and Fang, D and Su, Y},
Title = {Learning Many-Body Hamiltonians with Heisenberg-Limited
Scaling.},
Journal = {Physical review letters},
Volume = {130},
Number = {20},
Pages = {200403},
Year = {2023},
Month = {May},
url = {http://dx.doi.org/10.1103/physrevlett.130.200403},
Abstract = {Learning a many-body Hamiltonian from its dynamics is a
fundamental problem in physics. In this Letter, we propose
the first algorithm to achieve the Heisenberg limit for
learning an interacting N-qubit local Hamiltonian. After a
total evolution time of O(ε^{-1}), the proposed algorithm
can efficiently estimate any parameter in the N-qubit
Hamiltonian to ε error with high probability. Our algorithm
uses ideas from quantum simulation to decouple the unknown
N-qubit Hamiltonian H into noninteracting patches and learns
H using a quantum-enhanced divide-and-conquer approach. The
proposed algorithm is robust against state preparation and
measurement error, does not require eigenstates or thermal
states, and only uses polylog(ε^{-1}) experiments. In
contrast, the best existing algorithms require O(ε^{-2})
experiments and total evolution time. We prove a matching
lower bound to establish the asymptotic optimality of our
algorithm.},
Doi = {10.1103/physrevlett.130.200403},
Key = {fds372372}
}
@article{fds372524,
Author = {Liu, CH and Wei, F},
Title = {Phase transition of degeneracy in minor-closed
families},
Journal = {Advances in Applied Mathematics},
Volume = {146},
Year = {2023},
Month = {May},
url = {http://dx.doi.org/10.1016/j.aam.2023.102489},
Abstract = {Given an infinite family G of graphs and a monotone property
P, an (upper) threshold for G and P is a “fastest
growing” function p:N→[0,1] such that
limn→∞Pr(Gn(p(n))∈P)=1 for any sequence
(Gn)n∈N over G with limn→∞|V(Gn)|=∞, where
Gn(p(n)) is the random subgraph of Gn such that each edge
remains independently with probability p(n). In this paper
we study the upper threshold for the family of H-minor free
graphs and the property of being (r−1)-degenerate and
apply it to study the thresholds for general minor-closed
families and the properties for being r-choosable and
r-colorable. Even a constant factor approximation for the
upper threshold for all pairs (r,H) is expected to be
challenging by its close connection to a major open question
in extremal graph theory. We determine asymptotically the
thresholds (up to a constant factor) for being
(r−1)-degenerate (and r-choosable, respectively) for a
large class of pairs (r,H), including all graphs H of
minimum degree at least r and all graphs H with no
vertex-cover of size at most r, and provide lower bounds for
the rest of the pairs of (r,H).},
Doi = {10.1016/j.aam.2023.102489},
Key = {fds372524}
}
@article{fds370385,
Author = {Isaev, DY and Sabatos-DeVito, M and Di Martino and JM and Carpenter, K and Aiello, R and Compton, S and Davis, N and Franz, L and Sullivan, C and Dawson, G and Sapiro, G},
Title = {Computer Vision Analysis of Caregiver-Child Interactions in
Children with Neurodevelopmental Disorders: A Preliminary
Report.},
Journal = {J Autism Dev Disord},
Year = {2023},
Month = {April},
url = {http://dx.doi.org/10.1007/s10803-023-05973-0},
Abstract = {We report preliminary results of computer vision analysis of
caregiver-child interactions during free play with children
diagnosed with autism (N = 29, 41-91 months),
attention-deficit/hyperactivity disorder (ADHD, N = 22,
48-100 months), or combined autism + ADHD (N = 20,
56-98 months), and neurotypical children (NT, N = 7,
55-95 months). We conducted micro-analytic analysis of
'reaching to a toy,' as a proxy for initiating or responding
to a toy play bout. Dyadic analysis revealed two clusters of
interaction patterns, which differed in frequency of
'reaching to a toy' and caregivers' contingent responding to
the child's reach for a toy by also reaching for a toy.
Children in dyads with higher caregiver responsiveness had
less developed language, communication, and socialization
skills. Clusters were not associated with diagnostic groups.
These results hold promise for automated methods of
characterizing caregiver responsiveness in dyadic
interactions for assessment and outcome monitoring in
clinical trials.},
Doi = {10.1007/s10803-023-05973-0},
Key = {fds370385}
}
@article{fds370898,
Author = {Mahzarnia, A and Stout, JA and Anderson, RJ and Moon, HS and Yar Han and Z and Beck, K and Browndyke, JN and Dunson, DB and Johnson, KG and O'Brien,
RJ and Badea, A},
Title = {Identifying vulnerable brain networks associated with
Alzheimer's disease risk.},
Journal = {Cereb Cortex},
Volume = {33},
Number = {9},
Pages = {5307-5322},
Year = {2023},
Month = {April},
url = {http://dx.doi.org/10.1093/cercor/bhac419},
Abstract = {The selective vulnerability of brain networks in individuals
at risk for Alzheimer's disease (AD) may help differentiate
pathological from normal aging at asymptomatic stages,
allowing the implementation of more effective interventions.
We used a sample of 72 people across the age span, enriched
for the APOE4 genotype to reveal vulnerable networks
associated with a composite AD risk factor including age,
genotype, and sex. Sparse canonical correlation analysis
(CCA) revealed a high weight associated with genotype, and
subgraphs involving the cuneus, temporal, cingulate
cortices, and cerebellum. Adding cognitive metrics to the
risk factor revealed the highest cumulative degree of
connectivity for the pericalcarine cortex, insula, banks of
the superior sulcus, and the cerebellum. To enable scaling
up our approach, we extended tensor network principal
component analysis, introducing CCA components. We developed
sparse regression predictive models with errors of 17% for
genotype, 24% for family risk factor for AD, and 5 years for
age. Age prediction in groups including cognitively impaired
subjects revealed regions not found using only normal
subjects, i.e. middle and transverse temporal, paracentral
and superior banks of temporal sulcus, as well as the
amygdala and parahippocampal gyrus. These modeling
approaches represent stepping stones towards single subject
prediction.},
Doi = {10.1093/cercor/bhac419},
Key = {fds370898}
}
@article{fds370609,
Author = {Lu, J and Wu, Y and Xiang, Y},
Title = {Score-based Transport Modeling for Mean-Field Fokker-Planck
Equations},
Volume = {503},
Year = {2023},
Month = {April},
url = {http://dx.doi.org/10.1016/j.jcp.2024.112859},
Abstract = {We use the score-based transport modeling method to solve
the mean-field Fokker-Planck equations, which we call MSBTM.
We establish an upper bound on the time derivative of the
Kullback-Leibler (KL) divergence to MSBTM numerical
estimation from the exact solution, thus validates the MSBTM
approach. Besides, we provide an error analysis for the
algorithm. In numerical experiments, we study three types of
mean-field Fokker-Planck equation and their corresponding
dynamics of particles in interacting systems. The MSBTM
algorithm is numerically validated through qualitative and
quantitative comparison between the MSBTM solutions, the
results of integrating the associated stochastic
differential equation and the analytical solutions if
available.},
Doi = {10.1016/j.jcp.2024.112859},
Key = {fds370609}
}
@article{fds371510,
Author = {Gu, Y and Dunson, DB},
Title = {Bayesian Pyramids: identifiable multilayer discrete latent
structure models for discrete data},
Journal = {Journal of the Royal Statistical Society. Series B:
Statistical Methodology},
Volume = {85},
Number = {2},
Pages = {399-426},
Year = {2023},
Month = {April},
url = {http://dx.doi.org/10.1093/jrsssb/qkad010},
Abstract = {High-dimensional categorical data are routinely collected in
biomedical and social sciences. It is of great importance to
build interpretable parsimonious models that perform
dimension reduction and uncover meaningful latent structures
from such discrete data. Identifiability is a fundamental
requirement for valid modeling and inference in such
scenarios, yet is challenging to address when there are
complex latent structures. In this article, we propose a
class of identifiable multilayer (potentially deep) discrete
latent structure models for discrete data, termed Bayesian
Pyramids. We establish the identifiability of Bayesian
Pyramids by developing novel transparent conditions on the
pyramid-shaped deep latent directed graph. The proposed
identifiability conditions can ensure Bayesian posterior
consistency under suitable priors. As an illustration, we
consider the two-latent-layer model and propose a Bayesian
shrinkage estimation approach. Simulation results for this
model corroborate the identifiability and estimatability of
model parameters. Applications of the methodology to DNA
nucleotide sequence data uncover useful discrete latent
features that are highly predictive of sequence types. The
proposed framework provides a recipe for interpretable
unsupervised learning of discrete data and can be a useful
alternative to popular machine learning methods.},
Doi = {10.1093/jrsssb/qkad010},
Key = {fds371510}
}
@article{fds369224,
Author = {Byng, D and Thomas, SM and Rushing, CN and Lynch, T and McCarthy, A and Francescatti, AB and Frank, ES and Partridge, AH and Thompson, AM and Retèl, VP and van Harten, WH and Grimm, LJ and Hyslop, T and Hwang, ES and Ryser, MD},
Title = {Surveillance Imaging after Primary Diagnosis of Ductal
Carcinoma in Situ.},
Journal = {Radiology},
Volume = {307},
Number = {1},
Pages = {e221210},
Year = {2023},
Month = {April},
url = {http://dx.doi.org/10.1148/radiol.221210},
Abstract = {Background Guidelines recommend annual surveillance imaging
after diagnosis of ductal carcinoma in situ (DCIS).
Guideline adherence has not been characterized in a
contemporary cohort. Purpose To identify uptake and
determinants of surveillance imaging in women who underwent
treatment for DCIS. Materials and Methods A stratified
random sample of women who underwent breast-conserving
surgery for primary DCIS between 2008 and 2014 was
retrospectively selected from 1330 facilities in the United
States. Imaging examinations were recorded from date of
diagnosis until first distant recurrence, death, loss to
follow-up, or end of study (November 2018). Imaging after
treatment was categorized into 10 12-month periods
starting 6 months after diagnosis. Primary outcome was
per-period receipt of asymptomatic surveillance imaging
(mammography, MRI, or US). Secondary outcome was diagnosis
of ipsilateral invasive breast cancer. Multivariable
logistic regression with repeated measures and generalized
estimating equations was used to model receipt of imaging.
Rates of diagnosis with ipsilateral invasive breast cancer
were compared between women who did and those who did not
undergo imaging in the 6-18-month period after diagnosis
using inverse probability-weighted Kaplan-Meier estimators.
Results A total of 12 559 women (median age, 60 years;
IQR, 52-69 years) were evaluated. Uptake of surveillance
imaging was 75% in the first period and decreased over time
(P < .001). Across the first 5 years after treatment, 52% of
women participated in consistent annual surveillance.
Surveillance was lower in Black (adjusted odds ratio [OR],
0.80; 95% CI: 0.74, 0.88; P < .001) and Hispanic (OR, 0.82;
95% CI: 0.72, 0.94; P = .004) women than in White women.
Women who underwent surveillance in the first period had a
higher 6-year rate of diagnosis of invasive cancer (1.6%;
95% CI: 1.3, 1.9) than those who did not (1.1%; 95% CI: 0.7,
1.4; difference: 0.5%; 95% CI: 0.1, 1.0; P = .03).
Conclusion Half of women did not consistently adhere to
imaging surveillance guidelines across the first 5 years
after treatment, with racial disparities in adherence rates.
© RSNA, 2023 Supplemental material is available for this
article. See also the editorial by Rahbar and Dontchos in
this issue.},
Doi = {10.1148/radiol.221210},
Key = {fds369224}
}
@article{fds370417,
Author = {Isaev, DY and Vlasova, RM and Di Martino and JM and Stephen, CD and Schmahmann, JD and Sapiro, G and Gupta, AS},
Title = {Uncertainty of Vowel Predictions as a Digital Biomarker for
Ataxic Dysarthria.},
Journal = {Cerebellum (London, England)},
Year = {2023},
Month = {April},
url = {http://dx.doi.org/10.1007/s12311-023-01539-z},
Abstract = {Dysarthria is a common manifestation across cerebellar
ataxias leading to impairments in communication, reduced
social connections, and decreased quality of life. While
dysarthria symptoms may be present in other neurological
conditions, ataxic dysarthria is a perceptually distinct
motor speech disorder, with the most prominent
characteristics being articulation and prosody abnormalities
along with distorted vowels. We hypothesized that
uncertainty of vowel predictions by an automatic speech
recognition system can capture speech changes present in
cerebellar ataxia. Speech of participants with ataxia (N=61)
and healthy controls (N=25) was recorded during the "picture
description" task. Additionally, participants' dysarthric
speech and ataxia severity were assessed on a Brief Ataxia
Rating Scale (BARS). Eight participants with ataxia had
speech and BARS data at two timepoints. A neural network
trained for phoneme prediction was applied to speech
recordings. Average entropy of vowel tokens predictions
(AVE) was computed for each participant's recording,
together with mean pitch and intensity standard deviations
(MPSD and MISD) in the vowel segments. AVE and MISD
demonstrated associations with BARS speech score (Spearman's
rho=0.45 and 0.51), and AVE demonstrated associations with
BARS total (rho=0.39). In the longitudinal cohort, Wilcoxon
pairwise signed rank test demonstrated an increase in BARS
total and AVE, while BARS speech and acoustic measures did
not significantly increase. Relationship of AVE to both BARS
speech and BARS total, as well as the ability to capture
disease progression even in absence of measured speech
decline, indicates the potential of AVE as a digital
biomarker for cerebellar ataxia.},
Doi = {10.1007/s12311-023-01539-z},
Key = {fds370417}
}
@article{fds367820,
Author = {Shi, H and Vardhan, M and Randles, A},
Title = {The Role of Immersion for Improving Extended Reality
Analysis of Personalized Flow Simulations.},
Journal = {Cardiovascular engineering and technology},
Volume = {14},
Number = {2},
Pages = {194-203},
Year = {2023},
Month = {April},
url = {http://dx.doi.org/10.1007/s13239-022-00646-y},
Abstract = {<h4>Purpose</h4>Computational models of flow in
patient-derived arterial geometries have become a key
paradigm of biomedical research. These fluid models are
often challenging to visualize due to high spatial
heterogeneity and visual complexity. Virtual immersive
environments can offer advantageous visualization of
spatially heterogeneous and complex systems. However, as
different VR devices offer varying levels of immersion,
there remains a crucial lack of understanding regarding what
level of immersion is best suited for interactions with
patient-specific flow models.<h4>Methods</h4>We conducted a
quantitative user evaluation with multiple VR devices
testing an important use of hemodynamic simulations-analysis
of surface parameters within complex patient-specific
geometries. This task was compared for the semi-immersive
zSpace 3D monitor and the fully immersive HTC Vive
system.<h4>Results</h4>The semi-immersive device was more
accurate than the fully immersive device. The two devices
showed similar results for task duration and performance
(accuracy/duration). The accuracy of the semi-immersive
device was also higher for arterial geometries of greater
complexity and branching.<h4>Conclusion</h4>This assessment
demonstrates that the level of immersion plays a significant
role in the accuracy of assessing arterial flow models. We
found that the semi-immersive VR device was a generally
optimal choice for arterial visualization.},
Doi = {10.1007/s13239-022-00646-y},
Key = {fds367820}
}
@article{fds374495,
Author = {Kiselev, A and Luo, X},
Title = {On Nonexistence of Splash Singularities for the α -SQG
Patches},
Journal = {Journal of Nonlinear Science},
Volume = {33},
Number = {2},
Year = {2023},
Month = {April},
url = {http://dx.doi.org/10.1007/s00332-023-09893-2},
Abstract = {In this paper, we consider patch solutions to the α-SQG
equation and derive new criteria for the absence of splash
singularity where different patches or parts of the same
patch collide in finite time. Our criterion refines a result
due to Gancedo and Strain Gancedo and Strain (2014),
providing a condition on the growth of curvature of the
patch necessary for the splash and an exponential in time
lower bound on the distance between patches with bounded
curvature.},
Doi = {10.1007/s00332-023-09893-2},
Key = {fds374495}
}
@article{fds370969,
Author = {Liu, GR and Sheu, YC and Wu, HT},
Title = {CENTRAL AND NONCENTRAL LIMIT THEOREMS ARISING FROM THE
SCATTERING TRANSFORM AND ITS NEURAL ACTIVATION
GENERALIZATION},
Journal = {SIAM Journal on Mathematical Analysis},
Volume = {55},
Number = {2},
Pages = {1170-1213},
Year = {2023},
Month = {April},
url = {http://dx.doi.org/10.1137/21M1454511},
Abstract = {Motivated by the analysis of complicated time series, we
examine a generalization of the scattering transform that
includes broad neural activation functions. This
generalization is the neural activation scattering transform
(NAST). NAST comprises a sequence of "neural processing
units," each of which applies a high pass filter to the
input from the previous layer followed by a composition with
a nonlinear function as the output to the next neuron. Here,
the nonlinear function models how a neuron gets excited by
the input signal. In addition to showing properties like
nonexpansion, horizontal translational invariability, and
insensitivity to local deformation, we explore the
statistical properties of the second-order NAST of a
Gaussian process with various dependence structures and its
interaction with the chosen wavelets and activation
functions. We also provide central limit theorem (CLT) and
non-CLT results. Numerical simulations demonstrate the
developed theorems. Our results explain how NAST processes
complicated time series, paving a way toward statistical
inference based on NAST for real-world applications.},
Doi = {10.1137/21M1454511},
Key = {fds370969}
}
@article{fds369942,
Author = {Hamid, I and Korunes, KL and Schrider, DR and Goldberg,
A},
Title = {Localizing Post-Admixture Adaptive Variants with Object
Detection on Ancestry-Painted Chromosomes.},
Journal = {Molecular biology and evolution},
Volume = {40},
Number = {4},
Pages = {msad074},
Publisher = {Oxford University Press (OUP)},
Editor = {Rogers, R},
Year = {2023},
Month = {April},
url = {http://dx.doi.org/10.1093/molbev/msad074},
Abstract = {Gene flow between previously differentiated populations
during the founding of an admixed or hybrid population has
the potential to introduce adaptive alleles into the new
population. If the adaptive allele is common in one source
population, but not the other, then as the adaptive allele
rises in frequency in the admixed population, genetic
ancestry from the source containing the adaptive allele will
increase nearby as well. Patterns of genetic ancestry have
therefore been used to identify post-admixture positive
selection in humans and other animals, including examples in
immunity, metabolism, and animal coloration. A common method
identifies regions of the genome that have local ancestry
"outliers" compared with the distribution across the rest of
the genome, considering each locus independently. However,
we lack theoretical models for expected distributions of
ancestry under various demographic scenarios, resulting in
potential false positives and false negatives. Further,
ancestry patterns between distant sites are often not
independent. As a result, current methods tend to infer wide
genomic regions containing many genes as under selection,
limiting biological interpretation. Instead, we develop a
deep learning object detection method applied to images
generated from local ancestry-painted genomes. This approach
preserves information from the surrounding genomic context
and avoids potential pitfalls of user-defined summary
statistics. We find the method is robust to a variety of
demographic misspecifications using simulated data. Applied
to human genotype data from Cabo Verde, we localize a known
adaptive locus to a single narrow region compared with
multiple or long windows obtained using two other
ancestry-based methods.},
Doi = {10.1093/molbev/msad074},
Key = {fds369942}
}
@article{fds365445,
Author = {Cook, NA and Nguyen, HH and Yakir, O and Zeitouni,
O},
Title = {Universality of Poisson Limits for Moduli of Roots of Kac
Polynomials},
Journal = {International Mathematics Research Notices},
Volume = {2023},
Number = {8},
Pages = {6648-6690},
Publisher = {Oxford University Press (OUP)},
Year = {2023},
Month = {April},
url = {http://dx.doi.org/10.1093/imrn/rnac021},
Abstract = {We give a new proof of a recent resolution [18] by Michelen
and Sahasrabudhe of a conjecture of Shepp and Vanderbei [19]
that the moduli of roots of Gaussian Kac polynomials of
degree $n$, centered at $1$ and rescaled by $n^2$, should
form a Poisson point process. We use this new approach to
verify a conjecture from [18] that the Poisson statistics
are in fact universal.},
Doi = {10.1093/imrn/rnac021},
Key = {fds365445}
}
@article{fds369692,
Author = {Kiselev, A and Luo, X},
Title = {On Nonexistence of Splash Singularities for the α -SQG
Patches},
Journal = {Journal of Nonlinear Science},
Volume = {33},
Number = {2},
Publisher = {Springer Science and Business Media LLC},
Year = {2023},
Month = {April},
url = {http://dx.doi.org/10.1007/s00332-023-09893-2},
Abstract = {In this paper, we consider patch solutions to the α-SQG
equation and derive new criteria for the absence of splash
singularity where different patches or parts of the same
patch collide in finite time. Our criterion refines a result
due to Gancedo and Strain Gancedo and Strain (2014),
providing a condition on the growth of curvature of the
patch necessary for the splash and an exponential in time
lower bound on the distance between patches with bounded
curvature.},
Doi = {10.1007/s00332-023-09893-2},
Key = {fds369692}
}
@article{fds361408,
Author = {Li, X and Sung, A and Xie, J},
Title = {DART: Distance Assisted Recursive Testing},
Journal = {Journal of Machine Learning Research},
Volume = {24},
Number = {169},
Year = {2023},
Month = {April},
Abstract = {In many applications, a large number of features are
collected with the goal to identify a few important ones.
Sometimes, these features lie in a metric space with a known
distance matrix, which partially reflects their
co-importance pattern. Proper use of the distance matrix
will boost the power of identifying important features.
Hence, we develop a new multiple testing framework named the
Distance Assisted Recursive Testing (DART). DART has two
stages. In stage 1, we transform the distance matrix into an
aggregation tree, where each node represents a set of
features. In stage 2, based on the aggregation tree, we set
up dynamic node hypotheses and perform multiple testing on
the tree. All rejections are mapped back to the features.
