Examining the relationship between teacher’s theoretical beliefs and classroom practices in teaching Arabic by Aidillah Suja, Muassomah Muassomah, Sutaman Sutaman, M. Abdul Hamid, Abdul Wahab Rosyidi

“…However, it must align with teachers’ beliefs to influence classroom practices and impact learning outcomes, as teachers’ beliefs and classroom practices dynamically influence one another. …”
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Detecting Adversarial Examples Using Cross-Modal Semantic Embeddings From Images and Text by Sohee Park, Gwonsang Ryu, Daeseon Choi

“…When the embeddings extracted from an image and its label are semantically similar, they are closely positioned in this space. Based on these observations, we compared the similarities between the embeddings of the input images with those of their corresponding labels to detect adversarial examples. …”
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Refraction-Aware Structure from Motion for Airborne Bathymetry by Alexandros Makris, Vassilis C. Nicodemou, Evangelos Alevizos, Iason Oikonomidis, Dimitrios D. Alexakis, Anastasios Roussos

“…In this work, we introduce the first pipeline that combines a refraction-aware structure from motion (SfM) method with a deep learning model specifically designed for airborne bathymetry. …”
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Effectiveness Evaluation of "Refining Instruction and Support for Staff in Medical Education" Program on Improving the Knowledge Perspectives of Medical Education Development Offic... by Parvin Rezaei Gazki, Somayeh Noori Hekmat, Mahla Salajegheh

“…Given the vital role of education development office experts in improving the education in medical universities, this study aimed to evaluate the effectiveness of the training program "Refining Instruction and Support for staff in Medical Education" on improving the knowledge and perspectives of medical education development office experts. Method: A quasi-experimental study was designed to implement and evaluate a medium-term program which was developed based on literature review, study of upstream documents, and needs assessment through focus groups with medical education experts. …”
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SEM-Net: A Social–Emotional Music Classification Model for Emotion Regulation and Music Literacy in Individuals with Special Needs by Yu-Chi Chou, Shan-Ken Chien, Pen-Chiang Chao, Yuan-Jin Lin, Chih-Yun Chen, Kuang-Kai Yeh, Yen-Chia Peng, Chen-Hao Tsao, Shih-Lun Chen, Kuo-Chen Li

“…This study aims to establish an innovative AI-based social–emotional music classification model named SEM-Net, specifically designed to integrate three core positive social–emotional elements—positive outlook, empathy, and problem-solving—into classical music, facilitating accurate emotional classification of musical excerpts related to emotional states. …”
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Artificial intelligence in triage of COVID-19 patients by Yuri Oliveira, Iêda Rios, Paula Araújo, Alinne Macambira, Marcos Guimarães, Lúcia Sales, Marcos Rosa Júnior, André Nicola, Mauro Nakayama, Hermeto Paschoalick, Francisco Nascimento, Carlos Castillo-Salgado, Vania Moraes Ferreira, Hervaldo Carvalho

“…Considering that only data from hospital admission was used, and that this data came from low-cost clinical examination and laboratory testing, the low false positive rate and acceptable accuracy observed shows that it is feasible to implement prediction systems based on artificial intelligence as an effective triage method.…”
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MISDP: multi-task fusion visit interval for sequential diagnosis prediction by Shengrong Zhu, Ruijia Yang, Zifeng Pan, Xuan Tian, Hong Ji

“…The MISDP framework integrated sequential diagnosis prediction with visit interval prediction within a multi-task learning paradigm. It uses positional encoding and interval encoding to handle irregular patient visit intervals. …”
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Siamese network with squeeze-attention for incomplete multi-view multi-label classification by Mengqing Wang, Jiarui Chen, Lian Zhao, Yinghao Ye, Xiaohuan Lu

“…The VRC mechanism uses contrastive learning with positive and negative sample pairs to refine the shared semantic space, ensuring higher feature consistency and better alignment across views. …”
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Diagnostic accuracy of MRI-based radiomic features for EGFR mutation status in non-small cell lung cancer patients with brain metastases: a meta-analysis by Yuqin Long, Rong Zhao, Xianfeng Du

