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Paradoxical roles of inhibitory autapse and excitatory synapse in formation of counterintuitive anticipated synchronization

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Chinese Physics B 2023年第8期32卷 499-509页

作者：丁学利古华光李玉叶贾雁兵 Department of Public Basic Education Fuyang Institute of TechnologyFuyang 236031China School of Aerospace Engineering and Applied Mechanics Tongji UniversityShanghai 200092China College of Mathematics and Computer Science Chifeng UniversityChifeng 024000China School of Mathematics and Statistics Henan University of Science and TechnologyLuoyang 471000China

Different from the common delayed synchronization(DS)in which response appears after stimulation,anticipated synchronization(AS)in unidirectionally coupled neurons denotes a counterintuitive phenomenon in which response of the receiver neuron appears before stimulation of the sender neuron,showing an interesting function of brain to anticipate the *** dynamical mechanism for the AS remains unclear due to complex dynamics of inhibitory and excitatory *** this article,the paradoxical roles of excitatory synapse and inhibitory autapse in the formation of AS are ***,in addition to the common roles such that inhibitory modulation delays and excitatory modulation advances spike,paradoxical roles of excitatory stimulation to delay spike via type-II phase response and of inhibitory autapse to advance spike are obtained in suitable parameter regions,extending the dynamics and functions of the excitatory and inhibitory ***,AS is related to the paradoxical roles of the excitatory and inhibitory modulations,presenting deep understandings to the *** autapse induces spike of the receiver neuron advanced to appear before that of the sender neuron at first,and then excitatory synapse plays a delay role to prevent the spike further advanced,resulting in the AS as the advance and delay effects realize a dynamic ***,inhibitory autapse with strong advance,middle advance,and weak advance and delay effects induce phase drift(spike of the receiver neuron advances continuously),AS,and DS,respectively,presenting comprehensive relationships between AS and other *** results present potential measures to modulate AS related to brain function.

关键词： anticipated synchronization inhibitory autapse excitatory synapse paradoxical firing

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A Review on Air-Ground Coordination in Mobile Edge Computing:Key Technologies,Applications and Future Directions

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清华大学学报自然科学版（英文版） 2025年第3期30卷 1359-1386页

作者： Siqi Li Guoqiang Liu Li Li Zhongyuan Zhang Wenhao Fei Haolong Xiang School of Art Nanjing University of Information Science and TechnologyNanjing 210044China School of Software Nanjing University of Information Science and TechnologyNanjing 210044China College of Computer Science and Technology China University of Petroleum(East China)Qingdao 266555China School of Math and Applied Mathematics Nanjing University of Information Science and TechnologyNanjing 210044China

In recent years,Mobile Edge Computing(MEC)has received extensive research attention due to its characteristics,such as real-time data processing and flexible application ***,traditional MEC server deployment relies on the terrestrial Base Stations(BSs),resulting in high deployment costs and limited coverage *** response to these challenges,air-ground coordination has emerged,which effectively combines the advantages of edge computing and Unmanned Aerial Vehicles(UAVs),providing an effective architecture for edge *** utilizing the flexibility of UAVs and empowering them into edge nodes with computing resources,the coverage range of MEC can be expanded,thereby reducing the reliance of edge devices on terrestrial ***,leveraging terrestrial BSs as supplements to the computing power compensates for relatively limited computational capabilities of *** extensive studies have been conducted on air-ground coordination,there are few related summaries of application technologies and ***,the key technologies of air-ground coordination and applications are comprehensively reviewed in this ***,to provide guidance for interested researchers,the development trends and potential applications of air-ground coordination are explored.