Under mild assumptions, the false discovery proportion of
DART converges to the desired level in high probability
converging to one. We illustrate by theory and simulations
that DART has superior performance under various models
compared to the existing methods. We applied DART to a
clinical trial in the allogeneic stem cell transplantation
study to identify the gut microbiota whose abundance will be
impacted by the after-transplant care.},
Key = {fds361408}
}
@article{fds369852,
Author = {Arapura, D and Matsuki, K and Patel, D and Włodarczyk,
J},
Title = {A Kawamata–Viehweg type formulation of the logarithmic
Akizuki–Nakano vanishing theorem},
Journal = {Mathematische Zeitschrift},
Volume = {303},
Number = {4},
Year = {2023},
Month = {April},
url = {http://dx.doi.org/10.1007/s00209-023-03225-6},
Abstract = {In this article, we present a Kawamata–Viehweg type
formulation of the (logarithmic) Akizuki–Nakano Vanishing
Theorem. We give two proofs: one by reduction to an older
theorem of Steenbrink via Kawamata’s covering lemma, and
another by mod p reduction using results of
Deligne–Illusie and Hara. We also include two
applications.},
Doi = {10.1007/s00209-023-03225-6},
Key = {fds369852}
}
@article{fds373605,
Author = {Witt, CE and Mena, S and Holmes, J and Hersey, M and Buchanan, AM and Parke, B and Saylor, R and Honan, LE and Berger, SN and Lumbreras, S and Nijhout, FH and Reed, MC and Best, J and Fadel, J and Schloss, P and Lau,
T and Hashemi, P},
Title = {Serotonin is a Common Thread Linking Different Classes of
Antidepressants.},
Journal = {Res Sq},
Year = {2023},
Month = {March},
url = {http://dx.doi.org/10.21203/rs.3.rs-2741902/v1},
Abstract = {Depression pathology remains elusive. The monoamine
hypothesis has placed much focus on serotonin, but due to
the variable clinical efficacy of monoamine reuptake
inhibitors, the community is looking for alternative
therapies such as ketamine (synaptic plasticity and
neurogenesis theory of antidepressant action). There is
evidence that different classes of antidepressants may
affect serotonin levels; a notion we test here. We measure
hippocampal serotonin in mice with voltammetry and study the
effects of acute challenges of antidepressants. We find that
pseudo-equivalent doses of these drugs similarly raise
ambient serotonin levels, despite their differing
pharmacodynamics because of differences in Uptake 1 and 2,
rapid SERT trafficking and modulation of serotonin by
histamine. These antidepressants have different
pharmacodynamics but have strikingly similar effects on
extracellular serotonin. Our findings suggest that serotonin
is a common thread that links clinically effective
antidepressants, synergizing different theories of
depression (synaptic plasticity, neurogenesis and the
monoamine hypothesis).},
Doi = {10.21203/rs.3.rs-2741902/v1},
Key = {fds373605}
}
@article{fds374584,
Author = {L. Chariker and A. De Masi and J. Lebowitz and E.
Presutti},
Title = {Scaling limit of a generalized contact process},
Journal = {J. Stat. Phys},
Volume = {190},
Number = {3},
Year = {2023},
Month = {March},
ISSN = {1572-9613},
url = {https://www.researchwithrutgers.com/en/publications/scaling-limit-of-a-generalized-contact-process},
Keywords = {Generalized contact process Hydrodynamic limit Integrate and
fire Mean field Neurons with discrete voltage Spatial
dependence},
Abstract = {https://www.researchwithrutgers.com/en/publications/scaling-limit-of-a-generalized-contact-process},
Doi = {10.1007/s10955-022-03050-x},
Key = {fds374584}
}
@article{fds358017,
Author = {Bachmann, T and Wickelgren, K},
Title = {EULER CLASSES: SIX-FUNCTORS FORMALISM, DUALITIES,
INTEGRALITY AND LINEAR SUBSPACES OF COMPLETE
INTERSECTIONS},
Journal = {Journal of the Institute of Mathematics of
Jussieu},
Volume = {22},
Number = {2},
Pages = {681-746},
Year = {2023},
Month = {March},
url = {http://dx.doi.org/10.1017/S147474802100027X},
Abstract = {We equate various Euler classes of algebraic vector bundles,
including those of [12] and one suggested by M. J. Hopkins,
A. Raksit, and J.-P. Serre. We establish integrality results
for this Euler class and give formulas for local indices at
isolated zeros, both in terms of the six-functors formalism
of coherent sheaves and as an explicit recipe in the
commutative algebra of Scheja and Storch. As an application,
we compute the Euler classes enriched in bilinear forms
associated to arithmetic counts of d-planes on complete
intersections in in terms of topological Euler numbers over
and.},
Doi = {10.1017/S147474802100027X},
Key = {fds358017}
}
@article{fds367648,
Author = {Wang, YG and Womersley, RS and Wu, HT and Yu, WH},
Title = {Numerical computation of triangular complex spherical
designs with small mesh ratio},
Journal = {Journal of Computational and Applied Mathematics},
Volume = {421},
Year = {2023},
Month = {March},
url = {http://dx.doi.org/10.1016/j.cam.2022.114796},
Abstract = {This paper provides triangular spherical designs for the
complex unit sphere Ωd⊂ℂd by exploiting the natural
correspondence with the real unit sphere S2d−1⊂R2d. A
variational characterization of triangular complex designs
is provided, with particular emphasis on numerical
computation of efficient triangular complex designs with
good geometric properties as measured by their mesh ratio.
We give numerical examples of triangular spherical t-designs
on complex unit spheres of dimension d=2 to
6.},
Doi = {10.1016/j.cam.2022.114796},
Key = {fds367648}
}
@article{fds368028,
Author = {Beauville, A and Schoen, C},
Title = {A Non-Hyperelliptic Curve with Torsion Ceresa Cycle Modulo
Algebraic Equivalence},
Journal = {International Mathematics Research Notices},
Volume = {2023},
Number = {5},
Pages = {3671-3675},
Publisher = {Oxford University Press (OUP)},
Year = {2023},
Month = {March},
url = {http://dx.doi.org/10.1093/imrn/rnab344},
Abstract = {We exhibit a non-hyperelliptic curve C of genus 3 such that
the class of the Ceresa cycle [C]-[C-] in JC modulo
algebraic equivalence is torsion.},
Doi = {10.1093/imrn/rnab344},
Key = {fds368028}
}
@article{fds370567,
Author = {Bowen, M and King, JR and Witelski, TP},
Title = {CAUCHY-DIRICHLET PROBLEMS FOR THE POROUS MEDIUM
EQUATION},
Journal = {Discrete and Continuous Dynamical Systems- Series
A},
Volume = {43},
Number = {3-4},
Pages = {1143-1174},
Publisher = {American Institute of Mathematical Sciences
(AIMS)},
Year = {2023},
Month = {March},
url = {http://dx.doi.org/10.3934/dcds.2022182},
Abstract = {We consider the porous medium equation subject to
zero-Dirichlet conditions on a variety of two-dimensional
domains, namely strips, slender domains and sectors,
allowing us to capture a number of different classes of
behaviours. Our focus is on intermediate-asymptotic
descriptions, derived by formal arguments and validated
against numerical computations. While our emphasis is on
non-negative solutions to the slow-diffusion case, we also
derive a number of results for sign-change solutions and for
fast diffusion. Self-similar solutions of various kinds play
a central role, alongside the identification of suitable
conserved quantities. The characterisation of domains
exhibiting infinite-time hole closure is a particular upshot
and we highlight a number of open problems.},
Doi = {10.3934/dcds.2022182},
Key = {fds370567}
}
@article{fds366912,
Author = {Dou, X and Liu, JG and Zhou, Z},
Title = {A TUMOR GROWTH MODEL WITH AUTOPHAGY: THE
REACTION-(CROSS-)DIFFUSION SYSTEM AND ITS FREE BOUNDARY
LIMIT},
Journal = {Discrete and Continuous Dynamical Systems - Series
B},
Volume = {28},
Number = {3},
Pages = {1964-1992},
Publisher = {American Institute of Mathematical Sciences
(AIMS)},
Year = {2023},
Month = {March},
url = {http://dx.doi.org/10.3934/dcdsb.2022154},
Abstract = {In this paper, we propose a tumor growth model to
incorporate and investigate the spatial effects of
autophagy. The cells are classified into two phases: normal
cells and autophagic cells, whose dynamics are also coupled
with the nutrients. First, we construct a
reaction-(cross-)diffusion system describing the evolution
of cell densities, where the drift is determined by the
negative gradient of the joint pressure, and the reaction
terms manifest the unique mechanism of autophagy. Next, in
the incompressible limit, such a cell density model
naturally connects to a free boundary system, describing the
geometric motion of the tumor region. Analyzing the free
boundary model in a special case, we show that the ratio of
the two phases of cells exponentially converges to a
“well-mixed” limit. Within this “well-mixed” limit,
we obtain an analytical solution of the free boundary system
which indicates the exponential growth of the tumor size in
the presence of autophagy in contrast to the linear growth
without it. Numerical simulations are also provided to
illustrate the analytical properties and to explore more
scenarios.},
Doi = {10.3934/dcdsb.2022154},
Key = {fds366912}
}
@article{fds369041,
Author = {Gao, Y and Li, T and Li, X and Liu, JG},
Title = {TRANSITION PATH THEORY FOR LANGEVIN DYNAMICS ON MANIFOLDS:
OPTIMAL CONTROL AND DATA-DRIVEN SOLVER},
Journal = {Multiscale Modeling and Simulation},
Volume = {21},
Number = {1},
Pages = {1-33},
Publisher = {Society for Industrial & Applied Mathematics
(SIAM)},
Year = {2023},
Month = {March},
url = {http://dx.doi.org/10.1137/21M1437883},
Abstract = {We present a data-driven point of view for rare events,
which represent conformational transitions in biochemical
reactions modeled by overdamped Langevin dynamics on
manifolds in high dimensions. We first reinterpret the
transition state theory and the transition path theory from
the optimal control viewpoint. Given a point cloud probing
the manifold, we construct a discrete Markov chain with a
Q-matrix computed from an approximated Voronoi tesselation
via the point cloud. We use this Q-matrix to compute a
discrete committor function whose level set automatically
orders the point cloud. Then based on the committor
function, an optimally controlled random walk on point
clouds is constructed and utilized to efficiently sample
transition paths, which become an almost sure event in O(1)
time instead of a rare event in the original reaction
dynamics. To compute the mean transition path efficiently, a
local averaging algorithm based on the optimally controlled
random walk is developed, which adapts the finite
temperature string method to the controlled Monte Carlo
samples. Numerical examples on sphere/torus including a
conformational transition for the alanine dipeptide in
vacuum are conducted to illustrate the data-driven solver
for the transition path theory on point clouds. The mean
transition path obtained via the controlled Monte Carlo
simulations highly coincides with the computed dominant
transition path in the transition path theory.},
Doi = {10.1137/21M1437883},
Key = {fds369041}
}
@article{fds374549,
Author = {Miller, E and Zhang, J},
Title = {Geodesic complexity of convex polyhedra},
Year = {2023},
Month = {March},
Key = {fds374549}
}
@article{fds369850,
Author = {Wang, M and Lu, J},
Title = {Neural Network-Based Variational Methods for Solving
Quadratic Porous Medium Equations in High
Dimensions},
Journal = {Communications in Mathematics and Statistics},
Volume = {11},
Number = {1},
Pages = {21-57},
Year = {2023},
Month = {March},
url = {http://dx.doi.org/10.1007/s40304-023-00339-5},
Abstract = {In this paper, we propose and study neural network-based
methods for solutions of high-dimensional quadratic porous
medium equation (QPME). Three variational formulations of
this nonlinear PDE are presented: a strong formulation and
two weak formulations. For the strong formulation, the
solution is directly parameterized with a neural network and
optimized by minimizing the PDE residual. It can be proved
that the convergence of the optimization problem guarantees
the convergence of the approximate solution in the L1 sense.
The weak formulations are derived following (Brenier in
Examples of hidden convexity in nonlinear PDEs, 2020) which
characterizes the very weak solutions of QPME. Specifically
speaking, the solutions are represented with intermediate
functions who are parameterized with neural networks and are
trained to optimize the weak formulations. Extensive
numerical tests are further carried out to investigate the
pros and cons of each formulation in low and high
dimensions. This is an initial exploration made along the
line of solving high-dimensional nonlinear PDEs with neural
network-based methods, which we hope can provide some useful
experience for future investigations.},
Doi = {10.1007/s40304-023-00339-5},
Key = {fds369850}
}
@article{fds367604,
Author = {Ding, X and Wu, HT},
Title = {Impact of Signal-to-Noise Ratio and Bandwidth on Graph
Laplacian Spectrum From High-Dimensional Noisy Point
Cloud},
Journal = {IEEE Transactions on Information Theory},
Volume = {69},
Number = {3},
Pages = {1899-1931},
Publisher = {Institute of Electrical and Electronics Engineers
(IEEE)},
Year = {2023},
Month = {March},
url = {http://dx.doi.org/10.1109/TIT.2022.3216561},
Abstract = {We systematically study the spectrum of kernel-based graph
Laplacian (GL) constructed from high-dimensional and noisy
random point cloud in the nonnull setup. The problem is
motived by studying the model when the clean signal is
sampled from a manifold that is embedded in a
low-dimensional Euclidean subspace, and corrupted by
high-dimensional noise. We quantify how the signal and noise
interact in different regions of signal-to-noise ratio
(SNR), and report the resulting peculiar spectral behavior
of GL. In addition, we explore the impact of chosen kernel
bandwidth on the spectrum of GL over different regions of
SNR, which lead to an adaptive choice of kernel bandwidth
that coincides with the common practice in real data. This
result paves the way to a theoretical understanding of how
practitioners apply GL when the dataset is
noisy.},
Doi = {10.1109/TIT.2022.3216561},
Key = {fds367604}
}
@article{fds368886,
Author = {Steinerberger, S and Wu, HT},
Title = {Fundamental component enhancement via adaptive nonlinear
activation functions},
Journal = {Applied and Computational Harmonic Analysis},
Volume = {63},
Pages = {135-143},
Year = {2023},
Month = {March},
url = {http://dx.doi.org/10.1016/j.acha.2022.11.007},
Abstract = {In many real world oscillatory signals, the fundamental
component of a signal f(t) might be weak or does not exist.
This makes it difficult to estimate the instantaneous
frequency of the signal. A traditional approach is to apply
the rectification trick, working with |f(t)| or ReLu(f(t))
instead, to enhance the fundamental component. This raises
an interesting question: what type of nonlinear function
g:R→R has the property that g(f(t)) has a more pronounced
fundamental frequency? g(t)=|t| and g(t)=ReLu(t) seem to
work well in practice; we propose a variant of
g(t)=1/(1−|t|) and provide a theoretical guarantee.
Several simulated signals and real signals are analyzed to
demonstrate the performance of the proposed
solution.},
Doi = {10.1016/j.acha.2022.11.007},
Key = {fds368886}
}
@article{fds374288,
Author = {Benson, J and Bessonov, M and Burke, K and Cassani, S and Ciocanel, M-V and Cooney, DB and Volkening, A},
Title = {How do classroom-turnover times depend on lecture-hall
size?},
Journal = {Mathematical biosciences and engineering :
MBE},
Volume = {20},
Number = {5},
Pages = {9179-9207},
Year = {2023},
Month = {March},
url = {http://dx.doi.org/10.3934/mbe.2023403},
Abstract = {Academic spaces in colleges and universities span classrooms
for 10 students to lecture halls that hold over 600 people.
During the break between consecutive classes, students from
the first class must leave and the new class must find their
desks, regardless of whether the room holds 10 or 600
people. Here we address the question of how the size of
large lecture halls affects classroom-turnover times,
focusing on non-emergency settings. By adapting the
established social-force model, we treat students as
individuals who interact and move through classrooms to
reach their destinations. We find that social interactions
and the separation time between consecutive classes strongly
influence how long it takes entering students to reach their
desks, and that these effects are more pronounced in larger
lecture halls. While the median time that individual
students must travel increases with decreased separation
time, we find that shorter separation times lead to shorter
classroom-turnover times overall. This suggests that the
effects of scheduling gaps and lecture-hall size on
classroom dynamics depends on the perspective-individual
student or whole class-that one chooses to
take.},
Doi = {10.3934/mbe.2023403},
Key = {fds374288}
}
@article{fds367059,
Author = {Bernal, EA and Hauenstein, JD and Mehta, D and Regan, MH and Tang,
T},
Title = {Machine learning the real discriminant locus},
Journal = {Journal of Symbolic Computation},
Volume = {115},
Pages = {409-426},
Year = {2023},
Month = {March},
url = {http://dx.doi.org/10.1016/j.jsc.2022.08.001},
Abstract = {Parameterized systems of polynomial equations arise in many
applications in science and engineering with the real
solutions describing, for example, equilibria of a dynamical
system, linkages satisfying design constraints, and scene
reconstruction in computer vision. Since different parameter
values can have a different number of real solutions, the
parameter space is decomposed into regions whose boundary
forms the real discriminant locus. This article views
locating the real discriminant locus as a supervised
classification problem in machine learning where the goal is
to determine classification boundaries over the parameter
space, with the classes being the number of real solutions.
This article presents a novel sampling method which
carefully samples a multidimensional parameter space. At
each sample point, homotopy continuation is used to obtain
the number of real solutions to the corresponding polynomial
system. Machine learning techniques including nearest
neighbors, support vector classifiers, and neural networks
are used to efficiently approximate the real discriminant
locus. One application of having learned the real
discriminant locus is to develop a real homotopy method that
only tracks real solution paths unlike traditional methods
which track all complex solution paths. Examples show that
the proposed approach can efficiently approximate
complicated solution boundaries such as those arising from
the equilibria of the N=4 Kuramoto model which was
previously intractable using traditional
methods.},
Doi = {10.1016/j.jsc.2022.08.001},
Key = {fds367059}
}
@article{fds369807,
Author = {Pura, JA and Li, X and Chan, C and Xie, J},
Title = {TEAM: A MULTIPLE TESTING ALGORITHM ON THE AGGREGATION TREE
FOR FLOW CYTOMETRY ANALYSIS},
Journal = {Annals of Applied Statistics},
Volume = {17},
Number = {1},
Pages = {621-640},
Year = {2023},
Month = {March},
url = {http://dx.doi.org/10.1214/22-AOAS1645},
Abstract = {In immunology studies, flow cytometry is a commonly used
multivariate single-cell assay. One key goal in flow
cytometry analysis is to detect the immune cells responsive
to certain stimuli. Statistically, this problem can be
translated into comparing two protein expression probability
density functions (PDFs) before and after the stimulus; the
goal is to pinpoint the regions where these two PDFs differ.
Further screening of these differential regions can be
performed to identify enriched sets of responsive cells. In
this paper we model identifying differential density regions
as a multiple testing problem. First, we partition the
sample space into small bins. In each bin we form a
hypothesis to test the existence of differential PDFs.
Second, we develop a novel multiple testing method, called
TEAM (testing on the aggregation tree method), to identify
those bins that harbor differential PDFs while controlling
the false discovery rate (FDR) under the desired level. TEAM
embeds the testing procedure into an aggregation tree to
test from fine-to coarse-resolution. The procedure achieves
the statistical goal of pinpointing density differences to
the smallest possible regions. TEAM is computationally
efficient, capable of analyzing large flow cytometry data
sets in much shorter time compared with competing methods.
We applied TEAM and competing methods on a flow cytometry
data set to identify T cells responsive to the
cytomegalovirus (CMV)-pp65 antigen stimulation. With
additional downstream screening, TEAM successfully
identified enriched sets containing monofunctional,
bifunctional, and polyfunctional T cells. Competing methods
either did not finish in a reasonable time frame or provided
less interpretable results. Numerical simulations and
theoretical justifications demonstrate that TEAM has
asymptotically valid, powerful, and robust performance.
Overall, TEAM is a computationally efficient and
statistically powerful algorithm that can yield meaningful
biological insights in flow cytometry studies.},
Doi = {10.1214/22-AOAS1645},
Key = {fds369807}
}
@article{fds367922,
Author = {Faigenbaum-Golovin, S and Levin, D},
Title = {Manifold reconstruction and denoising from scattered data in
high dimension},
Journal = {Journal of Computational and Applied Mathematics},
Volume = {421},
Pages = {114818-114818},
Publisher = {Elsevier BV},
Year = {2023},
Month = {March},
url = {http://dx.doi.org/10.1016/j.cam.2022.114818},
Doi = {10.1016/j.cam.2022.114818},
Key = {fds367922}
}
@article{fds372443,
Author = {Bezemek, ZW and Spiliopoulos, K},
Title = {Rate of homogenization for fully-coupled McKean-Vlasov
SDEs},
Journal = {Stochastics and Dynamics},
Volume = {23},
Number = {2},
Publisher = {World Scientific Pub Co Pte Ltd},
Year = {2023},
Month = {March},
url = {http://dx.doi.org/10.1142/S0219493723500132},
Abstract = {In this paper, we consider a fully-coupled slow-fast system
of McKean-Vlasov stochastic differential equations with full
dependence on the slow and fast component and on the law of
the slow component and derive convergence rates to its
homogenized limit. We do not make periodicity assumptions,
but we impose conditions on the fast motion to guarantee
ergodicity. In the course of the proof we obtain related
ergodic theorems and we gain results on the regularity of
Poisson type of equations and of the associated Cauchy
problem on the Wasserstein space that are of independent
interest.},
Doi = {10.1142/S0219493723500132},
Key = {fds372443}
}
@article{fds372623,
Author = {Alon, N and Wei, F},
Title = {Irregular subgraphs},
Journal = {Combinatorics, Probability and Computing},
Volume = {32},
Number = {2},
Pages = {269-283},
Publisher = {Cambridge University Press (CUP)},
Year = {2023},
Month = {March},
url = {http://dx.doi.org/10.1017/s0963548322000220},
Abstract = {<jats:title>Abstract</jats:title><jats:p>We suggest two
related conjectures dealing with the existence of spanning
irregular subgraphs of graphs. The first asserts that any
<jats:inline-formula><jats:alternatives>??<jats:tex-math>
$d$ </jats:tex-math></jats:alternatives></jats:inline-formula>-regular
graph on <jats:inline-formula><jats:alternatives>??<jats:tex-math>
$n$ </jats:tex-math></jats:alternatives></jats:inline-formula>
vertices contains a spanning subgraph in which the number of
vertices of each degree between <jats:inline-formula><jats:alternatives>??<jats:tex-math>
$0$ </jats:tex-math></jats:alternatives></jats:inline-formula>
and <jats:inline-formula><jats:alternatives>??<jats:tex-math>
$d$ </jats:tex-math></jats:alternatives></jats:inline-formula>
deviates from <jats:inline-formula><jats:alternatives>??<jats:tex-math>
$\frac{n}{d+1}$ </jats:tex-math></jats:alternatives></jats:inline-formula>
by at most <jats:inline-formula><jats:alternatives>??<jats:tex-math>
$2$ </jats:tex-math></jats:alternatives></jats:inline-formula>.
The second is that every graph on <jats:inline-formula><jats:alternatives>??<jats:tex-math>
$n$ </jats:tex-math></jats:alternatives></jats:inline-formula>
vertices with minimum degree <jats:inline-formula><jats:alternatives>??<jats:tex-math>
$\delta$ </jats:tex-math></jats:alternatives></jats:inline-formula>
contains a spanning subgraph in which the number of vertices
of each degree does not exceed <jats:inline-formula><jats:alternatives>??<jats:tex-math>
$\frac{n}{\delta +1}+2$ </jats:tex-math></jats:alternatives></jats:inline-formula>.
Both conjectures remain open, but we prove several
asymptotic relaxations for graphs with a large number of
vertices <jats:inline-formula><jats:alternatives>??<jats:tex-math>
$n$ </jats:tex-math></jats:alternatives></jats:inline-formula>.
In particular we show that if <jats:inline-formula><jats:alternatives>??<jats:tex-math>
$d^3 \log n \leq o(n)$ </jats:tex-math></jats:alternatives></jats:inline-formula>
then every <jats:inline-formula><jats:alternatives>??<jats:tex-math>
$d$ </jats:tex-math></jats:alternatives></jats:inline-formula>-regular
graph with <jats:inline-formula><jats:alternatives>??<jats:tex-math>
$n$ </jats:tex-math></jats:alternatives></jats:inline-formula>
vertices contains a spanning subgraph in which the number of
vertices of each degree between <jats:inline-formula><jats:alternatives>??<jats:tex-math>
$0$ </jats:tex-math></jats:alternatives></jats:inline-formula>
and <jats:inline-formula><jats:alternatives>??<jats:tex-math>
$d$ </jats:tex-math></jats:alternatives></jats:inline-formula>
is <jats:inline-formula><jats:alternatives>??<jats:tex-math>
$(1+o(1))\frac{n}{d+1}$ </jats:tex-math></jats:alternatives></jats:inline-formula>.
