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Cerebrospinal fluid proteomics reveals the innate immunity and blood-brain barrier dysregulation in a patient with multidrug-resistant Acinetobacter baumannii ventriculitis treated with intrathecal and intravenous polymyxin B

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Heliyon 2024年第24期10卷 e40893页

作者： Li, Mengyao Liu, Dongyu Bergen, Phillip J. Liang, Silin Chen, Juan Kho, Zhi Ying Lu, Jing Sun, Huiying Hong, Weiqing Liu, Xiaofen Hong, Chengying Chen, Youlian Li, Wei You, Hongxia Xu, Shunyao Wang, Yu Gao, Huaiji Lam, Chun Hin Li, Jian Chen, Xiaoyin Liu, Xueyan Department of Critical Care Medicine The Second Clinical Medical College Jinan University (Shenzhen People's Hospital) Shenzhen 518020 China Integrated Chinese and Western Medicine Postdoctoral Research Station Jinan University Guangzhou 510632 China Biomedicine Discovery Institute Infection Program and Department of Microbiology Monash University Melbourne 3800 VIC Australia Department of Pharmacy The Second Clinical Medical College Jinan University (Shenzhen People's Hospital) Shenzhen 518020 China Institute of Infectious Diseases The Second Hospital of Tianjin Medical University 23 Pingjiang Road Tianjin 300211 China Institute of Antibiotics Huashan Hospital Fudan University / Key Laboratory of Clinical Pharmacology of Antibiotics National Health Commission of the People's Republic of China Shanghai 200040 China National Clinical Research Centre for Aging and Medicine Huashan Hospital affiliated to Fudan University Shanghai 200040 China Department of Stomatology The Second Clinical Medical College Jinan University (Shenzhen People's Hospital) Shenzhen 518020 China Mathematics and Statistics School of Computing Engineering and Mathematical Sciences La Trobe University Melbourne 3085 VIC Australia Faculty of Medicine Macau University of Science and Technology Taipa Macau 999078 China College of Traditional Chinese Medicine Jinan University Guangzhou 510632 China

Acinetobacter baumannii is a major pathogen of nosocomial meningitis and ventriculitis. Due to very limited antibiotic treatment options, polymyxins are often used as a last-line therapy. To optimise polymyxin use in the intraventricular environment, cerebrospinal fluid (CSF) proteomics was employed to investigate host-pathogen-polymyxin interactions in a 69-year-old patient with multidrug-resistant A. baumannii ventriculitis treated with a combination of intrathecal (ITH;50,000 IU q24h/q48h), intraventricular (IVT;50,000 IU q48h), and intravenous (500,000 IU, q12h) polymyxin B. CSF was collected before the first ITH dose in the ICU (0 h) and at 24 h, Day 7 and Day 26. The proteome was quantified at each time point and proteins with Qvalue <0.05 and fold change >1.2 were considered differentially expressed. Within 24 h of ITH/IVT polymyxin B administration, the innate immune system and neuroimmunity were highly active, evidenced by up-regulation of various pathways related to pathogen invasion, endocytosis and neutrophil degranulation. Blood-brain barrier impairment had worsened at 24 h but signs of repair were evident on Day 7 and Day 26. This is the first CSF proteomic study with polymyxins. Our findings provide critical mechanistic insights into optimizing ITH/IVT polymyxin administration. © 2024 The Authors

关键词： Acinetobacter baumannii Cerebrospinal fluid Intrathecal and intravenous administration Polymyxin B Proteomics Ventriculitis

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Computer Modelling of the Information Properties of Hyper Chaotic Lorenz System and Its Application in Secure Communication System

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Journal of Physics: Conference Series 2021年第1期1764卷

作者： Volodymyr Rusyn Mujiarto Mustafa Mamat Firmansyah Azharul W. S. Mada Sanjaya Aceng Sambas Estiyan Dwipriyoko Akhmad Sutoni Yuriy Fedkovych Chernivtsi National University Kotsybynsky str. 2 Chernivtsi 58012 Ukraine. Department of Mechanical Engineering Universitas Muhammadiyah Tasikmalaya Indonesia Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Kuala Terengganu Malaysia Department of Mechanical Engineering Sekolah Tinggi Teknologi Cileungsi Indonesia Department of Physics Universitas Islam Negeri Sunan Gunung Djati Bandung Indonesia Informatics Study Program Universitas Langlangbuana Bandung Indonesia Department of Industrial Engineering Universitas Suryakancana Cianjur Indonesia

This paper presents computer modeling, analysis and research of the hyper-chaotic Lorenz system based on programming interface that has been developed in LabView software environment. This study allows for generating and research of the main information properties of hyper-chaotic Lorenz system, focusing on time distribution of the four chaotic coordinates, phase portraits and Lyapunov exponents. The programming interface demonstrates the algorithm of masking and decrypt of the information carrier.

