Design and Prototype Verification of a 3-meter Aperture Wrap-rib Reflector by ZHANG Han, YAN Zhongxi, XIANG Ping, WU Minger

“…The shape of the lenticular tube wrap-rib was optimized by combining the form-finding analysis of the flexible reflector with the genetic algorithm. Finally, a reflector prototype was designed and assembled, and the deploying test, fundamental frequency test and surface accuracy measurement were carried out.Results and Discussions　Adding a wrapping guide to the root area of CFRP lenticular tube wrap-rib can prevent excessive wrapping stress in this area and improve the wrapping performance of the wrap-rib reflector. …”
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AAMS-YOLO: enhanced farmland parcel detection for high-resolution remote sensing images by Binyao Wang, Ya’nan Zhou, Weiwei Zhu, Li Feng, Jinke He, Tianjun Wu, Jiancheng Luo, Xin Zhang

“…Detecting farmland parcels in high-resolution remote sensing images is challenging in smallholder farming systems in China, characterized by fragmented plots, irregular shapes, and varying scales. To improve detection accuracy in these contexts, this study proposes AAMS-YOLO, a YOLO-based farmland parcel detection model. …”
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Image-Based Detection and Classification of Malaria Parasites and Leukocytes with Quality Assessment of Romanowsky-Stained Blood Smears by Jhonathan Sora-Cardenas, Wendy M. Fong-Amaris, Cesar A. Salazar-Centeno, Alejandro Castañeda, Oscar D. Martínez-Bernal, Daniel R. Suárez, Carol Martínez

“…This system’s adaptability to low-resource settings underscores its potential to improve malaria diagnostics globally.…”
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Clinical characteristics and mortality of patients with heart failure in Southern Sweden from 2013 to 2019: a population-based cohort study by Awais Ashfaq, Madlaina Costa-Scharplatz, Björn Agvall, Jason Davidge, Kristina Malene Ødegaard, Mattias Olsson

“…Furthermore, 1-year all-cause mortality was significantly higher among patients with HF who had not undergone a conclusive echocardiography at diagnosis, highlighting the importance of correct diagnostic procedure to improve treatment strategies and outcomes.…”
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A simple pedotransfer function to estimate fine fraction organic carbon contents of surface horizons in French soils by Eva Rabot, Pierre Barré, Claire Chenu, Amicie A. Delahaie, Manuel P. Martin, José-Luis Munera-Echeverri, Nicolas P.A. Saby

“…., fine fraction organic carbon (OCfine) and coarse fraction organic carbon, to improve our ability to understand controlling factors and predict SOC contents and SOC stability. …”
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Intraoperative hypotension prediction in cardiac and noncardiac procedures: is HPI truly worthwhile? A systematic review and meta-analysis by Erfan Shirmohamadi, Reza Hosseini Dolama, Narjes Mohammadzadeh, Navid Ebrahimi, Negar Ghasemloo

“…Studies were included if they utilized machine learning algorithms, including HPI, to predict or detect IOH in adult surgical patients. …”
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Exploring Machine Learning Classification of Movement Phases in Hemiparetic Stroke Patients: A Controlled EEG-tDCS Study by Rishishankar E. Suresh, M S Zobaer, Matthew J. Triano, Brian F. Saway, Parneet Grewal, Nathan C. Rowland

“…We hypothesized that transcranial direct current stimulation (tDCS), a form of NIBS, would enhance EEG signals related to movement phases and improve classification accuracy compared to sham stimulation. …”
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Spironolactone Reduces the Risk of Death in Veterans With Heart Failure With Preserved Ejection Fraction by Katherine E. Kurgansky, Rachel Parker, Luc Djousse, David R. Gagnon, Jacob Joseph

“…Results from explanatory clinical trials suggest that spironolactone may help to improve outcomes in patients with HFpEF. We sought to investigate the effectiveness of spironolactone in reducing death and hospitalization outcomes for patients with HFpEF in a real‐world setting. …”
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Jointly Optimized Placement of Application VM and VNF in NFV Based Data Center by Dandan Qi, Ruijun Gu

“…Finally, through a large number of experiments, compared with the algorithms that deal with the AppVM and VNF placement separately, the advantages of the proposed joint optimization methods in improving the request acceptance rate are verified.…”
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Non-invasive detection of Parkinson’s disease based on speech analysis and interpretable machine learning by Huanqing Xu, Wei Xie, Mingzhen Pang, Ya Li, Luhua Jin, Fangliang Huang, Xian Shao

