Developing a structural model of academic self-concept based on emotional regulation and differentiation with the mediating role of achievement goals in students by meheri bostani, abdollah mafakher, Hossein Mahdian

“…Methods: The research method is descriptive-correlational path analysis. …”
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Perceptions in 3.6 Million Web-Based Posts of Online Communities on the Use of Cancer Immunotherapy: Data Mining Using BERTopic by Xingyue Wu, Chun Sing Lam, Ka Ho Hui, Herbert Ho-fung Loong, Keary Rui Zhou, Chun-Kit Ngan, Yin Ting Cheung

“…Sentiment analysis was performed to determine the polarity of each topic and categorize them as positive or negative. Based on the topics generated through topic modeling, thematic analysis was conducted to identify themes associated with immunotherapy. …”
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The clinical significance of the ACRG classification in gastric adenocarcinoma and the establishment of a p53 expression prediction model based on biopsy histopathology by LIU Xinyu, LIU Yinbo, LIU Shunli, ZHAO Han, SONG Yaolin, XING Xiaoming

“…Subsequently, the images were input into a feature aggregation-based classification network to establish a predictive model for p53 protein expression in gastric adenocarcinoma. …”
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Generative artificial intelligence acceptance, anxiety, and behavioral intention in the middle east: a TAM-based structural equation modelling approach by Mona Gamal Mohamed, Polat Goktas, Shimaa Abdelrahim Khalaf, Aycan Kucukkaya, Ibrahim Al-Faouri, Ebtisam Abd Elazeem Saber Seleem, Awatef Ibraheem, Aya M. Abdelhafez, Saleh O. Abdullah, Hanan Nasef Zaki, Abdulqadir J. Nashwan

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Simulation-based training in ultrasound-guided regional anaesthesia for emergency physicians: insights from an Italian pre/post intervention study by Flavia Resta, Bruno Barcella, Valentina Angeli, Elena Lago, Annunziata Santaniello, Andrea Simone Dedato, Clarissa Elisabeth Centurioni, Elena Regeni, Simone Savastano, Enrico Baldi, Enrico Contri, Riccardo Maffeis, Pietro Denti, Valeria Musella, Azzurra Schicchi, Davide Lonati, Francesco Salinaro, Stefano Perlini, Santi Di Pietro, Regional Anaesthesia in Emergency Medicine Research Group (RAEM)

“…Methods In this pre/post intervention study, emergency physicians attended a course consisting of a 4-hour teaching on background knowledge and a practical part structured as follows: a scanning session on a healthy individual; a needling station with an ex-vivo model (turkey thighs); a simulation-based learning experience on local anaesthetic toxicity (LAST); a session on the UGRA simulator BlockSim™. …”
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Acceptance and Commitment Therapy-based empowerment intervention for asthma management in parent-child dyads: A pilot randomised controlled trial by Xu Wang, Wai Tong Chien, Yuen Yu Chong

“…Aim: To evaluate the feasibility, acceptability, and preliminary efficacy of an Acceptance and Commitment Therapy-based empowerment intervention for asthma management in school-age children with asthma and their parents. …”
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Organizational Readiness for Change: A Case Study on Change Drivers and Inhibitors from Oman’s Health Professions Education Institutions by Nada Al Moosa, Deena AL Asfoor, Reem AL Alawi

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Adaptive hybrid hyperparameter optimization with MRFO and Lévy flight for accurate melanoma classification by Shamsuddeen Adamu, Hitham Alhussian, Said Jadid Abdulkadir, Ayed Alwadin, Sallam O. F. Khairy, Hussaini Mamman, Shamsu Abdullahi, Saidu Yahaya, Aliyu Garba, Dahiru Adamu Aliyu, Muhammad Muntasir Yakubu, Daniel Tonye Oyefidein

“…Abstract Hyperparameter optimization (HPO) is essential for deep learning in medical image classification, yet standard metaheuristics such as Manta Ray Foraging Optimization (MRFO) often suffer from premature convergence in high-dimensional search spaces. …”
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A Distributional Regression Network With Data Transformation for Calibrating Rainfall Forecasts by Zeqing Huang, Andrew Schepen, James C. Bennett, David E. Robertson, Tongtiegang Zhao, Eun‐Soon Im, Quan J. Wang

