ON THE EXPEDIENCY AND DIRECTIONS OF IMPROVING THE METHODOLOGY OF TEACHING STUDENTS MATERIAL OF THE CONTENT LINE "FUNCTIONS AND THEIR GRAPHS" by Тетяна Года, Олександр Школьний

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Prediction of Soil Field Capacity and Permanent Wilting Point Using Accessible Parameters by Machine Learning by Liwei Liu, Xingmao Ma

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Correlations Between Cognitive and Social Functioning of Schoolchildren: Study of Population Data Using methods of intellectual Analysis of heterogeneous Data by Leyla S. Namazova-Baranova, Georgiy A. Karkashadze, Elena A. Vishnyova, A. I. Molodchenko

Subjects: “…machine learning…”
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LMO2 confers value as a potential immunotherapy marker in pan-cancer analysis and inhibits progression of Clear Cell Renal Cell Carcinoma by Huiping Wang, Cong Wang, Jia Wei, Xuan’er Zhao, Xuemei Yang, Renren Li, Mengmeng Li, Zhansheng Zhu

“…Background: Emerging evidence highlights LIM-domain only 2 (LMO2) as both a potential biomarker and therapeutic target in diverse cancers. However, its functional characterization and clinical significance remain insufficiently explored in cancers such as Clear Cell Renal Cell Carcinoma (ccRCC). …”
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A model of digital transformation of the learning process in higher education by Olga V. Ivanova

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Comparative Evaluation of Clear Twin Block and Conventional Twin Block in the Correction of Skeletal Class II Malocclusion: A Systematic Review and Meta-Analysis by Shubhangi Amit Mani, Vinaya Kumar Kulkarni, Dhananjay Gandage, Vikranth Omprakash Shetty, Sourabh Ramesh Joshi, Vandana Tripathi

“…TB in comparison with clear TB (CTB) has disadvantage of being a bulky appliance and limited patient acceptance. …”
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Identification of key genes CCL5, PLG, LOX and C3 in clear cell renal cell carcinoma through integrated bioinformatics analysis by Zhenwei Xie, Cheng Feng, Yude Hong, Libo Chen, Mingyong Li, Weiming Deng

“…BackgroundClear Cell Renal Cell Carcinoma (ccRCC) is a malignant tumor with high mortality and recurrence rates and the molecular mechanism of ccRCC genesis remains unclear. …”
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COL6A2 in clear cell renal cell carcinoma: a multifaceted driver of tumor progression, immune evasion, and drug sensitivity by Yashuang Yang, Ruixin Fan, Boming Zhang, Kai Liu

“…Abstract Background Renal Cell Carcinoma (RCC) is a leading cause of cancer-related mortality worldwide, with Clear Cell Renal Cell Carcinoma (ccRCC) comprising 75% of cases. …”
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Deep learning-based feature selection for detection of autism spectrum disorder by Ibrahim Nafisah, Nermine Mahmoud, Ahmed A. Ewees, Mohamed G. Khattap, Abdelghani Dahou, Safar M. Alghamdi, Ibrahim A. Fares, Mohammed Azmi Al-Betar, Mohammed Azmi Al-Betar, Mohamed Abd Elaziz, Mohamed Abd Elaziz

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Learning Constitutive Relations From Soil Moisture Data via Physically Constrained Neural Networks by Toshiyuki Bandai, Teamrat A. Ghezzehei, Peishi Jiang, Patrick Kidger, Xingyuan Chen, Carl I. Steefel

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Functional unknomics: Systematic screening of conserved genes of unknown function. by João J Rocha, Satish Arcot Jayaram, Tim J Stevens, Nadine Muschalik, Rajen D Shah, Sahar Emran, Cristina Robles, Matthew Freeman, Sean Munro

“…Knockdown of some genes resulted in loss of viability, and functional screening of the rest revealed hits for fertility, development, locomotion, protein quality control, and resilience to stress. …”
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Study of Heart Rate Variability to Comprehend the Significance of Singing Bowl Meditation on the Functioning of the Autonomic Nervous System by Ritika Upadhyay, Biswajeet Champaty, Suraj Kumar Nayak

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Analysis of Electron Distribution Functions From the Magnetospheric Multiscale (MMS) Mission Using the Gaussian Mixture Model by Beniamino Sanò, Nathan N. Maes Anno, David L. Newman, Marty Goldman, Francesco Valentini, Denise Perrone, Giovanni Lapenta

Subjects: “…unsupervised machine learning…”
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Integration of multimodal imaging data with machine learning for improved diagnosis and prognosis in neuroimaging by Saurabh Bhattacharya, Sashikanta Prusty, Sanjay P. Pande, Monali Gulhane, Santosh H. Lavate, Nitin Rakesh, Saravanan Veerasamy

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Deep Reinforcement Learning for Control of Time-Varying Musculoskeletal Systems With High Fatigability: A Feasibility Study by Jessica Abreu, Douglas C. Crowder, Robert F. Kirsch

Subjects: “…Reinforcement learning…”
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Evaluation of Rehabilitation Outcomes in Patients with Chronic Neurological Health Conditions Using a Machine Learning Approach by Gabriele Santilli, Massimiliano Mangone, Francesco Agostini, Marco Paoloni, Andrea Bernetti, Anxhelo Diko, Lucrezia Tognolo, Daniele Coraci, Federico Vigevano, Mario Vetrano, Maria Chiara Vulpiani, Pietro Fiore, Francesca Gimigliano

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MOMFNet: A Deep Learning Approach for InSAR Phase Filtering Based on Multi-Objective Multi-Kernel Feature Extraction by Xuedong Zhang, Cheng Peng, Ziqi Li, Yaqi Zhang, Yongxuan Liu, Yong Wang

“…This research provides important insights into the application of deep learning for InSAR denoising.…”
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Multi-Functional Optical Spectrum Analysis Using Multi-Task Cascaded Neural Networks by Haoyu Wang, Sheng Cui, Changjian Ke, Chenglong Yu, Zi Liang, Deming Liu

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The Use of Neural Networks in Distance Education Technologies for the Identification of Students by O. A. Kozlova, A. A. Protasova

Subjects: “…distance learning…”
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Prediction of suspended sediment concentration in fluvial flows using novel hybrid deep learning model by Sadra Shadkani, Yousef Hemmatzadeh, Amirreza Pak, Soroush Abolfathi

“…The proposed framework integrates feedforward neural networks (FFNN), long short-term memory (LSTM) networks, stochastic gradient descent (SGD), and radial basis function (RBF) models, augmented with a first-order differencing technique. …”
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