A Novel Dataset for Early Cardiovascular Risk Detection in School Children Using Machine Learning by Rafael Alejandro Olivera Solís, Emilio Francisco González Rodríguez, Roberto Castañeda Sheissa, Juan Valentín Lorenzo-Ginori, José García

“…The models were assessed using a stratified k-fold cross-validation approach to enhance the reliability of the findings. …”
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Feasibility and case studies on converting small hydropower stations to pumped storage by Yangqing Dan, Qingyue Chen, Daren Li, Wenhuan Bai, Weiming Zhou, Anyu Yang, Jia Yang

“…This study utilizes data from small hydropower stations and advanced software algorithms to preliminarily evaluate the feasibility of converting conventional small hydropower stations in Zhejiang Province into pumped storage hydropower stations, with the province serving as the focal research area. …”
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Extracting Information from Unstructured Medical Reports Written in Minority Languages: A Case Study of Finnish by Elisa Myllylä, Pekka Siirtola, Antti Isosalo, Jarmo Reponen, Satu Tamminen, Outi Laatikainen

“…This underscores the need for localised datasets and models, particularly for minority languages with unique grammatical structures.…”
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Enhanced quantitation of pathological α-synuclein in patient biospecimens by RT-QuIC seed amplification assays. by Ankit Srivastava, Qinlu Wang, Christina D Orrù, Manel Fernandez, Yaroslau Compta, Bernardino Ghetti, Gianluigi Zanusso, Wen-Quan Zou, Byron Caughey, Catherine A A Beauchemin

“…Using ED αSyn RT-QuIC as a model SAA, we show how to markedly improve the inter-assay reproducibility and quantitative accuracy. …”
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Lightweight defocus deblurring network for curved-tunnel line scanning using wide-angle lenses by Shaojie Qin, Taiyue Qi, Xiaodong Huang, Xiao Liang

“…While existing deblurring algorithms can improve image quality, they often prioritize results over inference time, which is not ideal for high-speed tunnel image acquisition. …”
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Enhancing prediction of fluid-saturated fracture characteristics using deep learning super resolution by Manju Pharkavi Murugesu, Vignesh Krishnan, Anthony R. Kovscek

“…While past literature has offered solutions to improve resolution of CT rock images, including deep learning-based algorithms, our study uniquely focuses on improving dynamic, partially and fully fluid-saturated geological images. …”
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A Comparative Study of Breast Cancer Detection and Recurrence Prediction Using CatBoost Classifier by Rana Dhia’a Abdu-aljabar, Khansaa Dheya Aljafaar, Zinah Jaffar Mohammed Ameen, Hala A. Naman

“…The goal is to evaluate models using key metrics (sensitivity, specificity, precision, F1 score, accuracy, ROC, and AUC score). …”
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Mapping the landscape of Artificial intelligence for serious games in Health: An enhanced meta review by Xiya Tao, Nicolás Sáenz-Lechón, Martina Eckert

“…This paper presents an enhanced meta-review of artificial intelligence (AI) applications in serious games (SGs) for health, focusing on adaptation, personalisation, and real-time data processing to improve rehabilitation outcomes. A systematic review methodology, following PRISMA-ScR guidelines, was employed to analyse studies from 2017 to 2025, identifying the AI algorithms most frequently used to personalise gaming experiences, improve patient engagement, and increase treatment efficacy. …”
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Optimized Two-Stage Anomaly Detection and Recovery in Smart Grid Data Using Enhanced DeBERTa-v3 Verification System by Xiao Liao, Wei Cui, Min Zhang, Aiwu Zhang, Pan Hu

“…The recovery mechanism achieves remarkably precise restoration with a mean absolute error (MAE) of only 0.0055 kWh, representing a 99.91% improvement compared to traditional ARIMA models and 98.46% compared to standard Anomaly Transformer models. …”
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Enhancing Efficiency and Reducing the Carbon Footprint of Cloud-Based Healthcare Applications through Optimal Data Preprocessing by El Aziz Btissam, Eddabbah Mohammed, Laaziz Yassin

“…Our results demonstrate that the impact of preprocessing on both accuracy and processing speed varies depending on the algorithm and the type of preprocessing applied. Notable improvements in precision and processing time reductions of up to 35% were observed, highlighting the potential of preprocessing to enhance the performance and sustainability of ML algorithms.…”
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Health poverty reduction effect of medical insurance in China’s middle-aged and elderly populations: a cross-sectional study by Haijun Yang, Rui Chen, Ye Li, Qunhong Wu, Linghan Shan, Bing Wu, Fang Yin, Yiyun Zhang, Yongqiang Lai, Xinwei Liu, Wanxin Tian, Xiyu Zhang, Yujuan Xu, Wenqing Miao, Baoguo Shi, Feifei Leng

