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arXiv 2024年

作者： Jin, Qiangguo Huang, Jiapeng Sun, Changming Cui, Hui Xuan, Ping Su, Ran Wei, Leyi Wu, Yu-Jie Wu, Chia-An Duh, Henry B.L. Lu, Yueh-Hsun School of Software Northwestern Polytechnical University Shaanxi China Yangtze River Delta Research Institute of NPU Suzhou China CSIRO Data61 Sydney Australia Department of Computer Science and Information Technology La Trobe University Melbourne Australia School of Engineering Shantou University Guangdong China College of Intelligence and Computing Tianjin University Tianjin China School of Information Xiamen University Xiamen China AIDD Faculty of Applied Science Macao Polytechnic University China Department of Radiology Shuang-Ho Hospital Taipei Medical University Taipei Taiwan Master of Public Health Program National Yang Ming Chiao Tung University Taipei Taiwan School of Design The Hong Kong Polytechnic University Hong Kong Department of Radiology School of Medicine College of Medicine Taipei Medical University Taipei Taiwan

The precise diagnosis of urinary stones is crucial for devising effective treatment strategies. The diagnostic process, however, is often complicated by the low contrast between stones and surrounding tissues, as well as the variability in stone locations across different patients. To address this issue, we propose a novel location embedding based pairwise distance learning network (LEPD-Net) that leverages low-dose abdominal X-ray imaging combined with location information for the fine-grained diagnosis of urinary stones. LEPD-Net enhances the representation of stone-related features through context-aware region enhancement, incorporates critical location knowledge via stone location embedding, and achieves recognition of fine-grained objects with our innovative fine-grained pairwise distance learning. Additionally, we have established an in-house dataset on urinary tract stones to demonstrate the effectiveness of our proposed approach. Comprehensive experiments conducted on this dataset reveal that our framework significantly surpasses existing state-of-the-art methods. Copyright © 2024, The Authors. All rights reserved.

关键词： Embeddings

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A Mechanism for Verifying the Integrity and Immutability of Tuberculosis Data sing IOTA Distributed Ledger Technology 15

A Mechanism for Verifying the Integrity and Immutability of ...

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15th Annual Conference on Health Informatics meets Digital Health, dHealth 2021

作者： Lima, Vinícius Bernardi, Filipe Rijo, Rui Ueyama, Jó Alves, Domingos Ribeirão Preto Medical School University of São Paulo Ribeirão Preto Brazil Bioengineering Postgraduate Program São Carlos School of Engineering University of São Paulo São Carlos Brazil School of Technology and Management Polytechnic Institute of Leiria Leiria Portugal Institute of Mathematical and Computer Sciences University of São Paulo São Carlos Brazil Department of Social Medicine Ribeirão Preto Medical School University of São Paulo Ribeirão Preto Brazil

ISBN: (纸本)9781643681801

Background: Intensified research and innovation and rapid uptake of new tools, interventions, and strategies are crucial to fight Tuberculosis, the world's deadliest infectious disease. The sharing of health data remains a significant challenge. Data consumers must be able to verify the consistency and integrity of data. Solutions based on distributed ledger technologies may be adequate, where each member in a network holds a unique credential and stores an identical copy of the ledger and contributes to the collective process of validating and certifying digital transactions. Objectives: This work proposes a mechanism and presents a use case in Digital Health to allow the verification of integrity and immutability of TB electronic health records. Methods: IOTA was selected as a supporting tool due to its data immutability, traceability and tamper-proof characteristics. Results: A mechanism to verify the integrity of data through hash functions and the IOTA network is proposed. Then, a set of TB related information systems was integrated with the network. Conclusion: IOTA technology offers performance and flexibility to enable a reliable environment for electronic health records. © 2021 The authors, AIT Austrian Institute of Technology and IOS Press.

关键词： Disease control

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Instruction Multi-Constraint Molecular Generation Using a Teacher-Student Large Language Model

arXiv

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arXiv 2024年

作者： Zhou, Peng Wang, Jianmin Li, Chunyan Wang, Zixu Liu, Yiping Sun, Siqi Lin, Jianxin Wei, Leyi Cai, Xibao Lai, Houtim Liu, Wei Wang, Longyue Liu, Yuansheng Zeng, Xiangxiang College of Information Science and Engineering Hunan University Changsha China The Interdisciplinary Graduate Program in Integrative Biotechnology Yonsei University Incheon21983 Korea Republic of School of Informatics Yunnan Normal University Kunming650500 China Department of Computer Science University of Tsukuba Tsukuba3058577 Japan Research Institute of Intelligent Complex Systems Fudan University Shanghai200433 China Shanghai AI Laboratory Shanghai200232 China Centre for Artificial Intelligence driven Drug Discovery Faculty of Applied Science Macao Polytechnic University China School of Informatics Xiamen University Xiamen China Tencent AI Lab China