We also prove that any graph with <jats:inline-formula><jats:alternatives>??<jats:tex-math>
$n$ </jats:tex-math></jats:alternatives></jats:inline-formula>
vertices and minimum degree <jats:inline-formula><jats:alternatives>??<jats:tex-math>
$\delta$ </jats:tex-math></jats:alternatives></jats:inline-formula>
contains a spanning subgraph in which no degree is repeated
more than <jats:inline-formula><jats:alternatives>??<jats:tex-math>
$(1+o(1))\frac{n}{\delta +1}+2$ </jats:tex-math></jats:alternatives></jats:inline-formula>
times.</jats:p>},
Doi = {10.1017/s0963548322000220},
Key = {fds372623}
}
@article{fds372373,
Author = {Fang, D and Vilanova, AT},
Title = {Observable Error Bounds of the Time-Splitting Scheme for
Quantum-Classical Molecular Dynamics},
Journal = {SIAM Journal on Numerical Analysis},
Volume = {61},
Number = {1},
Pages = {26-44},
Publisher = {Society for Industrial & Applied Mathematics
(SIAM)},
Year = {2023},
Month = {February},
url = {http://dx.doi.org/10.1137/21m1462349},
Doi = {10.1137/21m1462349},
Key = {fds372373}
}
@article{fds369338,
Author = {Robles, C},
Title = {Pseudoconvexity at infinity in Hodge theory: a codimension
one example},
Year = {2023},
Month = {February},
Abstract = {The generalization of the Satake--Baily--Borel
compactification to arbitrary period maps has been reduced
to a certain extension problem on certain "neighborhoods at
infinity". Extension problems of this type require that the
neighborhood be pseudoconvex. The purpose of this note is to
establish the desired pseudoconvexity in one relatively
simple, but non-trivial, example: codimension one
degenerations of a period map of weight two Hodge structures
with first Hodge number $h^{2,0}$ equal to
2.},
Key = {fds369338}
}
@article{fds369339,
Author = {Robles, C},
Title = {Extension of Hodge norms at infinity},
Year = {2023},
Month = {February},
Abstract = {It is a long-standing problem in Hodge theory to generalize
the Satake--Baily--Borel (SBB) compactification of a locally
Hermitian symmetric space to arbitrary period maps. A proper
topological SBB-type completion has been constructed, and
the problem of showing that the construction is algebraic
has been reduced to showing that the compact fibres A of the
completion admit neighborhoods X satisfying certain
properties. All but one of those properties has been
established; the outstanding problem is to show that
holomorphic functions on certain divisors "at infinity"
extend to $X$. Extension theorems of this type require that
the complex manifold X be pseudoconvex; that is, admit a
plurisubharmonic exhaustion function. The neighborhood X is
stratified, and the strata admit Hodge norms which are may
be used to produce plurisubharmonic functions on the strata.
One would like to extend these norms to X so that they may
be used to construct the desired plurisubharmonic exhaustion
of X. The purpose of this paper is show that there exists a
function that simultaneously extends all the Hodge norms
along the strata that intersect the fibre A
nontrivially.},
Key = {fds369339}
}
@article{fds369364,
Author = {Perochon, S and Matias Di Martino and J and Carpenter, KLH and Compton,
S and Davis, N and Espinosa, S and Franz, L and Rieder, AD and Sullivan, C and Sapiro, G and Dawson, G},
Title = {A tablet-based game for the assessment of visual motor
skills in autistic children.},
Journal = {NPJ Digit Med},
Volume = {6},
Number = {1},
Pages = {17},
Year = {2023},
Month = {February},
url = {http://dx.doi.org/10.1038/s41746-023-00762-6},
Abstract = {Increasing evidence suggests that early motor impairments
are a common feature of autism. Thus, scalable, quantitative
methods for measuring motor behavior in young autistic
children are needed. This work presents an engaging and
scalable assessment of visual-motor abilities based on a
bubble-popping game administered on a tablet. Participants
are 233 children ranging from 1.5 to 10 years of age (147
neurotypical children and 86 children diagnosed with autism
spectrum disorder [autistic], of which 32 are also diagnosed
with co-occurring attention-deficit/hyperactivity disorder
[autistic+ADHD]). Computer vision analyses are used to
extract several game-based touch features, which are
compared across autistic, autistic+ADHD, and neurotypical
participants. Results show that younger (1.5-3 years)
autistic children pop the bubbles at a lower rate, and their
ability to touch the bubble's center is less accurate
compared to neurotypical children. When they pop a bubble,
their finger lingers for a longer period, and they show more
variability in their performance. In older children
(3-10-years), consistent with previous research, the
presence of co-occurring ADHD is associated with greater
motor impairment, reflected in lower accuracy and more
variable performance. Several motor features are correlated
with standardized assessments of fine motor and cognitive
abilities, as evaluated by an independent clinical
assessment. These results highlight the potential of
touch-based games as an efficient and scalable approach for
assessing children's visual-motor skills, which can be part
of a broader screening tool for identifying early signs
associated with autism.},
Doi = {10.1038/s41746-023-00762-6},
Key = {fds369364}
}
@article{fds371406,
Author = {Kim, R and Nijhout, HF and Reed, MC},
Title = {Mathematical insights into the role of dopamine signaling in
circadian entrainment.},
Journal = {Mathematical biosciences},
Volume = {356},
Pages = {108956},
Year = {2023},
Month = {February},
url = {http://dx.doi.org/10.1016/j.mbs.2022.108956},
Abstract = {The circadian clock in the mammalian brain comprises
interlocked molecular feedback loops that have downstream
effects on important physiological functions such as the
sleep-wake cycle and hormone regulation. Experiments have
shown that the circadian clock also modulates the synthesis
and breakdown of the neurotransmitter dopamine. Imbalances
in dopamine are linked to a host of neurological conditions
including Parkinson's disease, attention-deficit/hyperactivity
disorder, and mood disorders, and these conditions are often
accompanied by circadian disruptions. We have previously
created a mathematical model using nonlinear ordinary
differential equations to describe the influences of the
circadian clock on dopamine at the molecular level. Recent
experiments suggest that dopamine reciprocally influences
the circadian clock. Dopamine receptor D1 (DRD1) signaling
has been shown to aid in the entrainment of the clock to the
24-hour light-dark cycle, but the underlying mechanisms are
not well understood. In this paper, we use our mathematical
model to support the experimental hypothesis that DRD1
signaling promotes circadian entrainment by modulating the
clock's response to light. We model the effects of a phase
advance or delay, as well as the therapeutic potential of a
REV-ERB agonist. In addition to phase shifts, we study the
influences of photoperiod, or day length, in the
mathematical model, connect our findings with the
experimental and clinical literature, and determine the
parameter that affects the critical photoperiod that signals
seasonal changes to physiology.},
Doi = {10.1016/j.mbs.2022.108956},
Key = {fds371406}
}
@article{fds368122,
Author = {Zito, A and Rigon, T and Dunson, DB},
Title = {Inferring taxonomic placement from DNA barcoding aiding in
discovery of new taxa},
Journal = {Methods in Ecology and Evolution},
Volume = {14},
Number = {2},
Pages = {529-542},
Year = {2023},
Month = {February},
url = {http://dx.doi.org/10.1111/2041-210X.14009},
Abstract = {Predicting the taxonomic affiliation of DNA sequences
collected from biological samples is a fundamental step in
biodiversity assessment. This task is performed by
leveraging existing databases containing reference DNA
sequences endowed with a taxonomic identification. However,
environmental sequences can be from organisms that are
either unknown to science or for which there are no
reference sequences available. Thus, taxonomic novelty of a
sequence needs to be accounted for when doing
classification. We propose Bayesian nonparametric taxonomic
classifiers, BayesANT, which use species sampling model
priors to allow unobserved taxa to be discovered at each
taxonomic rank. Using a simple product multinomial
likelihood with conjugate Dirichlet priors at the lowest
rank, a highly flexible supervised algorithm is developed to
provide a probabilistic prediction of the taxa placement of
each sequence at each rank. As an illustration, we run our
algorithm on a carefully annotated library of Finnish
arthropods (FinBOL). To assess the ability of BayesANT to
recognize novelty and to predict known taxonomic
affiliations correctly, we test it on two training-test
splitting scenarios, each with a different proportion of
taxa unobserved in training. We show how our algorithm
attains accurate predictions and reliably quantifies
classification uncertainty, especially when many sequences
in the test set are affiliated to taxa unknown in training.
By enabling taxonomic predictions for DNA barcodes to
identify unseen branches, we believe BayesANT will be of
broad utility as a tool for DNA metabarcoding within
bioinformatics pipelines.},
Doi = {10.1111/2041-210X.14009},
Key = {fds368122}
}
@article{fds368056,
Author = {Bray, H and Hirsch, S and Kazaras, D and Khuri, M and Zhang,
Y},
Title = {Spacetime Harmonic Functions and Applications to
Mass},
Journal = {Perspectives in Scalar Curvature},
Publisher = {World Scientific},
Editor = {Gromov, ML and Lawson, HB},
Year = {2023},
Month = {February},
Abstract = {In the pioneering work of Stern, level sets of harmonic
functions have been shown to be an effective tool in the
study of scalar curvature in dimension 3. Generalizations of
this idea, utilizing level sets of so called spacetime
harmonic functions as well as other elliptic equations, are
similarly effective in treating geometric inequalities
involving the ADM mass. In this paper, we survey recent
results in this context, focusing on applications of
spacetime harmonic functions to the asymptotically flat and
asymptotically hyperbolic versions of the spacetime positive
mass theorem, and additionally introduce a new concept of
total mass valid in both settings which is encoded in
interpolation regions between generic initial data and model
geometries. Furthermore, a novel and elementary proof of the
positive mass theorem with charge is presented, and the
level set approach to the Penrose inequality given by
Huisken and Ilmanen is related to the current developments.
Lastly, we discuss several open problems.},
Key = {fds368056}
}
@article{fds369849,
Author = {Qi, D and Liu, J-G},
Title = {A random batch method for efficient ensemble forecasts of
multiscale turbulent systems.},
Journal = {Chaos (Woodbury, N.Y.)},
Volume = {33},
Number = {2},
Pages = {023113},
Year = {2023},
Month = {February},
url = {http://dx.doi.org/10.1063/5.0129127},
Abstract = {A new efficient ensemble prediction strategy is developed
for a multiscale turbulent model framework with emphasis on
the nonlinear interactions between large and small-scale
variables. The high computational cost in running large
ensemble simulations of high-dimensional equations is
effectively avoided by adopting a random batch decomposition
of the wide spectrum of the fluctuation states, which is a
characteristic feature of the multiscale turbulent systems.
The time update of each ensemble sample is then only subject
to a small portion of the small-scale fluctuation modes in
one batch, while the true model dynamics with multiscale
coupling is respected by frequent random resampling of the
batches at each time updating step. We investigate both
theoretical and numerical properties of the proposed method.
First, the convergence of statistical errors in the random
batch model approximation is shown rigorously independent of
the sample size and full dimension of the system. Next, the
forecast skill of the computational algorithm is tested on
two representative models of turbulent flows exhibiting many
key statistical phenomena with a direct link to realistic
turbulent systems. The random batch method displays robust
performance in capturing a series of crucial statistical
features with general interests, including highly
non-Gaussian fat-tailed probability distributions and
intermittent bursts of instability, while requires a much
lower computational cost than the direct ensemble approach.
The efficient random batch method also facilitates the
development of new strategies in uncertainty quantification
and data assimilation for a wide variety of general complex
turbulent systems in science and engineering.},
Doi = {10.1063/5.0129127},
Key = {fds369849}
}
@article{fds369365,
Author = {Engelhard, MM and Henao, R and Berchuck, SI and Chen, J and Eichner, B and Herkert, D and Kollins, SH and Olson, A and Perrin, EM and Rogers, U and Sullivan, C and Zhu, Y and Sapiro, G and Dawson, G},
Title = {Predictive Value of Early Autism Detection Models Based on
Electronic Health Record Data Collected Before Age 1
Year.},
Journal = {JAMA Netw Open},
Volume = {6},
Number = {2},
Pages = {e2254303},
Year = {2023},
Month = {February},
url = {http://dx.doi.org/10.1001/jamanetworkopen.2022.54303},
Abstract = {IMPORTANCE: Autism detection early in childhood is critical
to ensure that autistic children and their families have
access to early behavioral support. Early correlates of
autism documented in electronic health records (EHRs) during
routine care could allow passive, predictive model-based
monitoring to improve the accuracy of early detection.
OBJECTIVE: To quantify the predictive value of early autism
detection models based on EHR data collected before age 1
year. DESIGN, SETTING, AND PARTICIPANTS: This retrospective
diagnostic study used EHR data from children seen within the
Duke University Health System before age 30 days between
January 2006 and December 2020. These data were used to
train and evaluate L2-regularized Cox proportional hazards
models predicting later autism diagnosis based on data
collected from birth up to the time of prediction (ages
30-360 days). Statistical analyses were performed between
August 1, 2020, and April 1, 2022. MAIN OUTCOMES AND
MEASURES: Prediction performance was quantified in terms of
sensitivity, specificity, and positive predictive value
(PPV) at clinically relevant model operating thresholds.
RESULTS: Data from 45 080 children, including 924 (1.5%)
meeting autism criteria, were included in this study.
Model-based autism detection at age 30 days achieved 45.5%
sensitivity and 23.0% PPV at 90.0% specificity. Detection by
age 360 days achieved 59.8% sensitivity and 17.6% PPV at
81.5% specificity and 38.8% sensitivity and 31.0% PPV at
94.3% specificity. CONCLUSIONS AND RELEVANCE: In this
diagnostic study of an autism screening test, EHR-based
autism detection achieved clinically meaningful accuracy by
age 30 days, improving by age 1 year. This automated
approach could be integrated with caregiver surveys to
improve the accuracy of early autism screening.},
Doi = {10.1001/jamanetworkopen.2022.54303},
Key = {fds369365}
}
@article{fds369337,
Author = {Bierman, J and Li, Y and Lu, J},
Title = {Improving the Accuracy of Variational Quantum Eigensolvers
with Fewer Qubits Using Orbital Optimization.},
Journal = {Journal of chemical theory and computation},
Volume = {19},
Number = {3},
Pages = {790-798},
Year = {2023},
Month = {February},
url = {http://dx.doi.org/10.1021/acs.jctc.2c00895},
Abstract = {Near-term quantum computers will be limited in the number of
qubits on which they can process information as well as the
depth of the circuits that they can coherently carry out. To
date, experimental demonstrations of algorithms such as the
Variational Quantum Eigensolver (VQE) have been limited to
small molecules using minimal basis sets for this reason. In
this work we propose incorporating an orbital optimization
scheme into quantum eigensolvers wherein a parametrized
partial unitary transformation is applied to the basis
functions set in order to reduce the number of qubits
required for a given problem. The optimal transformation is
found by minimizing the ground state energy with respect to
this partial unitary matrix. Through numerical simulations
of small molecules up to 16 spin orbitals, we demonstrate
that this method has the ability to greatly extend the
capabilities of near-term quantum computers with regard to
the electronic structure problem. We find that VQE paired
with orbital optimization consistently achieves lower ground
state energies than traditional VQE when using the same
number of qubits and even frequently achieves lower ground
state energies than VQE methods using more
qubits.},
Doi = {10.1021/acs.jctc.2c00895},
Key = {fds369337}
}
@article{fds366158,
Author = {Coskun, MC and Liva, G and Graell I Amat and A and Lentmaier, M and Pfister, HD},
Title = {Successive Cancellation Decoding of Single Parity-Check
Product Codes: Analysis and Improved Decoding},
Journal = {Ieee Transactions on Information Theory},
Volume = {69},
Number = {2},
Pages = {823-841},
Publisher = {Institute of Electrical and Electronics Engineers
(IEEE)},
Year = {2023},
Month = {February},
url = {http://dx.doi.org/10.1109/TIT.2022.3207802},
Abstract = {A product code with single parity-check component codes can
be described via the tools of a multi-kernel polar code,
where the rows of the generator matrix are chosen according
to the constraints imposed by the product code construction.
Following this observation, successive cancellation decoding
of such codes is introduced. In particular, the error
probability of single parity-check product codes over binary
memoryless symmetric channels under successive cancellation
decoding is characterized. A bridge with the analysis of
product codes introduced by Elias is also established for
the binary erasure channel. Successive cancellation list
decoding of single parity-check product codes is then
described. For the provided example, simulations over the
binary input additive white Gaussian channel show that
successive cancellation list decoding outperforms belief
propagation decoding applied to the code graph. Finally, the
performance of the concatenation of a product code with a
high-rate outer code is investigated via distance spectrum
analysis. Examples of concatenations performing within 0.7
dB from the random coding union bound are
provided.},
Doi = {10.1109/TIT.2022.3207802},
Key = {fds366158}
}
@article{fds368929,
Author = {Pepona, M and Gounley, J and Randles, A},
Title = {Effect of constitutive law on the erythrocyte membrane
response to large strains.},
Journal = {Computers & mathematics with applications (Oxford, England :
1987)},
Volume = {132},
Pages = {145-160},
Year = {2023},
Month = {February},
url = {http://dx.doi.org/10.1016/j.camwa.2022.12.009},
Abstract = {Three constitutive laws, that is the Skalak, neo-Hookean and
Yeoh laws, commonly employed for describing the erythrocyte
membrane mechanics are theoretically analyzed and
numerically investigated to assess their accuracy for
capturing erythrocyte deformation characteristics and
morphology. Particular emphasis is given to the nonlinear
deformation regime, where it is known that the discrepancies
between constitutive laws are most prominent. Hence, the
experiments of optical tweezers and micropipette aspiration
are considered here, for which relationships between the
individual shear elastic moduli of the constitutive laws can
also be established through analysis of the
tension-deformation relationship. All constitutive laws were
found to adequately predict the axial and transverse
deformations of a red blood cell subjected to stretching
with optical tweezers for a constant shear elastic modulus
value. As opposed to Skalak law, the neo-Hookean and Yeoh
laws replicated the erythrocyte membrane folding, that has
been experimentally observed, with the trade-off of
sustaining significant area variations. For the micropipette
aspiration, the suction pressure-aspiration length
relationship could be excellently predicted for a fixed
shear elastic modulus value only when Yeoh law was
considered. Importantly, the neo-Hookean and Yeoh laws
reproduced the membrane wrinkling at suction pressures close
to those experimentally measured. None of the constitutive
laws suffered from membrane area compressibility in the
micropipette aspiration case.},
Doi = {10.1016/j.camwa.2022.12.009},
Key = {fds368929}
}
@article{fds368885,
Author = {Kiselev, A and Yao, Y},
Title = {Small Scale Formations in the Incompressible Porous Media
Equation},
Journal = {Archive for Rational Mechanics and Analysis},
Volume = {247},
Number = {1},
Year = {2023},
Month = {February},
url = {http://dx.doi.org/10.1007/s00205-022-01830-z},
Abstract = {We construct examples of solutions to the incompressible
porous media (IPM) equation that must exhibit infinite in
time growth of derivatives provided they remain smooth. As
an application, this allows us to obtain nonlinear
instability for a class of stratified steady states of
IPM.},
Doi = {10.1007/s00205-022-01830-z},
Key = {fds368885}
}
@article{fds364956,
Author = {Alian, A and Shelley, K and Wu, H-T},
Title = {Amplitude and phase measurements from harmonic analysis may
lead to new physiologic insights: lower body negative
pressure photoplethysmographic waveforms as an
example.},
Journal = {Journal of clinical monitoring and computing},
Volume = {37},
Number = {1},
Pages = {127-137},
Year = {2023},
Month = {February},
url = {http://dx.doi.org/10.1007/s10877-022-00866-6},
Abstract = {The photoplethysmographic (PPG) waveform contains
hemodynamic information in its oscillations. We provide a
new method for quantitative study of the waveform morphology
and its relationship to the hemodynamics. A data adaptive
modeling of the waveform shape is used to describe the PPG
waveforms recorded from ear and finger. Several indices,
based on the phase and amplitude information of different
harmonics, are proposed to describe the PPG morphology. The
proposed approach is illustrated by analyzing PPG waveforms
recorded during a lower body negative pressure (LBNP)
experiment. Different phase and amplitude dynamics are
observed during the LBNP experiment. Specifically, we
observe that the phase difference between the high order
harmonics and fundamental components change more
significantly when the PPG signal is recorded from the ear
than the finger at the beginning of the study. In contrast,
the finger PPG amplitude changes more when compared to the
ear PPG during the recovery period. A more complete harmonic
analysis of the PPG appears to provide new hemodynamic
information when used during a LBNP experiment. We encourage
other investigators who possess modulated clinical waveform
data (e.g. PPG, arterial pressure, respiratory, and
autonomic) to re-examine their data, using phase information
and higher harmonics as a potential source of new insights
into underlying physiologic mechanisms.},
Doi = {10.1007/s10877-022-00866-6},
Key = {fds364956}
}
@article{fds369139,
Author = {Murdoch, DM and Barfield, R and Chan, C and Towe, SL and Bell, RP and Volkheimer, A and Choe, J and Hall, SA and Berger, M and Xie, J and Meade,
CS},
Title = {Neuroimaging and immunological features of neurocognitive
function related to substance use in people with
HIV.},
Journal = {J Neurovirol},
Volume = {29},
Number = {1},
Pages = {78-93},
Year = {2023},
Month = {February},
url = {http://dx.doi.org/10.1007/s13365-022-01102-2},
Abstract = {This study sought to identify neuroimaging and immunological
factors associated with substance use and that contribute to
neurocognitive impairment (NCI) in people with HIV (PWH). We
performed cross-sectional immunological phenotyping,
neuroimaging, and neurocognitive testing on virally
suppressed PWH in four substance groups: cocaine only users
(COC), marijuana only users (MJ), dual users (Dual), and
Non-users. Participants completed substance use assessments,
multimodal MRI brain scan, neuropsychological testing, and
blood and CSF sampling. We employed a two-stage analysis of
305 possible biomarkers of cognitive function associated
with substance use. Feature reduction (Kruskal Wallis
p-value < 0.05) identified 53 biomarkers associated with
substance use (22 MRI and 31 immunological) for model
inclusion along with clinical and demographic variables. We
employed eXtreme Gradient Boosting (XGBoost) with these
markers to predict cognitive function (global T-score).
SHapley Additive exPlanations (SHAP) values were calculated
to rank features for impact on model output and NCI.
