Machine‐Learning‐Assisted Design and Optimization of Single‐Atom Transition Metal‐Incorporated Carbon Quantum Dot Catalysts for Electrocatalytic Hydrogen Evolution Reaction by Unbeom Baeck, Min‐Cheol Kim, Duong Nguyen Nguyen, Jaekyum Kim, Jaehyoung Lim, Yujin Chae, Namsoo Shin, Heechae Choi, Joon Young Kim, Chan‐Hwa Chung, Woo‐Seok Choe, Ho Seok Park, Uk Sim, Jung Kyu Kim

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A blockchain based deep learning framework for a smart learning environment by Shimaa Ouf, Soha Ahmed, Yehia Helmy

“…Many educational institutions shifted to depend on the smart learning process but expressed concern about this solution due to its various challenges in securing the learning process and learners’ data. …”
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CrackVision: Effective Concrete Crack Detection With Deep Learning and Transfer Learning by Abdulrahman A. Alkannad, Ahmad Al Smadi, Shuyuan Yang, Mutasem K. Al-Smadi, Moeen Al-Makhlafi, Zhixi Feng, Zhenlong Yin

“…Crack evaluation is critical for assessing the structural integrity of concrete, significantly impacting safety, functionality, and durability. In response to the growing demand for more advanced crack detection techniques, this paper presents CrackVision, an advanced framework that leverages Transfer Learning (TL) to enhance traditional methods of concrete crack detection. …”
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Learned helplessness and learned controllability: from neurobiology to cognitive, emotional and behavioral neurosciences by Gustavo E. Tafet, Tomas Ortiz Alonso

“…Repeated perception of lack of control may lead to learned helplessness, which has been linked to the development of depression. …”
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Exploring the VAK model to predict student learning styles based on learning activity by Ahmed Rashad Sayed, Mohamed Helmy Khafagy, Mostafa Ali, Marwa Hussien Mohamed

“…Our results show that the Random Forest algorithm achieved the highest accuracy with 98 %.This research shows how machine learning techniques embedded in learning analytics could expand the functionalities of VLEs toward greater personalization and effectiveness, with every student receiving the best educational experience that suits their learning styles.…”
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Eigenvector Weighting Function in Face Recognition by Pang Ying Han, Andrew Teoh Beng Jin, Lim Heng Siong

“…In this paper, a piecewise weighting function, known as Eigenvector Weighting Function (EWF), is proposed and implemented in two graph based subspace learning techniques, namely Locality Preserving Projection and Neighbourhood Preserving Embedding. …”
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Evaluation of early donor renal function recovery after living-donor nephrectomy as a predictor of allograft failure after kidney transplantation: a longitudinal cohort and machine learning studyResearch in context by Saifu Yin, Xing Li, Chengze Liang, Rong Bao, Jun Zeng, Ming Ma, Mengli Zhu, Xianding Wang, Lijuan Wu, Turun Song, Tao Lin

“…We aimed to evaluate early donor renal function recovery following living-donor nephrectomy and investigate their relationship with long-term allograft outcomes. …”
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Novel Custom Loss Functions and Metrics for Reinforced Forecasting of High and Low Day-Ahead Electricity Prices Using Convolutional Neural Network–Long Short-Term Memory (CNN-LSTM) and Ensemble Learning by Ziyang Wang, Masahiro Mae, Takeshi Yamane, Masato Ajisaka, Tatsuya Nakata, Ryuji Matsuhashi

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On the utility function of experiments in fundamental science by Tommaso Dorigo, Michele Doro, Max Aehle, Muhammad Awais, Nicolas R. Gauger, Rafael Izbicki, Jan Kieseler, Ann B. Lee, Luca Masserano, Federico Nardi, Alexander Shen, Luis Recabarren Vergara

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An Evidential Solar Irradiance Forecasting Method Using Multiple Sources of Information by Mohamed Mroueh, Moustapha Doumiati, Clovis Francis, Mohamed Machmoum

Subjects: “…machine learning…”
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Anterior insular cortex glutamate-glutamine (Glx) levels predict general psychopathology via heightened error sensitivity by Haeorum Park, Minchul Kim, Minchul Kim, Jaejoong Kim, Jaejoong Kim, Sunghwan Kim, Sunghwan Kim, Bumseok Jeong

Subjects: “…reinforcement learning…”
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Impact of vestibular dysfunction on cognitive function by Ruiqi ZHANG, Yanli ZHAO, Dongmei ZHANG, Wenyan LI, Peixia WU

