检索结果-内蒙古大学图书馆

arXiv 2025年

作者： León, Iván Muolo, Riccardo Hata, Shigefumi Nakao, Hiroya Department of Applied Mathematics and Computer Science Universidad de Cantabria Santander39005 Spain Department of Systems and Control Engineering Tokyo Institute of Technology Tokyo152-8552 Japan Graduate School of Science and Engineering Kagoshima University Kagoshima890-0065 Japan Research Center for Autonomous Systems Materialogy Institute of Innovative Research Tokyo Institute of Technology Yokohama226-8501 Japan

Phase reduction is a powerful technique in the study of nonlinear oscillatory systems. Under certain assumptions, it allows us to describe each multidimensional oscillator by a single phase variable, giving rise to simple phase models such as the Kuramoto model. Classically, the method has been applied in the case where the interactions are only pairwise (two-body). However, increasing evidence shows that interactions in real-world systems are not pairwise but higher-order, i.e., many-body. Although synchronization in higher-order systems has received much attention, analytical results are scarce because of the highly nonlinear nature of the framework. In this paper, we fill the gap by presenting a general theory of phase reduction for the case of higher-order interactions. We show that the higher-order topology is preserved in the phase reduced model at the first order and that only odd couplings have an effect on the dynamics when certain symmetries are present. Additionally, we show the power and ductility of the phase reduction approach by applying it to a population of Stuart-Landau oscillators with an all-to-all configuration and with a ring-like hypergraph topology;in both cases, only the analysis of the phase model can provide insights and analytical results. © 2025, CC BY-NC-ND.

关键词： Topology

来源：评论

学校读者我要写书评

暂无评论

State-space models are accurate and efficient neural operators for dynamical systems

arXiv

引用

arXiv 2024年

作者： Hu, Zheyuan Daryakenari, Nazanin Ahmadi Shen, Qianli Kawaguchi, Kenji Em Karniadakis, George Department of Computer Science National University of Singapore Singapore119077 Singapore Center for Biomedical Engineering School of Engineering Brown University ProvidenceRI02912 United States Division of Applied Mathematics Brown University ProvidenceRI02912 United States Advanced Computing Mathematics and Data Division Pacific Northwest National Laboratory RichlandWA United States

Physics-informed machine learning (PIML) has emerged as a promising alternative to classical methods for predicting dynamical systems, offering faster and more generalizable solutions. However, existing models, including recurrent neural networks (RNNs), transformers, and neural operators, face challenges such as long-time integration, long-range dependencies, chaotic dynamics, and extrapolation, to name a few. To this end, this paper introduces state-space models implemented in Mamba for accurate and efficient dynamical system operator learning. Mamba addresses the limitations of existing architectures by dynamically capturing long-range dependencies and enhancing computational efficiency through reparameterization techniques. To extensively test Mamba and compare against another 11 baselines, we introduce several strict extrapolation testbeds that go beyond the standard interpolation benchmarks. We demonstrate Mamba’s superior performance in both interpolation and challenging extrapolation tasks. Mamba consistently ranks among the top models while maintaining the lowest computational cost and exceptional extrapolation capabilities. Moreover, we demonstrate the good performance of Mamba for a real-world application in quantitative systems pharmacology for assessing the efficacy of drugs in tumor growth under limited data scenarios. Taken together, our findings highlight Mamba’s potential as a powerful tool for advancing scientific machine learning in dynamical systems modeling. (The code will be available at https://***/zheyuanhu01/State_ Space_Model_Neural_Operator upon acceptance.) © 2024, CC BY.

关键词： Recurrent neural networks

来源：评论

学校读者我要写书评

暂无评论

Digital Twin-Enabled Real-Time Optimization System for Traffic and Power Grid Management in 6G-Driven Smart Cities

引用

IEEE Internet of Things Journal 2025年

作者： Prathiba, Sahaya Beni Krishnamoorthy, Sri Ram Kannan, Karuna Soundari Selvaraj, Arikumar K. Ranganayakulu, Dhanalakshmi Fang, Kai Gadekallu, Thippa Reddy Vellore Institute of Technology Centre for Cyber Physical Systems School of Computer Science and Engineering Chennai600127 India Vellore Institute of Technology School of Electronics Engineering Chennai600127 India College of Engineering and Technology Department of Data Science and Business Systems Kattankulathur603 203 India Zhejiang A and F University College of Mathematics and Computer Science Hangzhou311300 China Zhejiang A and F University Division of Research and Development Lovely Professional University College of Mathematics and Computer Science Hangzhou Phagwara311300 India Chitkara University Center of Research Impact and Outcome Punjab Rajpura140401 India