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Magnetic anisotropy reversal driven by structural symmetry-breaking in monolayer α-RuCl3

arXiv

引用

arXiv 2022年

作者： Yang, Bowen Goh, Yin Min Sung, Suk Hyun Ye, Gaihua Biswas, Sananda Kaib, David A.S. Dhakal, Ramesh Yan, Shaohua Li, Chenghe Jiang, Shengwei Chen, Fangchu Lei, Hechang He, Rui Valentí, Roser Winter, Stephen M. Hovden, Robert Tsen, Adam W. Institute for Quantum Computing University of Waterloo WaterlooONN2L 3G1 Canada Department of Physics and Astronomy University of Waterloo WaterlooONN2L 3G1 Canada Department of Physics University of Michigan Ann ArborMI48109 United States Department of Materials Science and Engineering University of Michigan Ann ArborMI48109 United States Department of Electrical and Computer Engineering Texas Tech University LubbockTX79409 United States Institut für Theoretische Physik Goethe-Universität Frankfurt Max-von-Laue-Strasse 1 Frankfurt am Main60438 Germany Department of Physics Center for Functional Materials Wake Forest University Winston-SalemNC27109 United States Department of Physics Beijing Key Laboratory of Opto-electronic Functional Materials & Micro-nano Devices Renmin University of China Beijing100872 China Department of Physics Cornell University IthacaNY United States School of Physics and Astronomy Shanghai Jiao Tong University Shanghai China Applied Physics Program University of Michigan Ann ArborMI48109 United States Department of Chemistry University of Waterloo WaterlooONN2L 3G1 Canada

The Kitaev model is a celebrated spin-½ model on the two-dimensional (2D) honeycomb lattice with bond-dependent Ising interactions1, which features a highly entangled quantum spin liquid (QSL) ground state, fractionalized Majorana excitations, and a series of magnetic-field-induced quantum phase transitions1-7. The search for materials realizing the Kitaev model has been an ongoing challenge for over a decade and may potentially lead to applications in fault-tolerant topological quantum computing8. Yet, the unavoidable presence of non-Kitaev interactions (Heisenberg, off-diagonal, next-nearest neighbor, etc.) almost always drives the ground state away from the QSL phase, and a careful tuning of the exchange parameters is needed9-12. α-RuCl3 is a layered van der Waals material that is a particularly promising candidate to realize Kitaev physics13-15. Although the ground state is zigzag (ZZ) antiferromagnetic (AFM), this ordering can be suppressed with the application of an ~ 6-8T in-plane magnetic field. The presence of a half-integer thermal quantum Hall effect has been reported in this intermediate phase at low temperature16,17, while an unusual continuum of magnetic excitations can be seen even without magnetic field that persists far above the Néel temperature (TN ~ 7-8K)18,19. Both observations hint at α-RuCl3 being in proximity to a QSL, making it a current subject of intense scrutiny. Yet from a theoretical point of view, a QSL induced by in-plane field generally cannot be accounted for, as most calculations for α-RuCl3 show Kitaev phases more broadly emerging from an out-of-plane field6,20-23. Due to the strong "easy-plane" magnetic anisotropy of bulk crystals, however, prohibitively high fields above 30T are required to access such states24-26. The strong coupling between the spin, charge, and lattice degrees of freedom in α-RuCl3 presents an exciting opportunity to tune its magnetic interactions via external perturbations. Although pressure27-29, strain30,

关键词： Ground state

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The EMPOWER blended digital intervention for relapse prevention in schizophrenia: a feasibility cluster randomised controlled trial in Scotland and Australia

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The Lancet Psychiatry 2022年第6期9卷 477-486页

