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Identify the potential pathways and candidate biomarkers of stroke associated with bipolar disorder: Bioinformatics and system biology approach

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Journal of Proteins and Proteomics 2025年第2期16卷 141-159页

作者： Hosen, Md. Faruk Basar, Md. Abul Yasmin, Mst. Farjana Hasan, Md. Rakibul Uddin, Muhammad Shahin Department of Information and Communication Technology (ICT) Mawlana Bhashani Science and Technology University (MBSTU) Tangail Bangladesh Department of Computing and Information System (CIS) Daffodil International University (DIU) Dhaka Bangladesh Department of Computer Science and Engineering (CSE) Uttara University Dhaka Bangladesh Department of Software Engineering (SWE) Daffodil International University (DIU) Dhaka Bangladesh

The field of computational bioinformatics and systems biology analysis is rapidly expanding due to advancements in bioinformatics tools. Bipolar disorder (BD) is a severe psychiatric condition affecting both adults and adolescents. In recent years, the risk of stroke has increased among individuals with BD. Background studies indicate that BD and stroke share numerous biochemical and genetic characteristics. Due to traditional endocrinological approaches, no collaborative research exists, and no treatment options have been established for BD and stroke patients. The aim of this study is to identify common molecular pathways and potential therapeutic targets in BD and stroke that could be utilized to predict disease progression. To achieve this, shared genes were identified to determine common pathways. Based on the biochemical, molecular, and genetic interactions among these shared genes, this study identifies the most significant hub genes. To further explore these interactions, analysis such as the protein–protein interaction (PPI) network, topological properties, enrichment analysis, co-expression network, gene regulatory network (GRN), and physical interaction network are conducted. The GO annotation indicates that most of the genes are linked to MAP kinase activity and tumor necrosis factor receptor superfamily binding. The KEGG pathway analysis revealed that the predominant genes are associated with apoptosis and the IL-18 signaling pathway. This comparison helps understand the biochemical and genetic characteristics shared between BD and stroke. Predictive drug analysis has identified consistent potential biomarkers associated with both conditions, providing a scientific foundation for investigating their diagnosis, treatment, and prognosis. Finally, chemical experiments could be conducted to further validate the efficacy of these drugs.

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Small Signal Stability-Guaranteed Moving Target Defense Against Load Redistribution Attack On IoT-based Smart Grid

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IEEE Internet of Things Journal 2025年第11期12卷 17413-17429页

作者： Wang, Bingdong Zhang, Zhenyong Wang, Mufeng Liu, Mengxiang Ye, Rui Deng, Ruilong Zhang, Xin Guizhou University State Key Laboratory of Public Big Data College of Computer Science and Technology Guiyang550025 China China Industrial Control Systems Cyber Emergency Response Team Beijing100040 China University of Sheffield Department of Automatic Control and System Engineering Sheffield United Kingdom Guizhou Power Grid Co. Ltd. Intelligent Operation Center China Zhejiang University State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Hangzhou310027 China Huzhou Institute of Industrial Control Technology Huzhou313000 China

Moving target defense (MTD) is a promising approach to defend against load redistribution attacks on the internet-of-things (IoT)-based smart grid networks by probing the distorted state estimates with the distributed flexible AC transmission system. However, existing studies mainly focus on optimizing the performance of MTD and ignore the safety effect of it on the system’s operation. In this paper, we fill this gap by deeply analyzing the effect of MTD on the small signal stability and aim to alleviate the negative impact and guarantee its defending performance simultaneously. Firstly, the stability is formally described using the eigenvalue sensitivity. The relationship between the MTD-induced perturbation (MTDper) and the stability criteria is derived. Secondly, a new indicator is proposed to measure the effectiveness of MTDper. Thirdly, a constrained optimization problem is formulated to compute the bound of MTDper for guaranteeing the small signal stability. In addition, a surprising finding is that the stability margin can be improved and enhanced by optimizing the value of MTDper without losing the MTD’s effectiveness. Finally, we evaluate the performance of MTDper and its impact on the small signal stability with extensive simulations on the IEEE 30-bus, 39-bus, and 68-bus test power systems. © 2014 IEEE.

关键词： Constrained optimization

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Transfer Learning Trained LSTM Models for Household Load Profile Forecasting

Transfer Learning Trained LSTM Models for Household Load Pro...