The advent of 6G-enabled Internet of Everything(IoE) technologies is set to revolutionize urban infrastructures by providing fast, consistent, and low-delay capabilities for communication. 6G connectivity will integrate traffic and power grids for adaptive urban management. However, current traffic networks and power grids face critical challenges such as fragmented data processing, delayed responses, and outdated resource management leading to inefficiencies like traffic congestion and power outages. In 6G-enabled smart grid cities, system complexity and interdependence demand dynamic, real-time solutions, further exacerbating inefficiencies. To address these issues, this study introduces Digital Twin-enabled Real-time Optimization System (DT-ROS), a dynamic framework designed to optimize urban traffic and power grid systems. DT-ROS integrates a dual-tier Digital Twin (DT) and an advanced scheduling framework based on Priority Age of Information Deep Q Scheduler (PAoI-QS). The dual-tier framework builds an elementary and Integrated Digital Twin (IDT) with Auto-Regressive Integrated Moving Average (ARIMA)-based forecasting for accurate real-time traffic and energy demand predictions. The advanced scheduling framework minimizes the Age of Information (AoI), ensuring decision-making relies on the most current and relevant data. By continuously monitoring and processing real-time data, DT-ROS creates virtual models to simulate system behavior and dynamically allocate resources. Simulation results demonstrate the effectiveness of DT-ROS, achieving a 30% reduction in traffic congestion and a 25% improvement in power grid stability compared to existing methods. To create effective, robust, and sustainable urban systems for future smart cities, DT-ROS addresses traffic and electricity problems. © 2014 IEEE.

关键词： Smart power grids

来源：评论

学校读者我要写书评

暂无评论

Advantage of Pausing: Parameter Setting for Quantum Annealers

引用

Physical Review Applied 2022年第5期18卷 054056-054056页

作者： Zoe Gonzalez Izquierdo Shon Grabbe Husni Idris Zhihui Wang Jeffrey Marshall Eleanor Rieffel QuAIL NASA Ames Research Center Moffett Field California 94035 USA USRA Research Institute for Advanced Computer Science Mountain View California 94043 USA Aviation Systems Division NASA Ames Research Center Moffett Field California 94035 USA

Prior work showed the efficacy of pausing midanneal: such a pause improved the probability of success by orders of magnitude in a class of native problem instances and improved the time to solution in a class of embedded problem instances. A physics-based picture provides qualitative suggestions for where pausing midanneal is effective, for the interplay between annealing schedule parameters and other annealing properties and parameters such as embedding size and strength of the ferromagnetic coupling |JF|, and for the conditions under which pausing can improve the time to solution. Here, through demonstrations on an updated annealing architecture that has higher connectivity than previous annealers, and on multiple embedded problem classes, we are able to confirm various aspects of this picture. We demonstrate the robustness of the optimal pause parameters across platforms and problem classes, explore how to set |JF| to optimize performance in different scenarios, and provide empirical evidence that short pauses trump longer overall annealing times in time to solution. We also identify the number of different coefficients in a problem as a predictor of problem hardness, and explore its interplay with the optimal |JF| and embedding size. Based on these results we are able to present qualitative guidelines for parameter setting in quantum annealers.

关键词： Adiabatic quantum optimization Magnetic coupling Quantum algorithms Quantum benchmarking Quantum networks Wireless communication networks Graph theory Spin chains

来源：评论

学校读者我要写书评

暂无评论

MR2CPPIS: Accurate prediction of protein–protein interaction sites based on multi-scale Res2Net with coordinate attention mechanism

