Optimal energy management of multi-carrier energy system considering uncertainty in renewable generation by Ankit Garg, K. R. Niazi, Shubham Tiwari, Sachin Sharma, Tanuj Rawat

“…In the first stage, the objective is to minimize daily operational costs while incorporating the uncertain behavior of renewables using a scenario-based stochastic approach. …”
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Variable Selection for Multivariate Failure Time Data via Regularized Sparse-Input Neural Network by Bin Luo, Susan Halabi

“…We propose a unified framework that identifies predictors shared across outcomes, applicable to both low- and high-dimensional settings. …”
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Research on Laser Radar Inspection Station Planning of Vehicle Body-In-White (BIW) with Complex Constraints by Lijuan Li, Siyi Wang, Jichao Ma, Xiaobing Gao

“…Firstly, a parametric geometric modeling approach is developed to define measurement spaces for individual features, accompanied by an innovative maximal complete subgraph mining algorithm to intelligently identify shared feasible measurement regions among multiple features. …”
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FedQP: Large-Scale Private and Flexible Federated Query Processing by Hussain M. J. Almohri, Layne T. Watson

“…State-of-the-art federated learning coordinates stochastic gradient descent across clients to refine shared model parameters while protecting individual datasets. …”
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Modernizing the Design Process for US Organ Allocation Policy: Toward a Continuous Distribution Policy for Kidneys by Elijah Pivo, PhD(c), James Alcorn, JD, Dimitris Bertsimas, PhD, Sarah E. Booker, MPH, Keighly Bradbrook, PhD, Thomas G. Dolan, MS, Lindsay V. Larkin, BA, Kayla R. Temple, BA, Nikolaos Trichakis, PhD

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Link-State-Aware Proactive Data Delivery in Integrated Satellite–Terrestrial Networks for Multi-Modal Remote Sensing by Ranshu Peng, Chunjiang Bian, Shi Chen, Min Wu

“…By integrating satellite cache states, user cache states, and multi-modal data attributes (including imagery, metadata, and temporal request patterns) into a unified Markov decision process (MDP), our approach pioneers the application of the multi-actor-attention-critic with parameter sharing (MAPPO) algorithm to ISTNs push tasks. Central to this framework is a dual-branch actor network architecture that dynamically fuses heterogeneous modalities: a lightweight MobileNet-v3-small backbone extracts semantic features from remote sensing imagery, while parallel branches—a multi-layer perceptron (MLP) for static attributes (e.g., payload specifications, geolocation tags) and a long short-term memory (LSTM) network for temporal user cache patterns—jointly model contextual and historical dependencies. …”
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Identification of potential diagnostic markers and molecular mechanisms of asthma and ulcerative colitis based on bioinformatics and machine learning by Chenxuyu Zhang, Chenxuyu Zhang, Zheng Luo, Liang Ji

“…Gene Set Enrichment Analysis (GSEA) explored pathway alterations, while immune infiltration patterns were analyzed using the CIBERSORT algorithm. …”
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Knowledge-guided self-learning control strategy for mixed vehicle platoons with delays by Jingyao Wang, Huinian Wang, Jian Song, Xingyu Chen, Jinghua Guo, Keqiang Li, Xunrui Li, Bowen Huang

“…Abstract As autonomous vehicles and traditional vehicles will coexist for several decades, how to efficiently manage the mixed traffic, while enhancing road throughput, fuel consumption and traffic stability becomes a challenge. …”
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Polarization of public opinions on feminism in China by Jinghua Piao, Fang Zhang, Tianpei Ren, Fengli Xu, Jinglei Zhou, Jun Su, Peng Ru, Yong Li

“…We further reveal that the AI-driven recommendation algorithm contributes to two primary drivers of this polarization: (i) echo chambers, where the algorithmic gathering of like-minded users reinforces their shared similar opinions and (ii) battlefields, where opposing users conflict, strengthening pre-existing opinions. …”
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Modelling and optimization for cognitive radio networks with preemption backoff mechanism by Yuan Zhao, Zhiyu Xiang, Kang Chen, Zhisheng Ye, Qi Lu

“…Under the centralized spectrum sharing structure, we construct a discrete-time queueing model by developing a 3-dimensional Markov-chain (3DMC). …”
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Identification of Gene Modules Associated with Low Temperatures Response in Bambara Groundnut by Network-Based Analysis. by Venkata Suresh Bonthala, Katie Mayes, Joanna Moreton, Martin Blythe, Victoria Wright, Sean Tobias May, Festo Massawe, Sean Mayes, Jamie Twycross

