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P-631 Day Length Predicts Ovulatory Shifts in Women’s Reproductive Function

Human Reproduction 2022年第SUPPLEMENT_1期37卷

作者： Pearson, J Shanmugam, D Espinosa, M Van Lamsweerde, A Benhar, E Berglund Scherwitzl, E Scherwitzl, R Hill, S.E Natural Cycles Nordic AB Medical Algorithms and Data Stockholm Sweden Massachusetts Institute of Technology Computer Science & Artificial Intelligence Laboratory Cambridge U.S.A Texas Christian University Department of Psychology Fort Worth U.S.A

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iScience 2023年第9期26卷 107524页

作者： Iwane, Fumiaki Sobolewski, Aleksander Chavarriaga, Ricardo Millán, José del R. Department of Electrical and Computer Engineering The University of Texas at Austin Austin 78712 TX United States Department of Neurology The University of Texas at Austin Austin 78712 TX United States Learning Algorithms and Systems Laboratory (LASA) École Polytechnique Fédérale de Lausanne (EPFL) Lausanne 1015 Switzerland Wyss Center for Bio and Neuroengineering Campus Biotech Genève 1202 Switzerland École Polytechnique Fédérale de Lausanne (EPFL) Campus Biotech Genève 1202 Switzerland Centre for Artificial Intelligence Zurich University of Applied Sciences (ZHAW) Winterthur 8401 Switzerland Mulva Clinic for the Neurosciences The University of Texas at Austin Austin 78712 TX United States

Error-related potentials (ErrPs) are a prominent electroencephalogram (EEG) correlate of performance monitoring, and so crucial for learning and adapting our behavior. It is poorly understood whether ErrPs encode further information beyond error awareness. We report an experiment with sixteen participants over three sessions in which occasional visual rotations of varying magnitude occurred during a cursor reaching task. We designed a brain-computer interface (BCI) to detect ErrPs that provided real-time feedback. The individual ErrP-BCI decoders exhibited good transfer across sessions and scalability over the magnitude of errors. A non-linear relationship between the ErrP-BCI output and the magnitude of errors predicts individual perceptual thresholds to detect errors. We also reveal theta-gamma oscillatory coupling that co-varied with the magnitude of the required adjustment. Our findings open new avenues to probe and extend current theories of performance monitoring by incorporating continuous human interaction tasks and analysis of the ErrP complex rather than individual peaks. © 2023 The Author(s)

关键词： Cognitive neuroscience Neuroscience

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State estimation-based robust optimal control of influenza epidemics in an interactive human society

arXiv

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arXiv 2020年

作者： Azimi, Vahid Sharifi, Mojtaba Fakoorian, Seyed Nguyen, Thang Tien Department of Energy Resources Engineering Stanford University StanfordCA United States Department of Electrical and Computer Engineering University of Alberta Edmonton Canada Department of Electrical Engineering and Computer Science Cleveland State University ClevelandOH United States Modeling Evolutionary Algorithms Simulation and Artificial Intelligence Faculty of Electrical & Electronics Engineering Ton Duc Thang University Ho Chi Minh City Viet Nam

This paper presents a state estimation-based robust optimal control strategy for influenza epidemics in an interactive human society in the presence of modeling uncertainties. Interactive society is influenced by random entrance of individuals from other human societies whose effects can be modeled as a non-Gaussian noise. Since only the number of exposed and infected humans can be measured, states of the influenza epidemics are first estimated by an extended maximum correntropy Kalman filter (EMCKF) to provide a robust state estimation in the presence of the non-Gaussian noise. An online quadratic program (QP) optimization is then synthesized subject to a robust control Lyapunov function (RCLF) to minimize susceptible and infected humans, while minimizing and bounding the rates of vaccination and antiviral treatment. The joint QP-RCLF-EMCKF meets multiple design specifications such as state estimation, tracking, pointwise control optimality, and robustness to parameter uncertainty and state estimation errors that have not been achieved simultaneously in previous studies. The uniform ultimate boundedness (UUB)/convergence of error trajectories is guaranteed using a Lyapunov stability argument. The soundness of the proposed approach is validated on the influenza epidemics of an interactive human society with population of 16000. Simulation results show that the QP-RCLF-EMCKF achieves appropriate tracking and state estimation performance. Robustness of the proposed controller is finally illustrated in the presence of modeling error and non-Gaussian noise. Copyright © 2020, The Authors. All rights reserved.

