Dynamic Route Network Planning Problem for Emergency Evacuation in Restricted-Space Scenarios by Yi Hong, Deying Li, Qiang Wu, Hua Xu

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Intelligent Dual Basal–Bolus Calculator for Multiple Daily Insulin Injections via Offline Reinforcement Learning by Junyoung Yoo, Vega Pradana Rachim, Suyeon Jung, Sung-Min Park

“…By analyzing the control performance metrics of time-in-range (TIR) and time-below-range (TBR) before and after implementing the proposed algorithm, we observed a TIR improvement of 9.7% and a TBR improvement of 1.1% when comparing the proposed algorithm with conventional basal–bolus calculation algorithms. …”
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Dynamic Modeling and Simulation of Wind Turbine Unit Primary Frequency Regulation Considering Multi-domain Coupling Characteristics by Zhanyang JI, Yang HU, Lingxing KONG, Ziqiu SONG, Dan DENG, Jizhen LIU

“…Firstly, a wind farm-turbine coordinated primary frequency regulation control strategy is set up, and a rapid frequency regulation controller at the unit level is developed for both below and above the rated wind speed based on a refined 5MW wind turbine model. …”
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Bioinformatics analysis to explore biomarkers and mechanisms of action associated with endoplasmic reticulum stress and ferroptosis in Parkinson's disease. by Hao Wang, Lijuan Feng, Limeng He, Nan Liu, Yan Wan, Wei Zhang

“…Subsequently, biomarkers were validated using the least absolute shrinkage and selection operator regression algorithm. Additionally, correlations among biomarkers, gene set enrichment analysis, chromosomal and subcellular localization, immune cell infiltration, regulatory mechanisms, and drug predictions were conducted.…”
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RL-QPSO net: deep reinforcement learning-enhanced QPSO for efficient mobile robot path planning by Yang Jing, Li Weiya

“…Traditional path planning methods such as genetic algorithms, Dijkstra's algorithm, and Floyd's algorithm typically rely on deterministic search strategies, which can lead to local optima and lack global search capabilities in dynamic settings. …”
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Machine learning based multi-parameter droplet optimisation model study by Ting Li, Likun Lu, Qingtao Zeng, Kexin Liao

“…In order to achieve the accurate generation of ideal droplets in continuous inkjet devices, this paper proposes a new parameter optimisation method, BO-GP, which combines the Bayesian optimisation algorithm with computer vision, and after 50 rounds of iterations, it can converge to the optimal values of the control parameters, and successfully constructs the Pareto frontier of the control parameters. …”
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A multi-scale multi-channel CNN introducing a channel-spatial attention mechanism hyperspectral remote sensing image classification method by Ru Zhao, Chaozhu Zhang, Dan Xue

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Heuristically enhanced multi-head attention based recurrent neural network for denial of wallet attacks detection on serverless computing environment by Sarah A. Alzakari, Mohammad Alamgeer, Abdullah M. Alashjaee, Monir Abdullah, Khalid Nazim Abdul Sattar, Asma Alshuhail, Ahmad A. Alzahrani, Abdulwhab Alkharashi

“…A comprehensive set of simulations was conducted to demonstrate the promising results of the MHARNN-DoWAD method. …”
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Development of a high-performing, cost-effective and inclusive Afrocentric predictive model for stroke: a meta-analysis approach  by M Nweke, P Oyirinnaya, P Nwoha, SB Mitha, N Mshunqane, N Govender, M Ukwuoma, SC Ibeneme

“…Relying solely on statistical significance to identify predictors may compromise algorithm performance. Also, some of the existing models include expensive biomarkers that are unsuitable for resource-limited settings. …”
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Harnessing greylag goose optimization for efficient MPPT and seven-level inverter in renewable energy systems by K. Rajaram, R. Kannan

“…Limited research has been conducted on the optimization of controller gains in response to variations in a single phase load, particularly reactive load variations, across several scenarios. …”
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Yield of TB screening in prisons in Tajikistan by S. Moe, M. Asozoda, A. Aung, Z. Dusmatova, F. Akintore, E. Nshimiyimana, A. Zavqibekov, N. Sitali, W.K. Mulanda, T. Cullip, A. Sinha

“…We recommend increasing the capacity for chest X-ray testing to enhance TB prevention and control within prison settings.…”
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Forecasting motion trajectories of elbow and knee joints during infant crawling based on long–short-term memory (LSTM) networks by Jieyi Mo, Qiliang Xiong, Ying Chen, Yuan Liu, Xiaoying Wu, Nong Xiao, Wensheng Hou

