Spectral Fingerprinting of Tencha Processing: Optimising the Detection of Total Free Amino Acid Content in Processing Lines by Hyperspectral Analysis by Qinghai He, Yihang Guo, Xiaoli Li, Yong He, Zhi Lin, Hui Zeng

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Improving the Performance of Electrotactile Brain–Computer Interface Using Machine Learning Methods on Multi-Channel Features of Somatosensory Event-Related Potentials by Marija Novičić, Olivera Djordjević, Vera Miler-Jerković, Ljubica Konstantinović, Andrej M. Savić

“…We systematically tested classification performance using machine learning algorithms, including logistic regression, k-nearest neighbors, support vector machines, random forests, and artificial neural networks. …”
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Real world pharmacovigilance study of antineoplastic drug related vitiligo risks by Yixuan Yang, Hanzhang Xie, Dongtao Li, Ying Jia, Bingnan Cui, Jianhua Zou, Zhanshuo Xiao

“…A significant statistical association was considered when a drug signal met the criteria of all four algorithms. Our analysis of the FAERS database revealed 533 adverse event (AE) reports implicating antineoplastic drugs in the development of vitiligo, with a higher prevalence among females compared to males. …”
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Deep learning approach with ConvNeXt-SE-attn model for in vitro oral squamous cell carcinoma and chemotherapy analysis by Abhay Nath, Om Roy, Priyanka Silveri, Sanskruti Patel

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Proportional myoelectric control of a virtual bionic arm in participants with hemiparesis, muscle spasticity, and impaired range of motion by Caleb J. Thomson, Fredi R. Mino, Danielle R. Lopez, Patrick P. Maitre, Steven R. Edgley, Jacob A. George

“…Ten stroke survivors and ten healthy, aged-matched controls completed a target-touching task with the virtual bionic arm. We compared the signal-to-noise ratio (SNR) of the recorded electromyography (EMG) signals used to train the control algorithms and the task performance using root mean square error, percent time in target, and maximum hold time within the target window. …”
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A novel approach to wind energy modeling in the context of climate change at Zaafrana region in Egypt by Bassem Khaled Kamel, Almoataz Y. Abdelaziz, Mahmoud A. Attia, Amr Khaled Khamees

“…Abstract Global warming, driven by the excessive emission of greenhouse gases from the combustion of fossil fuels, has emerged as a critical environmental challenge which is considered as a motivation for this research. Where, the switch to sustainable energy sources is crucial because of the pressing need to slow down climate change and lower carbon footprints. …”
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Spectral divergence prioritizes key classes, genes, and pathways shared between substance use disorders and cardiovascular disease by Everest Castaneda, Everest Castaneda, Elissa Chesler, Erich Baker

“…The graph clustering method simultaneously provides insight into the specific biological pathways underlying these distinctions and may reveal future basic and clinical research avenues into addressing the cardiovascular sequelae of SUD.…”
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Agricultural Machinery Path Tracking with Varying Curvatures Based on an Improved Pure-Pursuit Method by Jiawei Zhou, Junhao Wen, Liwen Yao, Zidong Yang, Lijun Xu, Lijian Yao

“…The current research on path tracking primarily focuses on improving control algorithms, such as adaptive and predictive models, to enhance tracking accuracy and stability. …”
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Prediction of successful weaning from renal replacement therapy in critically ill patients based on machine learning by Qiqiang Liang, Xin Xu, Shuo Ding, Jin Wu, Man Huang

“…Multiple logistic regression (MLR) and machine learning algorithms were adopted to construct the prediction models.Results A total of 976 patients were included, with 349 patients successfully weaned off RRT. …”
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Analysis of spatio-temporal fungal growth dynamics under different environmental conditions by Liselotte De Ligne, Guillermo Vidal-Diez de Ulzurrun, Jan M. Baetens, Jan Van den Bulcke, Joris Van Acker, Bernard De Baets

“…Abstract Traditionally, fungal growth dynamics were assessed manually, limiting the research to a few environmental conditions and/or fungal species. …”
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Decentralized energy trading in smart grid using secured post quantum encryption by S. Sofana Reka, Anantharaman Prasad, Prakash Venugopal, Fawaaz Sammil, Visakh Pradeep, Swaroop S Kaimal, Manoj Kumar Rajagopal