关键词： Robust control

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DPA-2:a large atomic model as a multitask learner

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npj Computational Materials 2024年第1期10卷 185-199页

作者： Duo Zhang Xinzijian Liu Xiangyu Zhang Chengqian Zhang Chun Cai Hangrui Bi Yiming Du Xuejian Qin Anyang Peng Jiameng Huang Bowen Li Yifan Shan Jinzhe Zeng Yuzhi Zhang Siyuan Liu Yifan Li Junhan Chang Xinyan Wang Shuo Zhou Jianchuan Liu Xiaoshan Luo Zhenyu Wang Wanrun Jiang Jing Wu Yudi Yang Jiyuan Yang Manyi Yang Fu-Qiang Gong Linshuang Zhang Mengchao Shi Fu-Zhi Dai Darrin M.York Shi Liu Tong Zhu Zhicheng Zhong Jian Lv Jun Cheng Weile Jia Mohan Chen Guolin Ke Weinan E Linfeng Zhang Han Wang AI for Science Institute BeijingP.R.China DP Technology BeijingP.R.China Academy for Advanced Interdisciplinary Studies Peking UniversityBeijingP.R.China State Key Lab of Processors Institute of Computing TechnologyChinese Academy of SciencesBeijingP.R.China University of Chinese Academy of Sciences BeijingP.R.China HEDPS CAPTCollege of EngineeringPeking UniversityBeijingP.R.China Ningbo Institute of Materials Technology and Engineering Chinese Academy of SciencesNingboP.R.China CAS Key Laboratory of Magnetic Materials and Devices and Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology Chinese Academy of SciencesNingboP.R.China School of Electronics Engineering and Computer Science Peking UniversityBeijingP.R.China Shanghai Engineering Research Center of Molecular Therapeutics&New Drug Development School of Chemistry and Molecular EngineeringEast China Normal UniversityShanghaiP.R.China Laboratory for Biomolecular Simulation Research Institute for Quantitative Biomedicine and Department of Chemistry and Chemical BiologyRutgers UniversityPiscatawayNJUSA Department of Chemistry Princeton UniversityPrincetonNJUSA College of Chemistry and Molecular Engineering Peking UniversityBeijingP.R.China Yuanpei College Peking UniversityBeijingP.R.China School of Electrical Engineering and Electronic Information Xihua UniversityChengduP.R.China State Key Laboratory of Superhard Materials College of PhysicsJilin UniversityChangchunP.R.China Key Laboratory of Material Simulation Methods&Software of Ministry of Education College of PhysicsJilin UniversityChangchunP.R.China International Center of Future Science Jilin UniversityChangchunP.R.China Key Laboratory for Quantum Materialsof Zhejiang Province Department of PhysicsSchool of ScienceWestlake UniversityHangzhouP.R.China Atomistic Simulations Italian Institute of TechnologyGenovaItaly State Key Laboratory of Physical Chemistry of Solid Surface iChEMCollege of Chemistry and Chemical EngineeringXiame

The rapid advancements in artificial intelligence(AI)are catalyzing transformative changes in atomic modeling,simulation,and ***-driven potential energy models havedemonstrated the capability to conduct large-scale,long-duration simulations with the accuracy of ab initio electronic structure ***,the model generation process remains a bottleneck for large-scale *** propose a shift towards a model-centric ecosystem,wherein a large atomic model(LAM),pretrained across multiple disciplines,can be efficiently fine-tuned and distilled for various downstream tasks,thereby establishing a new framework for molecular *** this study,we introduce the DPA-2 architecture as a prototype for ***-trained on a diverse array of chemical and materials systemsusing a multi-task approach,DPA-2demonstrates superior generalization capabilities across multiple downstream tasks compared to the traditional single-task pre-training and fine-tuning *** approach sets the stage for the development and broad application of LAMs in molecular and materials simulation research.