作者： Gumley, Andrew I Bradstreet, Simon Ainsworth, John Allan, Stephanie Alvarez-Jimenez, Mario Aucott, Lorna Birchwood, Maximillian Briggs, Andrew Bucci, Sandra Cotton, Sue M Engel, Lidia French, Paul Lederman, Reeva Lewis, Shôn Machin, Matthew MacLennan, Graeme McLeod, Hamish McMeekin, Nicola Mihalopoulos, Cathy Morton, Emma Norrie, John Schwannauer, Matthias Singh, Swaran P Sundram, Suresh Thompson, Andrew Williams, Chris Yung, Alison R Farhall, John Gleeson, John Glasgow Institute of Health and Wellbeing University of Glasgow Glasgow United Kingdom Division of Psychology and Mental Health School of Health Sciences Faculty of Biology Medicine and Health Manchester Academic Health Science Centre University of Manchester Manchester United Kingdom Division of Informatics Imaging and Data Sciences School of Health Sciences Faculty of Biology Medicine and Health Manchester Academic Health Science Centre University of Manchester Manchester United Kingdom Orygen Melbourne Melbourne VIC Australia Centre for Youth Mental Health University of Melbourne Melbourne VIC Australia School of Computing and Information Systems Faculty of Engineering and Information Technology University of Melbourne Melbourne VIC Australia Centre for Healthcare Randomised Trials (CHaRT) University of Aberdeen Aberdeen United Kingdom Centre for Mental Health and Wellbeing Research Warwick Medical School University of Warwick Warwick United Kingdom Department of Health Services Research and Policy London School of Hygiene & Tropical Medicine London United Kingdom Greater Manchester Mental Health NHS Foundation Trust Manchester United Kingdom School of Public Health and Preventive Medicine Monash University Melbourne VIC Australia Department of Psychiatry School of Clinical Sciences Monash University Melbourne VIC Australia School of Medicine Deakin University Melbourne VIC Australia Department of Psychiatry Manchester Metropolitan University Manchester United Kingdom Department of Psychiatry University of British Columbia Vancouver BC Canada The Usher Institute University of Edinburgh Edinburgh United Kingdom School for Health in Social Sciences University of Edinburgh Edinburgh United Kingdom Mental Health Program Monash Health Melbourne VIC Australia Department of Psychology and Counselling La Trobe University Melbourne VIC Australia NorthWestern Mental Health The Royal Melbourne Hospital Epping VIC Australia Healthy Brain and Mi

Background: Early warning signs monitoring by service users with schizophrenia has shown promise in preventing relapse but the quality of evidence is low. We aimed to establish the feasibility of undertaking a definitive randomised controlled trial to determine the effectiveness of a blended digital intervention for relapse prevention in schizophrenia. Methods: This multicentre, feasibility, cluster randomised controlled trial aimed to compare Early signs Monitoring to Prevent relapse in psychosis and prOmote Well-being, Engagement, and Recovery (EMPOWER) with treatment as usual in community mental health services (CMHS) in Glasgow and Melbourne. CMHS were the unit of randomisation, selected on the basis of those that probably had five or more care coordinators willing to participate. Participants were eligible if they were older than 16 years, had a schizophrenia or related diagnosis confirmed via case records, were able to provide informed consent, had contact with CMHS, and had had a relapse within the previous 2 years. Participants were randomised within stratified clusters to EMPOWER or to continue their usual approach to care. EMPOWER blended a smartphone for active monitoring of early warning signs with peer support to promote self-management and clinical triage to promote access to relapse prevention. Main outcomes were feasibility, acceptability, usability, and safety, which was assessed through face-to-face interviews. App usage was assessed via the smartphone and self-report. Primary end point was 12 months. Participants, research assistants and other team members involved in delivering the intervention were not masked to treatment conditions. Assessment of relapse was done by an independent adjudication panel masked to randomisation group. The study is registered at ISRCTN (99559262). Findings: We identified and randomised eight CMHS (six in Glasgow and two in Melbourne) comprising 47 care coordinators. We recruited 86 service users between Jan 19 and Au

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Scaling Limitations of Line TFETs at Sub-8-nm Technology Node

Scaling Limitations of Line TFETs at Sub-8-nm Technology Nod...