While various models and computational tools have been proposed for structure and property analysis of molecules, generating molecules that conform to all desired structures and properties remains a challenge. Here, we introduce a multi-constraint molecular generation large language model, TSMMG, which, akin to a student, incorporates knowledge from various small models and tools, namely, the 'teachers'. To train TSMMG, we construct a large set of text-molecule pairs by extracting molecular knowledge from these 'teachers', enabling it to generate novel molecules that conform to the descriptions through various text prompts. We experimentally show that TSMMG remarkably performs in generating molecules meeting complex, natural language-described property requirements across two-, three-, and four-constraint tasks, with an average molecular validity of over 99% and success ratio of 82.58%, 68.03%, and 67.48%, respectively. The model also exhibits adaptability through zero-shot testing, creating molecules that satisfy combinations of properties that have not been encountered. It can comprehend text inputs with various language styles, extending beyond the confines of outlined prompts, as confirmed through empirical validation. Additionally, the knowledge distillation feature of TSMMG contributes to the continuous enhancement of small models, while the innovative approach to dataset construction effectively addresses the issues of data scarcity and quality, which positions TSMMG as a promising tool in the domains of drug discovery and materials science. Copyright © 2024, The Authors. All rights reserved.

关键词： Students

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Technology Roadmap for Flexible Sensors

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ACS NANO 2023年第6期17卷 5211-5295页

作者： Luo, Yifei Abidian, Mohammad Reza Ahn, Jong-Hyun Akinwande, Deji Andrews, Anne M. Antonietti, Markus Bao, Zhenan Berggren, Magnus Berkey, Christopher A. Bettinger, Christopher John Chen, Jun Chen, Peng Cheng, Wenlong Cheng, Xu Choi, Seon-Jin Chortos, Alex Dagdeviren, Canan Dauskardt, Reinhold H. Di, Chong-an Dickey, Michael D. Duan, Xiangfeng Facchetti, Antonio Fan, Zhiyong Fang, Yin Feng, Jianyou Feng, Xue Gao, Huajian Gao, Wei Gong, Xiwen Guo, Chuan Fei Guo, Xiaojun Hartel, Martin C. He, Zihan Ho, John S. Hu, Youfan Huang, Qiyao Huang, Yu Huo, Fengwei Hussain, Muhammad M. Javey, Ali Jeong, Unyong Jiang, Chen Jiang, Xingyu Kang, Jiheong Karnaushenko, Daniil Khademhosseini, Ali Kim, Dae-Hyeong Kim, Il-Doo Kireev, Dmitry Kong, Lingxuan Lee, Chengkuo Lee, Nae-Eung Lee, Pooi See Lee, Tae-Woo Li, Fengyu Li, Jinxing Liang, Cuiyuan Lim, Chwee Teck Lin, Yuanjing Lipomi, Darren J. Liu, Jia Liu, Kai Liu, Nan Liu, Ren Liu, Yuxin Liu, Yuxuan Liu, Zhiyuan Liu, Zhuangjian Loh, Xian Jun Lu, Nanshu Lv, Zhisheng Magdassi, Shlomo Malliaras, George G. Matsuhisa, Naoji Nathan, Arokia Niu, Simiao Pan, Jieming Pang, Changhyun Pei, Qibing Peng, Huisheng Qi, Dianpeng Ren, Huaying Rogers, John A. Rowe, Aaron Schmidt, Oliver G. Sekitani, Tsuyoshi Seo, Dae-Gyo Shen, Guozhen Sheng, Xing Shi, Qiongfeng Someya, Takao Song, Yanlin Stavrinidou, Eleni Su, Meng Sun, Xuemei Takei, Kuniharu Tao, Xiao-Ming Tee, Benjamin C. K. Thean, Aaron Voon-Yew Trung, Tran Quang Wan, Changjin Wang, Huiliang Wang, Joseph Wang, Ming Wang, Sihong Wang, Ting Wang, Zhong Lin Weiss, Paul S. Wen, Hanqi Xu, Sheng Xu, Tailin Yan, Hongping Yan, Xuzhou Yang, Hui Yang, Le Yang, Shuaijian Yin, Lan Yu, Cunjiang Yu, Guihua Yu, Jing Yu, Shu-Hong Yu, Xinge Zamburg, Evgeny Zhang, Haixia Zhang, Xiangyu Zhang, Xiaosheng Zhang, Xueji Zhang, Yihui Zhang, Yu Zhao, Siyuan Zhao, Xuanhe Zheng, Yuanjin Zheng, Yu-Qing Zheng, Zijian Zhou, Tao Zhu, Bowen Zhu, Ming Zhu, Rong Zhu, Yangzhi Zhu, Yong Zou, Guijin Chen, Xiaodong 08-03 Innovis Singapore 138634 Republic of Singapore Innovative Centre for Flexible Devices (iFLEX) School of Materials Science and Engineering Nanyang Technological University Singapore 639798 Singapore Department of Biomedical Engineering University of Houston Houston Texas 77024 United States School of Electrical and Electronic Engineering Yonsei University Seoul 03722 Republic of Korea Department of Electrical and Computer Engineering The University of Texas at Austin Austin Texas 78712 United States Microelectronics Research Center The University of Texas at Austin Austin Texas 78758 United States Department of Chemistry and Biochemistry California NanoSystems Institute and Department of Psychiatry and Biobehavioral Sciences Semel Institute for Neuroscience and Human Behavior and Hatos Center for Neuropharmacology University of California Los Angeles Los Angeles California 90095 United States Colloid Chemistry Department Max Planck Institute of Colloids and Interfaces 14476 Potsdam Germany Department of Chemical Engineering Stanford University Stanford California 94305 United States Laboratory of Organic Electronics Department of Science and Technology Campus Norrköping Linköping University 83 Linköping Sweden Wallenberg Initiative Materials Science for Sustainability (WISE) and Wallenberg Wood Science Center (WWSC) SE-100 44 Stockholm Sweden Department of Materials Science and Engineering Stanford University Stanford California 94301 United States Department of Biomedical Engineering and Department of Materials Science and Engineering Carnegie Mellon University Pittsburgh Pennsylvania 15213 United States Department of Bioengineering University of California Los Angeles Los Angeles California 90095 United States School of Chemistry Chemical Engineering and Biotechnology Nanyang Technological University Singapore 637457 Singapore Nanobionics Group Department of Chemical and Biological Engineering Monash University Clayton Australia 3800 Monash

Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze continued...challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative

关键词： soft materials mechanics engineering flexible electronics conformable sensors bioelectronics human-machine interfaces body area sensor networks technology translation sustainable electronics

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Influence of submerged arc welding slag content variation on cementitious materials: A sustainable alternative

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Construction and Building Materials 2025年 483卷

作者： Castro-Lopes, S. Rodrigues, V.D. Marden, Sandro Peña-Garcia, R. Padrón-Hernández, E. Berenguer, Romildo Federal Institute of Education Science and Technology of Pará PA Altamira Brazil Laboratory of Composite Materials and Structural Integrity Corrosion and Biocorrosion - CompoLab/LBC Federal University of Pernambuco PE Recife Brazil Federal University of Paraiba Department of Mechanical Engineering PB Joao Pessoa Brazil Federal Rural University of Pernambuco Postgraduate Program in Physics Engineering Academic Unit of Cabo de Santo Agostinho Cabo de Santo PE Agostinho Brazil Federal University of Pernambuco Department of Physics PE Recife Brazil Polytechnic School University of Pernambuco PE Recife Brazil Federal University of Pernambuco Department of Mechanical Engineering PE Recife Brazil

This study evaluates the effects of submerged arc welding (SAW) slag as a partial replacement for Portland cement in cementitious materials. Cement pastes with 5 %, 10 %, 15 %, 20 %, 25 %, and 30 % SAW slag were tested for compressive strength, tensile strength, carbonation resistance, phase formation, and environmental impact. The results revealed that up to 10 % SAW slag significantly enhanced compressive strength, with the 5 % replacement showing a 20.10 % increase in strength at 28 days compared to the control. The mechanical improvement was attributed to the formation of the CSH phase, which was confirmed by X-ray diffraction (XRD) and thermogravimetric analysis (TGA). Carbonation tests indicated that the 5 % SAW samples reduced carbonation by 5 % compared to the control, while the 10 % SAW samples showed a 1 % reduction. This suggests that SAW slag enhances the resistance of cementitious materials to CO2 attack, improving long-term durability. XRD analysis also identified an increase in amorphous phases in the SAW samples, particularly in the 5 % addition, further supporting the pozzolanic activity of SAW slag. Pozzolanic effectiveness coefficient analysis revealed synergistic effects for SAW slag blends, with optimal performance observed at 5 % replacement, in line with microstructural evidence of enhanced CSH gel formation. Environmental analysis demonstrated that replacing 10 % of Portland cement with SAW slag could reduce CO2 emissions by approximately 4564 kg annually, while a 15 % replacement could lead to a reduction of 6846 kg of CO2. These results underscore the potential of SAW slag as a sustainable and performance-enhancing alternative to conventional cement in concrete production. © 2025 Elsevier Ltd