“…SHAp values highlighted the importance of fundamental frequency variation and harmonic-to-noise ratio in distinguishing PD patients from healthy individuals.ConclusionThe developed machine learning model accurately predicts Parkinson’s disease using speech recordings, with Random Forest and Gradient Boosting algorithms demonstrating superior performance. …”
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Machine Learning with Evolutionary Parameter Tuning for Singing Registers Classification by Tales Boratto, Gabriel de Oliveira Costa, Alexsandro Meireles, Anna Klara Sá Teles Rocha Alves, Camila M. Saporetti, Matteo Bodini, Alexandre Cury, Leonardo Goliatt

“…Thus, the present article proposes a novel approach that leverages the Differential Evolution (DE) algorithm to optimize hyperparameters within three selected ML models, with the aim of classifying singing-voice registers i.e., chest, mixed, and head registers). …”
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Machine Learning-Based Interpretable Screening for Osteoporosis in Tuberculosis Spondylitis Patients Using Blood Test Data: Development and External Validation of a Novel Web-Based... by Yasin P, Ding L, Mamat M, Guo W, Song X

“…The model demonstrated robust predictive performance and was effectively integrated into a user-friendly online application, offering a practical solution to enhance surgical decision-making and improve patient outcomes in real-time clinical settings.Keywords: tuberculosis spondylitis, osteoporosis, machine learning, threshold tuning, logistic regression…”
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A novel data-driven based high-precision building roof contour full-automatic extraction and structured 3D reconstruction method combining stereo images and LiDAR points by Xiongwu Xiao, Kai Wang, Zhichao Zhong, Wenhu Qu, Weiwei Wu, Zhigao Cui, Yanzhao Su, Aihua Li, Jianya Gong, Deren Li

“…Firstly, an improved Sobel-based-operator is designed, which effectively improves the detection rate of building-edge-features. …”
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Optimal sleep time controller based on traffic prediction and residual energy in duty-cycled wireless sensor networks by Haibo Luo, Minghua He, Zhiqiang Ruan, Xiaxia Zeng

“…Performance results show that our proposed algorithms can balance power consumption among nodes and improve power efficiency while guaranteeing packet latency is minimized.…”
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Integrating artificial Intelligence-Based metaheuristic optimization with Machine learning to enhance Nanomaterial-Containing latent heat thermal energy storage systems by Ali Basem, Hanaa Kadhim Abdulaali, As’ad Alizadeh, Pradeep Kumar Singh, Komal Parashar, Ali E. Anqi, Husam Rajab, Pancham Cajla, H. Maleki

“…The proposed strategy combines machine learning algorithms, including multilayer perceptron neural network (MLPNN), generalized additive model (GAM), Gaussian kernel regression (GKR), support vector machine (SVM), and Gaussian process regression (GPR) with artificial intelligence-based metaheuristic optimization algorithms (PSO and GA) to optimize their structural/training parameters. …”
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Integrative machine learning and bioinformatics analysis to identify cellular senescence-related genes and potential therapeutic targets in ulcerative colitis and colorectal cancer by Tianle Xue, Yunpeng Chen, Xiaomeng Li, Zhixiang Zhou, Qiyang Chen

“…An integrated machine learning (IML) model—utilizing 12 algorithms with 10-fold cross-validation—was constructed to pinpoint key diagnostic biomarkers. …”
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Early detection of woody plant encroachment in Canadian prairies using UAV imagery and transformer-based deep learning by Yihan Pu, Xiaojing Lu, Irini Soubry, Xulin Guo

“…Transfer learning improved the model performance in SegFormer by more than 5 % in the mF1-score and 7 % in mIoU. …”
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Experimental investigation of shaft misalignment effects on bearing reliability through vibration signal analysis using machine learning and deep learning by Fransiskus Tatas Dwi Atmaji, Jamasri, Hari Agung Yuniarto, I Made Miasa

“…Statistical time-domain feature extraction notably improved the performance of classical models, with KNN achieving a maximum accuracy of 92.9%. …”
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Cotton Crop Classification using Optical and Microwave Remote Sensing Datasets in Google Earth Engine by B. Meerasha, M. Sagayam

“…The classification of cotton, cropland and non-cropland model produced with producers accuracy of 98%, 88% and 90%. …”
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The impact of artificial intelligence on medical diagnostics: A letter to the editor by Sahar Imtiaz, Sheikh Abdul Qadir Jillani

“… Madam, Artificial intelligence (AI) describes the generation of intelligent machines that are capable of carrying out activities that usually call for human intellect. (1) It involves creating algorithms and models that enable computers to learn from and analyze vast amounts of data, recognize patterns, make decisions, and even engage in natural language processing…”
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