关键词： air-ground coordination air-ground control air-ground perception emergency management resource management

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On picking sequences for chores 23

On picking sequences for chores

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24th ACM Conference on Economics and Computation, EC 2023

作者： Feige, Uriel Huang, Xin Computer Science and Applied Mathematics Weizmann Institute of Science Rehovot Israel Computer Science Technion - Israel Institute of Technology Haifa Israel

ISBN: (纸本)9798400701047

We consider the problem of allocating m indivisible chores to n agents with additive disvaluation (cost) functions. It is easy to show that there are picking sequences that give every agent (that uses the greedy picking strategy) a bundle of chores of disvalue at most twice her share value (maximin share, MMS, for agents of equal entitlement, and anyprice share, APS, for agents of arbitrary entitlement). Aziz, Li and Wu (2022) designed picking sequences that improve this ratio to 5/3 for the case of equal entitlement. We design picking sequences that improve the ratio to 1.733 for the case of arbitrary entitlement, and to 8/5 for the case of equal entitlement. (In fact, computer assisted analysis suggests that the ratio is smaller than 1.543 in the equal entitlement case.) We also prove a lower bound of 3/2 on the obtainable ratio when n is sufficiently *** results trivially imply that (for additive valuation over chores) in the arbitrary entitlement case, there always is an allocation that gives every agent at most 1.733APS, and in the equal entitlement case, there always is a distribution over allocations that gives every agent at most 1.6MMS ex-post, and at most the proportional share ex-ante. Neither of these implications were previously known to *** contributions of our work include improved guarantees in the equal entitlement case when n is small;introduction of the chore share as a convenient proxy to other share notions for chores;introduction of ex-ante notions of envy for risk averse agents, and enhancements to our picking sequences that eliminate such envy. © 2023 Owner/Author(s).

关键词： Additives

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Availability assessment of repairable linear consecutive k-out-of-n: F systems incorporating uncertainty and multiple failure modes

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Life Cycle Reliability and Safety Engineering 2025年 1-10页

作者： Khati, Amisha Singh, S.B. Department of Mathematics Statistics and Computer Science G. B. Pant University of Agriculture and Technology Pantnagar India Department of Applied Science and Humanities RIT Roorkee India

This study evaluates the interval-valued availability of a linear consecutive k-out-of-n: F system while considering uncertainty, where the probability that the system will perform as intended is not known with precision. The proposed system is susceptible to µ number of different failure modes and undergoes periodic inspections. Each failure mode has a randomly assigned failure time, and upon failure due to the mth failure mode, an immediate corrective repair is carried out, taking an arbitrary length of time ψm (m = 1, 2,…, µ). By integrating these factors, this research establishes theorems describing point and steady-state availability bounds. Subsequently, it conducts a sensitivity assessment to evaluate how variations in the inspection period affect the system’s availability. The findings are demonstrated with an instance of an oil pipeline system. This study offers valuable insights into the reliability and availability modelling of complex systems under uncertainty, with applications across diverse engineering domains. © The Author(s), under exclusive licence to Society for Reliability and Safety (SRESA) 2025.

关键词： Interval valued point availability Interval valued steady state availability Linear consecutive k-out-of n: F system Multiple failure modes Sensitivity analysis Uncertainty

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Reliability Investigation of BiCGStab and IDR Solvers for the Advection-Diffusion-Reaction Equation

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Communications in Computational Physics 2022年第6期32卷 156-188页

作者： Chris Schoutrop Jan ten Thije Boonkkamp Jan van Dijk Department of Applied Physics Eindhoven University of TechnologyThe Netherlands Department of Mathematics and Computer Science Eindhoven University of TechnologyThe Netherlands

The reliability of BiCGStab and IDR solvers for the exponential scheme discretization of the advection-diffusion-reaction equation is *** resulting discretization matrices have real *** consider BiCGStab,IDR(S),BiCGStab(L)and various modifications of BiCGStab,where S denotes the dimension of the shadow space and L the degree of the polynomial used in the polynomial *** implementations of BiCGStab exist which are equivalent in exact arithmetic,however,not in finite precision *** modifications of BiCGStab we consider are;choosing a random shadow vector,a reliable updating scheme,and storing the best intermediate *** is shown that the Local Minimal Residual algorithm,a method similar to the“minimize residual”step of BiCGStab,can be interpreted in terms of a time-dependent advection-diffusion-reaction equation with homogeneous Dirichlet boundary conditions for the residual,which plays a key role in the convergence *** to the real eigenvalues,the benefit of BiCGStab(L)compared to BiCGStab is shown to be modest in numerical ***-sparse(*** random)shadow residual turns out to be essential for the reliability of *** reliable updating scheme ensures the required tolerance is truly *** the best intermediate solution has no significant *** is to modify BiCGStab with a random shadow residual and the reliable updating scheme,especially in the regime of large P´eclet and small Damk¨ohler *** alternative option is IDR(S),which outperforms BiCGStab for problems with strong advection in terms of the number of matrix-vector *** MATLAB code used in the numerical experiments is available on GitLab:https://***/ChrisSchoutrop/krylov-adr,a C++implementation of IDR(S)is available in the Eigen linear algebra library:http://***.

