Myricetin alleviates learning and memory deficits in trimethyltin Alzheimer’s phenotype via attenuating hippocampal endoplasmic reticulum stress and regulating inflammation and oxi... by Zahra Asgari, Saeid Iranzadeh, Mehrdad Roghani

“…Neurodegeneration was induced by intraperitoneal TMT injection (2.8 mg/kg), followed by daily oral administration of myricetin (25 mg/kg) for 21 days. Learning and memory-related function was assessed using passive avoidance, novel object recognition, and Y-maze tests. …”
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Effects of interaction with AI-assisted writing evaluation on EFL students’ writing performance by Ali Al Ghaithi, Behnam Behforouz

“…This study aimed to measure a newly developed automated written evaluation feedback instrument, EditGPT, on the writing performance of 30 Omani EFL learners and their perceptions of this tool’s functionality in learning English as a foreign language (EFL). …”
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A machine learning-based nomogram for predicting graft survival in allograft kidney transplant recipients: a 20-year follow-up study by Jiamin He, Pinlin Liu, Lingyan Cao, Feng Su, Yifei Li, Tao Liu, Wenxing Fan

“…Decision curve analysis (DCA) was utilized to estimate the net clinical benefit.ResultsThe machine learning-based nomogram included cardiovascular disease in recipients, delayed graft function in recipients, serum phosphorus in recipients, age of donors, serum creatinine in donors, and donation after cardiac death for kidney donation. …”
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A Study of a Drawing Exactness Assessment Method Using Localized Normalized Cross-Correlations in a Portrait Drawing Learning Assistant System by Yue Zhang, Zitong Kong, Nobuo Funabiki, Chen-Chien Hsu

“…To solve this limitation, we have developed a Portrait Drawing Learning Assistant System (<i>PDLAS</i>) to assist novices in learning portrait drawing. …”
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Adult education and training for the development of problem-solving skills by I. A. Korshunov, S. V. Lubnikov, N. N. Shirkova

“…Currently, the presence of employees with developed basic skills of working with textual and numerical information can no longer explain how effectively a person functions in society and the professional sphere. This is due to the rapid transformation of the innovative economy and the renewal of production technologies and business processes. …”
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YOLOv8n-WSE-Pest: A Lightweight Deep Learning Model Based on YOLOv8n for Pest Identification in Tea Gardens by Hongxu Li, Wenxia Yuan, Yuxin Xia, Zejun Wang, Junjie He, Qiaomei Wang, Shihao Zhang, Limei Li, Fang Yang, Baijuan Wang

“…The integration of the Efficient Multi-Scale Attention Module with Cross-Spatial Learning enables the model to have more flexible global attention. …”
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Impact-induced energy release of typical HCP metal/PTFE/W reactive materials: Experimental study and predictive modeling via machine learning by Zhenwei Zhang, Weixi Tian, Tianyi Wang, Zhiyuan Liu, Yansong Yang, Chao Ge, Lei Guo, Yuan He, Chuanting Wang, Yong He

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Gradual Variation-Based Dual-Stream Deep Learning for Spatial Feature Enhancement With Dimensionality Reduction in Early Alzheimer&#x2019;s Disease Detection by Najmul Hassan, Abu Saleh Musa Miah, Taro Suzuki, Jungpil Shin

“…Alzheimer&#x2019;s disease (AD) is one of the most common neurological brain disorders, developing gradually and primarily causing the deterioration of brain function, leading to memory loss and behavioral changes. …”
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Integrated transcriptome analysis and combinatorial machine learning to construct a homeostatic model of acetylation for ccRCC and validate the key gene GCNT4 by Baohua Zhu, Ziyang Mo, Yi Bao, Xinxin Gan, Linhui Wang

“…GSEA was used to analyze the enrichment of different signaling pathways in high-risk and low-risk groups, and the correlation between immune infiltration and risk scores was assessed. Finally, the function of the key gene GCNT4 was verified through cell experiments. …”
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Integrating convolutional neural networks for microscopic image analysis in acute lymphoblastic leukemia classification: A deep learning approach for enhanced diagnostic precision by Md. Samiul Alim, Suborno Deb Bappon, Shahriar Mahmud Sabuj, Md Jayedul Islam, M. Masud Tarek, Md. Shafiul Azam, Md. Monirul Islam

“…To accomplish this task, a novel deep-learning technique based on a fine-tuned ResNet-50 model has been developed. …”
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Identification of Alzheimer’s disease brain networks based on EEG phase synchronization by Jiayi Cao, Bin Li, Xiaoou Li