“…Subgroup analysis indicated that deep learning models and studies conducted in Asian showed higher diagnostic accuracy compared to their respective counterparts.ConclusionsMRI-based radiomic features demonstrate a high potential for accurately detecting EGFR mutations in NSCLC patients with brain metastases, particularly when advanced deep learning techniques were employed. …”
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The impact of peer feedback on collaborative problem-solving skills in the online environment by Seher Yalçın, Yeşim Karadağ

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A Hybrid Multi-Strategy Differential Creative Search Optimization Algorithm and Its Applications by Yuanyuan Zhang, Longquan Yong, Yijia Chen, Jintao Yang, Mengnan Zhang

“…A novel position update mechanism is introduced based on the original equation, enabling individuals to effectively escape from local optima during the iteration process. …”
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Acceptability of Home‐Based Urine Self‐Collection for Cervical Cancer Screening Among Women Receiving Care at the Arab Community Center for Economic and Social Services in Michigan... by Timothy C. Guetterman, Christelle El Khoury, Madiha Tariq, Ghada Aziz, Asraa Alhawli, Martha L. Alves, Elizabeth Haro, Emma A. Butcher, Alexandra H. Vinson, Diane M. Harper

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Pedestrian navigation: how can inertial measurment units assist smartphones? by I. A. Chistyakov, I. V. Grishov, A. A. Nikulin, M. V. Pikhletsky, I. B. Gartseev

“…Such trajectories can be used both for verification of classical algorithms of navigation or for application of machine learning technics. Reconstruction of closed trajectories based on data from foot-mounted inertial measurement units (IMU) is investigated. …”
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Expanding Multilingual Co-Speech Interaction: The Impact of Enhanced Gesture Units in Text-to-Gesture Synthesis for Digital Humans by Ghazanfar Ali, Woojoo Kim, Muhammad Shahid Anwar, Jae-In Hwang, Ahyoung Choi

“…Incorporating a cutting-edge gesture-pose matching model with deep contrastive learning, we retrieved gestures from a comprehensive rule base containing 210,000 rules. …”
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SMS3D: 3D Synthetic Mushroom Scenes Dataset for 3D Object Detection and Pose Estimation by Abdollah Zakeri, Bikram Koirala, Jiming Kang, Venkatesh Balan, Weihang Zhu, Driss Benhaddou, Fatima A. Merchant

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Synthetic Micrographs of Bacteria (SyMBac) allows accurate segmentation of bacterial cells using deep neural networks by Georgeos Hardo, Maximilian Noka, Somenath Bakshi

“…Abstract Background Deep-learning–based image segmentation models are required for accurate processing of high-throughput timelapse imaging data of bacterial cells. …”
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Development and Validation of a Dynamic Real-Time Risk Prediction Model for Intensive Care Units Patients Based on Longitudinal Irregular Data: Multicenter Retrospective Study by Zhuo Zheng, Jiawei Luo, Yingchao Zhu, Lei Du, Lan Lan, Xiaobo Zhou, Xiaoyan Yang, Shixin Huang

“…ObjectiveWe aimed to develop a real-time, interpretable risk prediction model that continuously assesses ICU patient mortality using irregular, longitudinal EMR data, with improved performance and generalizability over traditional static scoring systems. MethodsA time-aware bidirectional attention-based long short-term memory (TBAL) model was developed using EMR data from the MIMIC-IV (Medical Information Mart for Intensive Care) and eICU Collaborative Research Database (eICU-CRD) databases, comprising 176,344 ICU stays. …”
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The impact of migrant work experience on the adoption behavior of green production technologies among new professional farmers: evidence from Jiangxi and Guangdong provinces, China by Xian Kai Lei, Xian Kai Lei, Wen Li Zhao, Gui Hua Zhang, Yong Xin Chen

“…Based on the analytical framework of imprinting theory, this study employs survey data from 1,707 new professional farmers in Guangdong and Jiangxi provinces (2019–2021) and econometric methods to empirically examine the impact and mechanisms of migrant work experience on their adoption of green production technologies. …”
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Deep Neural Networks for Estimating Regularization Parameter in Sparse Time–Frequency Reconstruction by Vedran Jurdana

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ParaAntiProt provides paratope prediction using antibody and protein language models by Mahmood Kalemati, Alireza Noroozi, Aref Shahbakhsh, Somayyeh Koohi

“…On the other hand, machine learning-based methods, besides relying on structural data, entail descriptor computation, consideration of diverse physicochemical properties, and feature engineering. …”
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