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arXiv 2024年

作者： Wang, Sifan Seidman, Jacob H. Sankaran, Shyam Wang, Hanwen Pappas, George J. Perdikaris, Paris Institution for Foundation of Data Science Yale University United States Graduate Program in Applied Mathematics and Computational Science University of Pennsylvania United States Department of Mechanical Engineering and Applied Mechanics University of Pennsylvania United States Department of Electrical and Systems Engineering University of Pennsylvania United States

Operator learning, which aims to approximate maps between infinite-dimensional function spaces, is an important area in scientific machine learning with applications across various physical domains. Here we introduce the Continuous Vision Transformer (CViT), a novel neural operator architecture that leverages advances in computer vision to address challenges in learning complex physical systems. CViT combines a vision transformer encoder, a novel grid-based coordinate embedding, and a query-wise cross-attention mechanism to effectively capture multi-scale dependencies. This design allows for flexible output representations and consistent evaluation at arbitrary resolutions. We demonstrate CViT’s effectiveness across a diverse range of partial differential equation (PDE) systems, including fluid dynamics, climate modeling, and reaction-diffusion processes. Our comprehensive experiments show that CViT achieves state-of-the-art performance on multiple benchmarks, often surpassing larger foundation models, even without extensive pretraining and roll-out fine-tuning. Taken together, CViT exhibits robust handling of discontinuous solutions, multi-scale features, and intricate spatio-temporal dynamics. Our contributions can be viewed as a significant step towards adapting advanced computer vision architectures for building more flexible and accurate machine learning models in the physical sciences. All data and code are publicly available at https://***/PredictiveIntelligenceLab/cvit. © 2024, CC BY-NC-SA.

关键词： Computer vision

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Advancing the Use of Longitudinal Electronic Health Records: Tutorial for Uncovering Real-World Evidence in Chronic Disease Outcomes

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Journal of Medical Internet Research 2025年第1期27卷 e71873页

作者： Huang, Feiqing Hou, Jue Zhou, Ningxuan Greco, Kimberly Lin, Chenyu Sweet, Sara Morini Wen, Jun Shen, Lechen Gonzalez, Nicolas Zhang, Sinian Liao, Katherine P. Cai, Tianrun Xia, Zongqi Bourgeois, Florence T. Cai, Tianxi Department of Biostatistics Harvard T.H. Chan School of Public Health Boston MA United States Harvard-MIT Center for Regulatory Science Harvard Medical School Boston MA United States Division of Biostatistics and Health Data Science School of Public Health University of Minnesota Minneapolis MN United States Department of Biomedical Informatics Harvard Medical School Boston MA United States Department of Engineering University of Toronto Toronto ON Canada Division of Rheumatology Inflammation and Immunity Brigham and Women's Hospital Boston MA United States Department of Neurology University of Pittsburgh Pittsburgh PA United States Computational Health Informatics Program (CHIP) Boston Children's Hospital Boston MA United States Department of Pediatrics Harvard Medical School Boston MA United States

Managing chronic diseases requires ongoing monitoring of disease activity and therapeutic responses to optimize treatment plans. With the growing availability of disease-modifying therapies, it is crucial to investigate comparative effectiveness and long-term outcomes beyond those available from randomized clinical trials. We introduce a comprehensive pipeline for generating reproducible and generalizable real-world evidence on disease outcomes by leveraging electronic health record data. The pipeline first generates scalable disease outcomes by linking electronic health record data with registry data containing a small sample of labeled outcomes. It then applies causal analysis using these scalable outcomes to evaluate therapies for chronic diseases. The implementation of the pipeline is illustrated in a case study based on multiple sclerosis. Our approach addresses challenges in real-world evidence generation for disease activity of chronic conditions, specifically the lack of direct observations on key outcomes and biases arising from imperfect or incomplete data. We present advanced machine learning techniques such as semisupervised and ensemble methods to impute missing outcome data, further incorporating steps for calibrated causal analyses and bias correction. ©Feiqing Huang, Jue Hou, Ningxuan Zhou, Kimberly Greco, Chenyu Lin, Sara Morini Sweet, Jun Wen, Lechen Shen, Nicolas Gonzalez, Sinian Zhang, Katherine P Liao, Tianrun Cai, Zongqi Xia, Florence T Bourgeois, Tianxi Cai.