引用

computers in Biology and Medicine 2024年 176卷 108543-108543页

作者： Gong, Yinyin Li, Rui Liu, Yan Wang, Jilong Cao, Buwen Fu, Xiangzheng Li, Renfa Chen, Danny Z. College of Computer Science and Electronic Engineering Hunan University Changsha410082 China Hunan Engineering Research Center of Advanced Embedded Computing and Intelligent Medical Systems Hunan University Changsha410082 China Peng Cheng Laboratory Shenzhen518066 China College of Information and Electronic Engineering Hunan City University Yiyang413002 China Department of Computer Science and Engineering University of Notre Dame Notre DameIN46556 United States

Proteins play a vital role in various biological processes and achieve their functions through protein–protein interactions (PPIs). Thus, accurate identification of PPI sites is essential. Traditional biological methods for identifying PPIs are costly, labor-intensive, and time-consuming. The development of computational prediction methods for PPI sites offers promising alternatives. Most known deep learning (DL) methods employ layer-wise multi-scale CNNs to extract features from protein sequences. But, these methods usually neglect the spatial positions and hierarchical information embedded within protein sequences, which are actually crucial for PPI site prediction. In this paper, we propose MR2CPPIS, a novel sequence-based DL model that utilizes the multi-scale Res2Net with coordinate attention mechanism to exploit multi-scale features and enhance PPI site prediction capability. We leverage the multi-scale Res2Net to expand the receptive field for each network layer, thus capturing multi-scale information of protein sequences at a granular level. To further explore the local contextual features of each target residue, we employ a coordinate attention block to characterize the precise spatial position information, enabling the network to effectively extract long-range dependencies. We evaluate our MR2CPPIS on three public benchmark datasets (Dset 72, Dset 186, and PDBset 164), achieving state-of-the-art performance. The source codes are available at https://***/YyinGong/MR2CPPIS. © 2024 Elsevier Ltd

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

High Hospitalization Rates and Risk Factors Among Frail Patients With Cirrhosis: A 10-year Population-based Cohort Study

引用

Clinical Gastroenterology and Hepatology 2025年第7期23卷 1152-1163页

作者： Hasjim, Bima J. Mohammadi, Mohsen Balbale, Salva N. Paukner, Mitchell Banea, Therese Shi, Haoyan Furmanchuk, Al'ona VanWagner, Lisa B. Zhao, Lihui Duarte-Rojo, Andres Doll, Julianna Mehrotra, Sanjay Ladner, Daniela P. Northwestern University Transplant Outcomes Research Collaborative (NUTORC) Comprehensive Transplant Center (CTC) Northwestern University Chicago Illinois United States Center for Engineering and Health McCormick School of Engineering and Applied Science Northwestern University Chicago Illinois United States Department of Industrial Engineering and Management Sciences McCormick School of Engineering Northwestern University Evanston IL United States Division of Gastroenterology and Hepatology Department of Medicine Northwestern University Feinberg School of Medicine Chicago Illinois United States Center for Health Services and Outcomes Research Institute of Public Health and Medicine & Northwestern Quality Improvement Research & Education in Surgery (NQUIRES) Department of Surgery Northwestern University Feinberg School of Medicine Chicago Illinois United States Center of Innovation for Complex Chronic Healthcare (CINCCH) Edward Hines Jr. VA Hospital Hines IL United States Division of Biostatistics Department of Preventive Medicine Northwestern University Feinberg School of Medicine Chicago Illinois United States Department of Mathematics Northwestern University Evanston IL United States Department of Computer Science McCormick School of Engineering Northwestern University Evanston IL United States Department of General Internal Medicine Feinberg School of Medicine Northwestern University Chicago Illinois United States Division of Digestive and Liver Diseases Department of Medicine University of Texas Southwestern Medical Center Dallas Texas United States Division of Transplantation Department of Surgery Northwestern University Feinberg School of Medicine Chicago Illinois United States

