Reliable protein–protein docking with AlphaFold, Rosetta, and replica exchange by Ameya Harmalkar, Sergey Lyskov, Jeffrey J Gray

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Simulating fluvial sediment pulses using remote sensing and machine learning: Development of a modeling framework applicable to data rich and scarce regions by Abhinav Sharma, Celso Castro-Bolinaga, Natalie Nelson, Aaron Mittelstet

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Cross-modal adaptive reconstruction of open education resources by Tang Shengju, Feng Li, Zhan Wang, Xie Zhaoyuan

“…Implemented in an electronics course restructuring, this work provides an effective framework for techno-cognitive collaborative optimization. Integrating cognitive science insights with cross-modal AI demonstrates significant potential for enhancing resource accessibility and personalization in open education.…”
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Evaluating the feasibility of 12-lead electrocardiogram reconstruction from limited leads using deep learning by Oriana Presacan, Alexandru Dorobanţiu, Jonas L. Isaksen, Tobias Willi, Claus Graff, Michael A. Riegler, Arun R. Sridhar, Jørgen K. Kanters, Vajira Thambawita

“…Abstract Background Wearables with integrated electrocardiogram (ECG) acquisition have made single-lead ECGs widely accessible to patients and consumers. …”
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Using a Bodily Weight-Fat Scale for Cuffless Blood Pressure Measurement Based on the Edge Computing System by Shing-Hong Liu, Bo-Yan Wu, Xin Zhu, Chiun-Li Chin

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Selective Cleaning Enhances Machine Learning Accuracy for Drug Repurposing: Multiscale Discovery of MDM2 Inhibitors by Mohammad Firdaus Akmal, Ming Wah Wong

“…A key innovation of this work is the development and application of a selective cleaning algorithm that systematically filters assay data to mitigate noise and inconsistencies inherent in large-scale bioactivity datasets. …”
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Editorial by Christian Gütl

“…These contributions, together with the generous support of the KOALA initiative, maintain the quality of our journal.In the sixth regular issue, I am very pleased to present the following 4 accepted articles: Michele Berti, Matheus Camilo da Silva, Sebastiano Saccani, and Sylvio Barbon from Italy focus their research on synthetic data generation as an alternative to traditional data anonymization based on variational autoencoders to generate high-quality synthetic tabular datasets.Roger Vieira and Kleinner Farias from Brazil introduce in their research CognIDE, a tool-supported methodology that aims to seamlessly integrate psychophysiological data linked to cognitive indicators into VS Code by offering actionable contextual cues alongside dynamic source code.Pedro Henrique Dias Valle and Elisa Yumi Nakagawa from Brazil discuss in their research a catalog of the main interoperability architectural solutions for addressing the four levels of interoperability - namely technical, syntactic, semantic, and organizational – for solving interoperability issues in software systems by analyzing 65 studies from the scientific literature.Ji Woong Yoo, Kyoung Jun Lee and Arum Park from the Republic of Korea explore the potential of deep learning techniques - Long Short-Term Memory (LSTM) algorithm and Word2Vec model – for cleansing malicious comments from users, and enhancing the ethical nature of AI systems.Enjoy Reading!…”
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AESware: Developing AES-enabled low-power multicore processors leveraging open RISC-V cores with a shared lightweight AES accelerator by Eunjin Choi, Jina Park, Kyuseung Han, Woojoo Lee

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Innovative Dombi Aggregation Operators in Linguistic Intuitionistic Fuzzy Environments for Optimizing Telecommunication Networks by Dilshad Alghazzawi, Misbah Hayat, Ghaliah Alhamzi, Abdul Wakil Baidar

“…Abstract Network optimization is accomplished by integrating AI-powered technologies that are industry leading throughout the network lifecycle to optimize network performance in accordance with strategic objectives and maximize return on investment. …”
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Prospects of artificial intelligence for the sustainability of sugarcane production in the modern era of climate change: An overview of related global findings by Rajan Bhatt, Akbar Hossain, Debjyoti Majumder, Mandapelli Sharath Chandra, Rajiv Ghimire, Muhammad Faisal Shahzad, Krishan K. Verma, Amarinder Singh Riar, Vishnu D. Rajput, Mauro Wagner Oliveira, Adel Nisi, Riyadh S. Almalki, Viliam Bárek, Marian Brestic, Sagar Maitra