关键词： Compressive strength

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Finding shortest and nearly shortest path nodes in large substantially incomplete networks

arXiv

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arXiv 2022年

作者： Kitsak, Maksim Ganin, Alexander Elmokashfi, Ahmed Cui, Hongzhu Eisenberg, Daniel A. Alderson, David L. Korkin, Dmitry Linkov, Igor Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft Netherlands Network Science Institute Northeastern University BostonMA02115 United States Department of Systems and Information Engineering University of Virginia CharlottesvilleVA22904 United States U.S. Army Engineer Research and Development Center Contractor Concord MA01742 United States Simula Metropolitan Center for Digital Engineering Oslo Norway Bioinformatics and Computational Biology Program Worcester Polytechnic Institute WorcesterMA01609 United States Institute for Genomic Medicine Columbia University Medical Center New YorkNY United States Operations Research Department Naval Postgraduate School MontereyCA93943 United States Data Science Program Worcester Polytechnic Institute WorcesterMA01609 United States Computer Science Department Worcester Polytechnic Institute WorcesterMA01609 United States U.S. Army Engineer Research and Development Center Environmental Laboratory Concord MA01742 United States

Dynamic processes on networks, be it information transfer in the Internet, contagious spreading in a social network, or neural signaling, take place along shortest or nearly shortest paths. Unfortunately, our maps of most large networks are substantially incomplete due to either the highly dynamic nature of networks, or high cost of network measurements, or both, rendering traditional path finding methods inefficient. We find that shortest paths in large real networks, such as the network of protein-protein interactions (PPI) and the Internet at the autonomous system (AS) level, are not random but are organized according to latent-geometric rules. If nodes of these networks are mapped to points in latent hyperbolic spaces, shortest paths in them align along geodesic curves connecting endpoint nodes. We find that this alignment is sufficiently strong to allow for the identification of shortest path nodes even in the case of substantially incomplete networks. We demonstrate the utility of latent-geometric path finding in problems of cellular pathway reconstruction and communication security. Copyright © 2022, The Authors. All rights reserved.

关键词： Proteins

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REPEAT ANALYSIS program AS A QUALITY ASSURANCE SYSTEM FOR RADIOLOGY MANAGEMENT: CAUSAL REPEAT AND AN OVERVIEW

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Journal of Medical Imaging and Radiation sciences 2023年第3期54卷 S31-S31页

作者： Rochmayanti, Dwi Adi, Kusworo Widodo, Catur Edi Doctoral Program of Information System School of Postgraduate Diponegoro University Department of Radiodiagnostic and Radiotherapy Engineering Health Polytechnic Ministry of Health Semarang Central Java Department of Physics Faculty of Science and Mathematics Diponegoro University

OBJECTIVEThis paper aims to describe the image retakes program over several decades, and identify the causes of issues due to rejection rates. MATERIALS & METHODSThis study is a literature review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method. Articles were searched from Google Scholar (3140) and Scopus (18) using keywords " Reject" or " Repeat" or " Retakes" and " Analysis" and " in" and " Diagnostic" and " Imaging". The article range was expanded to describe the profile of repeat analysis from the use of film-screen to digital transformation systems. Based on the established criteria, 20 articles were extracted and analyzed. RESULTSFrom the literature, it was found that repeat rates above 5% were still found in some examination categories, with chest radiography contributing the highest rejection rate, reaching 51.67%, with the biggest contributing factor being positioning (84.8%). There are interesting findings related to this program, where subjective factors in determining the classification of rejection causes still exist. One study mentioned that AI can predict image rejection accuracy with a sensitivity of 93%. Therefore, the use of AI can be very helpful in classifying rejection causes, making data available for more efficient and easier radiology management. CONCLUSIONRepeat program is part of image quality management. The justification for rejection decisions still poses a challenge related to personnel's subjective factors and determining the causes of rejection/repeat must also be done to obtain concrete data related to radiography performance.

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Wireless-Powered UAV assisted Communication System in Nakagami-m Fading Channels 17

Wireless-Powered UAV assisted Communication System in Nakaga...