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Grid Edge Technologies Conference & Exposition (Grid Edge), IEEE PES

作者： Roshan Klein-Seetharaman Xiangqi Zhu Barry Mather Department of Mathematics Yale University New Haven USA Electrical Engineering and Computer Science Oregon State University Corvallis USA National Renewable Energy Laboratory Power System Engineering Center Golden USA

ISBN: (数字)9798350352528

ISBN: (纸本)9798350352535

Grid edge renewable energy resources, such as rooftop solar photovoltaics, closely interact with consumer load profiles. Therefore, forecasting future electricity demand, ideally at the individual household level, is indispensable. In this paper, we present a transfer learning enhanced household load profile forecasting method. First, we tune a long short-term memory forecasting model to perform day-ahead prediction of household electricity load profiles. Then we improve these individualized models using transfer learning, and we use k-means clustering to create optimal source data sets. We find average improvements of 4.38% (largest improvement of 10.71%) when the entire data set was used to train the source model and 2.45% (largest improvement of 11.57%) in the mean absolute error when households were first clustered and used to train separate source models for each cluster. We find that transfer learning with clustered data can effectively boost the forecasting performance of the LSTM models. We use realistic household power measurements for 148 real residential households in Austin, Texas.

关键词： Photovoltaic systems Renewable energy sources Power measurement Electricity Transfer learning Predictive models Data models Forecasting Long short term memory Load modeling

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Revolutionizing Digital Media Content using a Smart Drone and an Innovative ML Technique

Revolutionizing Digital Media Content using a Smart Drone an...

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Learning and Technology Conference (L&T)

作者： Faris A. Almalki Rahaf A Almarzouki Department of Computer Engineering College of Computers and Information Technology Taif University Taif Saudi Arabia Department of Management Information System Collage of Economics and Admissions King Abdulaziz University Jeddah Saudi Arabia

ISBN: (数字)9798331532215

ISBN: (纸本)9798331532222

In the contemporary digital age, the fields of journalism and social media assume a pivotal role in disseminating information about current events and issues to the public. However, conventional techniques for gathering news and capturing images frequently encounter constraints and limitations. In recent years, technological advancements have transformed the creation and consumption of digital media content. This study presents an innovative solution that combines a smart drone with a reinforcement learning (RL) machine learning technique to enhance digital media content in a timely manner. The proposed framework has been subjected to validation and testing in a real-world scenario in Taif City through the transfer of rich digital media content. The results demonstrate promising outcomes, which support Saudi Arabia's efforts to enrich digital media content for tourism.

关键词： Technological innovation Social networking (online) Urban areas Reinforcement learning Media Journalism Information age Reliability Drones Testing

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Performance Evaluation Customer Access Network Using Difference Modulation Technique 1st

Performance Evaluation Customer Access Network Using Differe...

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1st International Symposium on systems Modelling and Simulation, SMS 2024

作者： Mugunthan, Sivaguru Abdul Rahman, Juwairiyyah Abu Hassan, Hasliza Muslim, Norliana Ab Rahman, Mohammad Syuhaimi Department of Engineering Faculty of Engineering and Life Sciences Universiti Selangor Selangor Bestari Jaya45600 Malaysia Department of Computer and Communication Technology Universiti Tunku Abdul Rahman Perak Kampar31900 Malaysia Department of Electrical Electronic and System Engineering Faculty of Engineering and Built Environment Universiti Kebangsaan Malaysia Bangi Malaysia

ISBN: (纸本)9789819646128

Modeling Fiber To The Home (FTTH) networks involves several technical aspects and design considerations to enable effective and high-quality service delivery. This research seeks to boost the received signal quality for end-users inside a FTTH network. In order to create suitable and high-quality FTTH networks, this study will simulate FTTH networks utilizing network feasibility criteria, with an emphasis on BER and Q-factor. The signal distribution inside access networks is improved using Wavelength Division Multiplexing (WDM) and 10G-Passive Optical Network (PON) technology is used since it can deliver a fourfold improvement in downstream data transfer rates per user. Simulation result using Optisystem 21 software, by setting transmitter wavelengths of 1490 nm and 1550 nm with a loss of 0 dB for a maximum of 2 users for total access based on the Q-factor calculation, which must be more than 6, while the BER must be less than 1 × e−9. system performance parameters that demonstrate Q-factor and Bit Error Rate (BER) give good quality and good performance is also shown by eye pattern in optical simulation. For 1490 nm, the highest Q-factor for 2 users is 35.8226, with a minimum BER of 2.4360 × 10−281. For 1550 nm, the highest Q-factor is 15.3668 (in phase) and 14.8087 (in quadrature), with minimal BER values of 1.3674 × e−53 (in phase) and 6.4291 × e−50 (in quadrature). Good performance is also shown by eye pattern in optical simulation that displays amplitude signals. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Q factor measurement