“…We explore post-quantum cryptographic techniques, particularly lattice-based algorithms due to its compact signature sizes and strong security capability for the future-proof blockchain enabled smart grids. …”
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Assessment of sensor driven automatic smart soil and paddy seed metering mechanisms using artificial intelligence for paddy nurseries by Vinod Choudhary, Rajendra Machavaram, Prakhar Patidar, Gajendra Singh, Naseeb Singh, Lokesh Kumawat

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Identifying mating events of group-housed broiler breeders via bio-inspired deep learning models by Venkat U.C. Bodempudi, Guoming Li, J. Hunter Mason, Jeanna L. Wilson, Tianming Liu, Khaled M. Rasheed

“…The objective of this research was to develop Deep learning models (DLM) to identify mating behavior based on bird count changes and bio-characteristics of mating. …”
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Identification and validation of neutrophil-related biomarkers in acute-on-chronic liver failure by Wei Lin, Yongping Chen, Yongping Chen, Mingqin Lu, Cheng Peng, Cheng Peng, Xiang Chen, Xiang Chen, Xiaoqin Liu, Yunyun Wang, Yunyun Wang

“…However, additional research is required to substantiate the effects of these key genes and therapeutic agents on ACLF.…”
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Application of Mask R-CNN for automatic recognition of teeth and caries in cone-beam computerized tomography by Yujie Ma, Maged Ali Al-Aroomi, Yutian Zheng, Wenjie Ren, Peixuan Liu, Qing Wu, Ye Liang, Canhua Jiang

“…This study evaluates the efficacy of deep learning algorithms for detecting and diagnosing dental caries using cone-beam computed tomography (CBCT) with the Mask R-CNN architecture while comparing various hyperparameters to enhance detection. …”
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Coronary Heart Disease Risk Prediction Model Based on Machine Learning by YUE Haitao, HE Chanchan, CHENG Yuyou, ZHANG Sencheng, WU You, MA Jing

“…However, the issue of data imbalance in these studies is often overlooked, despite its crucial role in enhancing the accuracy of CHD risk identification within classification algorithms. Objective To investigate the factors influencing CHD and to establish predictive models for CHD risk using two data balancing methods based on five algorithms, comparing the predictive value of these models for CHD risk. …”
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NeuroSense: A Novel EEG Dataset Utilizing Low-Cost, Sparse Electrode Devices for Emotion Exploration by Tommaso Colafiglio, Angela Lombardi, Paolo Sorino, Elvira Brattico, Domenico Lofu, Danilo Danese, Eugenio Di Sciascio, Tommaso Di Noia, Fedelucio Narducci

“…We develop a comprehensive preprocessing pipeline and employ machine learning algorithms to translate EEG data into meaningful insights about emotional states. …”
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Cost-of-illness of gastroenteritis caused by rotavirus in Chinese children less than 5 years by Xiao-Li Fu, Yan Ma, Zheng Li, Yang-Yang Qi, Si-Jie Wang, Li-Jun Fu, Song-Mei Wang, Lorenz von Seidlein, Xuan-Yi Wang

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Implementation of Machine Vision Methods for Cattle Detection and Activity Monitoring by Roman Bumbálek, Tomáš Zoubek, Jean de Dieu Marcel Ufitikirezi, Sandra Nicole Umurungi, Radim Stehlík, Zbyněk Havelka, Radim Kuneš, Petr Bartoš

“…The goal of this research was to implement machine vision algorithms in a cattle stable to detect cattle in stalls and determine their activities. …”
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Analysis of soil salinization and land use change under water conservation retrofit in the Hetao irrigation district by Yi Zhao, Shuya Yang, Haibin Shi, Haoqi Han, Yunlei Dong, Xianyue Li, Jianwen Yan, Yan Yan, Xu Dou, Feng Tian, Qingfeng Miao

“…We establish soil sampling sites in this region, employ Google Earth Engine algorithms to develop models for soil salinity inversion and land use classification, and analyze the change patterns of land salinization and land use types. …”
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