Background & Aims: Cirrhosis-related inpatient hospitalizations have increased dramatically over the past decade. We used a longitudinal dataset capturing a large metropolitan area in the United States from 2011 to 2021 to evaluate contemporary hospitalization rates and risk factors among frail patients with cirrhosis. Methods: We conducted a retrospective, longitudinal cohort study using the Chicago Area Patient-centered Outcomes research Network (CAPriCORN) database, an electronic health record repository that aggregates de-duplicated data across 7 health care systems in the Chicago metropolitan area, from 2011 to 2021. The primary outcome of our study was the rate of hospitalization encounters. Frailty was defined by the Hospital Frailty Risk Score. Hospitalization rates were reported per 100 patients per year, and a multivariable logistic regression analysis identified predictors of annual hospitalization probability. Results: During the study period, of 36,971 patients, 16,265 patients (44%) were hospitalized (compensated, 18.4%;decompensated, 81.6%). Hospitalization rates were highest in patients with decompensated cirrhosis, reaching nearly 77.3 hospitalizations/100 patients per year. Hospitalization rates among patients with compensated cirrhosis were also high (14.2 vs 77.3 hospitalization/100 patients per year), with odds of annual hospitalization 3 times (odds ratio, 3.1;95% confidence interval, 2.9-3.4) as high among compensated patients with intermediate frailty and 5 times (odds ratio, 5.2;95% confidence interval, 4.5-6.0) as high among those with severe frailty (compared with compensated patients with low frailty). Conclusion: Compensated and decompensated cirrhosis patients with intermediate to severe frailty face a substantially increased odds of annual hospitalizations compared with those with low frailty. Future work should focus on targeted interventions to incorporate routine frailty screenings into cirrhosis care and to ultimately minimize high

关键词： Cirrhosis Frailty Hospitalizations

来源：评论

学校读者我要写书评

暂无评论

Special Issue on Artificial Intelligence for Synthetic Biology

引用

ACS SYNTHETIC BIOLOGY 2024年第2期13卷 408-410页

作者： Martin, Hector Garcia Mazurenko, Stanislav Zhao, Huimin Biological Systems and Engineering Division Lawrence Berkeley National Laboratory Berkeley California 94720 United States BCAM − Basque Center for Applied Mathematics Bilbao 48009 Spain DOE Agile BioFoundry Emeryville California 94608 United States DOE Joint BioEnergy Institute Emeryville California 94608 United States Loschmidt Laboratories Department of Experimental Biology and RECETOX Faculty of Science Masaryk University Kamenice 5 625 00 Brno Czech Republic International Clinical Research Center St. Anne’s University Hospital Brno Pekarska 53 656 91 Brno Czech Republic Department of Chemical and Biomolecular Engineering University of Illinois at Urbana−Champaign Urbana Illinois 61801 United States

来源：评论

学校读者我要写书评

暂无评论

Bilateral Contract for Load Frequency and Renewable Energy Sources Using advanced Controller

引用

computers, Materials & Continua 2022年第11期73卷 3165-3180页

作者： Krishan Arora Gyanendra Prasad Joshi Mahmoud Ragab Muhyaddin Rawa Ahmad H.Milyani Romany F.Mansour Eunmok Yang School of Electronics and Electrical Engineering Lovely Professional UniversityPhagwara144001PunjabIndia School of Department of Computer Science and Engineering Sejong UniversitySeoul05006Korea Information Technology Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Centre for Artificial Intelligence in Precision Medicines King Abdulaziz UniversityJeddah21589Saudi Arabia Mathematics Department Faculty of ScienceAl-Azhar UniversityNaser City11884CairoEgypt Center of Research Excellence in Renewable Energy and Power Systems King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Electrical and Computer Engineering Faculty of EngineeringKing Abdulaziz UniversityJeddah21589Saudi Arabia King Abdullah City for Atomic and Renewable Energy(K.A.CARE) RiyadhSaudi Arabia Department of Mathematics Faculty of ScienceNew Valley UniversityEl-Kharga72511Egypt Department of Information Security Cryptologyand MathematicsKookmin UniversitySeoul02707Korea

Reestablishment in power system brings in significant transformation in the power sector by extinguishing the possession of sound consolidated ***,the collaboration of various manufacturing agencies,autonomous power manufacturers,and buyers have created complex installation *** regular active load and inefficiency of best measures among varied associates is a huge *** sudden load deviation will give rise to immediate amendment in frequency and tie-line power *** is essential to deal with every zone’s frequency and tie-line power within permitted confines followed by fluctuations within the ***,it can be proficient by implementing Load Frequency Control under the Bilateral case,stabilizing the power and frequency distinction within the interrelated power *** the net deviation in multiple areas is possible by minimizing the unbalance of Bilateral Contracts with the help of proportional integral and advanced controllers like Harris Hawks *** proposed the advanced controller Harris Hawk optimizer-based model and validated it on a test *** experiment results show that the delay time is 0.0029 s and the settling time of 20.86 s *** model can also be leveraged to examine the decision boundaries of the Bilateral case.