“…Firstly, the acquired EEG data were preprocessed to extract the data in the α-band at 8–13 Hz; secondly, the phase lag index (PLI) and phase-locked value (PLV) were used to construct the brain functional network, and the brain functional connectivity map was visualized by brain functional connectivity analysis. …”
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An efficient trustworthy cyberattack defence mechanism system for self guided federated learning framework using attention induced deep convolution neural networks by Louai A. Maghrabi, Alanoud Subahi, Nouf Atiahallah Alghanmi, Turki Althaqafi, Nahla J. Abid, Nasser N. Albogami, Mahmoud Ragab

“…Conventional ML and DL techniques that function with data kept on a federal server increase the main privacy issues for user information. …”
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Machine learning enhanced ultra-high vacuum system for predicting field emission performance in graphene reinforced aluminium based metal matrix composites by Sunil Kumar Pradhan, Subhayu Kabiraj, Shivin Kumar Gupta, Abhishek Singh, Padmakar G. Chavan, Shubham S. Patil, Trilok Nath Pandey

“…By leveraging machine learning (ML) models, we predict the trends of emission current density (J) as a function of the applied electric field(E) and the emission current stability (I) over time(t) for Aluminium-Graphene (AlGr) composites with varying graphene weight% (wt%) greater than 1 and less than 2 (1.25, 1.5, 1.75, and 2.0). …”
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Estimation of chlorophyll-a in uncrewed aircraft systems imagery using autonomous surface vessel data with machine learning algorithms and feature selection techniques by Mohammad Shakiul Islam, Padmanava Dash, Abduselam M. Nur, Hafez Ahmad, Rajendra M. Panda, Jessica S. Wolfe, Gray Turnage, Lee Hathcock, Gary D. Chesser, Jr, Robert J. Moorhead

“…To ensure the algorithms were developed using accurate remote sensing reflectance data, the spectral response function of the UAS was applied to the radiometer measurements. …”
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Data-driven machine learning algorithm model for pneumonia prediction and determinant factor stratification among children aged 6–23 months in Ethiopia by Addisalem Workie Demsash, Rediet Abebe, Wubishet Gezimu, Gemeda Wakgari Kitil, Michael Amera Tizazu, Abera Lambebo, Firomsa Bekele, Solomon Seyife Alemu, Mohammedamin Hajure Jarso, Geleta Nenko Dube, Lema Fikadu Wedajo, Sanju Purohit, Mulugeta Hayelom Kalayou

“…Principal component analysis and heatmap function were used for correlation detection between features. …”
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Exploring Factors Related to Social Isolation Among Older Adults in the Predementia Stage Using Ecological Momentary Assessments and Actigraphy: Machine Learning Approach by Bada Kang, Min Kyung Park, Jennifer Ivy Kim, Seolah Yoon, Seok-Jae Heo, Chaeeun Kang, SungHee Lee, Yeonkyu Choi, Dahye Hong

“…Social isolation—which includes limited social interaction and feelings of loneliness—negatively affects cognitive function and is a significant risk factor for dementia. …”
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Music training and brain plasticity during development and adulthood by Krystyna Rymarczyk, Agata Cybulska

“…Musical training has proven to be a useful framework for examining training-related plasticity in the human brain. The learning to play an instrument is a highly complex task that involves the interaction of different modalities e.i. visual, sensorimotor as well as higher-order cognitive functions like inhibition or working memory. …”
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Machine learning-driven multi-omics analysis identifies a prognostic gene signature associated with programmed cell death and metabolism in hepatocellular carcinoma by Xiang Li, Donghao Yin, Jiahao Geng, Yanyu Xu, Zijing Xu, Xuemeng Yang, Quanwei Li, Zimeng Shang, Zhiyun Yang, Zhong Xu, Jiabo Wang, Enxiang Zhang, Xinhua Song

“…Drug repurposing was pursued by integrating machine learning, deep learning, and molecular docking strategies to uncover potential therapeutic options. …”
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Quantifying axonal features of human superficial white matter from three-dimensional multibeam serial electron microscopy data assisted by deep learning by Qiyuan Tian, Chanon Ngamsombat, Hong-Hsi Lee, Daniel R. Berger, Yuelong Wu, Qiuyun Fan, Berkin Bilgic, Ziyu Li, Dmitry S. Novikov, Els Fieremans, Bruce R. Rosen, Jeff W. Lichtman, Susie Y. Huang

“…Short-range association fibers located in the superficial white matter play an important role in mediating higher-order cognitive function in humans. Detailed morphological characterization of short-range association fibers at the microscopic level promises to yield important insights into the axonal features driving cortico-cortical connectivity in the human brain yet has been difficult to achieve to date due to the challenges of imaging at nanometer-scale resolution over large tissue volumes. …”
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Œuvrer en neurodidactique de la production d’écrits by Jocelyn REULIER

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