关键词： BiCGStab IDR shadow residual advection-diffusion-reaction equation

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Epileptic seizure detection in EEG signals via an enhanced hybrid CNN with an integrated attention mechanism

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Mathematical Biosciences and Engineering 2025年第1期22卷 73-105页

作者： Mekruksavanich, Sakorn Phaphan, Wikanda Jitpattanakul, Anuchit Department of Computer Engineering School of Information and Communication Technology University of Phayao Phayao56000 Thailand Department of Applied Statistics Faculty of Applied Science King Mongkut’s University of Technology North Bangkok Bangkok10800 Thailand Department of Mathematics Faculty of Applied Science King Mongkut’s University of Technology North Bangkok Bangkok10800 Thailand Intelligent and Nonlinear Dynamic Innovations Research Center Science and Technology Research Institute King Mongkut’s University of Technology North Bangkok Bangkok10800 Thailand

Epileptic seizures, a prevalent neurological condition, necessitate precise and prompt identification for optimal care. Nevertheless, the intricate characteristics of electroencephalography (EEG) signals, noise, and the want for real-time analysis require enhancement in the creation of dependable detection approaches. Despite advances in machine learning and deep learning, capturing the intricate spatial and temporal patterns in EEG data remains challenging. This study introduced a novel deep learning framework combining a convolutional neural network (CNN), bidirectional gated recurrent unit (BiGRU), and convolutional block attention module (CBAM). The CNN extracts spatial features, the BiGRU captures long-term temporal dependencies, and the CBAM emphasizes critical spatial and temporal regions, creating a hybrid architecture optimized for EEG pattern recognition. Evaluation of a public EEG dataset revealed superior performance compared to existing methods. The model achieved 99.00% accuracy in binary classification, 96.20% in three-class tasks, 92.00% in four-class scenarios, and 89.00% in five-class classification. High sensitivity (89.00–99.00%) and specificity (89.63–99.00%) across all tasks highlighted the model’s robust ability to identify diverse EEG patterns. This approach supports healthcare professionals in diagnosing epileptic seizures accurately and promptly, improving patient outcomes and quality of life. © 2025 American Institute of Mathematical sciences. All rights reserved.

关键词： Electroencephalography

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Weed detection in precision agriculture: leveraging encoder-decoder models for semantic segmentation

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Journal of Ambient Intelligence and Humanized Computing 2024年第9期15卷 3547-3561页

作者： Thiagarajan, Shreya Vijayalakshmi, A. Grace, G. Hannah Shell India Markets Private Limited Chennai India School of Computer Science and Engineering Vellore Institute of Technology Chennai India Division of Mathematics School of Advanced Sciences Vellore Institute of Technology Chennai India

Precision agriculture uses data gathered from various sources to improve agricultural yields and the effectiveness of crop management techniques like fertiliser application, irrigation management, and pesticide application. Reduced usage of agrochemicals is a key step towards more sustainable agriculture. Weed management robots which can perform tasks like selective sprinkling or mechanical weed elimination, contribute to this objective. A trustworthy crop/weed classification system that can accurately recognise and classify crops and weeds is required for these robots to function. In this paper, we explore various deep learning models for achieving reliable segmentation results in less training time. We classify every pixel of the images into different categories using semantic segmentation models. The models are based on an encoder-decoder architecture, where feature maps are extracted during encoding and spatial information is recovered during decoding. We examine the segmentation output on a beans dataset containing different weeds, which were collected under highly distinct environmental conditions, including cloudy, rainy, dawn, evening, full sun, and shadow. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Semantic Segmentation

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Estimating Risk-aware Flexibility Areas for Electric Vehicle Charging Pools via AC Stochastic Optimal Power Flow

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Journal of Modern Power Systems and Clean Energy 2023年第4期11卷 1247-1256页

