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Research Square 2021年

作者： Tertilt, Henri Bakker, Jesse Becker, Marlon de Wilde, Bram Klanberg, Indrek Geurts, Bernard J. van der Wiel, Wilfred G. Heuer, Andreas Bobbert, Peter A. Institut für physikalische Chemie Westfälische Wilhelms-Universität Münster Münster Germany University of Twente Enschede Netherlands Multiscale Modeling and Simulation Group Faculty of Electrical Engineering Mathematics and Computer Science Center for Brain-Inspired Nano Systems University of Twente Enschede Netherlands Eindhoven University of Technology Eindhoven5600 MB Netherlands Fachbereich Physik Westfälische Wilhelms-Universität Münster Münster Germany Molecular Materials and Nanosystems Group Center for Computational Energy Research Eindhoven University of Technology Eindhoven Netherlands

We present an atomic-scale mechanism based on variable-range hopping of interacting charges enabling reconfigurable logic and nonlinear classification tasks in dopant network processing units in silicon. Kinetic Monte Carlo simulations of the hopping process show temperature-dependent current-voltage characteristics, artificial evolution of basic Boolean logic gates, and fitness-dependent gate abundances in striking agreement with experiment. The simulations provide unique insights in the local electrostatic potential and current flow in the dopant network, showing subtle changes induced by control voltages that set the conditions for the logic operation. These insights will be crucial in the systematic further development of this burgeoning technology for unconventional computing. The establishment of the principles underlying the logic functionality of these devices encourages the exploration and utilization of the same principles in other materials and device geometries. © 2021, CC BY.

关键词： Monte Carlo methods

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Correction to: Near‑global summer circulation response to the spring surface temperature anomaly in Tibetan Plateau –– the GEWEX/LS4P first phase experiment

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Climate Dynamics 2024年第6期62卷 5743-5744页

作者： Zhang, Yang Pan, Yan Xue, Yongkang Diallo, Ismaila Zeng, Xubin Li, Shuting Neelin, J. David Lau, William K. M. Boone, Aaron A. Vitart, Frederic Yao, Tandong Tang, Qi Sato, Tomonori Koo, Myung-Seo Ardilouze, Constantin Saha, Subodh K. Yang, Jing Materia, Stefano Lin, Zhaohui Qi, Xin Qin, Yi Nakamura, Tetsu Nobre, Paulo Peano, Daniele Senan, Retish Takaya, Yuhei Wang, Hailan Zhang, Hongliang Zhan, Yanling Zhao, Mei Mechoso, Carlos R Bao, Qing Bottino, Marcus Jorge Hong, Songyou Lin, Yanluan Xie, Shaocheng Pan, Xiaoduo Nayak, Hara Prasad Chou, Sin Chan Guo, Weidong School of Atmospheric Sciences Nanjing University Nanjing China Duke University Durham USA University of California ? Los Angeles Los Angeles USA Pennsylvania State University University Park USA University of Arizona Tucson AZ USA Nanjing China Earth System Science Interdisciplinary Center Universityof Maryland College Park USA CNRM Universit? de Toulouse M?t?o-France CNRS Toulouse France European Centre for Medium-Range Weather Forecasts Reading UK Institute of Tibetan Plateau Research Chinese Academy of Sciences (CAS) Beijing China Lawrence Livermore National Laboratory Livermore USA Hokkaido University Sapporo Japan Korea Institute of Atmospheric Prediction Systems Seoul South Korea Indian Institute of Tropical Meteorology Pune India Beijing Normal University Beijing China Barcelona Supercomputing Centre Barcelona Spain Institute of Atmospheric Physics CAS Beijing China Pacific Northwest National Laboratory Richland USA National Institute for Space Research (INPE) São José dos Campos Brazil Climate Simulation and Prediction Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici Bologna Italy Meteorological Research Institute Japan MeteorologicalAgency Tsukuba Japan National Center for Environmental Prediction College Park USA Center for Earth System Modeling and Prediction CMA Beijing China Bureau of Meteorology Melbourne Australia LASG Institute of Atmospheric Physics CAS Beijing China NOAA/ESRL and University of Colorado/CIRES Boulder USA Tsinghua University Beijing China

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End-to-End Deep Learning for Real-Time Neuroimaging-Based Assessment of Bimanual Motor Skills

arXiv

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arXiv 2025年

作者： Subedi, Aseem Rahul Cavuoto, Lora Schwaitzberg, Steven Hackett, Matthew Norfleet, Jack De, Suvranu Center for Modeling Simulation and Imaging in Medicine Rensselaer Polytechnic Institute TroyNY12180 United States Department of Industrial and Systems Engineering University at Buffalo-State University of New York BuffaloNY14215 United States Department of Surgery University at Buffalo-State University of New York BuffaloNY14215 United States U.S. Army Futures Command Combat Capabilities Development Command Soldier Center STTC OrlandoFL32826 United States Florida A&M University Florida State University College of Engineering TallahasseeFL32310 United States

