Sustainability of a digital health intervention within Pakistan’s remote health system: learning from implementation research by Saleem Sayani, Momina Muzammil, Malika Saba, Fayaz Roomi, Mirajuddin Miraj, Zeenat Sulaiman

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Variational Quantum Circuit-Based Quantum Machine Learning Approach for Predicting Corrosion Inhibition Efficiency of Expired Pharmaceuticals by Muhamad Akrom, Muhammad Reesa Rosyid, Lubna Mawaddah, Akbar Priyo Santosa

“…This study examines the potential of quantum machine learning (QML) to predict the corrosion inhibition capacity of expired pharmaceutical compounds. …”
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Comparison of Reinforcement Learning Approaches for Automated Control Derivation in Design Space Exploration for Safety-Critical Automotive Applications by Patrick Hoffmann, Kirill Gorelik, Valentin Ivanov

“…This paper explores reinforcement learning for automated control derivation within design space exploration with focus on a functional safety concept for safety-critical automotive applications. …”
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TaGra: an open Python package for easily generating graphs from data tables through manifold learning by Davide Torre, Davide Chicco

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Following the robot’s lead: Predicting human and robot movement from EEG in a motor learning HRI task by Tanaya Chatterjee, Adrien Guzzo, Alejandro Tlaie, Ahmad Kaddour, Charalambos Papaxanthis, Jeremie Gaveau, Peter Ford Dominey

“…Summary: A large proportion of human behavior is organized in time in the form of sensorimotor sequences. Learning new behavioral sequences recruits cognitive functions with their neural underpinnings. …”
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OXidative Stress PREDictor: A Supervised Learning Approach for Annotating Cellular Oxidative Stress States in Inflammatory Cells by Po‐Yuan Chen, Tai‐Ming Ko

“…In this study, OXidative Stress PREDictor (OxSpred), a supervised learning model tailored to accurately annotate the oxidative stress state of innate immune cells at the single‐cell level, is introduced. …”
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Cognitive and linguistic implications of learning Japanese as foreign language: A case study of a Brazilian aphasic learner by Cinthia Sayuri Misaka, Amanda Cristina de Freitas

“…Considering that foreign language (FL) learning invokes a diverse brain network with different functions, this paper aims to discuss the activities proposed in a case study with a Brazilian participant with aphasia learning Japanese as a FL. …”
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Potentialities and development of groundwater resources applying machine learning models in the extended section of Manbhum-Singhbhum Plateau, India by Arijit Ghosh, Biswajit Bera

“…Groundwater is essential for living earth including ecosystem functioning and development of society worldwide. In recent times, demand and pressure on groundwater resources are progressively increasing over time. …”
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Principals’ Classroom Observation Practices and their Influence on Teaching and Learning in Public Secondary Schools in Machakos Sub-County, Kenya by J. Baryarma Kolako

“…The research recommended that the Ministry of Education, along with the relevant educational agencies, should provide in-service training for principals on their roles as instructional leaders to enable them to proficiently discharge their functions; there should be an increase in the provision of the necessary learning resources to help enhance teaching and learning.…”
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Adaptive fusion of multi-cultural visual elements using deep learning in cross-cultural visual communication design by HuPei Wang

“…Abstract This paper presents a novel deep learning approach for the adaptive fusion of multicultural visual elements in cross-cultural visual communication design for interface development. …”
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Predicting practical reduction potential of electrolyte solvents via computational hydrogen electrode and interpretable machine-learning models by Zonglin Yi, Yi Zhou, Hao Liu, Li Li, Yan Zhao, Jiayuan Li, Yixuan Mao, Fangyuan Su, Cheng-Meng Chen

“…Here, we provide a machine-learning-assisted workflow of thermodynamically quantified E red prediction for electrolyte solvents. …”
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A multimodal MRI-based machine learning framework for classifying cognitive impairment in cerebral small vessel disease by Guihan Lin, Weiyue Chen, Yongkang Geng, Bo Peng, Surui Liu, Minjiang Chen, Chunying Pang, Pengjun Chen, Chenying Lu, Zhihan Yan, Shuiwei Xia, Yakang Dai, Jiansong Ji

“…Multimodal MRI data, including T1-weighted, resting-state functional MRI, and diffusion tensor images, were collected. …”
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Hilbert-Huang Transform and machine learning based electromechanical analysis of induction machine under power quality disturbances by V. Indragandhi, R. Senthil Kumar, R. Saranya

“…The complicated electromechanical data is broken down into intrinsic mode functions (IMFs) using the Hilbert-Huang Transform (HHT), which reveals the modes present in the signals. …”
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A Review of OBD-II-Based Machine Learning Applications for Sustainable, Efficient, Secure, and Safe Vehicle Driving by Emmanouel T. Michailidis, Antigoni Panagiotopoulou, Andreas Papadakis

“…Concurrently, recent advancements in machine learning (ML) have further expanded the capabilities of OBD-II applications, unlocking advanced, intelligent, and data-centric functionalities that significantly surpass those of conventional methodologies. …”
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Thirty Years with HIV Infection—Nonprogression Is Still Puzzling: Lessons to Be Learned from Controllers and Long-Term Nonprogressors by Julie C. Gaardbo, Hans J. Hartling, Jan Gerstoft, Susanne D. Nielsen

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Overcoming Hardware Imperfections in Optical Neural Networks Through a Machine Learning-Driven Self-Correction Mechanism by Minjoo Kim, Beomju Kim, Yelim Kim, Lia Saptini Handriani, Suhee Jang, Dae Yeop Jeong, Sung Ik Yang, Won Il Park

“…This decline can be attributed to system imperfections associated with non-ideal functions of optical components and optical alignment. …”
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High-accuracy physical property prediction for pure organics via molecular representation learning: bridging data to discovery by Qi Ou, Hongshuai Wang, Minyang Zhuang, Shangqian Chen, Lele Liu, Ning Wang, Zhifeng Gao

“…Traditional trial-and-error methods for discovering highly functional organic compounds are expensive and time-consuming. …”
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Research on the experience of utilizing artificial intelligence in nursing learning from the perspective of nursing students – a qualitative study by Pengding Lei, Edward N. Duo, Yazhuo Gao, Xuehua Zhu

“…Results Five main themes and thirteen sub-themes emerged from the data analysis: functional experiences with AI, content-related experiences, performance-related experiences, attitudes toward AI and its behavioral impact, and considerations of academic ethics. …”
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Low-Light Image Enhancement Using Deep Learning: A Lightweight Network with Synthetic and Benchmark Dataset Evaluation by Manuel J. C. S. Reis

“…In this paper, we propose a lightweight deep learning framework for low-light image enhancement, designed to balance visual quality with computational efficiency, with potential for deployment in latency-sensitive and resource-constrained environments. …”
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An islanding detection method for grid-connect inverter based on parameter optimized variational mode decomposition and deep learning by Yan Xia, Yan Xia, Yuli Lv, Feihong Yu, Yiqiang Yang, Yili Yang, Wei Li, Ke Li

“…To address the drawbacks of active methods and passive methods, an intelligent islanding detection strategy based on parameter-optimized variational mode decomposition (VMD) and deep learning was developed. Firstly, the proposed adaptive variational mode decomposition (AVMD) strategy improves the optimal mode number and penalty term of VMD by utilizing the relative entropy between the original signal and the intrinsic mode functions (IMFs). …”
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