关键词： DPA establishing thereby

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Preface

Lecture Notes in Networks and Systems

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Lecture Notes in Networks and Systems 2023年 729 LNNS卷 v-vi页

作者： Vasant, Pandian Weber, Gerhard-Wilhelm Arefin, Mohammad Shamsul Rodriguez-Aguilar, Roman Panchenko, Vladimir Munapo, Elias Thomas, J. Joshua Faculty of Electrical and Electronics Engineering Modeling Evolutionary Algorithms Simulation and Artificial Intelligence Ton Duc Thang University Ho Chi Minh City Viet Nam Department of Computer Science Chittagong University of Engineering and Technology Chittagong Bangladesh Laboratory of Non-traditional Energy Systems Department of Theoretical and Applied Mechanics Federal Scientific Agroengineering Center VIM Russian University of Transport Moscow Russia Department of Computer Science UOW Malaysia KDU Penang University College George Town Malaysia Faculty of Engineering Management Poznań University of Technology Poznan Poland School of Economics and Decision Sciences North West University Mmabatho South Africa Facultad de Ciencias Económicas y Empresariales School of Economic and Business Sciences Universidad Panamericana Mexico City Mexico

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Differential evolution based on node strength

Differential evolution based on node strength

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作者： Skanderova, Lenka Fabian, Tomas Zelinka, Ivan Department of Computer Science Faculty of Electrical Engineering and Computer Science VSB – Technical University of Ostrava Ostrava Czech Republic Modeling Evolutionary Algorithms Simulation and Artificial Intelligence Faculty of Electrical and Electronics Engineering Ton Duc Thang University Ho Chi Minh Viet Nam

In this paper, three novel algorithms for optimisation based on the differential evolution algorithm are devised. The main idea behind those algorithms stems from the observation that differential evolution dynamics can be modelled via complex networks. In our approach, the individuals of the population are modelled by the nodes and the relationships between them by the directed lines of the graph. Subsequent analysis of non-trivial topological features further influence the process of parent selection in the mutation step and replace the traditional approach which is not reflecting the complex relationships between individuals in the population during evolution. This approach represents a general framework which can be applied to various kinds of differential evolution algorithms. We have incorporated this framework with the three well-performing variants of differential evolution algorithms to demonstrate the effectiveness of our contribution with respect to the convergence rate. Two well-known benchmark sets (including 49 functions) are used to evaluate the performance of the proposed algorithms. Experimental results and statistical analysis indicate that the enhanced algorithms perform better or at least comparable to their original versions. Copyright © 2018 Inderscience Enterprises Ltd.

关键词： Complex networks

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A new nonlinear oscillator with infinite number of coexisting hidden and self-excited attractors

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Chinese Physics B 2018年第4期27卷 208-213页

作者： Yan-Xia Tang Abdul Jalil M Khalaf Karthikeyan Rajagopal Viet-Thanh Pham Sajad Jafari Ye Tian College of Science Hebei North University Zhangjiakou 075000 China Engineering Technology Research Center of Population Health lnformatization in Hebei Province Zhangjiakou 075000 China Department of Mathematics Faculty of Computer Science and Mathematics University of Kufa Najaf Iraq Department of Electrical and Communication Engineering the PNG University of Technology Lae Centre for Nonlinear Dynamics Defense University Ethiopia Modeling Evolutionary Algorithms Simulation and Artificial Intelligence Faculty of Electrical & Electronics Engineering Ton Duc Thang University Ho Chi Mirth City Vietnam Biomedical Engineering Department Amirkabir University of Technology Tehran 15875-4413 Iran

In this paper,we introduce a new two-dimensional nonlinear oscillator with an infinite number of coexisting limit *** limit cycles form a layer-by-layer structure which is very *** percent of these limit cycles are self-excited attractors while sixty percent of them are hidden *** this new system to its forced version,we introduce a new chaotic system with an infinite number of coexisting strange *** implement this system through field programmable gate arrays.