The real-time assessment of complex motor skills presents a challenge in fields such as surgical training and rehabilitation. Recent advancements in neuroimaging, particularly functional near-infrared spectroscopy (fNIRS), have enabled objective assessment of such skills with high accuracy. However, these techniques are hindered by extensive preprocessing requirements to extract neural biomarkers. This study presents a novel end-to-end deep learning framework that processes raw fNIRS signals directly, eliminating the need for intermediate preprocessing steps. The model was evaluated on datasets from three distinct bimanual motor tasks—suturing, pattern cutting, and endotracheal intubation (ETI)—using performance metrics derived from both training and retention datasets. It achieved a mean classification accuracy of 93.9% (SD 4.4) and a generalization accuracy of 92.6% (SD 1.9) on unseen skill retention datasets, with a leave-one-subject-out cross-validation yielding an accuracy of 94.1% (SD 3.6). Contralateral prefrontal cortex activations exhibited task-specific discriminative power, while motor cortex activations consistently contributed to accurate classification. The model also demonstrated resilience to neurovascular coupling saturation caused by extended task sessions, maintaining robust performance across trials. Comparative analysis confirms that the end-to-end model performs on par with or surpasses baseline models optimized for fully processed fNIRS data, with statistically similar (p Copyright © 2025, The Authors. All rights reserved.

关键词： Brain mapping

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Automating Care by Self-maintainability for Full Laboratory Automation

arXiv

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arXiv 2025年

作者： Ochiai, Koji Tahara-Arai, Yuya Kato, Akari Kaizu, Kazunari Kariyazaki, Hirokazu Umeno, Makoto Takahashi, Koichi Kanda, Genki N. Ozaki, Haruka Laboratory for Biologically Inspired Computing RIKEN Center for Biosystems Dynamics Research 6-7-1 Minatojima Minamimachi Chuo-ku Hyogo Kobe650-0047 Japan Bioinformatics Laboratory Institute of Medicine University of Tsukuba 1-1-1 Tennodai Ibaraki Tsukuba305-8577 Japan Ph.D. Program in Humanics School of Integrative and Global Majors University of Tsukuba 1-1-1 Tennodai Ibaraki Tsukuba305-8577 Japan Laboratory Automation Suppliers’ Association 2-1-8 Minatojima Minamimachi Chuo-ku Hyogo Kobe650-0047 Japan Cell Modeling and Simulation Group Exploratory Research Center on Life and Living Systems National Institutes of Natural Sciences 5-1 Higashiyama Myodaiji Aichi Okazaki444-8787 Japan Robotics Division YASKAWA Electric Corporation 2-1 Kurosaki Shiroishi Yahatanishi-ku Kitakyushu Fukuoka806-0004 Japan BAIKEIDO LLC 3-8-1 Asano Kokurakita-ku Kitakyushu Fukuoka802-0001 Japan Graduate School of Media and Governance Keio University 5322 Endo Fujisawa-shi Kanagawa252-0882 Japan Medical Research Laboratory Institute of Integrated Research Institute of Science Tokyo 1-5-45 Yushima Bunkyo-ku Tokyo113-8519 Japan Center for Artificial Intelligence Research University of Tsukuba 1-1-1 Tennodai Ibaraki Tsukuba305-8577 Japan

The automation of experiments in life sciences and chemistry has significantly advanced with the development of various instruments and AI technologies. However, achieving full laboratory automation, where experiments conceived by scientists are seamlessly executed in automated laboratories, remains a challenge. We identify the lack of automation in planning and operational tasks—critical human-managed processes collectively termed "care"—as a major barrier. Automating care is the key enabler for full laboratory automation. To address this, we propose the concept of self-maintainability (SeM): the ability of a laboratory system to autonomously adapt to internal and external disturbances, maintaining operational readiness akin to living cells. A SeM-enabled laboratory features autonomous recognition of its state, dynamic resource and information management, and adaptive responses to unexpected conditions. This shifts the planning and execution of experimental workflows, including scheduling and reagent allocation, from humans to the system. We present a conceptual framework for implementing SeM-enabled laboratories, comprising three modules—Requirement manager, Labware manager, and Device manager—and a Central manager. SeM not only enables scientists to execute envisioned experiments seamlessly but also provides developers with a design concept that drives the technological innovations needed for full automation. Copyright © 2025, The Authors. All rights reserved.

