A Coupled Least Absolute Shrinkage and Selection Operator–Backpropagation Model for Estimating Evapotranspiration in Xizang Plateau Irrigation Districts with Reduced Meteorological... by Qiang Meng, Jingxia Liu, Fengrui Li, Peng Chen, Junzeng Xu, Yawei Li, Tangzhe Nie, Yu Han

“…Short-term ET_O predictions for the three districts were also conducted using the mean-generating function optimal subset regression algorithm. …”
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Case-control study combined with machine learning techniques to identify key genetic variations in GSK3B that affect susceptibility to diabetic kidney diseases by Jinfang Song, Yi Xu, Liu Xu, Tingting Yang, Ya Chen, Changjiang Ying, Qian Lu, Tao Wang, Xiaoxing Yin

“…A case-control study was conducted to evaluate the predictive effect of GSK3B genetic polymorphisms on the susceptibility to DKD, with the aim of providing a theoretical basis and laboratory rationale for the prediction of the risk of developing DKD in patients with type 2 diabetes mellitus (T2DM). …”
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Increased risk of COVID-19-related admissions in patients with active solid organ cancer in the West Midlands region of the UK: a retrospective cohort study by Peter Nightingale, Fahad Mahmood, Akinfemi Akingboye, Nabeel Amiruddin, Olorunseun O Ogunwobi

“…We aim to quantify the risk of hospitalisation in patients with active cancer and use a machine learning algorithm (MLA) and traditional statistics to predict clinical outcomes and mortality.Design Retrospective cohort study.Setting A single UK district general hospital.Participants Data on total hospital admissions between March 2018 and June 2020, all active cancer diagnoses between March 2019 and June 2020 and clinical parameters of COVID-19-positive admissions between March 2020 and June 2020 were collected. 526 COVID-19 admissions without an active cancer diagnosis were compared with 87 COVID-19 admissions with an active cancer diagnosis.Primary and secondary outcome measures 30-day and 90-day post-COVID-19 survival.Results In total, 613 patients were enrolled with male to female ratio of 1:6 and median age of 77 years. …”
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Vis/NIR Spectroscopy and Vis/NIR Hyperspectral Imaging for Non-Destructive Monitoring of Apricot Fruit Internal Quality with Machine Learning by Tiziana Amoriello, Roberto Ciorba, Gaia Ruggiero, Francesca Masciola, Daniela Scutaru, Roberto Ciccoritti

“…In recent years, machine learning techniques, such as artificial neural networks (ANNs), have been successfully applied to more efficiently extract valuable information from spectral data and to accurately predict quality traits. In this study, prediction models were developed based on a multilayer perceptron artificial neural network (ANN-MLP) combined with the Levenberg–Marquardt learning algorithm. …”
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A method for high-accuracy localization of microseismic sources in mines based on finite element simulation by Dianyan NING, KaiPeng ZHU, Yongsheng ZHU, Shuxia YUAN, Zhenfang ZHOU

“…Accordingly, water inrush warnings and geologic hazard prediction can be achieved. Acoustic source localization, allowing for the localization of energy release and the early warning of potential hazards, plays a key role in this technology. …”
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Low-Carbon Slag Concrete Design Optimization Method Considering the Coupled Effects of Formwork Stripping, Strength Progress, and Carbonation Durability by Li-Na Zhang, Seung-Jun Kwon, Xiao-Yong Wang

“…Through the formulation of constraints for optimization using a genetic algorithm, the appropriate mix proportions for each design scenario are obtained. …”
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Assessment of the Maize Crop Water Stress Index (CWSI) Using Drone-Acquired Data Across Different Phenological Stages by Mpho Kapari, Mbulisi Sibanda, James Magidi, Tafadzwanashe Mabhaudhi, Sylvester Mpandeli, Luxon Nhamo

“…This study used a unmanned aerial vehicle (UAV) to remotely collect data, to use in combination with the random forest regression algorithm to detect the maize CWSI in smallholder croplands. …”
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Relationship of transforming growth factor β1 with diabetic retinopathy in type 2 diabetes by A.S. Hudz, V.A. Serhiyenko, I.V. Kudryl, V.G. Guryanov, M.I. Kovtun, S.V. Ziablitsev

“…A three-factor classification model was created on the identified features, which included a system of equations that predicted PDR with 100% accuracy. The overall prediction accuracy of the model was 88.2 % (95% CI 80.4–93.8 %). …”
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Evaluation of four clinical decision rules in children with minor head trauma: NEXUS II, PECARN, CHALICE, and CATCH by Majid Zamani, Farhad Heydari, Farzin Feyzollahi, Mehrdad Esmaillian, Amir Bahador Boroumand

“…Background: Clinical decision rules could potentially help emergency department (ED) trauma triage, allowing clinicians to prioritize treatment for the most severely injured patients.Objectives: This study evaluated and compared the diagnostic accuracy of the National Emergency X-radiography Utilization Study II (NEXUS II), the Pediatric Emergency Care Applied Research Network (PECARN), the Canadian Assessment of Tomography for Childhood Head Injury (CATCH), and the Children’s Head Injury Algorithm for the Prediction of Important Clinical Events (CHALICE) in identifying intracranial injury (ICI) in children with minor head trauma.Methods: This prospective, cross-sectional, descriptive-comparative study was conducted on children with mild head trauma who presented to the ED. …”
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H-NMR metabolomics identifies three distinct metabolic profiles differentially associated with cardiometabolic risk in patients with obesity in the Di@bet.es cohort by Enrique Ozcariz, Montse Guardiola, Núria Amigó, Sergio Valdés, Wasima Oualla-Bachiri, Pere Rehues, Gemma Rojo-Martinez, Josep Ribalta