关键词： Bilateral contract load frequency control optimization harris hawks optimizer

来源：评论

学校读者我要写书评

暂无评论

Enabling technology and core theory of synthetic biology

引用

science China(Life sciences) 2023年第8期66卷 1742-1785页

作者： Xian-En Zhang Chenli Liu Junbiao Dai Yingjin Yuan Caixia Gao Yan Feng Bian Wu Ping Wei Chun You Xiaowo Wang Tong Si Faculty of Synthetic Biology Shenzhen Institute of Advanced TechnologyShenzhen 518055China Institute of Synthetic Biology Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China National Laboratory of Biomacromolecules Institute of BiophysicsChinese Academy of SciencesBeijing 100101China Frontiers Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering(Ministry of Education) School of Chemical Engineering and TechnologyTianjin UniversityTianjin 300072China State Key Laboratory of Plant Cell and Chromosome Engineering Institute of Genetics and Developmental BiologyChinese Academy of SciencesBeijing 100101China State Key Laboratory of Microbial Metabolism Shanghai Jiao Tong UniversityShanghai 200240China State Key Laboratory of Microbial Resources Institute of MicrobiologyChinese Academy of SciencesBeijing 100101China Tianjin Institute of Industrial Biotechnology Chinese Academy of SciencesTianjin 300308China Ministry of Education Key Laboratory of Bioinformatics Center for Synthetic and Systems BiologyBioinformatics DivisionBeijing National Research Center for Information Science and TechnologyDepartment of AutomationTsinghua UniversityBeijing 100084China

Synthetic biology provides a new paradigm for life science research(“build to learn”)and opens the future journey of biotechnology(“build to use”).Here,we discuss advances of various principles and technologies in the mainstream of the enabling technology of synthetic biology,including synthesis and assembly of a genome,DNA storage,gene editing,molecular evolution and de novo design of function proteins,cell and gene circuit engineering,cell-free synthetic biology,artificial intelligence(AI)-aided synthetic biology,as well as *** also introduce the concept of quantitative synthetic biology,which is guiding synthetic biology towards increased accuracy and predictability or the real rational *** conclude that synthetic biology will establish its disciplinary system with the iterative development of enabling technologies and the maturity of the core theory.

关键词： synthetic biology quantitative synthetic biology genome synthesis and assembly DNA storage molecular evolution de novo design computer-aided design cell engineering gene circuit chassis cell artificial intelligent(AI) biofoundry

来源：评论

学校读者我要写书评

暂无评论

A hybrid FEM-PINN method for time-dependent partial differential equations

arXiv

引用

arXiv 2024年

作者： Feng, Xiaodong Shangguan, Haojiong Tang, Tao Wan, Xiaoliang Zhou, Tao Division of Science and Technology BNU-HKBU United International College Zhuhai519087 China School of Electrical and Computer Engineering Guangzhou Nanfang College Guangzhou510970 China Department of Mathematics Center for Computation and Technology Louisiana State University Baton Rouge70803 United States Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing China

In this work, we present a hybrid numerical method for solving evolution partial differential equations (PDEs) by merging the time finite element method with deep neural networks. In contrast to the conventional deep learning-based formulation where the neural network is defined on a spatiotemporal domain, our methodology utilizes finite element basis functions in the time direction where the space-dependent coefficients are defined as the output of a neural network. We then apply the Galerkin or collocation projection in the time direction to obtain a system of PDEs for the space-dependent coefficients which is approximated in the framework of PINN. The advantages of such a hybrid formulation are twofold: statistical errors are avoided for the integral in the time direction, and the neural network’s output can be regarded as a set of reduced spatial basis functions. To further alleviate the difficulties from high dimensionality and low regularity, we have developed an adaptive sampling strategy that refines the training set. More specifically, we use an explicit density model to approximate the distribution induced by the PDE residual and then augment the training set with new time-dependent random samples given by the learned density model. The effectiveness and efficiency of our proposed method have been demonstrated through a series of numerical experiments. © 2024, CC BY.

关键词： Partial differential equations

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：