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When data disappear: public health pays as US policy strays

The Lancet Digital Health 2025年 100874页

作者： Thomas McAndrew Andrew A Lover Garrik Hoyt Maimuna S Majumder Department of Biostatistics and Health Data Science College of Health Lehigh University Bethlehem PA USA Department of Biostatistics and Epidemiology School of Public Health and Health Sciences University of Massachusetts Amherst Amherst MA USA Department of Computer Science and Engineering PC Rossin College of Engineering and Applied Sciences Lehigh University Bethlehem PA USA Department of Pediatrics Harvard Medical School Boston MA USA Computational Health Informatics Program Boston Children’s Hospital Boston MA USA

Presidential actions on Jan 20, 2025, by President Donald Trump, including executive orders, have delayed access to or led to the removal of crucial public health data sources in the USA. The continuous collection and maintenance of health data support public health, safety, and security associated with diseases such as seasonal influenza. To show how public health data surveillance enhances public health practice, we analysed data from seven US Government-maintained sources associated with seasonal influenza. We fit two models that forecast the number of national incident influenza hospitalisations in the USA: (1) a data-rich model incorporating data from all seven Government data sources; and (2) a data-poor model built using a single Government hospitalisation data source, representing the minimal required information to produce a forecast of influenza hospitalisations. The data-rich model generated reliable forecasts useful for public health decision making, whereas the predictions using the data-poor model were highly uncertain, rendering them impractical. Thus, health data can serve as a transparent and standardised foundation to improve domestic and global health. Therefore, a plan should be developed to safeguard public health data as a public good.

关键词： Health insurance

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An improved prior for image reconstruction in X-ray fiber diffraction

An improved prior for image reconstruction in X-ray fiber di...

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IEEE International Conference on Image Processing

作者： S. Baskaran R.P. Millane Computational Science and Engineering Program Purdue University West Lafayette IN USA

The structure completion problem in fiber diffraction is addressed from a Bayesian perspective. The experimental data are sums of the squares of the amplitudes of particular sets of Fourier coefficients of the electron density. In addition, a part of the electron density is known. The image reconstruction problem is to estimate the missing part of the electron density. A Bayesian approach is taken in which the prior model for the image is based on the fact that it consists of atoms, i.e. the unknown electron density consists of separated sharp peaks. The conventional prior assumes that the positions of the unknown atoms are uniformly distributed. We improve this prior by treating the positions of the known atoms as containing normally distributed coordinate errors. Currently used heuristic methods are shown to correspond to certain maximum a posteriori estimates of the Fourier coefficients. An analytical solution for the Bayesian minimum mean-square-error estimate is derived. Simulations show that the minimum mean-square-error estimate gives better results when the new prior is used.

关键词： Image reconstruction X-ray imaging Electrons Bayesian methods X-ray diffraction Maximum a posteriori estimation

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The bourque distances for mutation trees of cancers 20

The bourque distances for mutation trees of cancers

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20th International Workshop on Algorithms in Bioinformatics, WABI 2020

作者： Jahn, Katharina Beerenwinkel, Niko Zhang, Louxin Department of Biosystems Science and Engineering ETH Zurich Basel Switzerland SIB Swiss Institute of Bioinformatics Basel Switzerland Department of Mathematics and Computational Biology Program National University of Singapore Singapore

ISBN: (纸本)9783959771610

Mutation trees are rooted trees of arbitrary node degree in which each node is labeled with a mutation set. These trees, also referred to as clonal trees, are used in computational oncology to represent the mutational history of tumours. Classical tree metrics such as the popular RobinsonFoulds distance are of limited use for the comparison of mutation trees. One reason is that mutation trees inferred with different methods or for different patients often contain different sets of mutation labels. Here, we generalize the RobinsonFoulds distance into a set of distance metrics called Bourque distances for comparing mutation trees. A connection between the RobinsonFoulds distance and the nearest neighbor interchange distance is also presented. © Katharina Jahn, Niko Beerenwinkel, and Louxin Zhang;licensed under Creative Commons License CC-BY

关键词： Bourque distance Clonal trees Mutation trees Phylogenetic trees Robinson–Foulds distance Tree distance Tree metric

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Performance analysis of PDE based parallel algorithms on different computer architectures

Performance analysis of PDE based parallel algorithms on dif...