Participants were 110 PWH with sustained HIV viral
suppression (33 MJ, 12 COC, 22 Dual, and 43 Non-users). The
ten highest ranking biomarkers for predicting global T-score
were 4 neuroimaging biomarkers including functional
connectivity, gray matter volume, and white matter
integrity; 5 soluble biomarkers (plasma glycine, alanine,
lyso-phosphatidylcholine (lysoPC) aC17.0,
hydroxy-sphingomyelin (SM.OH) C14.1, and
phosphatidylcholinediacyl (PC aa) C28.1); and 1 clinical
variable (nadir CD4 count). The results of our machine
learning model suggest that substance use may indirectly
contribute to NCI in PWH through both metabolomic and
neuropathological mechanisms.},
Doi = {10.1007/s13365-022-01102-2},
Key = {fds369139}
}
@article{fds369693,
Author = {Nelson, AC and Fogelson, AL},
Title = {Towards understanding the effect of fibrinogen interactions
on fibrin gel structure.},
Journal = {Physical review. E},
Volume = {107},
Number = {2-1},
Pages = {024413},
Publisher = {American Physical Society (APS)},
Year = {2023},
Month = {February},
url = {http://dx.doi.org/10.1103/physreve.107.024413},
Abstract = {Fibrin gelation involves the enzymatic conversion of the
plasma protein fibrinogen to fibrin monomers which then
polymerize to form the gel that is a major structural
component of a blood clot. Because fibrinogen provides the
material from which fibrin is made, it is generally regarded
as promoting the gelation process. However, fibrinogen can
bind to a site on a fibrin oligomer, preventing another
fibrin oligomer from binding there, thus slowing the
polymerization process. "Soluble fibrin oligomers," which
are mixtures of fibrin and fibrinogen, are found in the
blood plasma and serve as biomarkers for various clotting
disorders, so understanding the interplay between fibrin and
fibrinogen during fibrin polymerization may have medical
importance. We present a kinetic gelation model of fibrin
polymerization which accounts for the dual and antagonistic
roles of fibrinogen. It builds on our earlier model of
fibrin polymerization that proposed a novel mechanism for
branch formation, which is a necessary component of
gelation. This previous model captured salient experimental
observations regarding the determinants of the structure of
the gel, but did not include fibrinogen binding. Here, we
add to that model reactions between fibrinogen and fibrin,
so oligomers are now mixtures of fibrin and fibrinogen, and
characterizing their dynamics leads to equations of
substantially greater complexity than previously. Using a
moment generating function approach, we derive a closed
system of moment equations and we track their dynamics
until the finite time blow-up of specific second moments
indicates that a gel has formed. In simulations begun with
an initial mixture of fibrin and fibrinogen monomers, a
sufficiently high relative concentration of fibrinogen
prevents gelation; the critical concentration increases with
the branch formation rate. In simulations begun with only
fibrinogen monomers that are converted to fibrin at a
specified rate, the rates of conversion, fibrinogen binding
to oligomers, and branch formation together determine
whether a gel forms, how long it takes to form, and the
structural properties of the gel that results.},
Doi = {10.1103/physreve.107.024413},
Key = {fds369693}
}
@article{fds360122,
Author = {Smith, CM and Goldrosen, N and Ciocanel, M-V and Santorella, R and Topaz, CM and Sen, S},
Title = {Racial Disparities in Criminal Sentencing Vary Considerably
across Federal Judges},
Journal = {Journal of Institutional and Theoretical
Economics},
Volume = {179},
Publisher = {Mohr Siebeck},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.1628/jite-2023-0005},
Doi = {10.1628/jite-2023-0005},
Key = {fds360122}
}
@article{fds361536,
Author = {Herzog, DP and Mattingly, JC and Nguyen, HD},
Title = {Gibbsian dynamics and the generalized Langevin
equation},
Journal = {Electronic Journal of Probability},
Volume = {28},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.1214/23-EJP904},
Abstract = {We study the statistically invariant structures of the
nonlinear generalized Langevin equation (GLE) with a
power-law memory kernel. For a broad class of memory
kernels, including those in the subdiffusive regime, we
construct solutions of the GLE using a Gibbsian framework,
which does not rely on existing Markovian approximations.
Moreover, we provide conditions on the decay of the memory
to ensure uniqueness of statistically steady states,
generalizing previous known results for the GLE under
particular kernels as a sum of exponentials.},
Doi = {10.1214/23-EJP904},
Key = {fds361536}
}
@article{fds365095,
Author = {Zito, A and Rigon, T and Ovaskainen, O and Dunson,
DB},
Title = {Bayesian Modeling of Sequential Discoveries.},
Journal = {Journal of the American Statistical Association},
Volume = {118},
Number = {544},
Pages = {2521-2532},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.1080/01621459.2022.2060835},
Abstract = {We aim at modeling the appearance of distinct tags in a
sequence of labeled objects. Common examples of this type of
data include words in a corpus or distinct species in a
sample. These sequential discoveries are often summarized
via accumulation curves, which count the number of distinct
entities observed in an increasingly large set of objects.
We propose a novel Bayesian method for species sampling
modeling by directly specifying the probability of a new
discovery, therefore, allowing for flexible specifications.
The asymptotic behavior and finite sample properties of such
an approach are extensively studied. Interestingly, our
enlarged class of sequential processes includes highly
tractable special cases. We present a subclass of models
characterized by appealing theoretical and computational
properties, including one that shares the same discovery
probability with the Dirichlet process. Moreover, due to
strong connections with logistic regression models, the
latter subclass can naturally account for covariates. We
finally test our proposal on both synthetic and real data,
with special emphasis on a large fungal biodiversity study
in Finland. Supplementary materials for this article are
available online.},
Doi = {10.1080/01621459.2022.2060835},
Key = {fds365095}
}
@article{fds371511,
Author = {Papadogeorgou, G and Bello, C and Ovaskainen, O and Dunson,
DB},
Title = {Covariate-Informed Latent Interaction Models: Addressing
Geographic & Taxonomic Bias in Predicting Bird–Plant
Interactions},
Journal = {Journal of the American Statistical Association},
Volume = {118},
Number = {544},
Pages = {2250-2261},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.1080/01621459.2023.2208390},
Abstract = {Reductions in natural habitats urge that we better
understand species’ interconnection and how biological
communities respond to environmental changes. However,
ecological studies of species’ interactions are limited by
their geographic and taxonomic focus which can distort our
understanding of interaction dynamics. We focus on
bird–plant interactions that refer to situations of
potential fruit consumption and seed dispersal. We develop
an approach for predicting species’ interactions that
accounts for errors in the recorded interaction networks,
addresses the geographic and taxonomic biases of existing
studies, is based on latent factors to increase flexibility
and borrow information across species, incorporates
covariates in a flexible manner to inform the latent
factors, and uses a meta-analysis dataset from 85 individual
studies. We focus on interactions among 232 birds and 511
plants in the Atlantic Forest, and identify 5% of pairs of
species with an unrecorded interaction, but posterior
probability that the interaction is possible over 80%.
Finally, we develop a permutation-based variable importance
procedure for latent factor network models and identify that
a bird’s body mass and a plant’s fruit diameter are
important in driving the presence of species interactions,
with a multiplicative relationship that exhibits both a
thresholding and a matching behavior. Supplementary
materials for this article are available
online.},
Doi = {10.1080/01621459.2023.2208390},
Key = {fds371511}
}
@article{fds372788,
Author = {Barrientos, AF and Sen, D and Page, GL and Dunson,
DB},
Title = {Bayesian Inferences on Uncertain Ranks and Orderings:
Application to Ranking Players and Lineups},
Journal = {Bayesian Analysis},
Volume = {18},
Number = {3},
Pages = {777-806},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.1214/22-BA1324},
Abstract = {It is common to be interested in rankings or order
relationships among entities. In complex settings where one
does not directly measure a univariate statistic upon which
to base ranks, such inferences typically rely on statistical
models having entity-specific parameters. These can be
treated as random effects in hierarchical models
characterizing variation among the entities. In this paper,
we are particularly interested in the problem of ranking
basketball players in terms of their contribution to team
performance. Using data from the National Basketball
Association (NBA) in the United States, we find that many
players have similar latent ability levels, making any
single estimated ranking highly misleading. The current
literature fails to provide summaries of order relationships
that adequately account for uncertainty. Motivated by this,
we propose a Bayesian strategy for characterizing
uncertainty in inferences on order relationships among
players and lineups. Our approach adapts to scenarios in
which uncertainty in ordering is high by producing more
conservative results that improve interpretability. This is
achieved through a reward function within a decision
theoretic framework. We apply our approach to data from the
2009–2010 NBA season.},
Doi = {10.1214/22-BA1324},
Key = {fds372788}
}
@article{fds372789,
Author = {Sachs, M and Sen, D and Lu, J and Dunson, D},
Title = {Posterior Computation with the Gibbs Zig-Zag
Sampler},
Journal = {Bayesian Analysis},
Volume = {18},
Number = {3},
Pages = {909-927},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.1214/22-BA1319},
Abstract = {An intriguing new class of piecewise deterministic Markov
processes (PDMPs) has recently been proposed as an
alternative to Markov chain Monte Carlo (MCMC). We propose a
new class of PDMPs termed Gibbs zig-zag samplers, which
allow parameters to be updated in blocks with a zig-zag
sampler applied to certain parameters and traditional
MCMC-style updates to others. We demonstrate the flexibility
of this framework on posterior sampling for logistic models
with shrinkage priors for high-dimensional regression and
random effects, and provide conditions for geometric
ergodicity and the validity of a central limit
theorem.},
Doi = {10.1214/22-BA1319},
Key = {fds372789}
}
@article{fds373933,
Author = {Li, D and Nguyen, P and Zhang, Z and Dunson, D},
Title = {Tree representations of brain structural connectivity via
persistent homology.},
Journal = {Frontiers in neuroscience},
Volume = {17},
Pages = {1200373},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.3389/fnins.2023.1200373},
Abstract = {The brain structural connectome is generated by a collection
of white matter fiber bundles constructed from diffusion
weighted MRI (dMRI), acting as highways for neural activity.
There has been abundant interest in studying how the
structural connectome varies across individuals in relation
to their traits, ranging from age and gender to
neuropsychiatric outcomes. After applying tractography to
dMRI to get white matter fiber bundles, a key question is
how to represent the brain connectome to facilitate
statistical analyses relating connectomes to traits. The
current standard divides the brain into regions of interest
(ROIs), and then relies on an <i>adjacency matrix</i> (AM)
representation. Each cell in the AM is a measure of
connectivity, e.g., number of fiber curves, between a pair
of ROIs. Although the AM representation is intuitive, a
disadvantage is the high-dimensionality due to the large
number of cells in the matrix. This article proposes a
simpler tree representation of the brain connectome, which
is motivated by ideas in computational topology and takes
topological and biological information on the cortical
surface into consideration. We demonstrate that our tree
representation preserves useful information and
interpretability, while reducing dimensionality to improve
statistical and computational efficiency. Applications to
data from the Human Connectome Project (HCP) are considered
and code is provided for reproducing our
analyses.},
Doi = {10.3389/fnins.2023.1200373},
Key = {fds373933}
}
@article{fds374277,
Author = {Chakraborty, A and Ou, R and Dunson, DB},
Title = {Bayesian Inference on High-Dimensional Multivariate Binary
Responses},
Journal = {Journal of the American Statistical Association},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.1080/01621459.2023.2260053},
Abstract = {It has become increasingly common to collect
high-dimensional binary response data; for example, with the
emergence of new sampling techniques in ecology. In smaller
dimensions, multivariate probit (MVP) models are routinely
used for inferences. However, algorithms for fitting such
models face issues in scaling up to high dimensions due to
the intractability of the likelihood, involving an integral
over a multivariate normal distribution having no analytic
form. Although a variety of algorithms have been proposed to
approximate this intractable integral, these approaches are
difficult to implement and/or inaccurate in high dimensions.
Our main focus is in accommodating high-dimensional binary
response data with a small-to-moderate number of covariates.
We propose a two-stage approach for inference on model
parameters while taking care of uncertainty propagation
between the stages. We use the special structure of latent
Gaussian models to reduce the highly expensive computation
involved in joint parameter estimation to focus inference on
marginal distributions of model parameters. This essentially
makes the method embarrassingly parallel for both stages. We
illustrate performance in simulations and applications to
joint species distribution modeling in ecology.
Supplementary materials for this article are available
online.},
Doi = {10.1080/01621459.2023.2260053},
Key = {fds374277}
}
@article{fds371114,
Author = {Koplik, G and Borggren, N and Voisin, S and Angeloro, G and Hineman, J and Johnson, T and Bendich, P},
Title = {Topological Simplification of Signals for Inference and
Approximate Reconstruction},
Journal = {IEEE Aerospace Conference Proceedings},
Volume = {2023-March},
Year = {2023},
Month = {January},
ISBN = {9781665490320},
url = {http://dx.doi.org/10.1109/AERO55745.2023.10115654},
Abstract = {As Internet of Things (loT) devices become both cheaper and
more powerful, researchers are increasingly finding
solutions to their scientific curiosities both financially
and com-putationally feasible. When operating with
restricted power or communications budgets, however, devices
can only send highly-compressed data. Such circumstances are
common for devices placed away from electric grids that can
only communicate via satellite, a situation particularly
plausible for environmental sensor networks. These
restrictions can be further complicated by potential
variability in the communications budget, for ex-ample a
solar-powered device needing to expend less energy when
transmitting data on a cloudy day. We propose a novel,
topology-based, lossy compression method well-equipped for
these restrictive yet variable circumstances. This
technique, Topological Signal Compression, allows sending
compressed sig-nals that utilize the entirety of a variable
communications budget. To demonstrate our algorithm's
capabilities, we per-form entropy calculations as well as a
classification exercise on increasingly topologically
simplified signals from the Free-Spoken Digit Dataset and
explore the stability of the resulting performance against
common baselines.},
Doi = {10.1109/AERO55745.2023.10115654},
Key = {fds371114}
}
@article{fds376284,
Author = {Solomon, E and Wagner, A and Bendich, P},
Title = {FROM GEOMETRY TO TOPOLOGY: INVERSE THEOREMS FOR DISTRIBUTED
PERSISTENCE},
Journal = {Journal of Computational Geometry},
Volume = {14},
Number = {2 Special Issue},
Pages = {172-196},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.20382/jocg.v14i2a8},
Abstract = {What is the “right” topological invariant of a large
point cloud X? Prior research has focused on estimating the
full persistence diagram of X, a quantity that is very
expensive to compute, unstable to outliers, and far from
injective. We therefore propose that, in many cases, the
collection of persistence diagrams of many small subsets of
X is a better invariant. This invariant, which we call
“distributed persistence,” is perfectly parallelizable,
more stable to outliers, and has a rich inverse theory. The
map from the space of metric spaces (with the quasi-isometry
distance) to the space of distributed persistence invariants
(with the Hausdorff-Bottleneck distance) is globally
bi-Lipschitz. This is a much stronger property than simply
being injective, as it implies that the inverse image of a
small neighborhood is a small neighborhood, and is to our
knowledge the only result of its kind in the TDA literature.
Moreover, the inverse Lipschitz constant depends on the size
of the subsets taken, so that as the size of these subsets
goes from small to large, the invariant interpolates between
a purely geometric one and a topological one. Lastly, we
note that our inverse results do not actually require
considering all subsets of a fixed size (an enormous
collection), but a relatively small collection satisfying
simple covering properties. These theoretical results are
complemented by synthetic experiments demonstrating the use
of distributed persistence in practice.},
Doi = {10.20382/jocg.v14i2a8},
Key = {fds376284}
}
@article{fds371501,
Author = {Fraiman, N and Mukherjee, S and Thoppe, G},
Title = {The Shadow Knows: Empirical Distributions of Minimum
Spanning Acycles and Persistence Diagrams of Random
Complexes},
Journal = {Discrete Analysis},
Volume = {2023},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.19086/da.73323},
Abstract = {In 1985, Frieze showed that the expected sum of the edge
weights of the minimum spanning tree (MST) in the uniformly
weighted graph converges to z (3). Recently, Hino and
Kanazawa extended this result to a uniformly weighted
simplicial complex, where the role of the MST is played by
its higher-dimensional analog—the Minimum Spanning Acycle
(MSA). Our work goes beyond and describes the histogram of
all the weights in this random MST and random MSA.
Specifically, we show that their empirical distributions
converge to a measure based on a concept called the shadow.
The shadow of a graph is the set of all the missing
transitive edges and, for a simplicial complex, it is a
related topological generalization. As a corollary, we
obtain a similar claim for the death times in the
persistence diagram corresponding to the above weighted
complex, a result of interest in applied
topology.},
Doi = {10.19086/da.73323},
Key = {fds371501}
}
@article{fds367868,
Author = {Caprio, M and Mukherjee, S},
Title = {Ergodic theorems for dynamic imprecise probability
kinematics},
Journal = {International Journal of Approximate Reasoning},
Volume = {152},
Pages = {325-343},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.1016/j.ijar.2022.10.016},
Abstract = {We formulate an ergodic theory for the (almost sure) limit
PE˜co of a sequence (PEnco) of successive dynamic imprecise
probability kinematics (DIPK, introduced in [10]) updates of
a set PE0co representing the initial beliefs of an agent. As
a consequence, we formulate a strong law of large
numbers.},
Doi = {10.1016/j.ijar.2022.10.016},
Key = {fds367868}
}
@article{fds370291,
Author = {Fei, F and Costa, A and Dolbow, JE and Settgast, RR and Cusini,
M},
Title = {Phase-Field Simulation of Near-Wellbore Nucleation and
Propagation of Hydraulic Fractures in Enhanced Geothermal
Systems (EGS)},
Journal = {Society of Petroleum Engineers Spe Reservoir Simulation
Conference, Rsc 2023},
Year = {2023},
Month = {January},
ISBN = {9781613998717},
url = {http://dx.doi.org/10.2118/212251-MS},
Abstract = {Enhanced geothermal systems (EGS) rely on the artificial
creation of fractures (i.e., hydraulic fractures) to enhance
the permeability of the formation which would, otherwise, be
too low to allow for fluid circulation. Hydraulic fracturing
involves complex nucleation and propagation processes, which
are key to the analysis and prediction of well productivity.
Numerical simulations are commonly employed to understand
the specific mechanisms behind nucleation and propagation of
hydraulic fractures. However, most numerical approaches face
tremendous challenges in tracking and accommodating the
evolving fracture geometry, especially when curved and
branched fractures occur. The phase-field method can
overcome this obstacle, as it can model fracture propagation
without the need for tracking the fracture tip nor for
remeshing. However, the most common phase-field formulation
is unable to accurately capture fracture nucleation. In this
work, we develop a new phase-field approach for hydraulic
fracturing that accounts for fracture nucleation due to the
strengths of geologic material and the existence of small
defects. Verification examples show that the proposed
formulation can accurately predict near-wellbore nucleation
and propagation of hydraulic fractures and the wellbore
breakdown pressure. Simulation of a three-dimensional
wellbore problem further demonstrates the efficiency of the
proposed phase-field method in handling fracture nucleation
and propagation.},
Doi = {10.2118/212251-MS},
Key = {fds370291}
}
@article{fds367493,
Author = {Gao, Y and Liu, JG and Wu, N},
Title = {Data-driven efficient solvers for Langevin dynamics on
manifold in high dimensions},
Journal = {Applied and Computational Harmonic Analysis},
Volume = {62},
Pages = {261-309},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.1016/j.acha.2022.09.003},
Abstract = {We study the Langevin dynamics of a physical system with
manifold structure M⊂Rp based on collected sample points
{xi}i=1n⊂M that probe the unknown manifold M. Through the
diffusion map, we first learn the reaction coordinates
{yi}i=1n⊂N corresponding to {xi}i=1n, where N is a
manifold diffeomorphic to M and isometrically embedded in
Rℓ with ℓ≪p. The induced Langevin dynamics on N in
terms of the reaction coordinates captures the slow time
scale dynamics such as conformational changes in biochemical
reactions. To construct an efficient and stable
approximation for the Langevin dynamics on N, we leverage
the corresponding Fokker-Planck equation on the manifold N
in terms of the reaction coordinates y. We propose an
implementable, unconditionally stable, data-driven finite
volume scheme for this Fokker-Planck equation, which
automatically incorporates the manifold structure of N.
Furthermore, we provide a weighted L2 convergence analysis
of the finite volume scheme to the Fokker-Planck equation on
N. The proposed finite volume scheme leads to a Markov chain
on {yi}i=1n with an approximated transition probability and
jump rate between the nearest neighbor points. After an
unconditionally stable explicit time discretization, the
data-driven finite volume scheme gives an approximated
Markov process for the Langevin dynamics on N and the
approximated Markov process enjoys detailed balance,
ergodicity, and other good properties.},
Doi = {10.1016/j.acha.2022.09.003},
Key = {fds367493}
}
@article{fds370086,
Author = {Liu, JG and Tang, Y and Zhao, Y},
Title = {ON THE EQUILIBRIUM OF THE POISSON-NERNST-PLANCK-BIKERMANN
MODEL EQUIPPING WITH THE STERIC AND CORRELATION
EFFECTS},
Journal = {Communications in Mathematical Sciences},
Volume = {21},
Number = {2},
Pages = {485-515},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.4310/CMS.2023.v21.n2.a8},
Abstract = {The Poisson-Nernst-Planck-Bikermann (PNPB) model, in which
the ions and water molecules are treated as different
species with non-uniform sizes and valences with
interstitial voids, can describe the steric and correlation
effects in ionic solution neglected by the
Poisson-Nernst-Planck and Poisson-Boltzmann theories with
point charge assumption. In the PNPB model, the electric
potential is governed by the fourth-order Poisson-Bikermann
(4PBik) equation instead of the Poisson equation so that it
can describe the correlation effect. Moreover, the steric
potential is included in the ionic and water fluxes as well
as the equilibrium Fermi-like distributions which
characterizes the steric effect quantitatively. In this
work, we analyze the self-adjointness and the kernel of the
fourth-order operator of the 4PBik equation. Also, we show
the positivity of the void volume function and the convexity
of the free energy. Following these properties, the
well-posedness of the PNPB model in equilibrium is given.
Furthermore, because the PNPB model has an energy dissipated
structure, we adopt a finite volume scheme which preserves
the energy dissipated property at the semi-discrete level.