关键词： Information management

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modeling the Tertiary Structure of a Multi-domain Protein: Structure Prediction of Multi-domain Proteins 18

Modeling the Tertiary Structure of a Multi-domain Protein: S...

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9th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics, ACM-BCB 2018

作者： Almsned, Fahad Gogovi, Gideon Bracci, Nicole Kehn-Hall, Kylene Blaisten-Barojas, Estela Shehu, Amarda Krasnow Institute for Advanced School of Systems Biology George Mason University United States Center for Simulation and Modeling Dept of Computational and Data Sciences George Mason University United States National Center for Biodefense and Infectious Diseases School of Systems Biology George Mason University United States Dept of Computer Science Dept of Bioengineering Center for Simulation and Modeling School of Systems Biology George Mason University United States

ISBN: (纸本)9781450357944

Due to the central role that tertiary structure plays in determining protein function, resolving protein tertiary structures is an integral research thrust in both wet and dry laboratories. Dry laboratories have primarily focused on small- to medium-size proteins. However, proteins central to human biology and human health are often quite complex, containing multiple domains and consisting of thou- sands of amino acids. Such proteins are challenging for various reasons, including the inability to crystallize. We present a case study of structure determination for the Rift Valley fever virus L-protein, a a large, multi-domain protein with currently no available tertiary structure. We employ this case study as an emerging paradigm and demonstrate how to leverage the rich and diverse landscape of bioinformatics tools for building tertiary structure models for multi-domain proteins with thousands of amino acids. © 2018 ACM.

关键词： Proteins

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Quality Control and Evaluation of the Observed Daily Data in the North American Soil Moisture Database

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Journal of Meteorological Research 2019年第3期33卷 501-518页

作者： Weilin LIAO Dagang WANG Guiling WANG Youlong XIA Xiaoping LIU School of Geography and Planning Sun Yat-sen University Guangzhou 510275 China Guangdong Key Laboratory for Urbanization and Geo-simulation Sun Yat-sen University Guangzhou 510275 China Key Laboratory of Water Cycle and Water Security in Southern China of Guangdong High Education Institute Sun Yat-sen University Guangzhou 510275 China Department of Civil and Environmental Engineering University of Connecticut Storrs CT 06269 USA I. M. Systems Group Environmental Modeling Center National Centers for Environmental Prediction College Park MD 20740 USA

The North American Soil Moisture Database (NASMD) was initiated in 2011 to assemble and homogenize in situ soil moisture measurements from 32 observational networks in the United States and Canada encompassing more than 1800 stations. Although statistical quality control (QC) procedures have been applied in the NASMD, the soil moisture content tends to be systematically underestimated by in situ sensors in frozen soils, and using a single maximum threshold (i.e., 0.6 m3 m-3) may not be sufficient for robust QC because of the diverse soil textures in North America. In this study, based on the in situ soil porosity and North American Land Data Assimilation System phase 2 (NLDAS-2) Noah soil temperature, the simple automated QC method is revised to supplement the existing QC approach. This revised QC method is first validated based on the assessment at 78 of the Soil Climate Analysis Network (SCAN) stations where the manually checked data are available, and is then applied to all stations in the NASMD to produce a more strict quality-controlled dataset. The results show that the revised automated QC procedure can flag the spurious and erroneous soil moisture measurements for the SCAN stations, especially for those located in high altitudes and latitudes. Relative to station measurements in the original NASMD, the quality-controlled data show a slightly better agreement with the manually checked soil moisture content. It should be noted that this quality-controlled dataset may be over-flagged for some valid soil moisture measurements due to potential errors of the soil temperature and soil porosity data, and validation in this study is limited by the availability of benchmark soil moisture data. The updated QC and additional validation will be desirable to boost confidence in the product when high-quality data become available in the future.

关键词： North American Soil Moisture Database (NASMD) quality control soil moisture North American Land Data Assimilation System phase 2 (NLDAS-2) soil temperature soil porosity

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A Value Sensitive ABM of the Refugee Crisis in the Netherlands

A Value Sensitive ABM of the Refugee Crisis in the Netherlan...