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International Conference on Soft Computing, Computing with Words and Perceptions in System Analysis, Decision and Control, ICSCCW

作者： İ lker Kopan M. Serdar Ç Informatics Institute Computational Science and Engineering Program ITU Istanbul Turkey

Performance of an algorithm mainly depends on both computer architecture and software. An Intel Xeon processor based HPC cluster and Intel Itanium2 based symmetric multiprocessing (SMP) architectures are used for performance analysis of PDE based parallel algorithm. Algorithm is parallelized using MPI and performance measurements are done using Tuning and Analysis Utilities (TAU). computational optimization reveals data independency and helps compiler to generate more efficient program for that specific processor. Removing data dependency inside loop is the key in this work. In iterative algorithms, like Gauss-Seidel method, each processor communicates with the same processors at every iteration. This feature makes persistent connection preferable. MPI has different types of communication methods for different communication characteristics. Persistent connection is one of them. Persistent connection removes connection overhead by leaving connection open for further communications. It can be preferred if data is transferred repeatedly between same nodes. In this work source code changed to help compiler to generate more efficient program for the specific processor. Also MPI persistent connection is used for communication at each iteration in Gauss-Seidel method. In some parallel algorithms, communication must be synchronized. Making communication between processors at the same time becomes a bottleneck if communication medium is shared. This fact has been studies and analyzed.

关键词： Performance analysis Parallel algorithms Computer architecture Clustering algorithms Iterative algorithms program processors Gaussian processes Software algorithms Software performance Measurement

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SYNAPTIC SPINE HEAD MORPHODYNAMICS FROM GRAPH GRAMMAR RULES FOR ACTIN DYNAMICS

arXiv

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arXiv 2025年

作者： Hur, Matthew Bartol, Thomas Rangamani, Padmini Sejnowski, Terrence Mjolsness, Eric Program in Mathematical Computational and Systems Biology Univeristy of California Irvine IrvineCA United States Computational Neurobiology Laboratory Salk Institute for Biological Studies La Jolla CA United States Departments of Pharmacology and Mechanical and Aerospace Engineering University of California San Diego La Jolla CA United States Deparment of Neurobiology University of California San Diego La Jolla CA United States Departments of Computer Science and Mathematics Univeristy of California Irvine IrvineCA United States

There is a morphodynamic component to synaptic learning by which changes in dendritic (postsynaptic) spine head size are associated with the strengthening or weakening of the synaptic connection between two neurons, in response to the temporal correlation of local presynaptic and postsynaptic signals. These morphological factors are in turn sculpted by the dynamics of the actin cytoskeleton. In this paper, we use Dynamical Graph Grammars (DGGs) implemented within a computer algebra system to model how networks of actin filaments can dynamically grow or shrink, reshaping the spine head. Dynamical Graph Grammars (DGGs) provide a well-defined way to accommodate dynamically changing system structure such as active cytoskeleton represented using dynamic graphs, within nonequilibrium statistical physics under the master equation. We show that DGGs can also incorporate biophysical forces between graph-connected objects at a finer time scale, with specialized DGG kinetic rules obeying biophysical constraints of Galilean invariance, conservation of momentum, and dissipation of conserved global energy. We use graph-local energy functions for cytoskeleton networks interacting with membranes, and derive DGG rules from the specialization of dissipative stochastic dynamics - separated into dissipative and thermal noise rule types - to a mutually exclusive and exhaustive collection of graph-local neighborhood types for the rule left hand sides. The dissipative rules comprise a stochastic version of gradient descent dynamics. The thermal noise rules use a Gaussian approximation of each position coordinate to sample jitter-like displacements. For the spine head model we designed and implemented DGG grammar mathematical sub-models including actin network growth, non-equilibrium statistical mechanics, and filament-membrane mechanical interaction to regulate the re-writing of graph objects. We simulate emergent biophysics of simplified networks of actin polymers and their interactions