“…In particular, precisely generating motion trajectories is a prerequisite to controlling exoskeleton assistive devices, and deep learning-based prediction algorithms, such as Long–Short-Term Memory (LSTM) networks, have proven effective in forecasting joint trajectories of gait. …”
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Upper limb human-exoskeleton system motion state classification based on semg: application of CNN-BiLSTM-attention model by Dongwei Zhao, Xiangming Ye, Song Wang, Chenfeng Zhang, Shouqian Sun, Xuequn Zhang, Ruidong Cheng

“…The proposed model achieved a classification accuracy of 97.29% on the test set, with an average accuracy of 88.17 ± 5.39% under leave-one-subject-out cross-validation, outperforming baseline algorithms. …”
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A Longitudinal Multimodal Dataset of Type 1 Diabetes by Ashwaq Alsuhaymi, Ahmad Bilal, Daniel Gasca García, Rujiravee Kongdee, Nicole Lubasinski, Hood Thabit, Paul W. Nutter, Simon Harper

“…The dataset includes longitudinal (3-month) real-world data collected from 17 PwT1D participants. By making this resource available, the study aims to advance algorithm development and improve diabetes management, particularly in settings where AID technology is less accessible.…”
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Security monitoring via sound analysis and voice identification with artificial intelligence by Balabanova Ivelina, Sidorova Kristina, Georgiev Georgi

“…About the achieved and analyzed results, a synthesis was conducted of a set of four informative features with the highest significance, respectively LAE (A-weighted, sound exposure level), Laeq (A-weighted, equivalent sound level), LAF (A-weighted, fast time-constant, sound level) and LAS (A-weighted, slow time constant response, sound level). …”
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Real-time temperature prediction of large-scale lithium battery module driven by data based on few measurement points by Jiajie HAN, Qingyang YUAN, Yu LI, Bo ZHANG, Ke XUE, Tian LAN

“…This database captures essential thermal characteristics of the battery module, allowing for accurate temperature predictions without exhaustive simulations. The Gappy POD algorithm is further enhanced by incorporating a correlation coefficient filtering technique, which identifies a minimal set of optimal measurement points to ensure high accuracy in the reconstructed temperature field while reducing sensor requirements. …”
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Exploring the role of ferroptosis in pemphigus: identification of diagnostic markers and regulatory mechanisms by Jing Mao, Jianping Lan, Zheyu Zhuang, Ying Chen, Ying Chen, Yushan Ou, Xinhong Su, Xueting Zeng, Fuchen Huang, Zequn Tong, Xiaoqing Lv, Xiaoqing Lv, Xiaoqing Lv, Hui Ke, Zhenlan Wu, Ying Zou, Bo Cheng, Bo Cheng, Bo Cheng, Chao Ji, Chao Ji, Chao Ji, Ting Gong

“…Immune cell infiltration was assessed using CIBERSORT and single-sample Gene Set Enrichment Analysis (ssGSEA). Finally, experimental validation was conducted through real-time quantitative PCR, transmission electron microscopy, and drug prediction.ResultsOur results identified 1,840 DEGs in pemphigus patients compared to controls, with significant enrichment in pathways such as PI3K-Akt signaling and fatty acid metabolism. …”
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Eulerian Oil Spills Model Using Finite-Volume Method with Moving Boundary and Wet-Dry Fronts by Ehsan Sarhadi Zadeh, Kourosh Hejazi

“…The solution has been achieved by the application of KPENTA algorithm for the set of the flow equations which constitutes a pentadiagonal matrix. …”
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The impact of the formal rationalization of healthcare on physician clinical teaching in a United States academic medical center by David A. Rogers, Katherine A. Meese, Cindy L. Cain

“…Session transcripts and field notes served as the data set analyzed. Results Four major categories of impact on physicians who teaching in the clinical setting were identified: (1) they hold the view that rationalizing processes will diminish positive features of practicing medicine for learners (2) the compensation plan emphasizes clinical productivity and efficiency at the expense of time to teach (3) the appropriate use of patient cares algorithms embedded in the electronic health care system is an emerging learning need that they are struggling to meet (4) this group of academic physicians is adapting in a number of ways to accommodate to these changes. …”
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Machine learning analysis of FOSL2 and RHoBTB1 as central immunological regulators in knee osteoarthritis synovium by Kun Gao, Zhenyu Huang, Zhouwei Liao, Yanfei Wang, Dayu Chen

“…Methods Differentially expressed genes between knee osteoarthritis and control synovial tissues were analyzed using the GSE55235 dataset. …”
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