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International Symposium on VLSI Technology, Systems and Applications

作者： Narasimhulu Thoti Yiming Li Sekhar Reddy Kola Parallel and Scientific Computing Laboratory National Chiao Tung University 1001 Ta-Hsueh Rd. Hsinchu Taiwan EECS International Graduate Program National Chiao Tung University 1001 Ta-Hsueh Rd. Hsinchu Taiwan Institute of Communications Engineering National Chiao Tung University 1001 Ta-Hsueh Rd. Hsinchu Taiwan Department of Electrical and Computer Engineering National Chiao Tung University 1001 Ta-Hsueh Rd. Hsinchu Taiwan Center for mmWave Smart Radar System and Technologies National Chiao Tung University 1001 Ta-Hsueh Rd. Hsinchu Taiwan

ISBN: (数字)9781728142326

ISBN: (纸本)9781728142333

The scope of the work is to investigate limitations in device scaling by identifying various parameters of short channel effects (SCEs) in current challenging geometries of the line tunnel field effect transistors (TFETs). Key factors of the considered device, such as the doping and the thickness (t n ) of n-epitaxial region, and source-to-drain length (L SDeff ) scaling cannot be tuned anymore to boost the device characteristics for the sub-8-nm technology node. The main results of this study indicates that the engineering acceptable performance are achieved at a low doping of 5 × 10 18 cm -3 , an optimal t n as low (about 0.5 nm), and a L SDeff greater than 12.5 nm. Hence, the line TFETs below sub-8-nm faces serious bottleneck of scaling and cannot be further scaled with the conventional scaling rule at all.

关键词： Electron devices Solids

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DeePMD-kit v2: A software package for Deep Potential models

arXiv

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arXiv 2023年

作者： Zeng, Jinzhe Zhang, Duo Lu, Denghui Mo, Pinghui Li, Zeyu Chen, Yixiao Rynik, Marián Huang, Li'ang Li, Ziyao Shi, Shaochen Wang, Yingze Ye, Haotian Tuo, Ping Yang, Jiabin Ding, Ye Li, Yifan Tisi, Davide Zeng, Qiyu Bao, Han Xia, Yu Huang, Jiameng Muraoka, Koki Wang, Yibo Chang, Junhan Yuan, Fengbo Bore, Sigbjørn Løland Cai, Chun Lin, Yinnian Wang, Bo Xu, Jiayan Zhu, Jia-Xin Luo, Chenxing Zhang, Yuzhi Goodall, Rhys E.A. Liang, Wenshuo Singh, Anurag Kumar Yao, Sikai Zhang, Jingchao Wentzcovitch, Renata Han, Jiequn Liu, Jie Jia, Weile York, Darrin M. Weinan, E. Car, Roberto Zhang, Linfeng Wang, Han Laboratory for Biomolecular Simulation Research Institute for Quantitative Biomedicine Department of Chemistry and Chemical Biology Rutgers University PiscatawayNJ08854 United States AI for Science Institute Beijing100080 China DP Technology Beijing100080 China Academy for Advanced Interdisciplinary Studies Peking University Beijing100871 China HEDPS CAPT College of Engineering Peking University Beijing100871 China College of Electrical and Information Engineering Hunan University Changsha China Yuanpei College Peking University Beijing100871 China Program in Applied and Computational Mathematics Princeton University PrincetonNJ08540 United States Department of Experimental Physics Comenius University Mlynská Dolina F2 Bratislava842 48 Slovakia Center for Quantum Information Institute for Interdisciplinary Information Sciences Tsinghua University Beijing100084 China Center for Data Science Peking University Beijing100871 China ByteDance Research Zhonghang Plaza No. 43 North 3rd Ring West Road Haidian District Beijing China College of Chemistry and Molecular Engineering Peking University Beijing100871 China Baidu Inc. Beijing China Key Laboratory of Structural Biology of Zhejiang Province School of Life Sciences Westlake University Zhejiang Hangzhou China Westlake AI Therapeutics Lab Westlake Laboratory of Life Sciences and Biomedicine Zhejiang Hangzhou China Department of Chemistry Princeton University PrincetonNJ08544 United States SISSA Scuola Internazionale Superiore di Studi Avanzati Trieste34136 Italy Laboratory of Computational Science and Modeling Institute of Materials École Polytechnique Fédérale de Lausanne Lausanne1015 Switzerland Department of Physics National University of Defense Technology Hunan Changsha410073 China State Key Lab of Processors Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China School of Electronics Engineerin

DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics simulations using machine learning potentials (MLP) known as Deep Potential (DP) models. This package, which was released in 2017, has been widely used in the fields of physics, chemistry, biology, and material science for studying atomistic systems. The current version of DeePMD-kit offers numerous advanced features such as DeepPot-SE, attention-based and hybrid descriptors, the ability to fit tensile properties, type embedding, model deviation, Deep Potential - Range Correction (DPRc), Deep Potential Long Range (DPLR), GPU support for customized operators, model compression, non-von Neumann molecular dynamics (NVNMD), and improved usability, including documentation, compiled binary packages, graphical user interfaces (GUI), and application programming interfaces (API). This article presents an overview of the current major version of the DeePMD-kit package, highlighting its features and technical details. Additionally, the article benchmarks the accuracy and efficiency of different models and discusses ongoing developments. © 2023, CC BY-NC-ND.