关键词： Stochastic models

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Convolutional neural networks with low-rank regularization 4

Convolutional neural networks with low-rank regularization

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4th International Conference on Learning Representations, ICLR 2016

作者： Tai, Cheng Xiao, Tong Zhang, Yi Wang, Xiaogang Weinan, E. Program in Applied and Computational Mathematics Princeton University United States Department of Electronic Engineering Chinese University of Hong Kong Hong Kong Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor United States

Large CNNs have delivered impressive performance in various computer vision applications. But the storage and computation requirements make it problematic for deploying these models on mobile devices. Recently, tensor decompositions have been used for speeding up CNNs. In this paper, we further develop the tensor decomposition technique. We propose a new algorithm for computing the low-rank tensor decomposition for removing the redundancy in the convolution kernels. The algorithm finds the exact global optimizer of the decomposition and is more effective than iterative methods. Based on the decomposition, we further propose a new method for training low-rank constrained CNNs from scratch. Interestingly, while achieving a significant speedup, sometimes the low-rank constrained CNNs delivers significantly better performance than their non-constrained counterparts. On the CIFAR-10 dataset, the proposed low-rank NIN model achieves 91.31% accuracy (without data augmentation), which also improves upon state-of-the-art result. We evaluated the proposed method on CIFAR-10 and ILSVRC12 datasets for a variety of modern CNNs, including AlexNet, NIN, VGG and GoogleNet with success. For example, the forward time of VGG-16 is reduced by half while the performance is still comparable. Empirical success suggests that low-rank tensor decompositions can be a very useful tool for speeding up large CNNs. © ICLR 2016: San Juan, Puerto Rico. All Rights Reserved.

关键词： Iterative methods

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Upwind and High-Resolution Schemes 1

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1000年

作者： M. Yousuff Hussaini Bram Leer John Rosendale

ISBN: (数字)9783642605437

ISBN: (纸本)9783642644528

One of the major achievements in computational fluid dynamics has been the development of numerical methods for simulating compressible flows, combining higher-order accuracy in smooth regions with a sharp, oscillation-free representation of embedded shocks methods and now known as "high-resolution schemes". Together with introductions from the editors written from the modern vantage point this volume collects in one place many of the most significant papers in the development of high-resolution schemes as occured at ICASE.

关键词： Mathematical Methods in Physics Numerical and computational Physics, Simulation Thermodynamics

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4D Monte Carlo dose calculations for particle therapy combined with the spring network model of lung motion

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World Congress on Medical Physics and Biomedical engineering: Radiation Oncology

作者： Ishikawa, K.L. Takagi, S. Matthys, K. Wada, S. Integrated Simulation of Living Matter Group RIKEN Computational Science Research Program 2-1 Hirosawa Wako Saitama Japan School of Engineering and Design Brunel University Uxbridge Middlesex United Kingdom School of Engineering Science Osaka University Toyonaka Osaka Japan

ISBN: (纸本)9783642034725

To enable the evaluation of the impact of respiratory motion on charged particle therapy and to realize 4D treatment planning while keeping CT exposure as low as possible, we are developing a Monte Carlo dose calculation system combined with a computational biomechanical model of lung motion. The human lung is CT scanned for a single phase of a respiratory motion. The CT images are transformed into tetrahedral elements by automated segmentation. Then, the respiratory motion is simulated using a computational biomechanical model called the spring network model, and the calculated 3D shape of the lung for a given phase is transformed to a voxel data set. For each phase, assuming carbon-ion beam irradiation, biological dose distribution is calculated using the Monte Carlo particle and heavy ion transport code PHITS coupled with a microdosimetric kinetic model. The dose is mapped onto the reference data set to obtain the accumulated dose. The first version of the 4D dose calculation system we have developed so far can realistically reproduce the lung motion, successfully read the data set for each phase and calculate the accumulated dose. The number of the phases to be sampled and their weights can be set arbitrarily, without need of additional CT scanning. Our first simulations for a 70 MeV/u carbon ion beam with a diameter of 2 cm indicate that the dose distribution can significantly change with phase and that many data sets may be needed to accurately evaluate the dose to the surrounding normal tissue. The impact of the system we developed is two-fold: in the short term, it can be used to investigate different issues of 4D treatment planning;our goal is an entirely simulation-based 4D planning from a single CT scanning. The system is being developed further. © 2009 Springer-Verlag.