Various numerical investigations are given to show the
parameter dependence of the steric effect to the steady
state},
Doi = {10.4310/CMS.2023.v21.n2.a8},
Key = {fds370086}
}
@article{fds372916,
Author = {Gao, Y and Liu, JG},
Title = {Random Walk Approximation for Irreversible Drift-Diffusion
Process on Manifold: Ergodicity, Unconditional Stability and
Convergence},
Journal = {Communications in Computational Physics},
Volume = {34},
Number = {1},
Pages = {132-172},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.4208/cicp.OA-2023-0021},
Abstract = {Irreversible drift-diffusion processes are very common in
biochemical reactions. They have a non-equilibrium
stationary state (invariant measure) which does not satisfy
detailed balance. For the corresponding Fokker-Planck
equation on a closed manifold, using Voronoi tessellation,
we propose two upwind finite volume schemes with or without
the information of the invariant measure. Both schemes
possess stochastic Q-matrix structures and can be decomposed
as a gradient flow part and a Hamiltonian flow part,
enabling us to prove unconditional stability, ergodicity and
error estimates. Based on the two upwind schemes, several
numerical examples – including sampling accelerated by a
mixture flow, image transformations and simulations for
stochastic model of chaotic system – are conducted. These
two structure-preserving schemes also give a natural random
walk approximation for a generic irreversible
drift-diffusion process on a manifold. This makes them
suitable for adapting to manifold-related computations that
arise from high-dimensional molecular dynamics
simulations.},
Doi = {10.4208/cicp.OA-2023-0021},
Key = {fds372916}
}
@article{fds373900,
Author = {Huang, X and Durrett, R},
Title = {Corrigendum to: The contact process on periodic trees
(Electronic Communications in Probability)},
Journal = {Electronic Communications in Probability},
Volume = {28},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.1214/23-ECP518},
Abstract = {In [1] we considered periodic trees in which the number of
children in successive generations is (n, a1, …, ak ) with
maxi ai ≤ Cn1−δ and (log ai)/ log n → bi as n →
∞. Our proof contained an error. In this note we correct
the proof. The theorem has changed: the critical value for
local survival is asymptotically√¯ck (log n)/n where lk =
max{i: 0 ≤ i ≤ k, ai ≠ 1} and ¯ck = min{k + 1 − lk
− blk, (k − b)/2}, where b = limn→∞ log(a1a2 · ·
· ak )/ log n.},
Doi = {10.1214/23-ECP518},
Key = {fds373900}
}
@article{fds365842,
Author = {Daubechies, I and Devore, R and Dym, N and Faigenbaum-Golovin, S and Kovalsky, SZ and Lin, KC and Park, J and Petrova, G and Sober,
B},
Title = {Neural Network Approximation of Refinable
Functions},
Journal = {IEEE Transactions on Information Theory},
Volume = {69},
Number = {1},
Pages = {482-495},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.1109/TIT.2022.3199601},
Abstract = {In the desire to quantify the success of neural networks in
deep learning and other applications, there is a great
interest in understanding which functions are efficiently
approximated by the outputs of neural networks. By now,
there exists a variety of results which show that a wide
range of functions can be approximated with sometimes
surprising accuracy by these outputs. For example, it is
known that the set of functions that can be approximated
with exponential accuracy (in terms of the number of
parameters used) includes, on one hand, very smooth
functions such as polynomials and analytic functions and, on
the other hand, very rough functions such as the Weierstrass
function, which is nowhere differentiable. In this paper, we
add to the latter class of rough functions by showing that
it also includes refinable functions. Namely, we show that
refinable functions are approximated by the outputs of deep
ReLU neural networks with a fixed width and increasing depth
with accuracy exponential in terms of their number of
parameters. Our results apply to functions used in the
standard construction of wavelets as well as to functions
constructed via subdivision algorithms in Computer Aided
Geometric Design.},
Doi = {10.1109/TIT.2022.3199601},
Key = {fds365842}
}
@article{fds371115,
Author = {Pu, W and Sober, B and Daly, N and Zhou, C and Sabetsarvestani, Z and Higgitt, C and Daubechies, I and Rodrigues, MRD},
Title = {Image Separation With Side Information: A Connected
Auto-Encoders Based Approach.},
Journal = {IEEE transactions on image processing : a publication of the
IEEE Signal Processing Society},
Volume = {32},
Pages = {2931-2946},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.1109/tip.2023.3275872},
Abstract = {X-radiography (X-ray imaging) is a widely used imaging
technique in art investigation. It can provide information
about the condition of a painting as well as insights into
an artist's techniques and working methods, often revealing
hidden information invisible to the naked eye. X-radiograpy
of double-sided paintings results in a mixed X-ray image and
this paper deals with the problem of separating this mixed
image. Using the visible color images (RGB images) from each
side of the painting, we propose a new Neural Network
architecture, based upon 'connected' auto-encoders, designed
to separate the mixed X-ray image into two simulated X-ray
images corresponding to each side. This connected
auto-encoders architecture is such that the encoders are
based on convolutional learned iterative shrinkage
thresholding algorithms (CLISTA) designed using algorithm
unrolling techniques, whereas the decoders consist of simple
linear convolutional layers; the encoders extract sparse
codes from the visible image of the front and rear paintings
and mixed X-ray image, whereas the decoders reproduce both
the original RGB images and the mixed X-ray image. The
learning algorithm operates in a totally self-supervised
fashion without requiring a sample set that contains both
the mixed X-ray images and the separated ones. The
methodology was tested on images from the double-sided wing
panels of the Ghent Altarpiece, painted in 1432 by the
brothers Hubert and Jan van Eyck. These tests show that the
proposed approach outperforms other state-of-the-art X-ray
image separation methods for art investigation
applications.},
Doi = {10.1109/tip.2023.3275872},
Key = {fds371115}
}
@article{fds371294,
Author = {Shan, S and Daubechies, I},
Title = {Diffusion Maps: Using the Semigroup Property for Parameter
Tuning},
Volume = {Part F6},
Pages = {409-424},
Booktitle = {Applied and Numerical Harmonic Analysis},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.1007/978-3-030-45847-8_18},
Abstract = {Diffusion maps (DM) constitute a classic dimension reduction
technique, for data lying on or close to a (relatively)
low-dimensional manifold embedded in a much larger
dimensional space. It consists in constructing a spectral
parametrization for the manifold from simulated random walks
or diffusion paths on the dataset. However, DM is hard to
tune in practice. In particular, the task to set a diffusion
time t when constructing the diffusion kernel matrix is
critical. We address this problem by using the semigroup
property of the diffusion operator. We propose a semigroup
criterion for picking the “right” value for t.
Experiments show that this principled approach is effective
and robust.},
Doi = {10.1007/978-3-030-45847-8_18},
Key = {fds371294}
}
@article{fds374632,
Author = {Etzioni, R and Gulati, R and Owens, L and Lange, J and Ryser,
MD},
Title = {Abstract IA018: Opportunity for interception as a driver of
benefit in cancer early detection: implications for
multi-cancer early detection testing},
Journal = {Cancer Prevention Research},
Volume = {16},
Number = {1_Supplement},
Pages = {IA018-IA018},
Publisher = {American Association for Cancer Research
(AACR)},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.1158/1940-6215.precprev22-ia018},
Abstract = {<jats:title>Abstract</jats:title> <jats:p>Early detection
cannot succeed unless there is adequate opportunity for
cancer to be diagnosed and intercepted within its early
preclinical phase. An understanding of opportunity for early
detection and interception is therefore critical in
predicting potential mortality reduction due to screening.
Opportunity is not directly observable but may be learned
using data from prospectively screened cohorts and
populations. In this presentation I will share a history of
methods for learning about early detection opportunity and
will present examples of how we have built on this work to
study opportunity for early detection in prostate and breast
cancer. I will describe a generic model of how opportunity
and sensitivity combine to produce stage shift and mortality
reduction and will briefly explore whether a lack of
opportunity may have been behind the results of the UCKCTOCS
trial. I will use this learning to motivate why I believe a
prospective study to investigate opportunity for
multi-cancer detection and interception is warranted before
or alongside ongoing and planned screening trials. This work
in in collaboration with Roman Gulat i and Lukas Owens (Fred
Hutch), Jane Lange (OHSU) and Marc Ryser (Duke University).
We acknowledge funding from the National Cancer Institute
and collaboration with and data from the Breast Cancer
Surveillance Consortium</jats:p> <jats:p>Citation Format:
Ruth Etzioni, Roman Gulati, Lukas Owens, Jane Lange, Marc D.
Ryser. Opportunity for interception as a driver of benefit
in cancer early detection: implications for multi-cancer
early detection testing. [abstract]. In: Proceedings of the
AACR Special Conference: Precision Prevention, Early
Detection, and Interception of Cancer; 2022 Nov 17-19;
Austin, TX. Philadelphia (PA): AACR; Can Prev Res 2023;16(1
Suppl): Abstract nr IA018.</jats:p>},
Doi = {10.1158/1940-6215.precprev22-ia018},
Key = {fds374632}
}
@article{fds365564,
Author = {Krishnappa Babu and PR and Di Martino and JM and Chang, Z and Perochon, S and Aiello, R and Carpenter, KLH and Compton, S and Davis, N and Franz, L and Espinosa, S and Flowers, J and Dawson, G and Sapiro,
G},
Title = {Complexity analysis of head movements in autistic
toddlers.},
Journal = {J Child Psychol Psychiatry},
Volume = {64},
Number = {1},
Pages = {156-166},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.1111/jcpp.13681},
Abstract = {BACKGROUND: Early differences in sensorimotor functioning
have been documented in young autistic children and infants
who are later diagnosed with autism. Previous research has
demonstrated that autistic toddlers exhibit more frequent
head movement when viewing dynamic audiovisual stimuli,
compared to neurotypical toddlers. To further explore this
behavioral characteristic, in this study, computer vision
(CV) analysis was used to measure several aspects of head
movement dynamics of autistic and neurotypical toddlers
while they watched a set of brief movies with social and
nonsocial content presented on a tablet. METHODS: Data were
collected from 457 toddlers, 17-36 months old, during
their well-child visit to four pediatric primary care
clinics. Forty-one toddlers were subsequently diagnosed with
autism. An application (app) displayed several brief movies
on a tablet, and the toddlers watched these movies while
sitting on their caregiver's lap. The front-facing camera in
the tablet recorded the toddlers' behavioral responses. CV
was used to measure the participants' head movement rate,
movement acceleration, and complexity using multiscale
entropy. RESULTS: Autistic toddlers exhibited significantly
higher rate, acceleration, and complexity in their head
movements while watching the movies compared to neurotypical
toddlers, regardless of the type of movie content (social
vs. nonsocial). The combined features of head movement
acceleration and complexity reliably distinguished the
autistic and neurotypical toddlers. CONCLUSIONS: Autistic
toddlers exhibit differences in their head movement dynamics
when viewing audiovisual stimuli. Higher complexity of their
head movements suggests that their movements were less
predictable and less stable compared to neurotypical
toddlers. CV offers a scalable means of detecting subtle
differences in head movement dynamics, which may be helpful
in identifying early behaviors associated with autism and
providing insight into the nature of sensorimotor
differences associated with autism.},
Doi = {10.1111/jcpp.13681},
Key = {fds365564}
}
@article{fds371718,
Author = {Solomon, O and Patriat, R and Braun, H and Palnitkar, TE and Moeller, S and Auerbach, EJ and Ugurbil, K and Sapiro, G and Harel,
N},
Title = {Motion robust magnetic resonance imaging via efficient
Fourier aggregation.},
Journal = {Medical image analysis},
Volume = {83},
Pages = {102638},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.1016/j.media.2022.102638},
Abstract = {We present a method for suppressing motion artifacts in
anatomical magnetic resonance acquisitions. Our proposed
technique, termed MOTOR-MRI, can recover and salvage images
which are otherwise heavily corrupted by motion induced
artifacts and blur which renders them unusable. Contrary to
other techniques, MOTOR-MRI operates on the reconstructed
images and not on k-space data. It relies on breaking the
standard acquisition protocol into several shorter ones
(while maintaining the same total acquisition time) and
subsequent efficient aggregation in Fourier space of locally
sharp and consistent information among them, producing a
sharp and motion mitigated image. We demonstrate the
efficacy of the technique on T<sub>2</sub>-weighted turbo
spin echo magnetic resonance brain scans with severe motion
corruption from both 3 T and 7 T scanners and show
significant qualitative and quantitative improvement in
image quality. MOTOR-MRI can operate independently, or in
conjunction with additional motion correction
methods.},
Doi = {10.1016/j.media.2022.102638},
Key = {fds371718}
}
@article{fds368436,
Author = {Cai, Z and Lu, J and Yang, S},
Title = {NUMERICAL ANALYSIS FOR INCHWORM MONTE CARLO METHOD: SIGN
PROBLEM AND ERROR GROWTH},
Journal = {Mathematics of Computation},
Volume = {92},
Number = {341},
Pages = {1141-1209},
Publisher = {American Mathematical Society (AMS)},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.1090/MCOM/3785},
Abstract = {We consider the numerical analysis of the inchworm Monte
Carlo method, which is proposed recently to tackle the
numerical sign problem for open quantum systems. We focus on
the growth of the numerical error with respect to the
simulation time, for which the inchworm Monte Carlo method
shows a flatter curve than the direct application of Monte
Carlo method to the classical Dyson series. To better
understand the underlying mechanism of the inchworm Monte
Carlo method, we distinguish two types of exponential error
growth, which are known as the numerical sign problem and
the error amplification. The former is due to the fast
growth of variance in the stochastic method, which can be
observed from the Dyson series, and the latter comes from
the evolution of the numerical solution. Our analysis
demonstrates that the technique of partial resummation can
be considered as a tool to balance these two types of error,
and the inchworm Monte Carlo method is a successful case
where the numerical sign problem is effectively suppressed
by such means. We first demonstrate our idea in the context
of ordinary differential equations, and then provide
complete analysis for the inchworm Monte Carlo method.
Several numerical experiments are carried out to verify our
theoretical results.},
Doi = {10.1090/MCOM/3785},
Key = {fds368436}
}
@article{fds370310,
Author = {Chen, Z and Lu, J and Lu, Y and Zhou, S},
Title = {A REGULARITY THEORY FOR STATIC SCHRÖDINGER EQUATIONS ON R
d IN SPECTRAL BARRON SPACES},
Journal = {SIAM Journal on Mathematical Analysis},
Volume = {55},
Number = {1},
Pages = {557-570},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.1137/22M1478719},
Abstract = {Spectral Barron spaces have received considerable interest
recently, as it is the natural function space for
approximation theory of two-layer neural networks with a
dimension-free convergence rate. In this paper, we study the
regularity of solutions to the whole-space static
Schrödinger equation in spectral Barron spaces. We prove
that if the source of the equation lies in the spectral
Barron space B s(R d) and the potential function admitting a
nonnegative lower bound decomposes as a positive constant
plus a function in B s(R d), then the solution lies in the
spectral Barron space B s+2(R d).},
Doi = {10.1137/22M1478719},
Key = {fds370310}
}
@article{fds371889,
Author = {Chen, Z and Lu, J and Qian, H and Wang, X and Yin, W},
Title = {HeteRSGD: Tackling Heterogeneous Sampling Costs via Optimal
Reweighted Stochastic Gradient Descent},
Journal = {Proceedings of Machine Learning Research},
Volume = {206},
Pages = {10732-10781},
Year = {2023},
Month = {January},
Abstract = {One implicit assumption in current stochastic gradient
descent (SGD) algorithms is the identical cost for sampling
each component function of the finite-sum objective.
However, there are applications where the costs differ
substantially, for which SGD schemes with uniform sampling
invoke a high sampling load. We investigate the use of
importance sampling (IS) as a cost saver in this setting, in
contrast to its traditional use for variance reduction. The
key ingredient is a novel efficiency metric for IS that
advocates low sampling costs while penalizing high gradient
variances. We then propose HeteRSGD, an SGD scheme that
performs gradient sampling according to optimal probability
weights stipulated by the metric, and establish theories on
its optimal asymptotic and finite-time convergence rates
among all possible IS-based SGD schemes. We show that the
relative efficiency gain of HeteRSGD can be arbitrarily
large regardless of the problem dimension and number of
components. Our theoretical results are validated
numerically for both convex and nonconvex
problems.},
Key = {fds371889}
}
@article{fds371890,
Author = {Lee, H and Lu, J and Tan, Y},
Title = {Convergence of score-based generative modeling for general
data distributions},
Journal = {Proceedings of Machine Learning Research},
Volume = {201},
Pages = {946-985},
Year = {2023},
Month = {January},
Abstract = {Score-based generative modeling (SGM) has grown to be a
hugely successful method for learning to generate samples
from complex data distributions such as that of images and
audio. It is based on evolving an SDE that transforms white
noise into a sample from the learned distribution, using
estimates of the score function, or gradient log-pdf.
Previous convergence analyses for these methods have
suffered either from strong assumptions on the data
distribution or exponential dependencies, and hence fail to
give efficient guarantees for the multimodal and non-smooth
distributions that arise in practice and for which good
empirical performance is observed. We consider a popular
kind of SGM—denoising diffusion models—and give
polynomial convergence guarantees for general data
distributions, with no assumptions related to functional
inequalities or smoothness. Assuming L2-accurate score
estimates, we obtain Wasserstein distance guarantees for any
distribution of bounded support or sufficiently decaying
tails, as well as TV guarantees for distributions with
further smoothness assumptions.},
Key = {fds371890}
}
@article{fds372260,
Author = {Chen, Z and Li, Y and Lu, J},
Title = {ON THE GLOBAL CONVERGENCE OF RANDOMIZED COORDINATE GRADIENT
DESCENT FOR NONCONVEX OPTIMIZATION*},
Journal = {SIAM Journal on Optimization},
Volume = {33},
Number = {2},
Pages = {713-738},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.1137/21M1460375},
Abstract = {In this work, we analyze the global convergence property of
a coordinate gradient descent with random choice of
coordinates and stepsizes for nonconvex optimization
problems. Under generic assumptions, we prove that the
algorithm iterate will almost surely escape strict saddle
points of the objective function. As a result, the algorithm
is guaranteed to converge to local minima if all saddle
points are strict. Our proof is based on viewing the
coordinate descent algorithm as a nonlinear random dynamical
system and a quantitative finite block analysis of its
linearization around saddle points.},
Doi = {10.1137/21M1460375},
Key = {fds372260}
}
@article{fds372774,
Author = {Sachs, M and Sen, D and Lu, J and Dunson, D},
Title = {Posterior Computation with the Gibbs Zig-Zag
Sampler},
Journal = {Bayesian Analysis},
Volume = {18},
Number = {3},
Pages = {909-927},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.1214/22-BA1319},
Abstract = {An intriguing new class of piecewise deterministic Markov
processes (PDMPs) has recently been proposed as an
alternative to Markov chain Monte Carlo (MCMC). We propose a
new class of PDMPs termed Gibbs zig-zag samplers, which
allow parameters to be updated in blocks with a zig-zag
sampler applied to certain parameters and traditional
MCMC-style updates to others. We demonstrate the flexibility
of this framework on posterior sampling for logistic models
with shrinkage priors for high-dimensional regression and
random effects, and provide conditions for geometric
ergodicity and the validity of a central limit
theorem.},
Doi = {10.1214/22-BA1319},
Key = {fds372774}
}
@article{fds372815,
Author = {Huang, H and Landsberg, JM and Lu, J},
Title = {GEOMETRY OF BACKFLOW TRANSFORMATION ANSATZE FOR QUANTUM
MANY-BODY FERMIONIC WAVEFUNCTIONS},
Journal = {Communications in Mathematical Sciences},
Volume = {21},
Number = {5},
Pages = {1447-1453},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.4310/CMS.2023.v21.n5.a12},
Abstract = {Wave function ansatze based on the backflow transformation
are widely used to parametrize anti-symmetric multivariable
functions for many-body quantum problems. We study the
geometric aspects of such ansatze, in particular we show
that in general totally antisymmetric polynomials cannot be
efficiently represented by backflow transformation ansatze
at least in the category of polynomials. In fact, if there
are N particles in the system, one needs a linear
combination of at least O(N3N−3) determinants to represent
a generic totally antisymmetric polynomial. Our proof is
based on bounding the dimension of the source of the ansatze
from above and bounding the dimension of the target from
below.},
Doi = {10.4310/CMS.2023.v21.n5.a12},
Key = {fds372815}
}
@article{fds373339,
Author = {Bal, G and Becker, S and Drouot, A and Kammerer, CF and Lu, J and Watson,
AB},
Title = {EDGE STATE DYNAMICS ALONG CURVED INTERFACES},
Journal = {SIAM Journal on Mathematical Analysis},
Volume = {55},
Number = {5},
Pages = {4219-4254},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.1137/22M1489708},
Abstract = {We study the propagation of wavepackets along weakly curved
interfaces between topologically distinct media. Our
Hamiltonian is an adiabatic modulation of Dirac operators
omnipresent in the topological insulators literature. Using
explicit formulas for straight edges, we construct a family
of solutions that propagates, for long times,
unidirectionally and dispersion-free along the curved edge.
We illustrate our results through various numerical
simulations.},
Doi = {10.1137/22M1489708},
Key = {fds373339}
}
@article{fds373537,
Author = {Zhang, S and Lu, J and Zhao, H},
Title = {On Enhancing Expressive Power via Compositions of Single
Fixed-Size ReLU Network},
Journal = {Proceedings of Machine Learning Research},
Volume = {202},
Pages = {41452-41487},
Year = {2023},
Month = {January},
Abstract = {This paper explores the expressive power of deep neural
networks through the framework of function compositions. We
demonstrate that the repeated compositions of a single
fixed-size ReLU network exhibit surprising expressive power,
despite the limited expressive capabilities of the
individual network itself. Specifically, we prove by
construction that L2◦g◦r◦L1 can approximate
1-Lipschitz continuous functions on [0, 1]d with an error
O(r−1/d), where g is realized by a fixed-size ReLU
network, L1 and L2 are two affine linear maps matching the
dimensions, and g◦r denotes the r-times composition of g.