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Special Issue on Contemporary Research Studies in Operations Research, Business Analytics, and Business Intelligence by Viswanath Kumar Ganesan, S. Vinodh, Malolan Sundararaman, M. Vimala Rani, M. Mathirajan

“…The mathematical model had possible scope for target detection and drug delivery at stenosed sites. Integrating Generative AI in Business Intelligence: A Practical Framework for Enhancing Augmented Analytics: This study offers a practical framework for integrating generative AI (Gen AI) into Business Intelligence (BI). …”
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Artificial intelligence - finite element method - hybrids for efficient nonlinear analysis of concrete structures by Michael A. Kraus, Rafael Bischof, Walter Kaufmann, Karel Thoma

“…Finally, some light is shed on the future work of integrating the AI surrogate material models back into the finite element method in the course of the numerical analysis of reinforced concrete structures.…”
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Advancement of artificial intelligence based treatment strategy in type 2 diabetes: A critical update by Aniruddha Sen, Palani Selvam Mohanraj, Vijaya Laxmi, Sumel Ashique, Rajalakshimi Vasudevan, Afaf Aldahish, Anupriya Velu, Arani Das, Iman Ehsan, Anas Islam, Sabina Yasmin, Mohammad Yousuf Ansari

“…At the same time, the rapidly increasing role of AI in diabetes care is woven into the story, mainly targeting how insulin therapy can be modified and personalized through algorithms and predictive modelling. …”
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Clinical applications of artificial intelligence and machine learning in neurocardiology: a comprehensive review by Jade Basem, Racheed Mani, Scott Sun, Kevin Gilotra, Neda Dianati-Maleki, Reza Dashti

“…In this review, we identify some of the widely utilized and upcoming AI/ML algorithms for some of the most common cardiac sources of stroke, strokes of undetermined etiology, and cardiac disease secondary to stroke. …”
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Federated Learning for privacy-Friendly Health Apps: A Case Study on Ovulation Tracking by Nikolaos Pavlidis, Andreas Sendros, Theodoros Tsiolakis, Periklis Kostamis, Christos Karasoulas, Eleni Briola, Christos Chrysanthos Nikolaidis, Vasilis Perifanis, George Drosatos, Eleftheria Katsiri, Despoina Elisavet Filippidou, Anastasios Manos, Pavlos S. Efraimidis

“…Health applications often need to balance advanced AI functionalities with sufficient privacy measures to ensure user engagement. …”
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Mapping in the Future: Advancing HD Maps Creation with Semi-Automated Feature Extraction by Y.-F. Chang, K.-W. Chiang, M.-L. Tsai, P.-L. Lee, C.-H. Chu, C.-Y. Hsieh, H.-R. Chen

“…This study introduces a semi-automated mapping tool aimed at addressing these challenges through the integration of point cloud data, trajectory information, and image-based AI algorithms. …”
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A 5G Roadside Infrastructure Assisting Connected and Automated Vehicles in Vulnerable Road User Protection by Raffaele Viterbo, Federico Campolo, Mattia Cerutti, Satyesh Shanker Awasthi, Stefano Arrigoni, Mattia Brambilla, Monica Nicoli

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Revolutionizing supramolecular materials design with artificial intelligence by Haoqi Zhu, Zhongyi Wang, Luofei Li, Liang Dong, Ying Li, Bin Xue, Yi Cao

“…We propose developing Intelligent Data Manufacturing Platforms—advanced laboratory automation systems designed to generate large volumes of high-quality data. By integrating AI algorithms with robotics in a closed-loop experimental system, these platforms enable high-throughput experimentation, autonomous decision-making, and iterative refinement of AI models through continuous data acquisition. …”
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Prefrontal meta-control incorporating mental simulation enhances the adaptivity of reinforcement learning agents in dynamic environments by JiHun Kim, Jee Hang Lee, Jee Hang Lee, Jee Hang Lee

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Review of machine learning applications for predicting the quality of biomass briquettes for sustainable and low-carbon energy solutions by Constance Nakato Nakimuli, Fred Kaggwa, Johan De Greef, David Kilama Okot, Julien Blondeau, Simon Kawuma

“…This review points to critical literature gaps regarding model generalizability across diverse biomass feedstocks and integration of broader quality parameters. Addressing these gaps will advance AI-based solutions, promote greener energy practices, and support sustainable development. …”
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