关键词： Molecular dynamics

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Performance Analysis of a Modified Conjugate Gradient Algorithm for Optimization Models

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IOP Conference Series: Materials Science and engineering 2021年第1期1115卷

作者： S E Olowo I M Sulaiman M Mamat A E Owoyemi M A Zaini Kalfin S H Yuningsih Department of Mathematics Kano University of science and Technology Kano Nigeria Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Campus Kuala Nerus 22200 Terengganu Malaysia Department of General Studies. Federal College of Agricultural Produce Technology Kano Nigeria Institute of Engineering Mathematics Universiti Malaysia Perlis Kangar Malaysia Doctor Program of Mathematics Faculty of Mathematics and Natural Sciences Universitas Padjadjaran Indonesia Master Program of Mathematics Faculty of Mathematics and Natural Sciences Universitas Padjadjaran Indonesia

The Conjugate gradient (CG) algorithms is very important and widely used in solving optimization models. This is due to its simplicity as well as global convergence properties. Various line search procedures as usually employ in the analysis of the CG methods. Recently, many studies have been done aimed at improving the CG method. In this paper, an alternative formula for conjugate gradient coefficient has been proposed which possesses the global convergence properties under exact minimization condition. The result of the numerical computation has shown that this new coefficient performs better than the existing CG methods.

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Interactive Protocols for Classically-Verifiable Quantum Advantage

arXiv

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arXiv 2021年

作者： Zhu, Daiwei Kahanamoku-Meyer, Gregory D. Lewis, Laura Noel, Crystal Katz, Or Harraz, Bahaa Wang, Qingfeng Risinger, Andrew Feng, Lei Biswas, Debopriyo Egan, Laird Gheorghiu, Alexandru Nam, Yunseong Vidick, Thomas Vazirani, Umesh Yao, Norman Y. Cetina, Marko Monroe, Christopher Joint Quantum Institute Departments of Physics and Electrical and Computer Engineering University of Maryland College ParkMD20742 United States Joint Center for Quantum Information and Computer Science NIST University of Maryland College ParkMD20742 United States Department of Physics University of California BerkeleyCA94720 United States Materials Sciences Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Department of Computing and Mathematical Sciences California Institute of Technology CA91125 United States Division of Physics Mathematics and Astronomy California Institute of Technology CA91125-0001 United States Duke Quantum Center Department of Physics Duke University DurhamNC27708 United States Department of Electrical and Computer Engineering Duke University DurhamNC27708 United States IonQ Inc. College ParkMD20740 United States Institute for Theoretical Studies ETH Zürich CH 8001 Switzerland Chemical Physics Program Institute for Physical Science and Technology University of Maryland College ParkMD20742 United States Departments of Electrical and Computer Engineering University of Maryland College ParkMD20742 United States

Interaction is a powerful resource for quantum computation. It can be utilized in applications ranging from the verification of quantum algorithms all the way to verifying quantum mechanics itself. Here, we present the first implementation of interactive protocols for proofs of quantumness — which when suitably scaled promise the efficient verification of quantum computational advantage. The key feature that distinguishes these protocols from existing demonstrations of quantum advantage is that the classical verification is efficient and scales polynomially rather than exponentially with the number of qubits. The experimental implementation of such interactive protocols requires the ability to independently measure subsets of qubits in the middle of a quantum circuit and to continue coherent evolution afterwards. This is achieved by spatially isolating target qubits via shuttling, and opens the door to a range of quantum interactive protocols as well as new information processing architectures. Copyright © 2021, The Authors. All rights reserved.