“…Analyses of the bambara groundnut transcriptome using cross-species gene expression data resulted in the identification of 375 and 659 differentially expressed genes (p<0.01) under the sub-optimal (23°C) and very sub-optimal (18°C) temperatures, respectively, of which 110 genes are commonly shared between the two stress conditions. The construction of a Highest Reciprocal Rank-based gene co-expression network, followed by its partition using a Heuristic Cluster Chiseling Algorithm resulted in 6 and 7 gene modules in sub-optimal and very sub-optimal temperature stresses being identified, respectively. …”
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Fast and Adaptive Multi-Agent Planning under Collaborative Temporal Logic Tasks via Poset Products by Zesen Liu, Meng Guo, Weimin Bao, Zhongkui Li

“…Efficient coordination and planning is essential for large-scale multi-agent systems that collaborate in a shared dynamic environment. Heuristic search methods or learning-based approaches often lack the guarantee on correctness and performance. …”
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An optimized multi-task contrastive learning framework for HIFU lesion detection and segmentation by Matineh Zavar, Hamid Reza Ghaffari, Hamid Tabatabaee

“…By employing a genetic algorithm, OMCLF explores and optimizes augmentation techniques suitable for medical data, avoiding distortions that could compromise diagnostic accuracy. …”
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Scalable quality control on processing of large diffusion-weighted and structural magnetic resonance imaging datasets. by Michael E Kim, Chenyu Gao, Nancy R Newlin, Gaurav Rudravaram, Aravind R Krishnan, Karthik Ramadass, Praitayini Kanakaraj, Kurt G Schilling, Blake E Dewey, David A Bennett, Sid O'Bryant, Robert C Barber, Derek Archer, Timothy J Hohman, Shunxing Bao, Zhiyuan Li, Bennett A Landman, Nazirah Mohd Khairi, Alzheimer’s Disease Neuroimaging Initiative, HABS-HD Study Team

“…Most efforts to reduce data QC time rely on quantitative outlier detection, which cannot capture every instance of algorithm failure. Thus, there is a need to visually inspect every output of data processing pipelines in a scalable manner. …”
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Cost-Effective Multitask Active Learning in Wearable Sensor Systems by Asiful Arefeen, Hassan Ghasemzadeh

“…Multitask learning models provide benefits by reducing model complexity and improving accuracy by concurrently learning multiple tasks with shared representations. Leveraging inductive knowledge transfer, these models mitigate the risk of overfitting on any specific task, leading to enhanced overall performance. …”
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Perceptions of, Barriers to, and Facilitators of the Use of AI in Primary Care: Systematic Review of Qualitative Studies by Héctor Martínez-Martínez, Julia Martínez-Alfonso, Belén Sánchez-Rojo-Huertas, Valeria Reynolds-Cortez, Andrea Turégano-Chumillas, Victoria A Meseguer-Ruiz, Shkelzen Cekrezi, Vicente Martínez-Vizcaíno

“…However, clinicians and patients share concerns regarding data privacy, security, and potential biases in AI algorithms. …”
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Designing a Multi-Objective Stable Mathematical Model for Routing Municipal Waste Collection Vehicles by Afrouz Rahmandoust, Ashkan Hafezalkotob, Bijan Rahmani Parchikolaei, َAmir Azizi

“…Multi-objective meta-heuristic algorithms were applied to solve the model in scenarios with larger dimensions. …”
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Bilevel Programming Model of Urban Public Transport Network under Fairness Constraints by Jingjing Hao, Xinquan Liu, Xiaojing Shen, Nana Feng

“…The model in addition utilised the noninferior sorting genetic algorithm II to validate the model via a simple network. …”
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Multimodal Fusion Multi-Task Learning Network Based on Federated Averaging for SDB Severity Diagnosis by Songlu Lin, Renzheng Tang, Yuzhe Wang, Zhihong Wang

“…The proposed framework is built upon a hybrid deep neural architecture that integrates convolutional layers (CNN) for spatial representation, bidirectional GRUs for temporal modeling, and multi-head self-attention for long-range dependency learning. A shared feature extractor is combined with task-specific heads to enable joint diagnosis, while the FedAvg algorithm is employed to facilitate decentralized training across multiple institutions without sharing raw data, thereby preserving privacy and addressing non-IID challenges. …”
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ESLC-YOLOv8: Advancing real-time pineapple recognition with lightweight deep learning by Weihua Shen, Mengyao Dong, Zhaoxin Zhang, Xiaying Hao, Yuzhen Su, Zhong Xue

“…Finally, we design a Lightweight Shared Convolutional Detection Head (LSCD) that dramatically reduces model parameters while maintaining detection accuracy, coupled with a Coordinate Attention (CA) mechanism to reinforce critical feature representation. …”
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