关键词： chaotic oscillators multistability hidden attractors

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Attentionxml: Label tree-based attention-aware deep model for high-performance extreme multi-label text classification

arXiv

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arXiv 2018年

作者： You, Ronghui Zhang, Zihan Wang, Ziye Dai, Suyang Mamitsuka, Hiroshi Zhu, Shanfeng Shanghai Key Lab of Intelligent Information Processing School of Computer Science Centre for Computational Systems Biology School of Mathematical Sciences Shanghai Institute of Artificial Intelligence Algorithms and ISTBI Fudan University Shanghai China Bioinformatics Center Institute for Chemical Research Kyoto University Japan Department of Computer Science Aalto University Helsinki Finland

Extreme multi-label text classification (XMTC) is an important problem in the era of big data, for tagging a given text with the most relevant multiple labels from an extremely large-scale label set. XMTC can be found in many applications, such as item categorization, web page tagging, and news annotation. Traditionally most methods used bag-of-words (BOW) as inputs, ignoring word context as well as deep semantic information. Recent attempts to overcome the problems of BOW by deep learning still suffer from 1) failing to capture the important subtext for each label and 2) lack of scalability against the huge number of labels. We propose a new label tree-based deep learning model for XMTC, called AttentionXML, with two unique features: 1) a multi-label attention mechanism with raw text as input, which allows to capture the most relevant part of text to each label;and 2) a shallow and wide probabilistic label tree (PLT), which allows to handle millions of labels, especially for "tail labels". We empirically compared the performance of AttentionXML with those of eight state-of-the-art methods over six benchmark datasets, including Amazon-3M with around 3 million labels. AttentionXML outperformed all competing methods under all experimental settings. Experimental results also show that AttentionXML achieved the best performance against tail labels among label tree-based methods. The code and datasets are available at http://***/yourh/AttentionXML . Copyright © 2018, The Authors. All rights reserved.

关键词： Benchmarking

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DPA-2: a large atomic model as a multi-task learner

arXiv

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arXiv 2023年

作者： Zhang, Duo Liu, Xinzijian Zhang, Xiangyu Zhang, Chengqian Cai, Chun Bi, Hangrui Du, Yiming Qin, Xuejian Peng, Anyang Huang, Jiameng Li, Bowen Shan, Yifan Zeng, Jinzhe Zhang, Yuzhi Liu, Siyuan Li, Yifan Chang, Junhan Wang, Xinyan Zhou, Shuo Liu, Jianchuan Luo, Xiaoshan Wang, Zhenyu Jiang, Wanrun Wu, Jing Yang, Yudi Yang, Jiyuan Yang, Manyi Gong, Fu-Qiang Zhang, Linshuang Shi, Mengchao Dai, Fu-Zhi York, Darrin M. Liu, Shi Zhu, Tong Zhong, Zhicheng Lv, Jian Cheng, Jun Jia, Weile Chen, Mohan Ke, Guolin Weinan, E. Zhang, Linfeng Wang, Han AI for Science Institute Beijing100080 China DP Technology Beijing100080 China Academy for Advanced Interdisciplinary Studies Peking University Beijing100871 China State Key Lab of Processors Institute of Computing Technology Chinese Academy of Sciences Beijing100871 China University of Chinese Academy of Sciences Beijing100871 China HEDPS CAPT College of Engineering Peking University Beijing100871 China Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Ningbo315201 China CAS Key Laboratory of Magnetic Materials and Devices Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology Chinese Academy of Sciences Ningbo315201 China School of Electronics Engineering and Computer Science Peking University Beijing100871 China Shanghai Engineering Research Center of Molecular Therapeutics & New Drug Development School of Chemistry and Molecular Engineering East China Normal University Shanghai200062 China Laboratory for Biomolecular Simulation Research Institute for Quantitative Biomedicine Department of Chemistry and Chemical Biology Rutgers University PiscatawayNJ08854 United States Department of Chemistry Princeton University PrincetonNJ08540 United States College of Chemistry and Molecular Engineering Peking University Beijing100871 China Yuanpei College Peking University Beijing100871 China School of Electrical Engineering and Electronic Information Xihua University Chengdu610039 China State Key Laboratory of Superhard Materials College of Physics Jilin University Changchun130012 China Key Laboratory of Material Simulation Methods & Software of Ministry of Education College of Physics Jilin University Changchun130012 China International Center of Future Science Jilin University Changchun130012 China Key Laboratory for Quantum Materials of Zhejiang Province Department of Physics School of Science Westlake University Zhejiang Hangzhou310030 China Atomistic Simulations Italia