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17th IEEE Annual Consumer Communications and Networking Conference, CCNC 2020

作者： Ponnimbaduge Perera, Tharindu D. Jayakody, Dushantha Nalin K. Garg, Sahil Kumar, Neeraj Cheng, Ling School of Computer Science and Robotics National Research Tomsk Polytechnic University Russia School of Postgraduate Studies Research Sri Lanka Technological Campus Padukka Sri Lanka Ecole de Technologie Supérieure Electrical Engineering Department MontrealQCH3C 1K3 Canada Thapar Institute of Engineering and Technology Department of Computer Science and Engineering India School of Electrical and Information Engineering University of the Witwatersrand South Africa

ISBN: (纸本)9781728138930

Recently, the use of unmanned aerial vehicles (UAVs) as a relay node has been envisaged as an enabling technology in the upcoming wireless communication era. Thus, in this paper, we consider a full-duplex (FD) cooperative communication system with a source and a destination, where UAV serves as a mobile relay. Here, the transmission power cost is debited to energy harvested using simultaneous wireless information and power transfer (SWIPT) and self-interference energy harvesting (EH) via power-splitting (PS) protocol. In poor channel conditions, UAV uses a soft angular modulation scheme to perceive the soft information. In this proposed system, we present the outage probability over the Nakagami-m fading channels. A closed-form solution for the outage probability is derived. In addition, we formulate an optimization problem to minimize end-to-end outage probability subject of the UAV's power profile. The KKT conditions have been used to obtain a closed-form solution of the proposed optimization problem. Finally, numerical results are provided to evaluate the proposed system under various setups. © 2020 IEEE.

关键词： Cooperative communication

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Norepinephrine changes behavioral state through astroglial purinergic signaling

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science (New York, N.Y.) 2025年第6748期388卷 769-775页

作者： Chen, Alex B. Duque, Marc Rymbek, Altyn Dhanasekar, Mahalakshmi Wang, Vickie M. Mi, Xuelong Tocquer, Loeva Narayan, Sujatha Legorreta, Emmanuel Marquez Eddison, Mark Yu, Guoqiang Wyart, Claire Prober, David A. Engert, Florian Ahrens, Misha B. Howard Hughes Medical Institute Janelia Research Campus Ashburn VA United States Department of Molecular and Cellular Biology Harvard University Cambridge MA United States Graduate Program in Neuroscience Harvard Medical School Boston MA United States Tianqiao and Chrissy Chen Institute for Neuroscience Division of Biology and Biological Engineering California Institute of Technology Pasadena CA United States Sorbonne Université Paris Brain Institute (Institut du Cerveau Institut National de la Santé et de la Recherche Médicale U1127 Centre National de la Recherche Scientifique Unité Mixte de Recherche 7225 Assistance Publique-Hôpitaux de Paris Campus Hospitalier Pitié-Salpêtrière Paris France Bradley Department of Electrical and Computer Engineering Virginia Polytechnic Institute and State University Arlington VA United States Present address: Allen Institute for Brain Science Seattle WA United States Department of Automation Tsinghua University Beijing China

Both neurons and glia communicate through diffusible neuromodulators;however, how neuron-glial interactions in such neuromodulatory networks influence circuit computation and behavior is unclear. During futility-induced behavioral transitions in the larval zebrafish, the neuromodulator norepinephrine (NE) drives fast excitation and delayed inhibition of behavior and circuit activity. We found that astroglial purinergic signaling implements the inhibitory arm of this motif. In larval zebrafish, NE triggers astroglial release of adenosine triphosphate (ATP), extracellular conversion of ATP into adenosine, and behavioral suppression through activation of hindbrain neuronal adenosine receptors. Our results suggest a computational and behavioral role for an evolutionarily conserved astroglial purinergic signaling axis in NE-mediated behavioral and brain state transitions and position astroglia as important effectors in neuromodulatory signaling.

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Developing Combat Behavior through Reinforcement Learning in Wargames and Simulations

Developing Combat Behavior through Reinforcement Learning in...

引用

IEEE Symposium on Computational Intelligence and Games, CIG

作者： Jonathan Boron Chris Darken MAGTF Staff Training Program United States Marine Corps Quantico USA Computer Science Naval Postgraduate School Monterey USA

ISBN: (数字)9781728145334

ISBN: (纸本)9781728145341

Progress in artificial intelligence (AI), particularly deep reinforcement learning (RL), has produced systems capable of performing at or above a professional-human level. This research explored the ability of RL to train AI agents to achieve optimal offensive behavior in small tactical engagements. Agents were trained in a simple, aggregate-level military constructive simulation with behaviors validated with the tactical principles of mass and economy of force. Results showed the combat model and RL algorithm applied had the largest impact on training performance. Additionally, specific training hyper-parameters also contributed to the quality and type of observed behaviors. Future work will seek to validate RL performance in larger and more complex combat scenarios.

关键词： Force Training Mathematical model Companies Stochastic processes Spinning Neural networks

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