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Decision-Focused Learning for Complex system Identification: HVAC Management system Application

arXiv

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arXiv 2025年

作者： Favaro, Pietro Toubeau, Jean-François Vallée, François Dvorkin, Yury Power Systems and Markets Research Group University of Mons Mons Belgium Ralph O’Connor Sustainable Energy Institute Department of Electrical and Computer Engineering Department of Civil and System Engineering Johns Hopkins University BaltimoreMD United States

As opposed to conventional training methods tailored to minimize a given statistical metric or task-agnostic loss (e.g., mean squared error), Decision-Focused Learning (DFL) trains machine learning models for optimal performance in downstream decision-making tools. We argue that DFL can be leveraged to learn the parameters of system dynamics, expressed as constraint of the convex optimization control policy, while the system control signal is being optimized, thus creating an end-to-end learning framework. This is particularly relevant for systems in which behavior changes once the control policy is applied, hence rendering historical data less applicable. The proposed approach can perform system identification — i.e., determine appropriate parameters for the system analytical model — and control simultaneously to ensure that the model’s accuracy is focused on areas most relevant to control. Furthermore, because black-box systems are non-differentiable, we design a loss function that requires solely to measure the system response. We propose pre-training on historical data and constraint relaxation to stabilize the DFL and deal with potential infeasibilities in learning. We demonstrate the usefulness of the method on a building Heating, Ventilation, and Air Conditioning day-ahead management system for a realistic 15-zone building located in Denver, US. The results show that the conventional RC building model, with the parameters obtained from historical data using supervised learning, underestimates HVAC electrical power consumption. For our case study, the ex-post cost is on average six times higher than the expected one. Meanwhile, the same RC model with parameters obtained via DFL underestimates the ex-post cost only by 3%. © 2025, CC BY-NC-ND.

关键词： Convex optimization

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Correction to: NeXtSRGAN: enhancing super-resolution GAN with ConvNeXt discriminator for superior realism (The Visual computer, (2025), 10.1007/s00371-024-03797-2)

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Visual computer 2025年 1-1页

作者： Park, Sung-Wook Jung, Se-Hoon Sim, Chun-Bo Interdisciplinary Program in IT-Bio Convergence System Sunchon National University Suncheon57922 Korea Republic of Department of Computer Engineering Sunchon National University Suncheon57922 Korea Republic of

The publication of this article unfortunately contained mistakes. The assignment of the affiliations was not correct. The corrected affiliation is given below. Wrong assignment: Chun-Bo Sim 1,2 1 Interdisciplinary Program in IT-Bio Convergence system, Sunchon National University, Suncheon 57922, Republic of Korea 2 department of computer engineering, Sunchon National University, Suncheon 57922, Republic of Korea Correct assignment: Chun-Bo Sim 1 1 Interdisciplinary Program in IT-Bio Convergence system, Sunchon National University, Suncheon 57922, Republic of Korea The original article has been corrected. © The Author(s) 2025.

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Adhesive bioelectronics for closed-loop therapy

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Med-X 2025年第1期3卷 1-32页

作者： Jung, Hyunjin Lee, Hyelim Shin, Mikyung Son, Donghee Department of Electrical and Computer Engineering Sungkyunkwan University (SKKU) Suwon Republic of Korea Center for Neuroscience Imaging Research Institute for Basic Science Suwon Republic of Korea Department of Intelligent Precision Healthcare Convergence Sungkyunkwan University (SKKU) Suwon Republic of Korea Department of Biomedical Engineering Sungkyunkwan University (SKKU) Suwon Republic of Korea Department of Artificial Intelligence System Engineering Sungkyunkwan University (SKKU) Suwon Republic of Korea

Wearable and implantable devices mark a major advancement in biomedical engineering, enabling continuous bio-signal monitoring and treatment based on precise feedback. However, traditional rigid bioelectronic devices face challenges in seamlessly interfacing with soft organs, often leading to tissue damage and inflammation. To address these issues, soft bioelectronics that better conform to the body while maintaining performance accuracy have been developed. Despite these advancements, the dynamic nature of body movements and the complex chemical environment in the body can compromise the stability of devices over time. Therefore, recent innovations have focused on ultrathin and stretchable designs that enhance conformal contact through van der Waals forces, as well as the incorporation of adhesive hydrogels, to improve adhesion, even in the presence of biofluids. This review provides a comprehensive overview of the advancements in wearable and implantable bioelectronics aimed at achieving conformal tissue adhesion and long-term stability, covering structural modifications to bilayer designs. Finally, the integration of bioelectronics with closed-loop therapies to significantly enhance treatment efficacy is explored. • Materials strategies and device fabrication/integration processes optimally tailored to various organs are addressed. • Mechanical and electrical characterizations of wearable and implantable adhesive bioelectronics are described, while emphasizing challenges and opportunities in long-term stable tissue interfacing. • Various demonstrations of closed-loop bio-integrated systems using soft stretchable adhesive materials, and their futuristic perspectives are introduced.

