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arXiv 2022年

作者： Hammoud, Mohamad Abed El Rahman Le Maître, Olivier Titi, Edriss S. Hoteit, Ibrahim Knio, Omar Division of Physical Sciences and Engineering King Abdullah University of Science and Technology Thuwal23955 Saudi Arabia Centre de Mathématiques Appliquées CNRS and Inria Ecole Polytechnique Palaiseau91120 France Department of Applied Mathematics and Theoretical Physics University of Cambridge CambridgeCB3 0WA United Kingdom Department of Mathematics Texas A & M University College StationTX77843 United States Division of Computer Electrical and Mathematical Sciences and Engineering King Abdullah University of Science and Technology Thuwal23955 Saudi Arabia

Obtaining accurate high-resolution representations of model outputs is essential to describe the system dynamics. In general, however, only spatially- and temporally-coarse observations of the system states are available. These observations can also be corrupted by noise. Downscaling is a process/scheme in which one uses coarse scale observations to reconstruct the high-resolution solution of the system states. Continuous Data Assimilation (CDA) is a recently introduced downscaling algorithm that constructs an increasingly accurate representation of the system states by continuously nudging the large scales using the coarse observations. We introduce a Discrete Data Assimilation (DDA) algorithm as a downscaling algorithm based on CDA with discrete-in-time nudging. We then investigate the performance of the CDA and DDA algorithms for downscaling noisy observations of the Rayleigh-Bénard convection system in the chaotic regime. In this computational study, a set of noisy observations was generated by perturbing a reference solution with Gaussian noise before downscaling them. The downscaled fields are then assessed using various error- and ensemble-based skill scores. The CDA solution was shown to converge towards the reference solution faster than that of DDA but at the cost of a higher asymptotic error. The numerical results also suggest a quadratic relationship between the 2 error and the noise level for both CDA and DDA. Cubic and quadratic dependences of the DDA and CDA expected errors on the spatial resolution of the observations were obtained, respectively. © 2022, CC BY.

关键词： Errors

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KLF2 maintains lineage fidelity and suppresses CD8 T cell exhaustion during acute LCMV infection

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Science (New York, N.Y.) 2025年第6735期387卷 eadn2337页

作者： Fagerberg, Eric Attanasio, John Dien, Christine Singh, Jaiveer Kessler, Emily A. Abdullah, Leena Shen, Jian Hunt, Brian G. Connolly, Kelli A. De Brouwer, Edward He, Jiaming Iyer, Nivedita R. Buck, Jessica Borr, Emily R. Damo, Martina Foster, Gena G. Giles, Josephine R. Huang, Yina H. Tsang, John S. Krishnaswamy, Smita Cui, Weiguo Joshi, Nikhil S. Department of Immunobiology Yale University School of Medicine New Haven CT United States Program in Computational Biology & Bioinformatics Yale University New Haven CT United States Department of Microbiology and Immunology Geisel School of Medicine at Dartmouth NH United States Department of Pathology Feinberg School of Medicine at Northwestern University Chicago IL United States Department of Genetics and Computer Science Yale University School of Medicine New Haven CT United States Department of Medicine University of Chicago Chicago IL United States Section of Hematology Department of Internal Medicine Yale University School of Medicine New Haven CT United States Department of Systems Pharmacology and Translational Therapeutics University of Pennsylvania Philadelphia PA United States Institute for Immunology Perelman School of Medicine University of Pennsylvania Philadelphia PA United States Parker Institute for Cancer Immunotherapy Perelman School of Medicine University of Pennsylvania Philadelphia PA United States Yale Center for Systems and Engineering Immunology Yale University School of Medicine New Haven CT United States New Haven CT United States Department of Biomedical Engineering Yale University New Haven CT United States Computational Biology and Bioinformatics Program Yale University CT USA New Haven United States Applied Math Program Yale University New Haven CT United States

Naïve CD8 T cells have the potential to differentiate into a spectrum of functional states during an immune response. How these developmental decisions are made and what mechanisms exist to suppress differentiation toward alternative fates remains unclear. We employed in vivo CRISPR-Cas9-based perturbation sequencing to assess the role of ~40 transcription factors (TFs) and epigenetic modulators in T cell fate decisions. Unexpectedly, we found that knockout of the TF Klf2 resulted in aberrant differentiation to exhausted-like CD8 T cells during acute infection. KLF2 was required to suppress the exhaustion-promoting TF TOX and to enable the TF TBET to drive effector differentiation. KLF2 was also necessary to maintain a polyfunctional tumor-specific progenitor state. Thus, KLF2 provides effector CD8 T cell lineage fidelity and suppresses the exhaustion program.