“…Cognitive function was evaluated using mini-mental state examination (MMSE), Montreal cognitive assessment (MoCA), Stroop color-word test, trail making test (TMT), and auditory verbal learning test (AVLT). …”
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The methodology of teaching of the integration techniques of the rational functions by using partial fraction decomposition method and integration of the trigonometric functions by D. D. Gadjiev

“…There are introduced newly generated unabridged problems with the topics such as (a) Integration by partial fractions, (b) Integration of trigonometric functions and (c) Reduction formulas for the integration. …”
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Disrupted structure and aberrant function of CHIP mediates the loss of motor and cognitive function in preclinical models of SCAR16. by Chang-He Shi, Carrie Rubel, Sarah E Soss, Rebekah Sanchez-Hodge, Shuo Zhang, Sabrina C Madrigal, Saranya Ravi, Holly McDonough, Richard C Page, Walter J Chazin, Cam Patterson, Cheng-Yuan Mao, Monte S Willis, Hai-Yang Luo, Yu-Sheng Li, Donte A Stevens, Mi-Bo Tang, Pan Du, Yao-He Wang, Zheng-Wei Hu, Yu-Ming Xu, Jonathan C Schisler

“…CHIP (carboxyl terminus of heat shock 70-interacting protein) has long been recognized as an active member of the cellular protein quality control system given the ability of CHIP to function as both a co-chaperone and ubiquitin ligase. …”
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Reinforcement learning when your life depends on it: A neuro-economic theory of learning. by Jiamu Jiang, Emilie Foyard, Mark C W van Rossum

“…Hence, a neuro-economic dilemma arises whether learning is a profitable investment or not, and the brain must therefore judiciously regulate learning. …”
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Inhibition of PTPRS function does not affect the survival or regeneration of dopaminergic neurons but alters synaptic function in the nigrostriatal pathway by Joshua Peter, Kaejaren C.N. Caldwell, Lucas McClain, Jason Tchieu, Ashley E. Ross, Yu Luo

“…Similarly, mDA-specific deletion of Ptprs does not affect the basal behavioral measurement in cKO mice, including general locomotion and motor learning. Interestingly, however, Ptprs deletion led to a reduced response in the behavior sensitization to repeated methamphetamine (METH) exposure in cKO mice, suggesting a dampened response in synaptic function in cKO mice under these conditions. …”
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Preference learning based deep reinforcement learning for flexible job shop scheduling problem by Xinning Liu, Li Han, Ling Kang, Jiannan Liu, Huadong Miao

“…First, a reward predictor based on preference learning is designed to model reward prediction by comparing random fragments, eliminating the need for complex reward function design. …”
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Advancements in one-dimensional protein structure prediction using machine learning and deep learning by Wafa Alanazi, Di Meng, Gianluca Pollastri

“…The accurate prediction of protein structures remains a cornerstone challenge in structural bioinformatics, essential for understanding the intricate relationship between protein sequence, structure, and function. Recent advancements in Machine Learning (ML) and Deep Learning (DL) have revolutionized this field, offering innovative approaches to tackle one- dimensional (1D) protein structure annotations, including secondary structure, solvent accessibility, and intrinsic disorder. …”
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Learning path planning methods based on learning path variability and ant colony optimization by Jing Zhao, Haitao Mao, Panpan Mao, Junyong Hao

“…With the advancement of education information, the scale of online education has been expanding, which brings challenges to students' learning path planning, i.e., course and learning method planning. …”
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Network analysis of cognitive function, glycemic–lipid profiles, and hepatic–renal function in individuals with diverse drinking patterns by Shuqi Xu, Shuqi Xu, Shuqi Xu, Shuqi Xu, Ranran Zhao, Ranran Zhao, Ranran Zhao, Jincheng Wang, Jincheng Wang, Jincheng Wang, Xue Yang, Xue Yang, Xue Yang, Lan Wang, Lan Wang, Lan Wang, Cuixia An, Cuixia An, Cuixia An, Xueyi Wang, Xueyi Wang, Xueyi Wang, Ran Wang, Ran Wang, Ran Wang

“…The Alcohol Dependence Scale (ADS) and the Alcohol Use Disorders Identification Test (AUDIT) were utilized to evaluate alcohol-related behaviors. Cognitive functions were assessed via the Hopkins Verbal Learning Test (HVLT), the Brief Visuospatial Memory Test (BVMT), Digit Symbol Coding Test (DSCT), and Digit Span Test (DST). …”
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