关键词： Qubits

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Scientific discovery in the age of artificial intelligence

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NATURE 2023年第7978期621卷 E33-E33页

作者： Wang, Hanchen Fu, Tianfan Du, Yuanqi Gao, Wenhao Huang, Kexin Liu, Ziming Chandak, Payal Liu, Shengchao Van Katwyk, Peter Deac, Andreea Anandkumar, Anima Bergen, Karianne Gomes, Carla P. Ho, Shirley Kohli, Pushmeet Lasenby, Joan Leskovec, Jure Liu, Tie-Yan Manrai, Arjun Marks, Debora Ramsundar, Bharath Song, Le Sun, Jimeng Tang, Jian Velickovic, Petar Welling, Max Zhang, Linfeng Coley, Connor W. Bengio, Yoshua Zitnik, Marinka Department of Engineering University of Cambridge Cambridge UK Department of Computing and Mathematical Sciences California Institute of Technology Pasadena CA USA NVIDIA Santa Clara CA USA Department of Computational Science and Engineering Georgia Institute of Technology Atlanta GA USA Department of Computer Science Cornell University Ithaca NY USA Department of Chemical Engineering Massachusetts Institute of Technology Cambridge MA USA Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge MA USA Department of Computer Science Stanford University Stanford CA USA Department of Physics Massachusetts Institute of Technology Cambridge MA USA Harvard-MIT Program in Health Sciences and Technology Cambridge MA USA Mila – Quebec AI Institute Montreal Quebec Canada Université de Montréal Montreal Quebec Canada HEC Montréal Montreal Quebec Canada CIFAR AI Chair Toronto Ontario Canada Department of Earth Environmental and Planetary Sciences Brown University Providence RI USA Data Science Institute Brown University Providence RI USA Center for Computational Astrophysics Flatiron Institute New York NY USA Department of Astrophysical Sciences Princeton University Princeton NJ USA Department of Physics Carnegie Mellon University Pittsburgh PA USA Department of Physics and Center for Data Science New York University New York NY USA Google DeepMind London UK Department of Computer Science and Technology University of Cambridge Cambridge UK Microsoft Research Beijing China Department of Biomedical Informatics Harvard Medical School Boston MA USA Broad Institute of MIT and Harvard Cambridge MA USA Harvard Data Science Initiative Cambridge MA USA Kempner Institute for the Study of Natural and Artificial Intelligence Harvard University Cambridge MA USA Department of Systems Biology Harvard Medical School Boston MA USA Deep Forest Sciences Palo Alto CA USA BioMap Beijing China Mo

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A Comparative Analysis Between Particle Swarm Optimization and Mathematical programming for Optimal Location of Maintenance Facilities

A Comparative Analysis Between Particle Swarm Optimization a...

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IEEE PES Conference on Innovative Smart Grid Technologies (ISGT Latin America)

作者： Paulo M. O. Filho Bruno S. M. C. Borba Vitor H. Ferreira Rafael V. Tavares Eduardo Queiroga João Marcos P. Silva Eduardo Uchoa Níssia C. R. Bergiante Bernardo Salgado Moreira Pedro Henrique Coelho Machado Electrical Engineering Department Universidade Federal Fluminense Niterói Brazil Computing Institute Universidade Federal Fluminense Niterói RJ Brazil Industrial Engineering Graduate Program Univeridade Federal da Paraíba João Pessoa PB Brazil Industrial Engineering Department Universidade Federal Fluminense Niterói RJ Brazil Energisa Distribuição Cuiabá MT Brazil Energisa Tocantins Palmas TO Brazil

ISBN: (纸本)9781538695685

This paper addresses the problem of maintenance facilities (depot) location in electric power distribution systems with a focus on strategic planning. Power interruptions can be harmful for both society and distribution companies. Determining the optimal number and sites of depot location to handle power interruptions in the long term can improve the quality of service. Through a good depot location, the distance from depots to work orders (WO) is minimized, operational costs can be minimized and customer interruption duration is reduced, which is a good indicator of the reliability of the system. The problem was solved by a Particle Swarm Optimization (PSO) algorithm and a Mixed Integer Linear programming (MILP) model. In addition to the real instance, some synthetic ones were generated to compare both approaches in large-sized scenarios. The computational results show that the two approaches are complementary strategies, being presented the scenarios where each proposal could provide better results.

关键词： Depot location Electric power distribution Reliability PSO MILP Electricity Distribution Systems parametric subharmonic oscillator Maintenance facilities WAREHOUSE Particle swarm optimization Manufacturing costs

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