Furthermore, we extend such a result to generic continuous
functions on [0, 1]d with the approximation error
characterized by the modulus of continuity. Our results
reveal that a continuous-depth network generated via a
dynamical system has immense approximation power even if its
dynamics function is time-independent and realized by a
fixed-size ReLU network.},
Key = {fds373537}
}
@article{fds373538,
Author = {Chen, H and Lee, H and Lu, J},
Title = {Improved Analysis of Score-based Generative Modeling:
User-Friendly Bounds under Minimal Smoothness
Assumptions},
Journal = {Proceedings of Machine Learning Research},
Volume = {202},
Pages = {5367-5382},
Year = {2023},
Month = {January},
Abstract = {We give an improved theoretical analysis of score-based
generative modeling. Under a score estimate with small L2
error (averaged across timesteps), we provide efficient
convergence guarantees for any data distribution with
second-order moment, by either employing early stopping or
assuming a smoothness condition on the score function of the
data distribution. Our result does not rely on any
log-concavity or functional inequality assumption and has a
logarithmic dependence on the smoothness. In particular, we
show that under only a finite second moment condition,
approximating the following in reverse KL divergence in
ϵ-accuracy can be done in (equation presented)Õ (
dlog(1ϵ/δ) ) steps: 1) the variance-δ Gaussian
perturbation of any data distribution; 2) data distributions
with 1/δ-smooth score functions. Our analysis also provides
a quantitative comparison between different discrete
approximations and may guide the choice of discretization
points in practice.},
Key = {fds373538}
}
@article{fds373539,
Author = {Agazzi, A and Lu, J and Mukherjee, S},
Title = {Global optimality of Elman-type RNNs in the mean-field
regime},
Journal = {Proceedings of Machine Learning Research},
Volume = {202},
Pages = {196-227},
Year = {2023},
Month = {January},
Abstract = {We analyze Elman-type Recurrent Reural Networks (RNNs) and
their training in the mean-field regime. Specifically, we
show convergence of gradient descent training dynamics of
the RNN to the corresponding mean-field formulation in the
large width limit. We also show that the fixed points of the
limiting infinite-width dynamics are globally optimal, under
some assumptions on the initialization of the weights. Our
results establish optimality for feature-learning with wide
RNNs in the mean-field regime.},
Key = {fds373539}
}
@article{fds373540,
Author = {Marwah, T and Lipton, ZC and Lu, J and Risteski, A},
Title = {Neural Network Approximations of PDEs Beyond Linearity: A
Representational Perspective},
Journal = {Proceedings of Machine Learning Research},
Volume = {202},
Pages = {24139-24172},
Year = {2023},
Month = {January},
Abstract = {A burgeoning line of research leverages deep neural networks
to approximate the solutions to high dimensional PDEs,
opening lines of theoretical inquiry focused on explaining
how it is that these models appear to evade the curse of
dimensionality. However, most prior theoretical analyses
have been limited to linear PDEs. In this work, we take a
step towards studying the representational power of neural
networks for approximating solutions to nonlinear PDEs. We
focus on a class of PDEs known as nonlinear elliptic
variational PDEs, whose solutions minimize an Euler-Lagrange
energy functional E(u) = RΩ L(x, u(x), ∇u(x)) −
f(x)u(x)dx. We show that if composing a function with Barron
norm b with partial derivatives of L produces a function of
Barron norm at most BLbp, the solution to the PDE can be
ϵ-approximated in the L2 sense by a function with Barron
norm O ( (dBL)max{p log(1/ϵ),plog(1/ϵ) }). By a classical
result due to (Barron, 1993), this correspondingly bounds
the size of a 2-layer neural network needed to approximate
the solution. Treating p, ϵ, BL as constants, this quantity
is polynomial in dimension, thus showing neural networks can
evade the curse of dimensionality. Our proof technique
involves neurally simulating (preconditioned) gradient in an
appropriate Hilbert space, which converges exponentially
fast to the solution of the PDE, and such that we can bound
the increase of the Barron norm at each iterate. Our results
subsume and substantially generalize analogous prior results
for linear elliptic PDEs over a unit hypercube.},
Key = {fds373540}
}
@article{fds372232,
Author = {Ladd, W and Jensen, C and Vardhan, M and Ames, J and Hammond, JR and Draeger, EW and Randles, A},
Title = {Optimizing Cloud Computing Resource Usage for Hemodynamic
Simulation},
Journal = {Proceedings - 2023 IEEE International Parallel and
Distributed Processing Symposium, IPDPS 2023},
Pages = {568-578},
Year = {2023},
Month = {January},
ISBN = {9798350337662},
url = {http://dx.doi.org/10.1109/IPDPS54959.2023.00063},
Abstract = {Cloud computing resources are becoming an increasingly
attractive option for simulation workflows but require users
to assess a wider variety of hardware options and associated
costs than required by traditional in-house hardware or
fixed allocations at leadership computing facilities. The
pay-as-you-go model used by cloud providers gives users the
opportunity to make more nuanced cost-benefit decisions at
runtime by choosing hardware that best matches a given
workload, but creates the risk of suboptimal allocation
strategies or inadvertent cost overruns. In this work, we
propose the use of an iteratively-refined performance model
to optimize cloud simulation campaigns against overall cost,
throughput, or maximum time to solution. Hemodynamic
simulations represent an excellent use case for these
assessments, as the relative costs and dominant terms in the
performance model can vary widely with hardware, numerical
parameters and physics models. Performance and scaling
behavior of hemodynamic simulations on multiple cloud
services as well as a traditional compute cluster are
collected and evaluated, and an initial performance model is
proposed along with a strategy for dynamically refining it
with additional experimental data.},
Doi = {10.1109/IPDPS54959.2023.00063},
Key = {fds372232}
}
@article{fds373528,
Author = {Chidambaram, M and Wu, C and Cheng, Y and Ge, R},
Title = {Hiding Data Helps: On the Benefits of Masking for Sparse
Coding},
Journal = {Proceedings of Machine Learning Research},
Volume = {202},
Pages = {5600-5615},
Year = {2023},
Month = {January},
Abstract = {Sparse coding, which refers to modeling a signal as sparse
linear combinations of the elements of a learned dictionary,
has proven to be a successful (and interpretable) approach
in applications such as signal processing, computer vision,
and medical imaging. While this success has spurred much
work on provable guarantees for dictionary recovery when the
learned dictionary is the same size as the ground-truth
dictionary, work on the setting where the learned dictionary
is larger (or over-realized) with respect to the ground
truth is comparatively nascent. Existing theoretical results
in this setting have been constrained to the case of
noise-less data. We show in this work that, in the presence
of noise, minimizing the standard dictionary learning
objective can fail to recover the elements of the
ground-truth dictionary in the over-realized regime,
regardless of the magnitude of the signal in the
data-generating process. Furthermore, drawing from the
growing body of work on self-supervised learning, we propose
a novel masking objective for which recovering the
ground-truth dictionary is in fact optimal as the signal
increases for a large class of data-generating processes. We
corroborate our theoretical results with experiments across
several parameter regimes showing that our proposed
objective also enjoys better empirical performance than the
standard reconstruction objective.},
Key = {fds373528}
}
@article{fds373529,
Author = {Zhou, M and Ge, R},
Title = {Implicit Regularization Leads to Benign Overfitting for
Sparse Linear Regression},
Journal = {Proceedings of Machine Learning Research},
Volume = {202},
Pages = {42543-42573},
Year = {2023},
Month = {January},
Abstract = {In deep learning, often the training process finds an
interpolator (a solution with 0 training loss), but the test
loss is still low. This phenomenon, known as benign
overfitting, is a major mystery that received a lot of
recent attention. One common mechanism for benign
overfitting is implicit regularization, where the training
process leads to additional properties for the interpolator,
often characterized by minimizing certain norms. However,
even for a simple sparse linear regression problem y =
β∗Tx + ξ with sparse β∗, neither minimum ℓ1 or ℓ2
norm interpolator gives the optimal test loss. In this work,
we give a different parametrization of the model which leads
to a new implicit regularization effect that combines the
benefit of ℓ1 and ℓ2 interpolators. We show that
training our new model via gradient descent leads to an
interpolator with near-optimal test loss. Our result is
based on careful analysis of the training dynamics and
provides another example of implicit regularization effect
that goes beyond norm minimization.},
Key = {fds373529}
}
@article{fds374447,
Author = {Chidambaram, M and Wang, X and Wu, C and Ge, R},
Title = {Provably Learning Diverse Features in Multi-View Data with
Midpoint Mixup},
Journal = {Proceedings of Machine Learning Research},
Volume = {202},
Pages = {5563-5599},
Year = {2023},
Month = {January},
Abstract = {Mixup is a data augmentation technique that relies on
training using random convex combinations of data points and
their labels. In recent years, Mixup has become a standard
primitive used in the training of state-of-the-art image
classification models due to its demonstrated benefits over
empirical risk minimization with regards to generalization
and robustness. In this work, we try to explain some of this
success from a feature learning perspective. We focus our
attention on classification problems in which each class may
have multiple associated features (or views) that can be
used to predict the class correctly. Our main theoretical
results demonstrate that, for a non-trivial class of data
distributions with two features per class, training a
2-layer convolutional network using empirical risk
minimization can lead to learning only one feature for
almost all classes while training with a specific
instantiation of Mixup succeeds in learning both features
for every class. We also show empirically that these
theoretical insights extend to the practical settings of
image benchmarks modified to have multiple
features.},
Key = {fds374447}
}
@article{fds376017,
Author = {Zhao, H and Panigrahi, A and Ge, R and Arora, S},
Title = {Do Transformers Parse while Predicting the Masked
Word?},
Journal = {EMNLP 2023 - 2023 Conference on Empirical Methods in Natural
Language Processing, Proceedings},
Pages = {16513-16542},
Year = {2023},
Month = {January},
ISBN = {9798891760608},
Abstract = {Pre-trained language models have been shown to encode
linguistic structures like parse trees in their embeddings
while being trained unsupervised. Some doubts have been
raised whether the models are doing parsing or only some
computation weakly correlated with it. Concretely: (a) Is it
possible to explicitly describe transformers with realistic
embedding dimensions, number of heads, etc. that are capable
of doing parsing -or even approximate parsing? (b) Why do
pre-trained models capture parsing structure? This paper
takes a step toward answering these questions in the context
of generative modeling with PCFGs. We show that masked
language models like BERT or RoBERTa of moderate sizes can
approximately execute the Inside-Outside algorithm for the
English PCFG (Marcus et al., 1993). We also show that the
Inside-Outside algorithm is optimal for masked language
modeling loss on the PCFG-generated data. We conduct probing
experiments on models pre-trained on PCFG-generated data to
show that this not only allows recovery of approximate parse
tree, but also recovers marginal span probabilities computed
by the Inside-Outside algorithm, which suggests an implicit
bias of masked language modeling towards this
algorithm.},
Key = {fds376017}
}
@article{fds371245,
Author = {Ou, YJ and Barnett, AJ and Mitra, A and Schwartz, FR and Chen, C and Grimm,
L and Lo, JY and Rudin, C},
Title = {A user interface to communicate interpretable AI decisions
to radiologists},
Journal = {Progress in Biomedical Optics and Imaging - Proceedings of
SPIE},
Volume = {12467},
Year = {2023},
Month = {January},
ISBN = {9781510660397},
url = {http://dx.doi.org/10.1117/12.2654068},
Abstract = {Tools for computer-aided diagnosis based on deep learning
have become increasingly important in the medical field.
Such tools can be useful, but require effective
communication of their decision-making process in order to
safely and meaningfully guide clinical decisions. Inherently
interpretable models provide an explanation for each
decision that matches their internal decision-making
process. We present a user interface that incorporates the
Interpretable AI Algorithm for Breast Lesions (IAIA-BL)
model, which interpretably predicts both mass margin and
malignancy for breast lesions. The user interface displays
the most relevant aspects of the model's explanation
including the predicted margin value, the AI confidence in
the prediction, and the two most highly activated prototypes
for each case. In addition, this user interface includes
full-field and cropped images of the region of interest, as
well as a questionnaire suitable for a reader study. Our
preliminary results indicate that the model increases the
readers' confidence and accuracy in their decisions on
margin and malignancy.},
Doi = {10.1117/12.2654068},
Key = {fds371245}
}
@article{fds372810,
Author = {Lanners, Q and Parikh, H and Volfovsky, A and Rudin, C and Page,
D},
Title = {Variable Importance Matching for Causal Inference},
Journal = {Proceedings of Machine Learning Research},
Volume = {216},
Pages = {1174-1184},
Year = {2023},
Month = {January},
Abstract = {Our goal is to produce methods for observational causal
inference that are auditable, easy to troubleshoot, accurate
for treatment effect estimation, and scalable to
high-dimensional data. We describe a general framework
called Model-to-Match that achieves these goals by (i)
learning a distance metric via outcome modeling, (ii)
creating matched groups using the distance metric, and (iii)
using the matched groups to estimate treatment effects.
Model-to-Match uses variable importance measurements to
construct a distance metric, making it a flexible framework
that can be adapted to various applications. Concentrating
on the scalability of the problem in the number of potential
confounders, we operationalize the Model-to-Match framework
with LASSO. We derive performance guarantees for settings
where LASSO outcome modeling consistently identifies all
confounders (importantly without requiring the linear model
to be correctly specified). We also provide experimental
results demonstrating the method's auditability, accuracy,
and scalability as well as extensions to more general
nonparametric outcome modeling.},
Key = {fds372810}
}
@article{fds373003,
Author = {Agnew, E and Qiu, M and Zhu, L and Wiseman, S and Rudin,
C},
Title = {The Mechanical Bard: An Interpretable Machine Learning
Approach to Shakespearean Sonnet Generation},
Journal = {Proceedings of the Annual Meeting of the Association for
Computational Linguistics},
Volume = {2},
Pages = {1627-1638},
Year = {2023},
Month = {January},
ISBN = {9781959429715},
Abstract = {We consider the automated generation of sonnets, a poetic
form constrained according to meter, rhyme scheme, and
length. Sonnets generally also use rhetorical figures,
expressive language, and a consistent theme or narrative.
Our constrained decoding approach allows for the generation
of sonnets within preset poetic constraints, while using a
relatively modest neural backbone. Human evaluation confirms
that our approach produces Shakespearean sonnets that
resemble human-authored sonnets, and which adhere to the
genre’s defined constraints and contain lyrical language
and literary devices.},
Key = {fds373003}
}
@article{fds373531,
Author = {Chen, Z and Tan, S and Chajewska, U and Rudin, C and Caruana,
R},
Title = {Missing Values and Imputation in Healthcare Data: Can
Interpretable Machine Learning Help?},
Journal = {Proceedings of Machine Learning Research},
Volume = {209},
Pages = {86-99},
Year = {2023},
Month = {January},
Abstract = {Missing values are a fundamental problem in data science.
Many datasets have missing values that must be properly
handled because the way missing values are treated can have
large impact on the resulting machine learning model. In
medical applications, the consequences may affect healthcare
decisions. There are many methods in the literature for
dealing with missing values, including state-of-the-art
methods which often depend on black-box models for
imputation. In this work, we show how recent advances in
interpretable machine learning provide a new perspective for
understanding and tackling the missing value problem. We
propose methods based on high-accuracy glass-box Explainable
Boosting Machines (EBMs) that can help users (1) gain new
insights on missingness mechanisms and better understand the
causes of missingness, and (2) detect – or even alleviate
– potential risks introduced by imputation algorithms.
Experiments on real-world medical datasets illustrate the
effectiveness of the proposed methods.},
Key = {fds373531}
}
@article{fds374496,
Author = {Kiselev, A and Nazarov, F and Ryzhik, L and Yao, Y},
Title = {Chemotaxis and reactions in biology},
Journal = {Journal of the European Mathematical Society},
Volume = {25},
Number = {7},
Pages = {2641-2696},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.4171/JEMS/1247},
Abstract = {Chemotaxis plays a crucial role in a variety of processes in
biology and ecology. Quite often it acts to improve
efficiency of biological reactions. One example is the
immune system signalling, where infected tissues release
chemokines attracting monocytes to fight invading bacteria.
Another example is reproduction, where eggs release
pheromones that attract sperm. A macro scale example is
flower scent appealing to pollinators. In this paper we
consider a system of PDEs designed to model such processes.
Our interest is to quantify the effect of chemotaxis on
reaction rates compared to pure reaction-diffusion. We limit
consideration to surface chemotaxis, which is well motivated
from the point of view of many applications. Our results
provide the first insight into situations where chemotaxis
can be crucial for reaction success, and where its effect is
likely to be limited. The proofs are based on new analytical
tools; a significant part of the paper is dedicated to
building up the linear machinery that can be useful in more
general settings. In particular, we establish precise
estimates on the rates of convergence to the ground state
for a class of Fokker–Planck operators with potentials
that grow at a logarithmic rate at infinity. These estimates
are made possible by a new sharp weak weighted Poincaré
inequality.},
Doi = {10.4171/JEMS/1247},
Key = {fds374496}
}
@article{fds375269,
Author = {Levine, AS},
Title = {A note on rationally slice knots},
Journal = {New York Journal of Mathematics},
Volume = {29},
Pages = {1363-1372},
Year = {2023},
Month = {January},
Abstract = {Kawauchi proved that every strongly negative amphichiral
knot (Formula Presented) bounds a smoothly embedded disk in
some rational homology ball VK, whose construction a priori
depends on K. We show that VK is inde-pendent of K up to
diffeomorphism. Thus, a single 4-manifold, along with
connected sums thereof, accounts for all known examples of
knots that are rationally slice but not slice.},
Key = {fds375269}
}
@article{fds374293,
Author = {Lee, J and Xie, Y and Cheng, X},
Title = {Training Neural Networks for Sequential Change-Point
Detection},
Journal = {ICASSP, IEEE International Conference on Acoustics, Speech
and Signal Processing - Proceedings},
Volume = {2023-June},
Year = {2023},
Month = {January},
ISBN = {9781728163277},
url = {http://dx.doi.org/10.1109/ICASSP49357.2023.10095005},
Abstract = {Detecting an abrupt distributional shift of a data stream,
known as change-point detection, is a fundamental problem in
statistics and machine learning. We introduce a novel
approach for online change-point detection using neural
net-works. To be specific, our approach is training neural
net-works to compute the cumulative sum of a detection
statistic sequentially, which exhibits a significant change
when a change-point occurs. We demonstrated the superiority
and potential of the proposed method in detecting
change-point using both synthetic and real-world
data.1},
Doi = {10.1109/ICASSP49357.2023.10095005},
Key = {fds374293}
}
@article{fds365844,
Author = {Chen, Z and Wu, HT},
Title = {Disentangling modes with crossover instantaneous frequencies
by synchrosqueezed chirplet transforms, from theory to
application},
Journal = {Applied and Computational Harmonic Analysis},
Volume = {62},
Pages = {84-122},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.1016/j.acha.2022.08.004},
Abstract = {Analysis of signals with oscillatory modes with crossover
instantaneous frequencies is a challenging problem in time
series analysis. One way to handle this problem is lifting
the 2-dimensional time-frequency representation to a
3-dimensional representation, called time-frequency-chirp
rate (TFC) representation, by adding one extra chirp rate
parameter so that crossover frequencies are disentangled in
higher dimension. The chirplet transform is an algorithm for
this lifting idea, which leads to a TFC representation.
However, in practice, we found that it has a strong
“blurring” effect in the chirp rate axis, which limits
its application in real-world data. Moreover, to our
knowledge, we have limited mathematical understanding of the
chirplet transform in the literature. Motivated by the need
for the real-world data analysis, in this paper, we propose
the synchrosqueezed chirplet transform (SCT) that enhances
the TFC representation given by the chirplet transform. The
resulting concentrated TFC representation has high contrast
so that one can better distinguish different modes with
crossover instantaneous frequencies. The basic idea is to
use the phase information in the chirplet transform to
determine a reassignment rule that sharpens the TFC
representation determined by the chirplet transform. We also
analyze the chirplet transform and provide theoretical
guarantees of SCT.},
Doi = {10.1016/j.acha.2022.08.004},
Key = {fds365844}
}
@article{fds369945,
Author = {Colominas, MA and Wu, HT},
Title = {An Iterative Warping and Clustering Algorithm to Estimate
Multiple Wave-Shape Functions From a Nonstationary
Oscillatory Signal},
Journal = {IEEE Transactions on Signal Processing},
Volume = {71},
Pages = {701-712},
Publisher = {Institute of Electrical and Electronics Engineers
(IEEE)},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.1109/TSP.2023.3252883},
Abstract = {Nonsinusoidal oscillatory signals are everywhere. In
practice, the nonsinusoidal oscillatory pattern, modeled as
a 1-periodic wave-shape function (WSF), might vary from
cycle to cycle. When there are finite different WSFs, s1,sK,
so that the WSF jumps from one to another suddenly, the
different WSFs and jumps encode useful information. We
present an iterative warping and clustering algorithm to
estimate s1,sK from a nonstationary oscillatory signal with
time-varying amplitude and frequency, and hence the change
points of the WSFs. The algorithm is a novel combination of
time-frequency analysis, singular value decomposition
entropy and vector spectral clustering. We demonstrate the
efficiency of the proposed algorithm with simulated and real
signals, including the voice signal, arterial blood
pressure, electrocardiogram and accelerometer signal.
Moreover, we provide a mathematical justification of the
algorithm under the assumption that the amplitude and
frequency of the signal are slowly time-varying and there
are finite change points that model sudden changes from one
wave-shape function to another one.},
Doi = {10.1109/TSP.2023.3252883},
Key = {fds369945}
}
@article{fds375272,
Author = {Chen, HY and Wu, HT and Chen, CY},
Title = {Quality Aware Sleep Stage Classification over RIP Signals
with Persistence Diagrams},
Journal = {2023 IEEE 19th International Conference on Body Sensor
Networks, BSN 2023 - Proceedings},
Year = {2023},
Month = {January},
ISBN = {9798350338416},
url = {http://dx.doi.org/10.1109/BSN58485.2023.10331130},
Abstract = {Automated sleep stage classification is a valuable tool for
analyzing sleep patterns and has numerous applications in
wearable healthcare systems. However, the accuracy of sleep
stage classification using signals from wearable devices can
be affected by data quality issues such as signal
interference or packet loss. In this study, we present an
algorithm that addresses packet loss in respiratory
inductive plethysmography (RIP) signals for sleep stage
detection. RIP signals can be conveniently collected using
abdominal and thoracic belts. By exploring the rich
structural patterns in such signals, we utilize persistence
diagrams to uncover macro-structures for sleep stage
classification, which is particularly suitable for high data
missing rates. Our model achieves a promising performance of
76% accuracy and a 0.54 Cohen's kappa coefficient for
three-stage classification. Additionally, we evaluate the
model across different missing data rates and highlight the
superior fault tolerance of persistence diagram features
compared to other conventional temporal and spectral
features.},
Doi = {10.1109/BSN58485.2023.10331130},
Key = {fds375272}
}
@article{fds368211,
Author = {Dasgupta, S and Kakde, M},
Title = {On the Brumer-Stark conjecture},
Journal = {Annals of Mathematics},
Volume = {197},
Number = {1},
Pages = {289-388},
Publisher = {Annals of Mathematics},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.4007/annals.2023.197.1.5},
Abstract = {Let H=F be a finite abelian extension of number fields with
F totally real and H a CM field. Let S and T be disjoint
finite sets of places of F satisfying the standard
conditions. The Brumer-Stark conjecture states that the
Stickelberger element ΦH/FS,T annihilates the T-smoothed
class group ClT(H). We prove this conjecture away from p=2,
that is, after tensoring with Z[1/2]. We prove a stronger
version of this result conjectured by Kurihara that gives a
formula for the 0th Fitting ideal of the minus part of the
Pontryagin dual of [Formula Presented] in terms of
Stickelberger elements. We also show that this stronger
result implies Rubin's higher rank version of the
Brumer-Stark conjecture, again away from 2. Our technique is
a generalization of Ribet's method, building upon on our
earlier work on the Gross-Stark conjecture. Here we work
with group ring valued Hilbert modular forms as introduced
by Wiles. A key aspect of our approach is the construction
of congruences between cusp forms and Eisenstein series that
are stronger than usually expected, arising as shadows of
the trivial zeroes of p-adic L-functions. These stronger
congruences are essential to proving that the cohomology
classes we construct are unramified at p.},
Doi = {10.4007/annals.2023.197.1.5},
Key = {fds368211}
}
@article{fds369772,
Author = {Tackett, M and Viel, S and Manturuk, K},
Title = {A validation of the short-form classroom community scale for
undergraduate mathematics and statistics
students},
Journal = {Journal of University Teaching and Learning
Practice},
Volume = {20},
Number = {1},
Pages = {1-17},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.53761/1.20.01.08},
Abstract = {This study examines Cho & Demmans Epp’s short-form
adaptation of Rovai’s well-known Classroom Community Scale
(CCS-SF) as a measure of classroom community among
introductory undergraduate math and statistics students. A
series of statistical analyses were conducted to investigate
the validity of the CCS-SF for this new population. Data
were collected from 351 students enrolled in 21 online
classes, offered for credit in Fall 2020 and Spring 2021 at
a private university in the United States. Further
confirmatory analysis was conducted with data from 128
undergraduates enrolled in 13 in-person and hybrid classes,
offered for credit in Fall 2021 at the same institution.
Following Rovai’s original 20-item CCS, the 8-item CCS-SF
yields two interpretable factors, connectedness and
learning. This study confirms the two-factor structure of
the CCS-SF, and concludes that it is a valid measure of
classroom community among undergraduate students enrolled in
remote, hybrid, and in-person introductory mathematics and
statistics courses. Practitioner Notes 1. Cho & Demmans
Epp's 2019 Classroom Community Scale Short Form (CCS-SF) is
a promising but relatively new instrument for measuring
students’ sense of community, previously validated only
for graduate online courses. This research article validates
the instrument's use for undergraduate students in online,
hybrid, and in-person courses. 2. According to Rovai’s
original Classroom Community Scale from which the CCS-SF is
adapted, students’ sense of community can be understood by
two subscales, connectedness and learning. These subscales
measure how students relate to their peers and their
perception of being in a supportive learning environment. 3.
Through exploratory factor analysis, we have shown more
nuanced views of the subscales demonstrating the multiple
facets in which students evaluate belongingness among their
peers and perception of having shared learning goals. 4.