“…In addition, H-NMR metabolomics improved the prediction of future cardiometabolic disease in comparison with models relying on just anthropometric measures. …”
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Comparison and Analysis on the Existing Single-Herbal Strategies against Viral Myocarditis by Yu Cao, Yang Liu, Tian Zhang, Jing Pan, Wei Lei, Boli Zhang

“…SLC6A2, SLC6A4, NOS2, PPARA, PPARG, ACHE, CYP2C19, CYP51A1, and CHRM2 were equally targeted by six herbs and identified as viral myocarditis-associated symbols. MCODE algorithm exposed the hub role of SRC and EGFR in strategies without Jianghuang. …”
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Cloning and Spatiotemporal Expression Analysis of <i>IGF1R</i> Gene cDNA in <i>Alopex lagopus</i> (Arctic Fox) by Wei Xu, Hualin Fu, Xiangyu Meng, Yiwen Sun, Fangyong Ning, Zhiheng Du

“…Phosphorylation site prediction identified 27 phosphorylation sites, with secondary structures dominated by α-helices (26.39%) and random coils (52.79%). …”
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Lesion assessment in multiple sclerosis: a comparison between synthetic and conventional fluid-attenuated inversion recovery imaging by Roald Ruwen Essel, Britta Krieger, Barbara Bellenberg, Dajana Müller, Theodoros Ladopoulos, Ralf Gold, Ruth Schneider, Carsten Lukas, Carsten Lukas

“…Lesion segmentation was performed using the Lesion Prediction Algorithm within the Lesion Segmentation Toolbox. …”
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HyQ2:&#x2009;A&#x2009;Hybrid&#x2009;Quantum&#x2009;Neural&#x2009;Network for&#x2009;NextG&#x2009;Vulnerability&#x2009;Detection by Yifeng Peng, Xinyi Li, Zhiding Liang, Ying Wang

“…The results show that the prediction accuracy and receiver operating characteristic AUC value fluctuate around 0.2&#x0025;, indicating HyQ2&#x2019;s robustness in noisy quantum environments. …”
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Integrated single-cell and bulk RNA dequencing to identify and validate prognostic genes related to T Cell senescence in acute myeloid leukemia by Mengyao Sha, Jun Chen, Haifeng Hou, Huaihui Dou, Yan Zhang

“…RT-qPCR verified that prognostic gene expression was consistent with the data prediction results.ConclusionCALR, CDK6, HOXA9, and PARP1 predicted disease progression and prognosis in patients with AML. …”
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An Operational Status Assessment Model for SF₆ High-Voltage Circuit Breakers Based on IAR-BTR by Ningfang Wang, Yujia Wang, Yifei Zhang, Ci Tang, Chenhao Sun

“…In recent years, the frequency of extreme weather events has been increasing, necessitating a comprehensive consideration of both internal and external factors in the operational status prediction of SF₆ high-voltage circuit breakers. …”
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New State Identification Method for Rotating Machinery under Variable Load Conditions Based on Hybrid Entropy Features and Joint Distribution Adaptation by Xiaoming Xue, Nan Zhang, Suqun Cao, Wei Jiang, Jianzhong Zhou, Liyan Liu

“…As for the training and testing set under different load conditions, all data was mapped into a reproducing space by joint distribution adaptation to reduce the distribution discrepancies between datasets, where the pseudolabels of the testing set and the final diagnostic results were obtained by the k-nearest neighbor algorithm. Finally, five cases with the training and testing set under variable load conditions were used to demonstrate the performance of the proposed method, and comparisons with some other diagnosis models combined with the same features and other dimensionality reduction methods were also discussed. …”
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Dynamic Coal Flow-Based Energy Consumption Optimization of Scraper Conveyor by Qi Lu, Yonghao Chen, Xiangang Cao, Tao Xie, Qinghua Mao, Jiewu Leng

“…The multi-objective optimization model for energy consumption is solved using the NSGA-II-ARSBX algorithm, yielding a 33.7% reduction in energy consumption, while the lump coal area is reduced by 27.7%, indicating a trade-off between energy efficiency and coal fragmentation. …”
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Smart Packet Delivery in Mobile Underwater Sensors Networks (M-CTSP) by Abdul Khan, Miguel-Angel Luque-Nieto, Ali Akbar Siddique

“…This results in a 40% rise in energy use reduction, 15% improvement in packet delivery with a 30% increase in network lifetime when compared to normal clustering-based protocols: LEACH and EECBP-FOA. …”
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Collaborative Optimization of Model Pruning and Knowledge Distillation for Efficient and Lightweight Multi-Behavior Recognition in Piglets by Yizhi Luo, Kai Lin, Zixuan Xiao, Yuankai Chen, Chen Yang, Deqin Xiao

“…In the first stage, the LAMP pruning algorithm is used to prune and optimize redundant channels, resulting in the lightweight YOLOv8-Prune. …”
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