关键词： Monte Carlo methods

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Why Gabor frames? Two fundamental measures of coherence and their role in model selection

Why Gabor frames? Two fundamental measures of coherence and ...

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作者： Bajwa, Waheed U. Calderbank, Robert Jafarpour, Sina Department of Electrical Engineering Program in Applied and Computational Mathematics Princeton University Princeton NJ 08544 United States Department of Computer Science Princeton University Princeton NJ 08544 United States

The problem of model selection arises in a number of contexts, such as subset selection in linear regression, estimation of structures in graphical models, and signal denoising. This paper studies non-asymptotic model selection for the general case of arbitrary (random or deterministic) design matrices and arbitrary nonzero entries of the signal. In this regard, it generalizes the notion of incoherence in the existing literature on model selection and introduces two fundamental measures of coherence- termed as the worst-case coherence and the average coherence-among the columns of a design matrix. It utilizes these two measures of coherence to provide an in-depth analysis of a simple, model-order agnostic one-step thresholding (OST) algorithm for model selection and proves that OST is feasible for exact as well as partial model selection as long as the design matrix obeys an easily verifiable property, which is termed as the coherence property. One of the key insights offered by the ensuing analysis in this regard is that OST can successfully carry out model selection even when methods based on convex optimization such as the lasso fail due to the rank deficiency of the submatrices of the design matrix. In addition, the paper establishes that if the design matrix has reasonably small worst-case and average coherence then OST performs near-optimally when either (i) the energy of any nonzero entry of the signal is close to the average signal energy per nonzero entry or (ii) the signal-to-noise ratio in the measurement system is not too high. Finally, two other key contributions of the paper are that (i) it provides bounds on the average coherence of Gaussian matrices and Gabor frames, and (ii) it extends the results on model selection using OST to low-complexity, model-order agnostic recovery of sparse signals with arbitrary nonzero entries. In particular, this part of the analysis in the paper implies that an Alltop Gabor frame together with OST can successfully carr

关键词： Recovery

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Numerical study on supersonic inlet buzz under various throttling conditions and fluid-structure interaction

Numerical study on supersonic inlet buzz under various throt...

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29th AIAA Applied Aerodynamics Conference 2011

作者： Hong, Wooram Kim, Chongam Interdisciplinary Program in Computational Science and Technology Seoul National University Seoul Korea Republic of Department of Aerospace Engineering Institute of Advanced Aerospace Technology Seoul National University Seoul Korea Republic of

ISBN: (纸本)9781624101458

This paper presents numerical investigations on the buzz characteristics of a supersonic inlet. By applying dynamic throttling conditions and using FSI (Fluid-Structure Interaction) technique, we were able to match operating conditions close to the real cases. In order to evaluate the effects of the dynamic throttling conditions and FSI, numerical simulations of a supersonic inlet configuration were performed sequentially for the following three stages. At first, the physical phenomena related to the inlet buzz such as shock-shock and shock-boundary interactions were studied under static throttling condition. In the second stage, the effect of the dynamic throttling ratio on the inlet buzz was examined. A dynamic throttling condition is assumed that the inlet is initially in high frequency buzz condition, from which throttling plug at the exit nozzle starts to move. Finally, the structural deformation effect was figured out using FSI for the same throttling conditions. The results of these studies reveal the detailed effects of the throttling ratio and the structural deformation on the buzz characteristics. © 2011 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

关键词： Fluid structure interaction

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