作者： Juan S.Giraldo Nataly Bañol Arias Pedro P.Vergara Maria Vlasiou Gerwin Hoogsteen Johann L.Hurink Energy Transition Studies Group Netherlands Organisation for Applied Scientific Research(TNO)Amsterdam1043 NTThe Netherlands Department of Electrical Engineering Mathematics and Computer ScienceUniversity of TwenteEnschede7522 NBThe Netherlands Intelligent Electrical Power Grids Group Electrical EngineeringMathematics and Computer ScienceDelft University of TechnologyDelft2628 CDThe Netherlands

This paper introduces an AC stochastic optimal power flow(SOPF)for the flexibility management of electric vehicle(EV)charging pools in distribution networks under *** AC SOPF considers discrete utility functions from charging pools as a compensation mechanism for eventual energy not served to their charging *** application of the AC SOPF is described where a distribution system operator(DSO)requires flexibility to each charging pool in a day-ahead time frame,minimizing the cost for flexibility while guaranteeing technical *** areas are defined for each charging pool and calculated as a function of a risk parameter involving the uncertainty of the *** show that all players can benefit from this approach,i.e.,the DSO obtains a riskaware solution,while charging pools/tasks perceive a reduction in the total energy payment due to flexibility services.

关键词： Electric vehicle flexibility management stochastic optimal power flow(SOPF) risk awareness compensation mechanism

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Leveraging Semantic Parsing using Text Embeddings and Reinforcement Learning

Leveraging Semantic Parsing using Text Embeddings and Reinfo...

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2024 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2024

作者： Piza-Londono, Jessenia Andrade-Lotero, Edgar J. Universidad Del Rosario Applied Mathematics and Computer Science Bogotá Colombia Universidad Del Rosario School of Engineering Science and Technology Bogotá Colombia

ISBN: (纸本)9798350374575

Representing natural language information is a key challenge in Artificial Intelligence and Cognitive science, requiring the transformation of unstructured data into formats suitable for computational tasks. While logical formalisms offer robust methods for information representation, their complexity often limits widespread adoption. Conversely, transformer architectures provide strong generalization capabilities but struggle with logical inference tasks. To address both the need for generalization and reliable logical inference, we propose a novel approach using deep reinforcement learning, enabling agents to autonomously learn the rules of semantic parsing. Our preliminary results indicate successful generation of appropriate representations for simple queries. Future work will extend the environment to handle a wider range of real-world sentences. © 2024 IEEE.

关键词： Deep reinforcement learning

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ANALYTICAL TIME-DEPENDENT DISTRIBUTIONS FOR GENE EXPRESSION MODELS WITH COMPLEX PROMOTER SWITCHING MECHANISMS

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Telecommunications and Radio Engineering (English translation of Elektrosvyaz and Radiotekhnika) 2023年第8期82卷 1572-1602页

作者： Jia, Chen Li, Youming Applied and Computational Mathematics Division Beijing Computational Science Research Center Beijing100193 China School of Mathematical Sciences University of Electronic Science and Technology of China Chengdu611731 China

Classical gene expression models assume exponential switching time distributions between the active and inactive promoter states. However, recent experiments have shown that many genes in mammalian cells may produce nonexponential switching time distributions, implying the existence of multiple promoter states and molecular memory in the promoter switching dynamics. Here we analytically solve a gene expression model with random bursting and complex promoter switching, and derive the time-dependent distributions of the mRNA and protein copy numbers, generalizing the steady-state solution obtained in [T. Zhou and J. Zhang, SIAM J. Appl. Math., 72 (2012), pp. 789-818] and [U. Herbach, SIAM J. Appl. Math., 79 (2019), pp. 1007-1029]. Using multiscale simplification techniques, we find that molecular memory has no influence on the time-dependent distribution when promoter switching is very fast or very slow, while it significantly affects the distribution when promoter switching is neither too fast nor too slow. By analyzing the dynamical phase diagram of the system, we also find that molecular memory in the inactive gene state weakens transient and stationary bimodality of the copy number distribution, while molecular memory in the active gene state enhances such bimodality. © 2023 Society for Industrial and applied mathematics.

关键词： Gene expression

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