“…Objectives In the context of demographic structure and disease spectrum changes: to study the role of the medical insurance system in providing protection and risk resilience for middle-aged and elderly vulnerable groups who are prone to impoverishment by medical expenses (IME), identify the vulnerable points and propose recommendations for improving the medical insurance system.Setting The research used data from the 2018 China Health and Retirement Longitudinal Study.Participants 9184 households were included in the research ultimately.Primary and secondary outcome measures We use the WHO’s recommended composite measure of disease-related poverty and algorithm to determine the occurrence of IME in households. …”
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A New LQR Optimal Control for a Single-Link Flexible Joint Robot Manipulator Based on Grey Wolf Optimizer by Navid Razmjooy, Mehdi Ramezani, Ali Namadchian

“…By considering the proposed performance index and comparing with the PSO-based controller as a popular algorithm, the superiority of the proposed LQR controller in improving the stability and performance of the manipulator is shown. …”
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LEO satellite Internet resource allocation strategy based on terminal traffic prediction by SHEN Fei, LYU Chengcheng, ZHANG Jiaxuan, RUAN Xiaoting

“…A resource allocation strategy for the low earth orbit (LEO) satellite Internet based on terminal traffic prediction was proposed to address the problems of blind coverage spots in ground network and the low resource utilization of satellite network. An improved LSTM-ARIMA algorithm was proposed with real datasets by the strategy to accurately predict the data traffic generated in the ground area over a certain period of time in the future. …”
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Congestion Influence on Optimal Bidding in a Competitive Electricity Market using Particle Swarm Optimization by OICC Press Authors

“…Electricity market plays an important role in improving the economics of electrical power system. …”
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HEVC information hiding approach based on intra prediction modes modulation by Jie YANG, Song-bin LI, Hao-jiang DENG

“…For further improving the embedding efficiency in the processing of HEVC information hiding,a method for HEVC information hiding based on intra prediction models modulation was proposed.The space lattice dimen-sion N(N = 2,3,4)of each CTU was generated according to the key.The selection rule of intra prediction mode was utilized to select N modes which were located at vertex angle.The N modes were mapped to the value F through the space lattice mapping algorithm.Then N bits secret information were read from the bit file and converted to a deci-mal number D.In this way,N secret information bits were embedded in N intra prediction modes by modifying at most one mode.The experimental results approve that the proposed method has high embedding efficiency,small rate increase and minimal influence on the video quality and the anti-steganalysis experiment confirms that the pro-posed method has high concealment.…”
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Approximate solution of higher-order oscillatory differential equations via modified linear block techniques by Folashade Mistura Jimoh, Adam Ajimoti Ishaq, Kazeem Issa

“…In many areas of science and engineering, problems modeled by ordinary differential equations (ODEs) often lack analytical solutions, requiring the use of numerical methods for approximation. …”
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Deep learning radiomics and mediastinal adipose tissue-based nomogram for preoperative prediction of postoperative‌ brain metastasis risk in non-small cell lung cancer by Ye Niu, Hao-Bo Jia, Xue-Meng Li, Wen-Juan Huang, Ping-Ping Liu, Le Liu, Zeng-Yao Liu, Qiu-Jun Wang, Yuan-Zhou Li, Shi-Di Miao, Rui-Tao Wang, Ze-Xun Duan

“…Multivariate logistic regression identified independent BM predictors, which were incorporated into a nomogram. Model performance was assessed via area under the receiver operating characteristic curve (AUC), calibration plots, integrated discrimination improvement (IDI), net reclassification improvement (NRI), and decision curve analysis (DCA). …”
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A strategy for network multi-layer information fusion based on multimodel in user emotional polarity analysis by Ronghua Wang, Peng Zhuang

“…The study employed multiple emotional analysis models to analyze emotions in text data. Then the emotional analysis results of different models were integrated to improve accuracy through a hierarchical information fusion strategy. …”
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Genomic selection for meat quality traits based on VIS/NIR spectral information by Xi Tang, Lei Xie, Min Yan, Longyun Li, Tianxiong Yao, Siyi Liu, Wenwu Xu, Shijun Xiao, Nengshui Ding, Zhiyan Zhang, Lusheng Huang

“…Therefore, it is meaningful to investigate the incorporation of VIS/NIRS information into GS models to establish an efficient and low-cost breeding model. …”
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First In-Orbit Validation of Interferometric GNSS-R Altimetry: Mission Overview and Initial Results by Yixuan Sun, Yueqiang Sun, Junming Xia, Lingyong Huang, Qifei Du, Weihua Bai, Xianyi Wang, Dongwei Wang, Yuerong Cai, Lichang Duan, Zhenhe Zhai, Bin Guan, Zhiyong Huang, Shizhong Li, Feixiong Huang, Cong Yin, Rui Liu

“…We developed a refined DM waveform-matching algorithm that precisely extracts the propagation delays between reflected and direct GNSS signals, enabling the retrieval of global sea surface height (SSH) through the interferometric altimetry model. …”
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