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Spring simulation Conference (SpringSim)

作者： Ross Gore Phillip Wozny Frank P. M. Dignum F. LeRon Shults Christine Boshuijzen - van Burken Lamber Royakkers Virginia Modeling Analysis & Simulation Center Old Dominion University Norfolk VA USA Department of Information & Computing Sciences Universiteit Utrecht Utrecht Netherlands NORCE Center for Modeling Social Systems University of Agder Kristiansand Norway Industrial Engineering & Innovation Sciences Eindhoven University of Technology Eindhoven Netherlands

We develop an agent based model to characterize the wellbeing of newcomers (i.e. asylum seeking refugees) in the context of asylum logistics using Schwartz's theory of values. The model produces recommendations for decision-makers with respect to avoiding catastrophic outcomes and maximizing best case outcomes. We conduct analysis to show that while a relatively simple set of conditions is necessary to avoid catastrophic outcomes, these conditions are insufficient to maximize the best case outcomes. Furthermore, the conditions that maximize one best case outcome do so at the expense of another. The result is a platform for decision-makers to understand tradeoffs in policies for government and non-government organizations.

关键词： Law Interviews Context modeling Computational modeling Analytical models Government

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Applying the DASE protocol to a high-speed engine performance analysis

Applying the DASE protocol to a high-speed engine performanc...

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AIAA modeling and simulation Technologies Conference, 2018

作者： Henderson, Ryan O. Snyder, Sharon E. Ward, Christopher A. C. Hurst, Terril N. Raytheon Missile Systems TucsonAZ85756 United States Advanced Systems Development Center TucsonAZ85756 United States Guidance Navigation and Control Center TucsonAZ85756 United States Modeling Simulation and Analysis Center TucsonAZ85756 United States

ISBN: (数字)9781624105289

ISBN: (纸本)9781624105289

A 7-step protocol called Design and Analysis of simulation of Experiments (DASE) was applied to a high-speed engine study. Two multivariate surrogate model types were compared for engine performance sensitivity analysis: a polynomial regression model and a regression tree. The polynomial regression model produced imprecise results. The regression tree model produced significantly more precise results, with almost all data falling within the discernible (practical) difference declared for the simulation experiment. © 2018, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Sensitivity analysis

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A WEB-SERVICE FRAMEWORK FOR THE WATER EVALUATION AND PLANNING SYSTEM

A WEB-SERVICE FRAMEWORK FOR THE WATER EVALUATION AND PLANNIN...

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simulation Multi-Conference

作者： Mostafa D. Fard Hessam Sarjoughian Arizona Center for Integrative Modeling & Simulation School of Computing Informatics and Decision Systems Engineering Tempe AZ USA

For systems-of-systems, the use of different modeling methods is important not only because each system can be described more correctly, but also benefit from tools that are in use by different communities. Using an opaque or closed source-code tool with others, however, is challenging. Consequently, to facilitate the development of simulations for systems-of-systems it is useful to cast closed-source models in a flexible component-based framework. Using this concept, a RESTful web service framework is developed for the Water Evaluation And Planning (WEAP) software system. The WEAP RESTful framework has a suite of model components for all the model entities defined in the WEAP system. An example water system model shows the computational cost for the web-service framework is negligible. Casting the model entities to components can play a key role in using the WEAP system with other modeling frameworks useful for simulating the complexities of the Food-Energy-Water systems.

关键词： Component-based modeling MDA RESTful services systems-of-systems WEAP

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Accuracy control for large-eddy simulation of turbulent mixing - Integral length-scale approach 11

Accuracy control for large-eddy simulation of turbulent mixi...

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11th International Symposium on Turbulence and Shear Flow Phenomena, TSFP 2019

作者： Geurts, B.J. Rouhi, A. Piomelli, U. Multiscale Modeling and Simulation Faculty EEMCS University of Twente P.O. Box 517 Enschede7500 AE Netherlands Multiscale Physics of Energy Systems Center for Computational Energy Research Faculty of Applied Physics Eindhoven University of Technology P.O. Box 213 Eindhoven5600 MB Netherlands Department of Mechanical and Materials Engineering Queen’s University KingstonONK7L 4L9 Canada Department of Mechanical Engineering University of Melbourne Victoria3010 Australia

Turbulent flow at high Reynolds numbers is currently not accessible on the basis of direct numerical simulation (DNS) of the Navier-Stokes equations - the computational complexity is too high to allow DNS in most realistic flow conditions. Instead, Large-Eddy simulation (LES) offers an alternative in which the focus is on capturing the larger dynamic scales of a problem. However, the fundamental closure problem in LES induced by spatial filtering of nonlinear terms, and the role of discretization errors in the numerical treatment of the LES equations, induce a principal uncertainty in any LES prediction. This uncertainty requires quantification and control. We investigate error control capabilities of the Integral Length-Scale Approximation (ILSA) and apply this modeling to transitional and turbulent mixing, focussing on the achieved reliability of LES as function of the grid resolution and ‘sub-filter activity’. © 2019 International Symposium on Turbulence and Shear Flow Phenomena, TSFP. All rights reserved.

关键词： Large eddy simulation

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