The rapid advancements in artificial intelligence (AI) are catalyzing transformative changes in atomic modeling, simulation, and design. AI-driven potential energy models have demonstrated the capability to conduct large-scale, long-duration simulations with the accuracy of ab initio electronic structure methods. However, the model generation process remains a bottleneck for large-scale applications. We propose a shift towards a model-centric ecosystem, wherein a large atomic model (LAM), pre-trained across multiple disciplines, can be efficiently fine-tuned and distilled for various downstream tasks, thereby establishing a new framework for molecular modeling. In this study, we introduce the DPA-2 architecture as a prototype for LAMs. Pre-trained on a diverse array of chemical and materials systems using a multi-task approach, DPA-2 demonstrates superior generalization capabilities across multiple downstream tasks compared to the traditional single-task pre-training and fine-tuning methodologies. Our approach sets the stage for the development and broad application of LAMs in molecular and materials simulation research. Copyright © 2023, The Authors. All rights reserved.

关键词： Multi-task learning

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Three Colors Suffice: Conflict-Free Coloring of Planar Graphs 17

Three Colors Suffice: Conflict-Free Coloring of Planar Graph...

引用

Annual ACM-Society for Industrial and Applied Mathmatics Symposium on Discrete algorithms

作者： Zachary Abel Victor Alvarez Erik D. Demaine Sandor P. Fekete Aman Gour Adam Hesterberg Phillip Keldenich Christian Scheffer Mathematics Department MIT Algorithms Group TU Braunschweig Computer Science and Artificial Intelligence Laboratory MIT Computer Science and Engineering IIT Bombay

ISBN: (纸本)9781510836358

A conflict-free k-coloring of a graph assigns one of k different colors to some of the vertices such that, for every vertex v, there is a color that is assigned to exactly one vertex among v and v's neighbors. Such colorings have applications in wireless networking, robotics, and geometry, and are well-studied in graph theory. Here we study the natural problem of the conflict-free chromatic number χ_(CF)(G) (the smallest k for which conflict-free k-colorings exist), with a focus on planar graphs. For general graphs, we prove the conflict-free variant of the famous Hadwiger Conjecture: If G does not contain K_(k+1) as a minor, then χ_(CF)(G) ≤ k. For planar graphs, we obtain a tight worst-case bound: three colors are sometimes necessary and always sufficient. In addition, we give a complete characterization of the algorithmic/computational complexity of conflict-free coloring. It is NP-complete to decide whether a planar graph has a conflict-free coloring with one color, while for outer-planar graphs, this can be decided in polynomial time. Furthermore, it is NP-complete to decide whether a planar graph has a conflict-free coloring with two colors, while for outerplanar graphs, two colors always suffice. For the bicriteria problem of minimizing the number of colored vertices subject to a given bound k on the number of colors, we give a full algorithmic characterization in terms of complexity and approximation for outerplanar and planar graphs.

关键词： planning drawings Color Planar vertex head Graph theory

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