Harnessing Generative AI in Higher Education: Opportunities, Challenges, and Ethical Imperatives by R. Ravichandran, P. Sasikala

“…The paper also interrogates key ethical concerns, such as academic integrity, data privacy, algorithmic bias, and equity, while analysing current government initiatives aimed at responsible AI adoption. …”
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Informing Disaster Recovery Through Predictive Relocation Modeling by Chao He, Da Hu

“…Housing recovery represents a critical component of disaster recovery, and accurately forecasting household relocation decisions is essential for guiding effective post-disaster reconstruction policies. This study explores the use of machine learning algorithms to improve the prediction of household relocation in the aftermath of disasters. …”
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Innovative AI Solutions for Water-Efficient Smart Irrigation in Agriculture by Saha Laboni, Dubey Ahilya

“…The proposed AI solutions are integrated platform of machine learning algorithms and sensor data, predictive analytics for the purpose to generate a water efficient irrigation framework reacts dynamically to the crops' needs and environmental conditions. …”
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An eye for an ‘I:’ a critical assessment of artificial intelligence tools in migration and asylum management by Lucia Nalbandian

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Multilevel determinants of racial/ethnic disparities in severe maternal morbidity and mortality in the context of the COVID-19 pandemic in the USA: protocol for a concurrent triang... by Bankole Olatosi, Jiajia Zhang, Xiaoming Li, Chen Liang, Jihong Liu, Peiyin Hung, Shan Qiao, Berry A Campbell, Myriam E Torres, Neset Hikmet

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Predictive Analysis of Cardiovascular Disease Risk Factors in Romania using Machine Learning and Medical Statistics by Radu-Anton MOLDOVAN, Sebastian-Aurelian ŞTEFĂNIGĂ

“…Our findings identify the most powerful determinants of cardiovascular disease in Romania, with an integrated risk model evaluation. Based on our findings, a series of preventive interventions and policy recommendations for cardiovascular risk reduction at the individual and population levels can be implemented. …”
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Artificial Intelligence and MCDA in Circular Economy: Governance Strategies and Optimization for Reverse Supply Chains of Solid Waste by Joel Joaquim de Santana Filho, Arminda do Paço, Pedro Dinis Gaspar

“…The integration of multi-criteria decision analysis (MCDA) and Artificial Intelligence (AI) is revolutionizing the governance of reverse supply chains for solid waste (RSCSW) within a circular economy framework. …”
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Innovative approaches to standardisation in forest commodity science: Trends and prospects by O. Sytnyk, I. Kimeichuk

“…It has been determined that leading countries have already implemented integrated ecosystems that combine standards, intelligent algorithms, and certification chains. …”
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Gender biases within Artificial Intelligence and ChatGPT: Evidence, Sources of Biases and Solutions by Jerlyn Q.H. Ho, Andree Hartanto, Andrew Koh, Nadyanna M. Majeed

“…To mitigate these issues, various interventions are discussed, including improving data quality, diversifying datasets and annotator pools, integrating fairness-centric algorithmic approaches, and establishing robust policy frameworks at corporate, national, and international levels. …”
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Dynamic Network Plasticity and Sample Efficiency in Biological Neural Cultures: A Comparative Study with Deep Reinforcement Learning by Moein Khajehnejad, Forough Habibollahi, Alon Loeffler, Aswin Paul, Adeel Razi, Brett J. Kagan

“…To explore whether this was meaningful in a broader context, we compared the learning efficiency of these biological systems with state-of-the-art deep reinforcement learning (RL) algorithms (Deep Q Network, Advantage Actor-Critic, and Proximal Policy Optimization) in a simplified Pong simulation. …”
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Balancing Ethics and Privacy in the Use of Artificial Intelligence in Institutions of Higher Learning: A Framework for Responsive AI Systems by Belinda Ndlovu, Kudakwashe Maguraushe

“…These concerns include issues such as intrusive data collection, algorithmic bias, threats to student autonomy, and unequal access to AI-enhanced learning. …”
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Transformations in academic work and faculty perceptions of artificial intelligence in higher education by Jorge Buele, Leonel Llerena-Aguirre

“…Additionally, ethical debates are emerging around algorithmic transparency, data privacy, and institutional responsibility. …”
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Advancing cardiovascular care through actionable AI innovation by Giuseppe Biondi-Zoccai, Arjun Mahajan, Dylan Powell, Mariangela Peruzzi, Roberto Carnevale, Giacomo Frati

“…Indeed, offline RL refers to a class of ML algorithms that learn optimal decision-making policies from a fixed dataset of previously collected experiences—such as electronic health records or registries—without the need for active, real-time interaction with the clinical environment. …”
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A Systematic Literature Review on the Application of Machine Learning for Predicting Stunting Prevalence in Indonesia (2020–2024) by Emilda Indrisari, Hidayat Febiansyah, Bambang Adiwinoto

“…In conclusion, machine learning holds strong potential to support predictive systems and data-driven policies for stunting prevention in Indonesia. This study recommends future research to focus on integrating spatial-temporal data, implementing Explainable AI (XAI), and conducting cross-regional validation to enhance model reliability and policy relevance.…”
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Temporal-Sequence Offline Reinforcement Learning for Transition Control of a Novel Tilt-Wing Unmanned Aerial Vehicle by Shiji Jin, Wenjie Zhao

“…Although online reinforcement learning algorithms offer adaptability, they depend on real-world exploration, posing considerable safety and cost risks for safety-critical UAV applications. …”
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Marine Voyage Optimization and Weather Routing with Deep Reinforcement Learning by Charilaos Latinopoulos, Efstathios Zavvos, Dimitrios Kaklis, Veerle Leemen, Aristides Halatsis

“…This study explores two model-free Deep Reinforcement Learning (DRL) algorithms: (i) a Double Deep Q Network (DDQN) and (ii) a Deep Deterministic Policy Gradient (DDPG). …”
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Unraveling the Reshaping of Human Resource Management Function: the mediating role of artificial intelligence by Samuel Bangura, Anos Chitamba Chitamba, Lucia Zithobile Ngidi, Sizwe Mbona

“…However, the study also identifies potential challenges associated with AI adoption, including concerns related to algorithmic bias, data privacy, transparency, and employee apprehensions. …”
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Land Use Transition and Regional Development Patterns Under Shared Socioeconomic Pathways: Evidence from Prefecture-Level Cities in China by Xiaodong Zhang, Mingjie Yang, Rui Guo, Yaolong Li, Fanglei Zhong

“…This study evaluates the spatial–temporal evolution of land use intensity and regional development under five shared socioeconomic pathways (SSPs) through prefecture-level projections in China (2020–2050). This study integrates the population–development–environment model with back propagation (BP) neural networks, a supervised learning algorithm, to analyze how differentiated development trajectories reshape land systems. …”
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A Multi-Scale Airspace Sectorization Framework Based on QTM and HDQN by Qingping Liu, Xuesheng Zhao, Xinglong Wang, Mengmeng Qin, Wenbin Sun

“…To address this issue, a multi-scale airspace sectorization framework is proposed, which integrates a multi-resolution grid system and a hierarchical deep reinforcement learning algorithm. …”
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Enhancing CO2 emissions prediction for electric vehicles using Greylag Goose Optimization and machine learning by Ahmed El-Sayed Saqr, Mohamed S. Saraya, El-Sayed M. El-Kenawy

“…In this research, a novel Greylag Goose Optimization (GGO) algorithm is integrated with a Multi-Layer Perceptron (MLP) model to improve $$\hbox {CO}_2$$ emissions prediction. …”
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