“…Abstract Machine learning methods provide a promising approach for exploiting relationships between raw forecasts and observations for forecast calibration. …”
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Eating habits and carotenoid skin content among children based on their attendance at the school meals: A cross-sectional pilot study by Giovanna Caparello, Fabrizio Ceraudo, Francesca Meringolo, Giuseppina Augimeri, Giuseppe Morino, Daniela Bonofiglio

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Home-based digital counselling by frontline community workers for anxiety and depression symptoms in rural Sindh, Pakistan: the mPareshan intervention by Fauziah Rabbani, Javeria Nafis, Samina Akhtar, Amna Siddiqui, Zul Merali

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Video and Online Courses in the Educational Process of Plekhanov Russian University of Economics: opportunities, advantages and problems for students and professors by A. A. Dokukina, D. A. Shtykhno

“…The problem area is discussed from the positions of lecturers and students. The hypothesis is based on the assumption that online techniques are positively perceived by both sides, despite a number of limitations which reduced professors’ enthusiasm for expanding the scope of traditional teaching methods. …”
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Preparing physiotherapists for the future: the development and evaluation of an innovative curriculum by Niki Stolwijk, Anne van Bergen, Evy Jetten, Marjo Maas

“…The PACE concept features an integrated approach to learning and assessment based on pre-set learning outcomes, personalized learning goals, flexible learning routes, and programmatic assessment. …”
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DMAC: Discovering Multi-Attribute Correlations of Deep Quality Features for Defect Detection in Mechanical Components by Yue Yu

“…DMAC advances the state-of-the-art by constructing a large-scale hypergraph to model the complex, multi-attribute relationships among defect features, uncovering high-order interactions that traditional methods cannot detect. Additionally, a Gaussian Mixture Model (GMM)-based posterior probability is used to rank candidate patches for defect detection, prioritizing high-risk areas and minimizing false positives. …”
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Wi-FiAG: Fine-Grained Abnormal Gait Recognition via CNN-BiGRU with Attention Mechanism from Wi-Fi CSI by Anming Dong, Jiahao Zhang, Wendong Xu, Jia Jia, Shanshan Yun, Jiguo Yu

“…Specifically, we propose a deep learning-based framework for multi-class abnormal gait recognition, comprising three key modules: data collection, data preprocessing, and gait classification. …”
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INTEGRATION OF INTRADISCIPLINARY TOPICS AND GEOGRAPHY IN THE TEACHING PROCESS OF TECHNOLOGY by M. S Kazimov

“…All these knowledge should be delivered to students through an integrative teaching process.Methods. Study method of this research paper involves two main methods: statistical analysis as quantitative research method and literature review as qualitative research method. …”
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Extraction of Clinically Relevant Temporal Gait Parameters from IMU Sensors Mimicking the Use of Smartphones by Aske G. Larsen, Line Ø. Sadolin, Trine R. Thomsen, Anderson S. Oliveira

“…As populations age and workforces decline, the need for accessible health assessment methods grows. The merging of accessible and affordable sensors such as inertial measurement units (IMUs) and advanced machine learning techniques now enables gait assessment beyond traditional laboratory settings. …”
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Precision Weed Management for Straw-Mulched Maize Field: Advanced Weed Detection and Targeted Spraying Based on Enhanced YOLO v5s by Xiuhong Wang, Qingjie Wang, Yichen Qiao, Xinyue Zhang, Caiyun Lu, Chao Wang

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Remote Sensing Scene Classification using ConvNeXt-Tiny Model with Attention Mechanism and Label Smoothing by Rachmawan Atmaji Perdana, Aniati Murni Arimurthy, Risnandar

“…This study focuses on solving the RSSC problem by proposing a deep learning-based method (CNN) with the ConvNeXt-Tiny model integrated with Efficient Channel Attention Module (ECANet) and label smoothing regularization (LSR). …”
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DE-Net: A Dual-Encoder Network for Local and Long-Distance Context Information Extraction in Semantic Segmentation of Large-Scale Scene Point Clouds by Zhipeng He, Jing Liu, Shuai Yang

“…However, this task remains challenging due to the imbalanced distribution of categories in large-scale point cloud data and the similarity in local geometric structures. Most current deep learning–based methods concentrate on designing local feature extraction modules while neglecting the significance of long-distance contextual information. …”
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