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White matter hyperintensities and relapse risk in late-life depression

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Journal of Affective Disorders 2025年 383卷 298-305页

作者： Pearcy, Leigh B. Karim, Helmet T. Butters, Meryl A. Krafty, Robert Boyd, Brian D. Banihashemi, Layla Szymkowicz, Sarah M. Landman, Bennett A. Ajilore, Olusola Taylor, Warren D. Andreescu, Carmen Department of Psychiatry University of Pittsburgh Pittsburgh PA United States Department of Bioengineering University of Pittsburgh Pittsburgh PA United States Center for Cognitive Medicine Department of Psychiatry and Behavioral Science Vanderbilt University Medical Center Nashville TN United States Geriatric Research Education and Clinical Center Veterans Affairs Tennessee Valley Health System Nashville TN United States Department of Psychiatry University of Illinois-Chicago Chicago IL United States Department of Biostatistics and Bioinformatics Emory University Atlanta GA United States Departments of Computer Science Electrical Engineering and Biomedical Engineering Vanderbilt University United States Department of Radiology and Radiological Sciences Vanderbilt University Medical Center United States

Background: White matter hyperintensities (WMHs) are associated with late-life depression (LLD) and are considered a hallmark of MRI-defined vascular depression. However, their impact on depression recurrence in LLD is less well known. Methods: We investigated this relationship using data from a 2-year multi-site, longitudinal study, where baseline WMH volumes were obtained using 3 T FLAIR magnetic resonance imaging (MRI) from 145 participants, of which 102 had remitted LLD and 43 were control participants. We analyzed the effect of baseline WMH volume on LLD relapse over 2 years using regression and adjusting for total intracranial volume, age, sex, race, education, and study site. We performed survival analyses using a Cox proportional hazard model to determine whether baseline WMH volume was associated with time to relapse in LLD. Results: We found that participants with LLD had greater WMH volume at baseline than control participants, but not if accounting for peripheral cardiovascular disease. Participants with LLD who relapsed within 8 months of baseline had larger WMH volume than control participants but did not statistically differ from those that remained remitted;this effect was lost when expanding to participants that relapsed at any point in the 2-year study. WMH burden was not associated with time to relapse, suggesting greater WMH volumes are not indicative of faster relapse rates in LLD. Conclusion: Our results show that WMH burden may play a role in the early - but not the delayed - relapse of LLD, and they underscore the intricate dynamic of the biological markers underlying LLD treatment response and relapse. © 2025 The Authors

关键词： Depression Late-life LLD Recurrence Relapse Small vessel disease WMH

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Streamlining the New Product Introduction by Integrating the Escalation Process 18th

Streamlining the New Product Introduction by Integrating the...

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18th International Conference on Interdisciplinarity in engineering, INTER-ENG 2024

作者： Zgirdea, Mihai Ionica, Andreea Cristina Leba, Monica Engineering and Management Doctoral School University of Petrosani 20 Universitatii Petrosani332006 Romania Management and Industrial Engineering Department University of Petrosani 20 Universitatii Petrosani332006 Romania Computer and System Control Engineering Department University of Petrosani 20 Universitatii Petrosani332006 Romania

ISBN: (纸本)9783031813771

In the dynamic landscape of modern business, companies face the challenge of rapidly introducing new products to meet consumer demands. This research aims to propel NPI efficiency, focusing on the automotive industry, by enhancing cooperative effectiveness and streamlining processes. The overarch- ing objective is to expedite high-quality product with the focus of introducing a controlled escalation process to facilitate swift corrections and improvements throughout each phase of NPI. To realize these objectives, a comprehensive NPI system has been developed. Integration of an escalation process into this sys- tem enables hierarchical escalation of concerns, blocking points, and new pro- cesses, addressing common project delays. The proposed software stands out for its unique integration of the escalation process, ensuring that all organizational members are promptly informed of any deviations using a dynamic project status feature, adapting as the project progresses. The integrated escalation process not only addresses anomalies promptly but also quantifies the time taken to restore normalcy or implement corrections, thereby fostering a more responsive and effi- cient NPI framework. The paper is organized into sections comprising a literature review on NPI methodologies, the integration of an escalation process into the NPI framework, a case study illustrating the implementation of the escalation process in an existing NPI methodology, and the subsequent results. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Automotive Industry Collaborative Teamwork Controlled Escalation Process Dynamic NPI Software New Product Introduction (NPI)

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