Hydrogen-Rich Water Consumption for Acute and Residual Fatigue After Simulated Football Matches: Protocol for a Randomized, Double-Blinded, Placebo-Controlled, Parallel Trial by Michal Hruby, Karel Hulka, David Bernatik

“…These assessments will occur at critical time points: immediately post warm-up; directly following the simulated football match to detect acute fatigue; and 24, 48, and 72 hours after training sessions to detect residual fatigue. …”
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An integrated machine learning and fractional calculus approach to predicting diabetes risk in women by David Amilo, Khadijeh Sadri, Evren Hincal, Muhammad Farman, Kottakkaran Sooppy Nisar, Mohamed Hafez

“…We employ seven machine learning algorithms: Decision Tree, Logistic Regression, Support Vector Machine (SVM), Random Forest, Bagged Trees, Naive Bayes, and XGBoost, to identify key risk factors, with XGBoost demonstrating higher performance. …”
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Research on Welfare Robots: A Multifunctional Assistive Robot and Human–Machine System by Shuoyu Wang

“…In this paper, we discuss the research challenge points of human–machine welfare robot systems and their current situation using the multifunctional assistive robot as a typical example.…”
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Super Virus Machines: Faster Virus Transmission, More Efficiency Using Superchannels by Antonio Ramírez-de-Arellano-Marrero, Luis Valencia-Cabrera, David Orellana-Martín, Mario J. Pérez-Jiménez

“…The branch that approaches it from a theoretical point of view, inspired by nature, is called natural computation. …”
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Application of Machine Learning for Bulbous Bow Optimization Design and Ship Resistance Prediction by Yujie Shen, Shuxia Ye, Yongwei Zhang, Liang Qi, Qian Jiang, Liwen Cai, Bo Jiang

“…To solve the problem of insufficient accuracy in the single surrogate model, this study proposes a CBR surrogate model that integrates convolutional neural networks with backpropagation and radial basis function models. The coordinates of the control points of the NURBS surface at the bulbous bow are taken as the design variables. …”
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Gold nanobiosensors and Machine Learning: Pioneering breakthroughs in precision breast cancer detection by Soheil Sadr, Ashkan Hajjafari, Abbas Rahdar, Sadanand Pandey, Parian Poorjafari Jafroodi, Narges Lotfalizadeh, Mahdi Soroushianfar, Shahla Salimpour Kavasebi, Zelal Kharaba, Sonia Fathi-karkan, Hassan Borji

“…The integration of gold nanobiosensors with emerging technologies, including microfluidics and machine learning, opens new perspectives for personalized diagnostics and point-of-care testing in resource-constrained settings. …”
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A machine learning-based model for predicting survival in patients with Rectosigmoid Cancer. by Yifei Wang, Bingbing Chen, Jinhai Yu

“…<h4>Background</h4>The unique anatomical characteristics and blood supply of the rectosigmoid junction confer particular significance to its physiological functions and clinical surgeries. However, research on the prognosis of rectosigmoid junction cancer (RSC) is scarce, and reliable clinical prediction models are lacking.…”
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Functional Connectome Fingerprinting Through Tucker Tensor Decomposition by Vitor Carvalho, Mintao Liu, Jaroslaw Harezlak, Ana María Estrada Gómez, Joaquín Goñi

“…The human functional connectome (FC) is a representation of the functional couplings between brain regions derived from blood oxygen level-dependent (BOLD) signals. …”
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Legal aspects of functional security standardisation of the Internet of Things by P. S. Klimushyn, V. Ye. Roh, T. P. Kolisnyk

“…The functional security of the Internet of Things has been studied in terms of the security function, security completeness and resilience, which are subject to regulation in the technical requirements for the product being designed. …”
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Platelet turnover and function in end-stage renal disease by Filipov Predrag, Božić Dušan, Mijović Romana, Mitić Gorana

“…The prospective, observational clinical study included 63 ESRD patients and 30 age and sex matched healthy volunteers. Following laboratory parameters of platelet turnover and function (platelet count, reticulated platelets, platelet indices, whole blood impedance platelet aggregation), inflammatory and procoagulant markers (number of neutrophils, neutrophil to lymphocyte ratio, C-reactive protein, plasma fibrinogen, D dimer, von Willebrand factor) were obtained. …”
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The VNF Cybersecurity Dataset for Research (VNFCYBERDATA) by Believe Ayodele, Victor Buttigieg

“…Virtualisation has received widespread adoption and deployment across a wide range of enterprises and industries throughout the years. Network Function Virtualisation (NFV) is a technical concept that presents a method for dynamically delivering virtualised network functions as virtualised or software components. …”
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Modelling Soil Water Retention Using Support Vector Machines with Genetic Algorithm Optimisation by Krzysztof Lamorski, Cezary Sławiński, Felix Moreno, Gyöngyi Barna, Wojciech Skierucha, José L. Arrue

“…This work presents point pedotransfer function (PTF) models of the soil water retention curve. …”
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Best Possible Approximation Algorithms for Single Machine Scheduling with Increasing Linear Maintenance Durations by Xuefei Shi, Dehua Xu

“…We consider a single machine scheduling problem with multiple maintenance activities, where the maintenance duration function is of the linear form ft=a+bt with a≥0 and b>1. …”
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Machine learning models highlight environmental and genetic factors associated with the Arabidopsis circadian clock by Connor Reynolds, Joshua Colmer, Hannah Rees, Ehsan Khajouei, Rachel Rusholme-Pilcher, Hiroshi Kudoh, Antony N. Dodd, Anthony Hall

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A Planar-Dimensions Machine Vision Measurement Method Based on Lens Distortion Correction by Qiucheng Sun, Yueqian Hou, Qingchang Tan, Guannan Li

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Detection of mite infested saffron plants using aerial imaging and machine learning classifier by Hossein Sahabi, Jalal Baradaran-Motie

“…In order to detect affected plants, two support vector machine (SVM) classifiers with radial basis function (RBF) kernels were used separately for NIR and RGB images. …”
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Industrial data-driven machine learning soft sensing for optimal operation of etching tools by Feiyang Ou, Henrik Wang, Chao Zhang, Matthew Tom, Sthitie Bom, James F. Davis, Panagiotis D. Christofides

“…For example, artificial intelligence (AI) machine learning-based soft sensors can increase operational productivity and machine tool performance while still ensuring that critical product specifications are met. …”
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Geological model calibration based on gradual deformation and connectivity function by Junhao Jin, Shaohua Li, Jun Li, Fang Ding

“…This involves defining and minimizing an objective function, which quantifies the mismatch between the model connectivity function and the connectivity data. …”
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Progress and prospect of surface self-cleaning technology of machine vision system in underground mining by Shengli YANG, Yongsheng CHEN, Jiachen WANG, Lianghui LI, Fengqi LIU, Shixiong SONG, Dingheng HUI

“…The technical challenges faced by the underground mining machine vision system are pointed out from three aspects: comprehensive self-cleaning strategy, optimization of explosion-proof design and multi-functionalization of lens film materials. …”
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LINEAR GENERATOR PROTOTYPE WITH VERTICAL CONFIGURATION OF SEA WAVE POWER PLANT by Ane Prasetyowati, Wisnu Broto, Noor Suryaningsih

“…The application of the ocean wave energy conversion technology, a linear generator system is an electrical machine that functions to convert the mechanical energy of linear motion into electrical energy using the principle of electromagnetic induction. …”
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