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A deterministic Susceptible–Infected–Recovered model for studying the impact of media on epidemic dynamics

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Healthcare Analytics 2023年 3卷 100189-100189页

作者： Fome, Anna D. Rwezaura, Herieth Diagne, Mamadou L. Collinson, Shannon Tchuenche, Jean M. Department of Economics Mathematics and Statistics Jordan University College Morogoro Tanzania Mathematics Department University of Dar es Salaam P.O. Box 35062 Dar es Salaam Tanzania Département de Mathématiques UFR des Sciences et Technologies Université de Thiès BP 967 Thiès Senegal Centre for Disease Modelling York University Canada School of Computational and Communication Sciences and Engineering Nelson Mandela African Institution of Science and Technology P.O. Box 447 Arusha Tanzania School of Computer Science and Applied Mathematics University of the Witwatersrand Private Bag 3 Wits 2050 Johannesburg South Africa

It is important to understand how the provision of information influences individuals’ behavior and its impact on disease transmission dynamics. We formulate a simple deterministic Susceptible–Infected–Recovered (SIR) model with vital dynamics and incorporate, one at a time, four media functions used in previous studies to mimic media reporting of a disease outbreak to investigate their impact on the dynamics of an epidemic. The most sensitive model parameter for the epidemic outcome at initial disease transmission and disease prevalence are obtained through normalized forward-sensitivity analyses. Media reporting does not impact initial disease transmission but affects the effective reproduction number as the media coverage begins. Numerical results show that the epidemic will affect a large proportion of the population with no media functions. Still, the epidemic time line may be short. In contrast, the key epidemiological quantities (such as age at infection, peak magnitude, peak time, end of the epidemic, and final epidemic size) vary depending on the media function used. The choice of the media function in a pandemic is critical. The media reporting on the spread of disease during pandemics should be done with care since it could counter-intuitively lead to under or overestimating the disease outbreak. © 2023 The Author(s)

关键词： Deterministic model Disease outbreak Epidemic dynamics Media coverage Sensitivity analysis Susceptible–infected–recovered

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Inverse scattering on the quantum graph for graphene

arXiv

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arXiv 2021年

作者： Ando, Kazunori Isozaki, Hiroshi Korotyaev, Evgeny Morioka, Hisashi Department of Electrical and Electronic Engineering and Computer Science Ehime University Matsuyama790-8577 Japan Graduate School of Pure and Applied Sciences Professor Emeritus University of Tsukuba Tsukuba305-8571 Japan Department of Math. Analysis Saint-Petersburg State University Universitetskaya nab. 7/9 St. Petersburg199034 Russia National Research University Higher School of Economics St. Petersburg Russia

We consider the inverse scattering on the quantum graph associated with the hexagonal lattice. Assuming that the potentials on the edges are compactly supported and symmetric, we show that the S-matrix for all energies in any given open set in the continuous spectrum determines the *** Codes 81U40, 47A40 Copyright © 2021, The Authors. All rights reserved.

关键词： Inverse problems

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Artificial intelligence advances for de novo molecular structure modeling in cryo-EM

arXiv

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arXiv 2021年

作者： Si, Dong Nakamura, Andrew Tang, Runbang Guan, Haowen Hou, Jie Firozi, Ammaar Cao, Renzhi Hippe, Kyle Zhao, Minglei Division of Computing and Software Systems University of Washington Bothell BothellWA98011 United States Molecular Engineering and Sciences Institute University of Washington Seattle SeattleWA98105 United States Applied and Computational Math Sciences University of Washington Seattle SeattleWA98195 United States Department of Computer Science Saint Louis University Saint. LouisMO63103 United States Department of Computer Science Pacific Lutheran University TacomaWA98447 United States Department of Biochemistry and Molecular Biology University of Chicago ChicagoIL60637 United States