With this validation article, instructors can now administer
the CCS-SF instrument in undergraduate courses to assess the
classroom community, as well as using the instrument for
research on undergraduate students. 5. With this validation
article, educational researchers can use the CCS-SF to
better understand situational factors and pedagogies
associated with students’ sense of community and how these
associations vary for students with different
identities.},
Doi = {10.53761/1.20.01.08},
Key = {fds369772}
}
@article{fds374300,
Author = {Davis, R and Pries, R and Wickelgren, K},
Title = {The Galois action on the lower central series of the
fundamental group of the Fermat curve},
Journal = {Israel Journal of Mathematics},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.1007/s11856-023-2571-z},
Abstract = {Information about the absolute Galois group GK of a number
field K is encoded in how it acts on the étale fundamental
group π of a curve X defined over K. In the case that K =
ℚ(ζn) is the cyclotomic field and X is the Fermat curve
of degree n ≥ 3, Anderson determined the action of GK on
the étale homology with coefficients in ℤ/nℤ. The
étale homology is the first quotient in the lower central
series of the étale fundamental group. In this paper, we
determine the Galois module structure of the graded Lie
algebra for π. As a consequence, this determines the action
of GK on all degrees of the associated graded quotient of
the lower central series of the étale fundamental group of
the Fermat curve of degree n, with coefficients in
ℤ/nℤ.},
Doi = {10.1007/s11856-023-2571-z},
Key = {fds374300}
}
@article{fds370199,
Author = {Kush, D and Rossman, B},
Title = {TREE-DEPTH AND THE FORMULA COMPLEXITY OF SUBGRAPH
ISOMORPHISM},
Journal = {SIAM Journal on Computing},
Volume = {52},
Number = {1},
Pages = {273-325},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.1137/20M1372925},
Abstract = {For a fixed "pattern"" graph G, the colored G-subgraph
isomorphism problem (denoted by SUB(G)) asks, given an
n-vertex graph H and a coloring V (H) → V (G), whether H
contains a properly colored copy of G. The complexity of
this problem is tied to parameterized versions of P =? NP
and L =? NL, among other questions. An overarching goal is
to understand the complexity of SUB(G), under different
computational models, in terms of natural invariants of the
pattern graph G. In this paper, we establish a close
relationship between the formula complexity of SUB(G) and an
invariant known as tree-depth (denoted by (G)). SUB(G) is
known to be solvable by monotone AC0 formulas of size O(n
(G)). Our main result is an n Ω ((G)1/3) lower bound for
formulas that are monotone or have sublogarithmic depth.
This complements a lower bound of Li, Razborov, and Rossman
[SIAM J. Comput., 46 (2017), pp. 936-971] relating
tree-width and AC0 circuit size. As a corollary, it implies
a stronger homomorphism preservation theorem for firstorder
logic on finite structures [B. Rossman, An improved
homomorphism preservation theorem from lower bounds in
circuit complexity, in 8th Innovations in Theoretical
Computer Science Conference, LIPIcs. Leibniz Int. Proc.
Inform. 67, Schloss Dagstuhl. Leibniz-Zent. Inform., Wadern,
Germany, 2017, 27]. The technical core of this result is an
nΩ (k) lower bound in the special case where G is a
complete binary tree of height k, which we establish using
the pathset framework introduced in B. Rossman [SIAM J.
Comput., 47 (2018), pp. 1986-2028]. (The lower bound for
general patterns follows via a recent excluded-minor
characterization of tree-depth [W. Czerwiński, W. Nadara,
and M. Pilipczuk, SIAM J. Discrete Math., 35 (2021), pp.
934-947; K. Kawarabayashi and B. Rossman, A polynomial
excluded-minor approximation of treedepth, in Proceedings of
the 2018 Annual ACMSIAM Symposium on Discrete Algorithms,
2018, pp. 234-246]. Additional results of this paper extend
the pathset framework and improve upon both the best known
upper and lower bounds on the average-case formula size of
SUB(G) when G is a path.},
Doi = {10.1137/20M1372925},
Key = {fds370199}
}
@article{fds369327,
Author = {He, W and Rossman, B},
Title = {Symmetric Formulas for Products of Permutations},
Journal = {Leibniz International Proceedings in Informatics,
LIPIcs},
Volume = {251},
Year = {2023},
Month = {January},
ISBN = {9783959772631},
url = {http://dx.doi.org/10.4230/LIPIcs.ITCS.2023.68},
Abstract = {We study the formula complexity of the word problem WordSn,k
: (0, 1)kn2 → (0, 1): given n-by-n permutation matrices
M1,..., Mk, compute the (1, 1)-entry of the matrix product
M1 · · · Mk. An important feature of this function is
that it is invariant under action of Snk−1 given by
(π1,..., πk−1)(M1,..., Mk) = (M1π1−1,
π1M2π2−1,..., πk−2Mk−1πk−−11, πk−1Mk). This
symmetry is also exhibited in the smallest known unbounded
fan-in (and, or, not)-formulas for WordSn,k, which have size
nO(log k). In this paper we prove a matching nΩ(log k)
lower bound for Snk−1-invariant formulas computing
WordSn,k. This result is motivated by the fact that a
similar lower bound for unrestricted (non-invariant)
formulas would separate complexity classes NC1 and Logspace.
Our more general main theorem gives a nearly tight
nd(k1/d−1) lower bound on the Gk−1invariant depth-d
(maj, and, or, not)-formula size of WordG,k for any finite
simple group G whose minimum permutation representation has
degree n. We also give nearly tight lower bounds on the
Gk−1-invariant depth-d (and, or, not)-formula size in the
case where G is an abelian group.},
Doi = {10.4230/LIPIcs.ITCS.2023.68},
Key = {fds369327}
}
@article{fds374519,
Author = {He, Y and Zhao, H and Zhong, Y},
Title = {How Much Can One Learn a Partial Differential Equation from
Its Solution?},
Journal = {Foundations of Computational Mathematics},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.1007/s10208-023-09620-z},
Abstract = {In this work, we study the problem of learning a partial
differential equation (PDE) from its solution data. PDEs of
various types are used to illustrate how much the solution
data can reveal the PDE operator depending on the underlying
operator and initial data. A data-driven and data-adaptive
approach based on local regression and global consistency is
proposed for stable PDE identification. Numerical
experiments are provided to verify our analysis and
demonstrate the performance of the proposed
algorithms.},
Doi = {10.1007/s10208-023-09620-z},
Key = {fds374519}
}
@article{fds374520,
Author = {Zhang, S and Lu, J and Zhao, H},
Title = {On Enhancing Expressive Power via Compositions of Single
Fixed-Size ReLU Network},
Journal = {Proceedings of Machine Learning Research},
Volume = {202},
Pages = {41452-41487},
Year = {2023},
Month = {January},
Abstract = {This paper explores the expressive power of deep neural
networks through the framework of function compositions. We
demonstrate that the repeated compositions of a single
fixed-size ReLU network exhibit surprising expressive power,
despite the limited expressive capabilities of the
individual network itself. Specifically, we prove by
construction that L2◦g◦r◦L1 can approximate
1-Lipschitz continuous functions on [0, 1]d with an error
O(r−1/d), where g is realized by a fixed-size ReLU
network, L1 and L2 are two affine linear maps matching the
dimensions, and g◦r denotes the r-times composition of g.
Furthermore, we extend such a result to generic continuous
functions on [0, 1]d with the approximation error
characterized by the modulus of continuity. Our results
reveal that a continuous-depth network generated via a
dynamical system has immense approximation power even if its
dynamics function is time-independent and realized by a
fixed-size ReLU network.},
Key = {fds374520}
}
@article{fds368023,
Author = {Dawson, M and Dudley, C and Omoma, S and Tung, H-R and Ciocanel,
M-V},
Title = {Characterizing emerging features in cell dynamics using
topological data analysis methods.},
Journal = {Mathematical biosciences and engineering :
MBE},
Volume = {20},
Number = {2},
Pages = {3023-3046},
Publisher = {American Institute of Mathematical Sciences
(AIMS)},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.3934/mbe.2023143},
Abstract = {Filament-motor interactions inside cells play essential
roles in many developmental as well as other biological
processes. For instance, actin-myosin interactions drive the
emergence or closure of ring channel structures during wound
healing or dorsal closure. These dynamic protein
interactions and the resulting protein organization lead to
rich time-series data generated by using fluorescence
imaging experiments or by simulating realistic stochastic
models. We propose methods based on topological data
analysis to track topological features through time in cell
biology data consisting of point clouds or binary images.
The framework proposed here is based on computing the
persistent homology of the data at each time point and on
connecting topological features through time using
established distance metrics between topological summaries.
The methods retain aspects of monomer identity when
analyzing significant features in filamentous structure
data, and capture the overall closure dynamics when
assessing the organization of multiple ring structures
through time. Using applications of these techniques to
experimental data, we show that the proposed methods can
describe features of the emergent dynamics and
quantitatively distinguish between control and perturbation
experiments.},
Doi = {10.3934/mbe.2023143},
Key = {fds368023}
}
@article{fds374131,
Author = {Fintzen, J and Kaletha, T and Spice, L},
Title = {A TWISTED YU CONSTRUCTION, HARISH-CHANDRA CHARACTERS, AND
ENDOSCOPY},
Journal = {Duke Mathematical Journal},
Volume = {172},
Number = {12},
Pages = {2241-2301},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.1215/00127094-2022-0080},
Abstract = {We give a modification of Yu’s construction of
supercuspidal representations of a connected reductive group
G over a non-Archimedean local field F . This modification
restores the validity of certain key intertwining property
claims made by Yu, which were recently proved to be false
for the original construction. This modification is also an
essential ingredient in the construction of supercuspidal
L-packets in a preprint by the second author. As further
applications, we prove the stability and many instances of
endoscopic character identities of these supercuspidal
L-packets, subject to some conditions on the base field F .
In particular, for regular supercuspidal parameters, we
prove all instances of standard endoscopy. In addition, we
prove that these supercuspidal L-packets satisfy a recent
conjecture by the second author, which, together with
standard endoscopy, uniquely characterizes the local
Langlands correspondence for supercuspidal L-packets (again
subject to the conditions on F ). These results are based on
a statement of the Harish-Chandra character formula for the
supercuspidal representations arising from the twisted Yu
construction.},
Doi = {10.1215/00127094-2022-0080},
Key = {fds374131}
}
@article{fds374132,
Author = {Fintzen, J},
Title = {Supercuspidal representations in non-defining
characteristics},
Journal = {Journal of Algebra},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.1016/j.jalgebra.2023.05.019},
Abstract = {We show that a mod-ℓ-representation of a p-adic group
arising from the analogue of Yu's construction is
supercuspidal if and only if it arises from a supercuspidal
representation of a finite reductive group. This has been
previously shown by Henniart and Vigneras under the
assumption that the second adjointness holds.},
Doi = {10.1016/j.jalgebra.2023.05.019},
Key = {fds374132}
}
@article{fds373671,
Author = {Zhang, S and Lu, J and Zhao, H},
Title = {On Enhancing Expressive Power via Compositions of Single
Fixed-Size ReLU Network},
Journal = {Proceedings of Machine Learning Research},
Volume = {202},
Pages = {41452-41487},
Year = {2023},
Month = {January},
Abstract = {This paper explores the expressive power of deep neural
networks through the framework of function compositions. We
demonstrate that the repeated compositions of a single
fixed-size ReLU network exhibit surprising expressive power,
despite the limited expressive capabilities of the
individual network itself. Specifically, we prove by
construction that L2◦g◦r◦L1 can approximate
1-Lipschitz continuous functions on [0, 1]d with an error
O(r−1/d), where g is realized by a fixed-size ReLU
network, L1 and L2 are two affine linear maps matching the
dimensions, and g◦r denotes the r-times composition of g.
Furthermore, we extend such a result to generic continuous
functions on [0, 1]d with the approximation error
characterized by the modulus of continuity. Our results
reveal that a continuous-depth network generated via a
dynamical system has immense approximation power even if its
dynamics function is time-independent and realized by a
fixed-size ReLU network.},
Key = {fds373671}
}
@article{fds374491,
Author = {Bréchet, P and Papagiannouli, K and An, J and Montúfar,
G},
Title = {Critical Points and Convergence Analysis of Generative Deep
Linear Networks Trained with Bures-Wasserstein
Loss},
Journal = {Proceedings of Machine Learning Research},
Volume = {202},
Pages = {3106-3147},
Year = {2023},
Month = {January},
Abstract = {We consider a deep matrix factorization model of covariance
matrices trained with the Bures-Wasserstein distance. While
recent works have made advances in the study of the
optimization problem for overparametrized low-rank matrix
approximation, much emphasis has been placed on
discriminative settings and the square loss. In contrast,
our model considers another type of loss and connects with
the generative setting. We characterize the critical points
and minimizers of the Bures-Wasserstein distance over the
space of rank-bounded matrices. The Hessian of this loss at
low-rank matrices can theoretically blow up, which creates
challenges to analyze convergence of gradient optimization
methods. We establish convergence results for gradient flow
using a smooth perturbative version of the loss as well as
convergence results for finite step size gradient descent
under certain assumptions on the initial
weights.},
Key = {fds374491}
}
@article{fds372374,
Author = {Fang, D and Lin, L and Tong, Y},
Title = {Time-marching based quantum solvers for time-dependent
linear differential equations},
Journal = {Quantum},
Volume = {7},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.22331/Q-2023-03-20-955},
Abstract = {The time-marching strategy, which propagates the solution
from one time step to the next, is a natural strategy for
solving time-dependent differential equations on classical
computers, as well as for solving the Hamiltonian simulation
problem on quantum computers. For more general homogeneous
linear differential equations ddt|ψ(t)i = A(t)|ψ(t)i,
|ψ(0)i = |ψ0i, a time-marching based quantum solver can
suffer from exponentially vanishing success probability with
respect to the number of time steps and is thus considered
impractical. We solve this problem by repeatedly invoking a
technique called the uniform singular value amplification,
and the overall success probability can be lower bounded by
a quantity that is independent of the number of time steps.
The success probability can be further improved using a
compression gadget lemma. This provides a path of designing
quantum differential equation solvers that is alternative to
those based on quantum linear systems algorithms (QLSA). We
demonstrate the performance of the time-marching strategy
with a high-order integrator based on the truncated Dyson
series. The complexity of the algorithm depends linearly on
the amplification ratio, which quantifies the deviation from
a unitary dynamics. We prove that the linear dependence on
the amplification ratio attains the query complexity lower
bound and thus cannot be improved in the worst case. This
algorithm also surpasses existing QLSA based solvers in
three aspects: (1) A(t) does not need to be diagonalizable.
(2) A(t) can be non-smooth, and is only of bounded
variation. (3) It can use fewer queries to the initial state
|ψ0i. Finally, we demonstrate the time-marching strategy
with a first-order truncated Magnus series, which simplifies
the implementation compared to high-order truncated Dyson
series approach, while retaining the aforementioned
benefits. Our analysis also raises some open questions
concerning the differences between time-marching and QLSA
based methods for solving differential equations.},
Doi = {10.22331/Q-2023-03-20-955},
Key = {fds372374}
}
@article{fds372442,
Author = {Bezemek, ZW and Spiliopoulos, K},
Title = {Moderate deviations for fully coupled multiscale weakly
interacting particle systems},
Journal = {Stochastics and Partial Differential Equations: Analysis and
Computations},
Publisher = {Springer Science and Business Media LLC},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.1007/s40072-023-00301-0},
Abstract = {We consider a collection of fully coupled weakly interacting
diffusion processes moving in a two-scale environment. We
study the moderate deviations principle of the empirical
distribution of the particles’ positions in the combined
limit as the number of particles grow to infinity and the
time-scale separation parameter goes to zero simultaneously.
We make use of weak convergence methods, which provide a
convenient representation for the moderate deviations rate
function in a variational form in terms of an effective mean
field control problem. We rigorously obtain equivalent
representation for the moderate deviations rate function in
an appropriate “negative Sobolev” form, proving their
equivalence, which is reminiscent of the large deviations
rate function form for the empirical measure of weakly
interacting diffusions obtained in the 1987 seminal paper by
Dawson–Gärtner. In the course of the proof we obtain
related ergodic theorems and we consider the regularity of
Poisson type of equations associated to McKean–Vlasov
problems, both of which are topics of independent interest.
A novel “doubled corrector problem” is introduced in
order to control derivatives in the measure arguments of the
solutions to the related Poisson equations used to control
behavior of fluctuation terms.},
Doi = {10.1007/s40072-023-00301-0},
Key = {fds372442}
}
@article{fds372444,
Author = {Bezemek, ZW and Spiliopoulos, K},
Title = {Large deviations for interacting multiscale particle
systems},
Journal = {Stochastic Processes and their Applications},
Volume = {155},
Pages = {27-108},
Publisher = {Elsevier BV},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.1016/j.spa.2022.09.010},
Abstract = {We consider a collection of weakly interacting diffusion
processes moving in a two-scale locally periodic
environment. We study the large deviations principle of the
empirical distribution of the particles’ positions in the
combined limit as the number of particles grow to infinity
and the time-scale separation parameter goes to zero. We
make use of weak convergence methods providing a convenient
representation for the large deviations rate function, which
allow us to characterize the effective controlled mean field
dynamics. In addition, we rigorously obtain equivalent
non-variational representations for the large deviations
rate function as introduced by Dawson–Gärtner.},
Doi = {10.1016/j.spa.2022.09.010},
Key = {fds372444}
}
@article{fds374606,
Author = {Lang, Q and Lu, F},
Title = {IDENTIFIABILITY OF INTERACTION KERNELS IN MEAN-FIELD
EQUATIONS OF INTERACTING PARTICLES},
Journal = {Foundations of Data Science},
Volume = {5},
Pages = {480-502},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.3934/fods.2023007},
Abstract = {This study examines the identifiability of interaction
kernels in mean-field equations of interacting particles or
agents, an area of growing interest across various
scientific and engineering fields. The main focus is
identifying data-dependent function spaces where a quadratic
loss functional possesses a unique minimizer. We consider
two data-adaptive L2 spaces: one weighted by a data-adaptive
measure and the other using the Lebesgue measure. In each L2
space, we show that the function space of identifiability is
the closure of the RKHS associated with the integral
operator of inversion. Alongside prior research, our study
completes a full characterization of identifiability in
interacting particle systems with either finite or infinite
particles, highlighting critical differences between these
two settings. Moreover, the identifiability analysis has
important implications for computational practice. It shows
that the inverse problem is ill-posed, necessitating
regularization. Our numerical demonstrations show that the
weighted L2 space is preferable over the unweighted L2
space, as it yields more accurate regularized
estimators.},
Doi = {10.3934/fods.2023007},
Key = {fds374606}
}
@article{fds372526,
Author = {Conlon, D and Fox, J and Sudakov, B and Wei, F},
Title = {Threshold Ramsey multiplicity for paths and even
cycles},
Journal = {European Journal of Combinatorics},
Volume = {107},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.1016/j.ejc.2022.103612},
Abstract = {The Ramsey number r(H) of a graph H is the minimum integer n
such that any two-coloring of the edges of the complete
graph Kn contains a monochromatic copy of H. While this
definition only asks for a single monochromatic copy of H,
it is often the case that every two-edge-coloring of the
complete graph on r(H) vertices contains many monochromatic
copies of H. The minimum number of such copies over all
two-colorings of Kr(H) will be referred to as the threshold
Ramsey multiplicity of H. Addressing a problem of Harary and
Prins, who were the first to systematically study this
quantity, we show that there is a positive constant c such
that the threshold Ramsey multiplicity of a path or an even
cycle on k vertices is at least (ck)k. This bound is tight
up to the constant c. We prove a similar result for odd
cycles in a companion paper.},
Doi = {10.1016/j.ejc.2022.103612},
Key = {fds372526}
}
@article{fds374607,
Author = {Przybyłlo, J and Wei, F},
Title = {Short Proof of the Asymptotic Confirmation of the
Faudree-Lehel Conjecture},
Journal = {Electronic Journal of Combinatorics},
Volume = {30},
Number = {4},
Year = {2023},
Month = {January},
url = {http://dx.doi.org/10.37236/11413},
Abstract = {Given a simple graph G, the irregularity strength of G,
denoted s(G), is the least positive integer k such that
there is a weight assignment on edges (Formula present) for
which each vertex weight (Formula present) is unique amongst
all (Formula present). In 1987, Faudree and Lehel
conjectured that there is a constant c such that (Formula
present) for all d-regular graphs G on n vertices with d >
1, whereas it is trivial that (Formula present) In this
short note we prove that the Faudree-Lehel Conjecture holds
(Formula present) for any fixed ɛ > 0, with a small
additive constant c = 28 for n large enough. Furthermore, we
confirm the conjecture asymptotically by proving that for
any fixed (Formula present) there is a constant C such that
for all d-regular graphs (Formula present) extending and
improving a recent result of Przybyłlo that (Formula
present) and n is large enough.},
Doi = {10.37236/11413},
Key = {fds374607}
}
@article{fds374583,
Author = {B. Li and J. Lu},
Title = {Quantum variational embedding for ground-state energy
problems: sum of squares and cluster selection},
Year = {2023},
url = {http://arxiv.org/abs/2305.18571},
Key = {fds374583}
}
@article{fds370635,
Author = {Young, AL and van den Boom, W and Schroeder, RA and Krishnamoorthy,
V and Raghunathan, K and Wu, H-T and Dunson, DB},
Title = {Mutual information: Measuring nonlinear dependence in
longitudinal epidemiological data.},
Journal = {PLoS One},
Volume = {18},
Number = {4},
Pages = {e0284904},
Year = {2023},
url = {http://dx.doi.org/10.1371/journal.pone.0284904},
Abstract = {Given a large clinical database of longitudinal patient
information including many covariates, it is computationally
prohibitive to consider all types of interdependence between
patient variables of interest. This challenge motivates the
use of mutual information (MI), a statistical summary of
data interdependence with appealing properties that make it
a suitable alternative or addition to correlation for
identifying relationships in data. MI: (i) captures all
types of dependence, both linear and nonlinear, (ii) is zero
only when random variables are independent, (iii) serves as
a measure of relationship strength (similar to but more
general than R2), and (iv) is interpreted the same way for
numerical and categorical data. Unfortunately, MI typically
receives little to no attention in introductory statistics
courses and is more difficult than correlation to estimate
from data. In this article, we motivate the use of MI in the
analyses of epidemiologic data, while providing a general
introduction to estimation and interpretation. We illustrate
its utility through a retrospective study relating
intraoperative heart rate (HR) and mean arterial pressure
(MAP). We: (i) show postoperative mortality is associated
with decreased MI between HR and MAP and (ii) improve
existing postoperative mortality risk assessment by
including MI and additional hemodynamic statistics.},
Doi = {10.1371/journal.pone.0284904},
Key = {fds370635}
}
@article{fds374861,
Author = {Gao, Y and Liu, J-G and Li, W},
Title = {Master equations for finite state mean field games with
nonlinear activations},
Journal = {Discrete and Continuous Dynamical Systems -
B},
Publisher = {American Institute of Mathematical Sciences
(AIMS)},
Year = {2023},
url = {http://dx.doi.org/10.3934/dcdsb.2023204},
Doi = {10.3934/dcdsb.2023204},
Key = {fds374861}
}
@article{fds373606,
Author = {Gao, Y and Liu, J-G},
Title = {Stochastic Chemical Reaction Systems in Biology},
Journal = {SIAM REVIEW},
Volume = {65},
Number = {2},
Pages = {593-+},
Year = {2023},
Key = {fds373606}
}
@article{fds360099,
Author = {Miller, E},
Title = {Stratifications of real vector spaces from constructible
sheaves with conical microsupport},
Journal = {Journal of Applied and Computational Topology},
Volume = {7},
Number = {3},
Pages = {473-489},
Publisher = {Springer},
Year = {2023},
url = {http://dx.doi.org/10.1007/s41468-023-00112-1},
Doi = {10.1007/s41468-023-00112-1},
Key = {fds360099}
}
@article{fds374550,
Author = {Miller, E and Geist, N},
Title = {Global dimension of real-exponent polynomial
rings},
Journal = {Algebra and Number Theory},
Volume = {17},
Number = {10},
Pages = {1779-1788},
Publisher = {Mathematical Sciences Publishers (MSP)},
Year = {2023},
url = {http://dx.doi.org/10.2140/ant.2023.17.1779},
Doi = {10.2140/ant.2023.17.1779},
Key = {fds374550}
}
@article{fds370133,
Author = {Etzioni, R and Gulati, R and Owens, L and Lange, J and Ryser,
MD},
Title = {Opportunity for interception as a driver of benefit in
cancer early detection: implications for multi-cancer early
detection testing.},
Journal = {CANCER PREVENTION RESEARCH},
Volume = {16},
Number = {1},
Pages = {6-6},
Year = {2023},
Key = {fds370133}
}
@article{fds373669,
Author = {Lynch, T and Basila, D and Schnitt, SJ and Marks, JR and Strand, SH and Hyslop, T and Badve, SS and Watson, MA and Le-Petross, HT and Grimm, L and West, RB and Weiss, A and Rapperport, A and King, L and Factor, RE and Ryser, MD and Partridge, AH and Hwang, E-SS and Thompson, AM and Collyar, DE},
Title = {From the lab to the clinic: Lessons learned from a
translational working group.},
Journal = {JOURNAL OF CLINICAL ONCOLOGY},
Volume = {41},
Number = {16},
Year = {2023},
Key = {fds373669}
}
@article{fds359483,
Author = {Babu, PRK and Di Martino and JM and Chang, Z and Perochon, S and Carpenter,
KLH and Compton, S and Espinosa, S and Dawson, G and Sapiro,
G},
Title = {Exploring Complexity of Facial Dynamics in Autism Spectrum
Disorder.},
Journal = {IEEE Trans Affect Comput},
Volume = {14},
Number = {2},
Pages = {919-930},
Year = {2023},
url = {http://dx.doi.org/10.1109/taffc.2021.3113876},
Abstract = {Atypical facial expression is one of the early symptoms of
autism spectrum disorder (ASD) characterized by reduced
regularity and lack of coordination of facial movements.