关键词： calibration causal inference chronic disease outcomes data imputation electronic health records longitudinal disease activity machine learning real-world evidence

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Density of States for a Specified Correlation Function and the Energy Landscape

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Physical Review Letters 2012年第8期108卷 080601-080601页

作者： C. J. Gommes Y. Jiao S. Torquato Department of Chemical Engineering University of Liège B-4000 Liège Belgium Department of Chemistry Princeton University Princeton New Jersey 08544 USA Program in Applied and Computational Mathematics and Princeton Center for Theoretical Science Princeton University Princeton New Jersey 08544 USA

The degeneracy of two-phase disordered microstructures consistent with a specified correlation function is analyzed by mapping it to a ground-state degeneracy. We determine for the first time the associated density of states via a Monte Carlo algorithm. Our results are explained in terms of the roughness of an energy landscape, defined on a hypercubic configuration space. The use of a Hamming distance in this space enables us to define a roughness metric, which is calculated from the correlation function alone and related quantitatively to the structural degeneracy. This relation is validated for a wide variety of disordered structures.

关键词： ENERGY levels (Quantum mechanics) CORRELATION (Statistics) MICROSTRUCTURE GROUND state (Quantum mechanics) MONTE Carlo method CONFIGURATION space QUANTITATIVE research

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A Sparse DAE Solver in Maple

arXiv

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arXiv 2022年

作者： Jang, Taejin Uppaluri, Maitri Subramanian, Venkat R. Materials Science and Engineering Program Texas Materials Institute The University of Texas at Austin AustinTX78712 United States Walker Department of Mechanical Engineering The University of Texas at Austin AustinTX78712 United States Oden Institute for Computational Science and Engineering The University of Texas at Austin AustinTX United States

In this paper, some adaptive single-step methods like Trapezoid (TR), Implicit-mid point (IMP), Euler-backward (EB), and Radau IIA (Rad) methods are implemented in Maple to solve index-1 nonlinear Differential Algebraic Equations (DAEs). Maple's robust and efficient ability to search within a list/set is exploited to identify the sparsity pattern and the analytic Jacobian. The algorithm and implementation were found to be robust and efficient for index-1 DAE problems and scales well for finite difference/finite element discretization of two-dimensional models with system size up to 10,000 nonlinear DAEs and solves the same in few seconds. © 2022, CC BY-NC-ND.

关键词： Differential equations

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Gorgon and pathwalking: Macromolecular modeling tools for subnanometer resolution density maps

Gorgon and pathwalking: Macromolecular modeling tools for su...

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作者： Baker, Matthew L. Baker, Mariah R. Hryc, Corey F. Ju, Tao Chiu, Wah Verna and Marrs McLean Department of Biochemistry and Molecular Biology National Center for Macromolecular Imaging Baylor College of Medicine Houston TX 77030 United States Program in Structural and Computational Biology and Molecular Biophysics Baylor College of Medicine Houston TX 77030 United States Department of Computer Science and Engineering Washington University in St. Louis St. Louis MO 63130 United States

The complex interplay of proteins and other molecules, often in the form of large transitory assemblies, are critical to cellular function. Today, X-ray crystallography and electron cryo-microscopy (cryo-EM) are routinely used to image these macromolecular complexes, though often at limited resolutions. Despite the rapidly growing number of macromolecular structures, few tools exist for modeling and annotating structures in the range of 3-10 Å resolution. To address this need, we have developed a number of utilities specifically targeting subnanometer resolution density maps. As part of the 2010 Cryo-EM Modeling Challenge, we demonstrated two of our latest de novo modeling tools, Pathwalking and Gorgon, as well as a tool for secondary structure identification (SSEHunter) and a new rigid-body/flexible fitting tool in Gorgon. In total, we submitted 30 structural models from ten different subnanometer resolution data sets in four of the six challenge categories. Each of our utlities produced accurate structural models and annotations across the various density maps. In the end, the utilities that we present here offer users a robust toolkit for analyzing and modeling protein structure in macromolecular assemblies at non-atomic resolutions. © 2012 Wiley Periodicals, Inc.