Cryo-electron microscopy (cryo-EM) has become a major experimental technique to determine the structures of large protein complexes and molecular assemblies, as evidenced by the 2017 Nobel Prize. Although cryo-EM has been drastically improved to generate high-resolution three-dimensional (3D) maps that contain detailed structural information about macromolecules, the computational methods for using the data to automatically build structure models are lagging far behind. The traditional cryo-EM model building approach is template-based homology modeling. Manual de novo modeling is very time-consuming when no template model is found in the database. In recent years, de novo cryo-EM modeling using machine learning (ML) and deep learning (DL) has ranked among the top-performing methods in macromolecular structure modeling. Deep-learning-based de novo cryo-EM modeling is an important application of artificial intelligence, with impressive results and great potential for the next generation of molecular biomedicine. Accordingly, we systematically review the representative ML/DL-based de novo cryo-EM modeling methods. And their significances are discussed from both practical and methodological viewpoints. We also briefly describe the background of cryo-EM data processing workflow. Overall, this review provides an introductory guide to modern research on artificial intelligence (AI) for de novo molecular structure modeling and future directions in this emerging field. © 2021, CC BY-NC-ND.

关键词： Electron microscopes

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BlockCAM: A blockchain-based cross-domain authentication model 3

BlockCAM: A blockchain-based cross-domain authentication mod...

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3rd IEEE International Conference on Data Science in Cyberspace, DSC 2018

作者： Wang, Wentong Hu, Ning Liu, Xin School of Cyberspace Security National University of Defense Technology Changsha China Department of Computer Engineering and Applied Math Changsha University Changsha China

ISBN: (纸本)9781538642108

In a distributed network environment, companies and institutions have their own sharing resource. To prevent unauthorized users to access these shared resources, cross-domain authentication is necessary. For ensuring the safety and efficiency to access resources in different domain, we propose a blockchain-based cross-domain authentication model called BlockCAM and designed the cross-domain authentication protocol. BlockCAM employs consortium blockchain technology to construct a decentralized network with the root Certificate Authorities as the verification nodes. The hash values of the authorized certificates are stored in each block and the verification process only needs to compare whether the hash calculated by the certificate provided by the user is consistent with the hash stored in the blockchain. The authentication process omits the key encryption and decryption overhead. BlockCAM has the characteristics of decentralization, anonymity and temper-resistant. Analyses show that BlockCAM has the advantage over the existing public key infrastructure (PKI) cross-domain authentication schemes at efficiency. © 2018 IEEE.

关键词： Blockchain

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Simultaneous dimensionality and complexity model selection for spectral graph clustering

arXiv

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arXiv 2019年

作者： Yang, Congyuan Priebe, Carey E. Park, Youngser Marchette, David J. Department of Electrical and Computer Engineering Johns Hopkins University Department of Applied Math and Statistics Johns Hopkins University Center for Imaging Science Johns Hopkins University Applied Mathematics and Data Analytics Group Naval Surface Warfare Center Dahlgren Division

Our problem of interest is to cluster vertices of a graph by identifying underlying community structure. Among various vertex clustering approaches, spectral clustering is one of the most popular methods because it is easy to implement while often outperforming more traditional clustering algorithms. However, there are two inherent model selection problems in spectral clustering, namely estimating both the embedding dimension and number of clusters. This paper attempts to address the issue by establishing a novel model selection framework specifically for vertex clustering on graphs under a stochastic block model. The first contribution is a probabilistic model which approximates the distribution of the extended spectral embedding of a graph. The model is constructed based on a theoretical result of asymptotic normality of the informative part of the embedding, and on a simulation result providing a conjecture for the limiting behavior of the redundant part of the embedding. The second contribution is a simultaneous model selection framework. In contrast with the traditional approaches, our model selection procedure estimates embedding dimension and number of clusters simultaneously. Based on our conjectured distributional model, a theorem on the consistency of the estimates of model parameters is stated and proven. The theorem provides statistical support for the validity of our method. Heuristic algorithms via the simultaneous model selection framework for vertex clustering are proposed, with good performance shown in the experiment on synthetic data and on the real application of connectome analysis. Copyright © 2019, The Authors. All rights reserved.

关键词： Embeddings

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Thresholded non-uniform fourier frame-based reconstruction for stripmap SAR

arXiv

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arXiv 2019年

作者： McKay, John Gelb, Anne Jayasuriya, Suren Monga, Vishal Applied Research Laboratory Pennsylvania State University Dept. of Electrical Engineering Pennsylvania State University Dept of Math Dartmouth College Department of Arts Media and Engineering as well as Electrical Computer and Energy Engineering Arizona State University

Fourier domain methods are fast algorithms for SAR imaging. They typically involve an interpolation in the frequency domain to re-grid non-uniform data so inverse fast Fourier transforms can be performed. In this paper, we apply a frame reconstruction algorithm, extending the non-uniform fast Fourier transform, to stripmap SAR data. Further, we present an improved thresholded frame reconstruction algorithm for robust performance and improved computational efficiency. We demonstrate compelling results on real stripmap SAR data. Copyright © 2019, The Authors. All rights reserved.