Automatic quantification of these behaviors can offer novel
biomarkers for screening, diagnosis, and treatment
monitoring of ASD. In this work, 40 toddlers with ASD and
396 typically developing toddlers were shown
developmentally-appropriate and engaging movies presented on
a smart tablet during a well-child pediatric visit. The
movies consisted of social and non-social dynamic scenes
designed to evoke certain behavioral and affective
responses. The front-facing camera of the tablet was used to
capture the toddlers' face. Facial landmarks' dynamics were
then automatically computed using computer vision
algorithms. Subsequently, the complexity of the landmarks'
dynamics was estimated for the eyebrows and mouth regions
using multiscale entropy. Compared to typically developing
toddlers, toddlers with ASD showed higher complexity (i.e.,
less predictability) in these landmarks' dynamics. This
complexity in facial dynamics contained novel information
not captured by traditional facial affect analyses. These
results suggest that computer vision analysis of facial
landmark movements is a promising approach for detecting and
quantifying early behavioral symptoms associated with
ASD.},
Doi = {10.1109/taffc.2021.3113876},
Key = {fds359483}
}
@article{fds368049,
Author = {Garrett, BL and Rudin, C},
Title = {The Right to a Glass Box: Rethinking the Use of Artificial
Intelligence in Criminal Justice},
Journal = {Cornell Law Review},
Year = {2023},
Key = {fds368049}
}
@article{fds370611,
Author = {Young, AL and van den Boom, W and Schroeder, RA and Krishnamoorthy,
V and Raghunathan, K and Wu, H-T and Dunson, DB},
Title = {Mutual information: Measuring nonlinear dependence in
longitudinal epidemiological data.},
Journal = {PLoS One},
Volume = {18},
Number = {4},
Pages = {e0284904},
Year = {2023},
url = {http://dx.doi.org/10.1371/journal.pone.0284904},
Abstract = {Given a large clinical database of longitudinal patient
information including many covariates, it is computationally
prohibitive to consider all types of interdependence between
patient variables of interest. This challenge motivates the
use of mutual information (MI), a statistical summary of
data interdependence with appealing properties that make it
a suitable alternative or addition to correlation for
identifying relationships in data. MI: (i) captures all
types of dependence, both linear and nonlinear, (ii) is zero
only when random variables are independent, (iii) serves as
a measure of relationship strength (similar to but more
general than R2), and (iv) is interpreted the same way for
numerical and categorical data. Unfortunately, MI typically
receives little to no attention in introductory statistics
courses and is more difficult than correlation to estimate
from data. In this article, we motivate the use of MI in the
analyses of epidemiologic data, while providing a general
introduction to estimation and interpretation. We illustrate
its utility through a retrospective study relating
intraoperative heart rate (HR) and mean arterial pressure
(MAP). We: (i) show postoperative mortality is associated
with decreased MI between HR and MAP and (ii) improve
existing postoperative mortality risk assessment by
including MI and additional hemodynamic statistics.},
Doi = {10.1371/journal.pone.0284904},
Key = {fds370611}
}
@article{fds374521,
Author = {Zhao, H and Zhong, Y},
Title = {How much can one learn from a single solution of a
PDE?},
Journal = {Pure and Applied Functional Analysis},
Volume = {8},
Number = {2},
Pages = {751-773},
Year = {2023},
Key = {fds374521}
}
@article{fds372521,
Author = {Hou, L and Ji, Z and Wang, J and Xie, J},
Title = {Editorial: Statistical and computational methods for
single-cell sequencing analysis.},
Journal = {Front Genet},
Volume = {14},
Pages = {1235174},
Year = {2023},
url = {http://dx.doi.org/10.3389/fgene.2023.1235174},
Doi = {10.3389/fgene.2023.1235174},
Key = {fds372521}
}
@article{fds376402,
Author = {Li, X and Sung, AD and Xie, J},
Title = {DART: Distance Assisted Recursive Testing},
Journal = {JOURNAL OF MACHINE LEARNING RESEARCH},
Volume = {24},
Year = {2023},
Key = {fds376402}
}
@inproceedings{MM:EEG,
Author = {E Causevic and R~R Coifman and R Isenhart and A Jacquin and E~R John and M Maggioni and L~S Prichep and F~J
Warner},
Title = {{QEEG}-based classification with wavelet packets and
microstate features for triage applications in the
{ER}},
Year = {2005},
Key = {MM:EEG}
}
@inproceedings{csb05-poly,
Author = {L. Wang and R. Mettu and B. R. Donald},
Title = {An Algebraic Geometry Approach to Protein Backbone Structure
Determination from {NMR} Data},
Pages = {235--246},
Booktitle = {Proceedings of the {IEEE} Computational Systems
Bioinformatics Conference ({CSB})},
Address = {Stanford, CA},
Year = {2005},
Key = {csb05-poly}
}
@inproceedings{isrr-05,
Author = {B. R. Donald and C. Levey and C. McGray and I. Paprotny and D. Rus},
Title = {A Steerable, Untethered, 250 $\times$ 60 $\mu$m {MEMS}
Mobile Micro-Robot},
Booktitle = {Proceedings of the 12th {\it International Symposium of
Robotics Research (ISRR)}},
Address = {San Francisco, CA.},
Year = {2005},
Key = {isrr-05}
}
@booklet{Greer04a,
Author = {J. B. Greer and A. L. Bertozzi},
Title = {H-1 solutions of a class of fourth order nonlinear equations
for image processing},
Journal = {Discrete And Continuous Dynamical Systems},
Volume = {10},
Number = {1-2},
Pages = {349 -- 366},
Year = {2004},
Key = {Greer04a}
}
@misc{PathNIH2004,
Author = {GL Davis and Mauro Maggioni and FJ Warner and FB Geshwind and AC Coppi and RA DeVerse and RR Coifman},
Title = {Hyper-spectral Analysis of normal and malignant colon tissue
microarray sections using a novel DMD system},
Year = {2004},
Key = {PathNIH2004}
}
@techreport{CMTech,
Author = {Ronald R Coifman and Mauro Maggioni},
Title = {Multiresolution Analysis associated to diffusion semigroups:
construction and fast algorithms},
Number = {YALE/DCS/TR-1289},
Organization = {Dept. Comp. Sci., Yale University},
Institution = {Dept. Comp. Sci., Yale University},
Year = {2004},
Key = {CMTech}
}
@misc{gordon04-poster-langmead,
Author = {C. Langmead and B. R. Donald},
Title = {A Framework for Automated {NMR} Resonance Assignments and
3{D} Structural Homology Detection},
Address = {Ventura, CA},
Year = {2004},
Key = {gordon04-poster-langmead}
}
@misc{gordon04-poster-wang,
Author = {L. Wang and R. Mettu and R. Lilien and A. Yan and B. R.
Donald},
Title = {Exact Solutions for Internuclear Vectors and Dihedral Angles
from Two {RDC}s and Their Application in a Systematic Search
Algorithm for Determining Protein Backbone
Structure},
Address = {Ventura, CA},
Year = {2004},
Key = {gordon04-poster-wang}
}
@techreport{Dartmouth:TR2004-492,
Author = {Ryan H. Lilien and Mohini Sridharan and Bruce R.
Donald},
Title = {{Identification of Novel Small Molecule Inhibitors of
Core-Binding Factor Dimerization by Computational Screening
against NMR Molecular Ensembles}},
Number = {TR2004-492},
Organization = {Dartmouth College, Computer Science},
Institution = {Dartmouth College, Computer Science},
Address = {Hanover, NH},
Year = {2004},
url = {ftp://ftp.cs.dartmouth.edu/TR/TR2004-492.pdf},
Key = {Dartmouth:TR2004-492}
}
@inproceedings{wafr04,
Author = {B. R. Donald},
Title = {Plenary lecture: {Algorithmic} Challenges in Structural
Molecular Biology and Proteomics},
Pages = {1--10},
Booktitle = {Proceedings of the Sixth International Workshop on the
Algorithmic Foundations of Robotics (WAFR)},
Publisher = {University of Utrecht},
Address = {Utrecht/Zeist, The Netherlands},
Year = {2004},
Key = {wafr04}
}
@inproceedings{recomb-04langmead-poster,
Author = {C. Langmead and B. R. Donald},
Title = {High-Throughput 3{D} homology Detection via {NMR} Resonance
Assignment},
Series = {Eighth Annual International Conference on Research in
Computational Molecular Biology ({RECOMB})},
Pages = {522},
Booktitle = {Currents in Computational Molecular Biology,
2004},
Address = {San Diego},
Editor = {A. Gramada and P. Bourne},
Year = {2004},
Key = {recomb-04langmead-poster}
}
@inproceedings{recomb-04a,
Author = {A. Yan and C. Langmead and B. R. Donald},
Title = {A Probability-Based Similarity Measure for Saupe Alignment
Tensors with Applications to Residual Dipolar Couplings in
{NMR} Structural Biology},
Series = {Eighth Annual International Conference on Research in
Computational Molecular Biology ({RECOMB})},
Pages = {437--438},
Booktitle = {Currents in Computational Molecular Biology,
2004},
Address = {San Diego},
Editor = {A. Gramada and P. Bourne},
Year = {2004},
Key = {recomb-04a}
}
@inproceedings{WangDonald-csb04,
Author = {L. Wang and B. R. Donald},
Title = {Analysis of a Systematic Search-Based Algorithm for
Determining Protein Backbone Structure from a Minimal Number
of Residual Dipolar Couplings},
Pages = {319--330},
Booktitle = {Proceedings of the {IEEE} Computational Systems
Bioinformatics Conference ({CSB})},
Address = {Stanford, CA},
Year = {2004},
Key = {WangDonald-csb04}
}
@misc{acs03-poster-anderson,
Author = {A. Anderson and R. Lilien and V. Popov and B. R.
Donald},
Title = {Ensembles of Active Site Conformations Allow Structure-Based
Redesign and Drug Design},
Address = {New Orleans},
Year = {2003},
Key = {acs03-poster-anderson}
}
@techreport{Dartmouth:TR2004-494,
Author = {Christopher J. Langmead and Bruce R. Donald},
Title = {{An Improved Nuclear Vector Replacement Algorithm for
Nuclear Magnetic Resonance Assignment}},
Number = {TR2004-494},
Organization = {Dartmouth College, Computer Science},
Institution = {Dartmouth College, Computer Science},
Address = {Hanover, NH},
Year = {2003},
url = {ftp://ftp.cs.dartmouth.edu/TR/TR2004-494.pdf},
Key = {Dartmouth:TR2004-494}
}
@inproceedings{isrr-03,
Author = {B. R. Donald and C. Levey and C. McGray and D. Rus and M.
Sinclair},
Title = {Untethered Micro-Actuators for Autonomous Micro-robot
Locomotion: Design, Fabrication, Control, and
Performance},
Booktitle = {Proceedings of the 11th {\it International Symposium of
Robotics Research}},
Address = {Siena, Italy},
Year = {2003},
Key = {isrr-03}
}
@inproceedings{recomb02-poster,
Author = {R. Lilien and A. Anderson and B. Donald},
Title = {Modeling Protein Flexibility for Structure-Based Active Site
Redesign},
Series = {The Sixth Annual International Conference on Research in
Computational Molecular Biology (RECOMB)},
Pages = {122-123},
Booktitle = {Currents in Computational Molecular Biology},
Address = {Washington DC},
Editor = {L. Florea and others},
Year = {2002},
Key = {recomb02-poster}
}
@misc{ismb00-poster-langmead,
Author = {C. J. Langmead and B. R. Donald},
Title = {Time-frequency Analysis of Protein {NMR}
Data},
Year = {2000},
Key = {ismb00-poster-langmead}
}
@misc{ismb00-poster-cbk,
Author = {C. Bailey-Kellogg and A. Widge and J. J. {Kelley III} and M.
J. Berardi and J. H. Bushweller and B. R.
Donald},
Title = {The {NOESY} {Jigsaw}: Automated Protein Secondary Structure
and Main-Chain Assignment from Sparse, Unassigned {NMR}
Data},
Year = {2000},
Key = {ismb00-poster-cbk}
}
@misc{ismb00-poster-lilien,
Author = {R. Lilien and M. Sridharan and X. Huang and J. H. Bushweller and B. R. Donald},
Title = {Computational Screening Studies for Core Binding Factor
Beta: Use of Multiple Conformations to Model Receptor
Flexibility},
Year = {2000},
Key = {ismb00-poster-lilien}
}
@inproceedings{recomb00,
Author = {C. Bailey-Kellogg and A. Widge and J. J. {Kelley III} and M.
J. Berardi and J. H. Bushweller and B. R.
Donald},
Title = {The {NOESY} {Jigsaw}: Automated Protein Secondary Structure
and Main-Chain Assignment from Sparse, Unassigned {NMR}
Data},
Pages = {33--44},
Booktitle = {The Fourth Annual International Conference on Research in
Computational Molecular Biology ({RECOMB-2000})},
Year = {2000},
Key = {recomb00}
}
@inproceedings{BaileyKelloggZhaoDonald00,
Author = {C. Bailey-Kellogg and F. Zhao and B. R. Donald},
Title = {Spatial Aggregation in Scientific Data Mining},
Booktitle = {Proceedings of the First {SIAM} Conference on Computational
Science and Engineering},
Address = {Washington, DC},
Year = {2000},
Key = {BaileyKelloggZhaoDonald00}
}
@article{BohringerDonaldMacDonald97A,
Author = {K.-F.~B{\"o}hringer and B.~R.~Donald and N.~C.~MacDonald},
Title = {{\em Programmable Vector Fields for Distributed
Manipulation, with Applications to MEMS Actuator Arrays and
Vibratory Parts Feeders}},
Journal = {International Journal of Robotics Research},
Volume = {18},
Number = {2},
Year = {1999},
Key = {BohringerDonaldMacDonald97A}
}
@inproceedings{icra99b,
Author = {K.-F.~B{\"o}hringer and B.~R.~Donald and F.~Lamiraux and L.~Kavraki},
Title = {Part Orientation with One or Two Stable Equilibria Using
Programmable Force Fields},
Booktitle = {IEEE International Conference on Robotics and Automation,
Workshop on Distributed Manipulation},
Year = {1999},
Key = {icra99b}
}
@inproceedings{BohringerLamirauxKavrakiDonald99,
Author = {K.-F. B{\"o}hringer and B. R. Donald and F. Lamiraux and L.
Kavraki},
Title = {Part Orientation with One or Two Stable Equilibria Using
Programmable Vector Fields},
Booktitle = {{IEEE} International Conference on Robotics and Automation,
Workshop on Distributed Manipulation},
Address = {Detroit},
Year = {1999},
Key = {BohringerLamirauxKavrakiDonald99}
}
@inproceedings{isrr99,
Author = {K.-F.~B{\"o}hringer and B.~R.~Donald and F.~Lamiraux and L.~Kavraki},
Title = {A Single Universal Force Field Can Uniquely Pose Any Part Up
To Symmetry},
Booktitle = {9th International Symposium of Robotics Research
(ISRR)},
Year = {1999},
Key = {isrr99}
}
@inproceedings{GariepyRusDonald99B,
Author = {B. R. Donald and L. Gariepy and D. Rus},
Title = {Experiments in Constrained Prehensile Manipulation:
Distributed Manipulation with Ropes},
Booktitle = {{IEEE} International Conference on Robotics and Automation,
Workshop on Distributed Manipulation},
Address = {Detroit},
Year = {1999},
Key = {GariepyRusDonald99B}
}
@inproceedings{icra99a,
Author = {J.~Suh and B.~Darling and K.-F.~B{\"o}hringer and B.~R.~Donald and H.~Baltes and G.~Kovacs},
Title = {{CMOS} Integrated Organic Ciliary Actuator Array as a
General-Purpose Micromanipulation Tool},
Booktitle = {IEEE International Conference on Robotics and Automation,
Workshop on Distributed Manipulation},
Year = {1999},
Key = {icra99a}
}
@inproceedings{BohringerDonald98,
Author = {K.-F. B{\"o}hringer and B. R. Donald},
Title = {Algorithmic {MEMS}},
Booktitle = {Proceedings of the 3rd International Workshop on the
Algorithmic Foundations of Robotics {WAFR}},
Address = {Houston, TX},
Year = {1998},
Key = {BohringerDonald98}
}
@inproceedings{BriggsDonald96,
Author = {A. Briggs and B. R. Donald},
Title = {Robust Geometric Algorithms for Sensor Planning},
Booktitle = {Proceedings of the International Workshop on the Algorithmic
Foundations of Robotics {WAFR}},
Address = {Toulouse, France},
Year = {1996},
Key = {BriggsDonald96}
}
@misc{JenningsRusDonald-poster-94,
Author = {B. R. Donald and J. Jennings and D. Rus},
Title = {Cooperating Autonomous Mobile Robots: Theory and
Experiments},
Address = {{MIT}, Cambridge, MA},
Year = {1994},
Key = {JenningsRusDonald-poster-94}
}
@article{PaiDonald93,
Author = {B. R. Donald and D. Pai},
Title = {The Motion of Planar Compliantly-Connected Rigid Bodies in
Contact, with Applications to Automatic Fastening},
Journal = {International Journal of Robotics Research},
Volume = {12},
Number = {4},
Pages = {307--338},
Year = {1993},
Key = {PaiDonald93}
}
@inproceedings{BrownChewDonald93,
Author = {R. Brown and P. Chew and B. R. Donald},
Title = {Mobile Robots, Map-making, Shape Metrics, and
Localization},
Booktitle = {Proceedings of the International Association of Science and
Technology for Development ({IASTED}) International
Conference on Robotics and Manufacturing},
Address = {Oxford, England},
Year = {1993},
Key = {BrownChewDonald93}
}
@inproceedings{JenningsRusDonald93B,
Author = {J. Jennings and D. Rus and B. R. Donald},
Title = {Experimental Information Invariants for Cooperating
Autonomous Mobile Robots},
Booktitle = {Proceedings of the International Joint Conference on
Artificial Intelligence ({IJCAI}) Workshop on Dynamically
Interacting Robots},
Address = {Chambery, France},
Year = {1993},
Key = {JenningsRusDonald93B}
}
@inproceedings{JenningsRusDonald93A,
Author = {B. R. Donald and J. Jennings and D. Rus},
Title = {Towards a Theory of Information Invariants for Cooperating
Autonomous Mobile Robots},
Booktitle = {Proceedings of the International Symposium of Robotics
Research {ISRR}},
Address = {Hidden Valley, PA},
Year = {1993},
Key = {JenningsRusDonald93A}
}
@article{ieee-92,
Author = {B. R. Donald},
Title = {Robot Motion Planning},
Journal = {{IEEE} Trans. on Robotics and Automation},
Volume = {8},
Number = {2},
Year = {1992},
Key = {ieee-92}
}
@inproceedings{CannyResslerDonald92,
Author = {J. Canny and B. R. Donald and G. Ressler},
Title = {A Rational Rotation Method for Robust Geometric
Algorithms},
Pages = {251--260},
Booktitle = {Proc. {ACM} Symposium on Computational Geometry},
Address = {Berlin},
Year = {1992},
Key = {CannyResslerDonald92}
}
@inproceedings{JenningsDonald91A,
Author = {J. Jennings and B. R. Donald},
Title = {Programming Autonomous Agents: A theory of Perceptual
Equivalence},
Booktitle = {Proceedings of the 1st {AAAI} Fall Symposium on Sensory
Aspects of Robotic Intelligence},
Address = {Asilomar, CA},
Year = {1991},
Key = {JenningsDonald91A}
}
@inproceedings{XavierDonald89B,
Author = {B. R. Donald and P. Xavier},
Title = {A Provably Good Approximation Algorithm for Optimal-Time
Trajectory Planning},
Pages = {958--964},
Booktitle = {Proc. {IEEE} International Conference on Robotics and
Automation},
Address = {Scottsdale, AZ},
Year = {1989},
Key = {XavierDonald89B}
}
@inproceedings{Donald88,
Author = {B. R. Donald},
Title = {The Complexity of Planar Compliant Motion Planning with
Uncertainty},
Pages = {309--318},
Booktitle = {Proc. 4th {ACM} Symposium on Computational
Geometry},
Address = {Urbana. IL},
Year = {1988},
Key = {Donald88}
}
@inproceedings{Donald86A,
Author = {B. R. Donald},
Title = {A Theory of Error Detection and Recovery: Robot Motion
Planning with Uncertainty in the Geometric Models of the
Robot and Environment},
Booktitle = {Proceedings of the International Workshop on Geometric
Reasoning},
Address = {Oxford University, England},
Year = {1986},
Key = {Donald86A}
}
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