关键词： X ray crystallography

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Metapopulation models imply non-Poissonian statistics of interevent times

arXiv

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arXiv 2021年

作者： dos Reis, Elohim Fonseca Masuda, Naoki Department of Mathematics State University of New York at Buffalo BuffaloNY United States Computational and Data-Enabled Science and Engineering Program State University of New York at Buffalo BuffaloNY United States

Interevent times in temporal contact data from humans and animals typically obey heavy-tailed distributions, and this property impacts contagion and other dynamical processes on networks. We theoretically show that distributions of interevent times heavier-tailed than exponential distributions are a consequence of the most basic metapopulation model used in epidemiology and ecology, in which individuals move from a patch to another according to the simple random walk. Our results hold true irrespectively of the network structure and also for more realistic mobility rules such as high-order random walks and the recurrent mobility patterns used for modeling human dynamics. Copyright © 2021, The Authors. All rights reserved.

关键词： Random processes

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Individual-based simulation of sexual selection: A quantitative genetic approach

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Procedia Computer science 2010年第1期1卷 2003-2011页

作者： D. van Dijk P.M.A. Sloot J.C. Tay M.C. Schut Computational Science University of Amsterdam Sciencepark 107 1098 XG Amsterdam The Netherlands Evolutionary and Complex Systems Program School of Computer Engineering Nanyang Technological University Singapore 639798 Singapore Department of Artificial Intelligence Vrije Universiteit Amsterdam 1081 HV Amsterdam The Netherlands

Sexual selection has been mathematically modeled using quantitative genetics as well as population genetics. Two-locus simulation models have been used to study the evolution of male display and female preference. We present an individual-based simulation model of sexual selection in a quantitative genetic context. We show that under certain conditions Fisherian self-reinforcing sexual selection takes effect, predicted by Lande’s analytic model of female choice. We also show that the dynamics involved in the co-evolution of male display and female preference is much more complex than mathematics would predict. We therefore argue that the study of sexual selection through individual-based simulation could give new and more realistic insight into a world dominated by overly simplified equations.

关键词： Sexual selection Individual-based modeling Agent-based modeling

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Agile parallel bioinformatics workflow management using Pwrake

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BMC Research Notes 2011年第1期4卷 1-8页

作者： Mishima, Hiroyuki Sasaki, Kensaku Tanaka, Masahiro Tatebe, Osamu Yoshiura, Koh-Ichiro Department of Human Genetics Nagasaki University Graduate School of Biomedical Sciences Nagasaki Nagasaki 1-12-4 Sakamoto Japan Nagasaki University Global Center of Excellence Program Nagasaki Nagasaki 1-12-4 Sakamoto Japan Center for Computational Sciences University of Tsukuba Tsukuba Ibaraki 1-1-1 Tennodai Japan Core Research for Evolutional Science and Technology Japan Science and Technology Agency Kawaguchi Saitama 4-1-8 Honcho Japan Departmentent of Computer Science Graduate School of Systems and Information Engineering University of Tsukuba Tsukuba Ibaraki 1-1-1 Tennodai Japan

Background: In bioinformatics projects, scientific workflow systems are widely used to manage computational procedures. Full-featured workflow systems have been proposed to fulfil the demand for workflow management. However, such systems tend to be over-weighted for actual bioinformatics practices. We realize that quick deployment of cutting-edge software implementing advanced algorithms and data formats, and continuous adaptation to changes in computational resources and the environment are often prioritized in scientific workflow management. These features have a greater affinity with the agile software development method through iterative development phases after trial and error. Here, we show the application of a scientific workflow system Pwrake to bioinformatics workflows. Pwrake is a parallel workflow extension of Ruby's standard build tool Rake, the flexibility of which has been demonstrated in the astronomy domain. Therefore, we hypothesize that Pwrake also has advantages in actual bioinformatics workflows. Findings. We implemented the Pwrake workflows to process next generation sequencing data using the Genomic Analysis Toolkit (GATK) and Dindel. GATK and Dindel workflows are typical examples of sequential and parallel workflows, respectively. We found that in practice, actual scientific workflow development iterates over two phases, the workflow definition phase and the parameter adjustment phase. We introduced separate workflow definitions to help focus on each of the two developmental phases, as well as helper methods to simplify the descriptions. This approach increased iterative development efficiency. Moreover, we implemented combined workflows to demonstrate modularity of the GATK and Dindel workflows. Conclusions: Pwrake enables agile management of scientific workflows in the bioinformatics domain. The internal domain specific language design built on Ruby gives the flexibility of rakefiles for writing scientific workflows. Furthermore, readability