关键词： Frequency domain analysis

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HIV and COVID-19 co-infection: A mathematical model and optimal control

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Informatics in Medicine Unlocked 2022年 31卷 100978页

作者： Ringa, N. Diagne, M.L. Rwezaura, H. Omame, A. Tchoumi, S.Y. Tchuenche, J.M. Data and Analytic Services British Columbia Centre for Disease Control 655 W 12th Ave Vancouver BC V5Z 4R4 Canada School of Population and Public Health University of British Columbia 2329 West Mall Vancouver BC V6T 1Z4 Canada Département de Mathématiques UFR des Sciences et Technologies Université de Thiès Thiès BP 967 Senegal Mathematics Department University of Dar es Salaam P.O. Box 35062 Dar es Salaam Tanzania Department of Mathematics Federal University of Technology Owerri Nigeria Abdus Salam School of Mathematical Sciences Government College University Lahore Pakistan Department of Mathematics and Computer Sciences ENSAI University of Ngaoundéré P.O. Box 455 Ngaoundéré Cameroon School of Computer Science and Applied Mathematics University of the Witwatersrand Private Bag 3 Wits 2050 Johannesburg South Africa School of Computational and Communication Sciences and Engineering Nelson Mandela African Institution of Science and Technology P.O. Box 447 Arusha Tanzania

A new mathematical model for COVID-19 and HIV/AIDS is considered to assess the impact of COVID-19 on HIV dynamics and vice-versa. Investigating the epidemiologic synergy between COVID-19 and HIV is important. The dynamics of the full model is driven by that of its sub-models;therefore, basic analysis of the two sub-models;HIV-only and COVID-19 only is carried out. The basic reproduction number is computed and used to prove local and global asymptotic stability of the sub-models’ disease-free and endemic equilibria. Using the fmincon function in the Optimization Toolbox of MATLAB, the model is fitted to real COVID-19 data set from South Africa. The impact of intervention measures, namely, COVID-19 and HIV prevention interventions and COVID-19 treatment are incorporated into the model using time-dependent controls. It is observed that HIV prevention measures can significantly reduce the burden of co-infections with COVID-19, while effective treatment of COVID-19 could reduce co-infections with opportunistic infections such as HIV/AIDS. In particular, the COVID-19 only prevention strategy averted about 10,500 new co-infection cases, with similar number also averted by the HIV-only prevention control. © 2022 The Author(s)

关键词： Basic reproduction number Co-infection COVID-19 HIV Optimal control

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Cell-DEVS modeling and simulation of artificial hydraulic fracturing of rocks in boreholes (WIP)

Cell-DEVS modeling and simulation of artificial hydraulic fr...

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TMS/DEVS Symposium on Theory of Modeling and Simulation, TMS/DEVS 2018, Part of the 2018 Spring Simulation Multi-Conference, SpringSim 2018

作者： Oyelowo, Ifeoluwa Wainer, Gabriel Echegini, Ngozi Silas Ukeme, Joseph Boi Zlotnik, Sergio Department of Systems and Computer Engineering Carleton University 1125 Colonel by Drive OttawaONKIS 5B6 Canada LaCaN Applied Math Department III UPC - BarcelonaTech Jordi Girona 1-3 Rm 204 Building C2 BarcelonaE-08034 Spain

ISBN: (纸本)9781510860209

Hydraulic Fracturing is a technique used in the extraction and exploration of oil and gas. During hydraulic fracturing, a high-pressure fluid is injected into a wellbore;this fluid flows through some artificially made holes and into some rock fragments. As a result of the high pressure of the fluid, the rock fragments crack or fracture. These fractures form patterns that grow in a complicated manner. In practice, hydraulic fracturing is widely used;therefore, people and companies have a great interest in understanding the fracturing process. They aim to predict where the new fractures will be located and what the length, width and shape of the fractures will be. A model of hydraulic fracturing using the Cell-DEVS paradigm is described and implemented, discussing a discrete-event specification of such application. © 2018 Society for Modeling & Simulation (SCS) International.

关键词： Hydraulic fracturing

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