关键词： Ruby Iterative Development Agile Software Development Host Language Bioinformatics Domain

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Phase Transformations, Microstructural Refinement and Defect Evolution Mechanisms in Al-Si Alloys under Non-Hydrostatic Diamond Anvil Cell Compression

SSRN

引用

SSRN 2020年

作者： Liu, Tingkun Olszta, Matthew Gwalani, Bharat Park, Changyong Mathaudhu, Suveen Devaraj, Arun Physical and Computational Science Directorate Pacific Northwest National Laboratory Energy and Environment Directorate Pacific Northwest National Laboratory High Pressure Collaborative Access Team X-ray Science Division Argonne National Laboratory Material Science and Engineering Program University of California Riverside Mechanical Engineering Department University of California Riverside

Non-hydrostatic compression of materials using a diamond anvil cell (DAC) can transform equilibrium microstructure of an alloy to novel, potentially metastable states. In this study, in situ synchrotron X-ray diffraction (XRD) during compression up to 24 GPa and subsequent ex situ, high resolution analytical electron microscopy (AEM) after decompression of an Al-Si alloy provided insight into the crystallographic changes during the compression as well as microstructural refinement, and defect structures caused by such a high pressure compression-decompression process. Pressure resolved in-situ synchrotron XRD was used to detail the phase transformation pathway of the eutectic Si phase in Al-Si alloy, from Si-I → Si-XI → Si-V during compression, and a final transformation predominantly to Si-III after decompression. Using scanning and transmission electron microscopy (S/TEM), site specific analysis of the alloy immediately underneath the anvil contact surface demonstrated a highly complex microstructure. A narrow region of thick amorphous Al oxide interspersed with nanocrystalline grains was found at the top surface. Underneath this Al oxide, while the majority the eutectic Si was transformed into highly-deformed, polycrystalline (PC) Si-III, a complex intermediate layer was discovered at the interface between Al and Si, comprised of a small fraction of Al nanocrystals and a majority of nanocrystalline Si-I. This combination of pressure resolved in-situ synchrotron XRD coupled with subsequent high resolution, electron microscopy resolved the phase transformation as well as non-equilibrium microstructures in a metallic alloy induced by a non-hydrostatic high pressure compression followed by decompression. © 2020, The Authors. All rights reserved.

关键词： Silicon alloys

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Toward the Multi-scale Simulation for a Human Body Using the Next-generation Supercomputer

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Procedia IUTAM 2014年 10卷 193-200页

作者： Yoichiro Matsumoto Satoshi Ii Seiji Shiozaki Kazuyasu Sugiyama Shu Takagi School of Engineering The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-8656 Japan Department of Mechanical Science and Bioengineering Osaka University 1-1 Machikaneyama Toyonaka Osaka 560-0043 Japan Computational Science Research Program RIKEN 2-1 Hirosawa Wako Saitama 351-0198 Japan

We have developed novel numerical methods for fluid-structure and fluid-membrane interaction problems. The basic equation set is formulated in a full Eulerian framework. The method is based on the finite difference volume-of-fluid scheme with fractional step algorithm. It is validated through a numerical solution to a deformable vesicle problem, and applied to blood flows including red blood cells (RBCs) and platelets. Further, to gain insight into the mechanism of thrombus formation, a stochastic Monte Carlo model to describe the platelet-vessel wall interaction is incorporated into the Eulerian method. The effect of the RBCs on the platelet motion is discussed.

关键词： Eulerian method fluid-structure interaction blood flow stochastic Monte Carlo method

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