3D IntelliGenes: AI/ML application using multi-omics data for biomarker discovery and disease prediction with multi-dimensional visualization by Rishabh Narayanan, Elizabeth Peker, William DeGroat, Dinesh Mendhe, Saman Zeeshan, Zeeshan Ahmed

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Toward value-based care using cost mining: cost aggregation and visualization across the entire colorectal cancer patient pathway by Maura Leusder, Sven Relijveld, Derya Demirtas, Jon Emery, Michelle Tew, Peter Gibbs, Jeremy Millar, Victoria White, Michael Jefford, Fanny Franchini, Maarten IJzerman

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Multi-Agent Deep Reinforcement Learning Cooperative Control Model for Autonomous Vehicle Merging into Platoon in Highway by Jiajia Chen, Bingqing Zhu, Mengyu Zhang, Xiang Ling, Xiaobo Ruan, Yifan Deng, Ning Guo

“…To enhance training efficiency, we develop a dual-layer multi-agent maximum Q-value proximal policy optimization (MAMQPPO) method, which extends the multi-agent PPO algorithm (a policy gradient method ensuring stable policy updates) by incorporating maximum Q-value action selection for platoon gap control and discrete command generation. …”
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Enhancing Port Shipping Synergy Through Bayesian Network: A Case of Major Chinese Ports by Siqian Cheng, Jiankun Hu, Youfang Huang, Zhihua Hu

“…Five leverage points stand out: customer engagement in green supply chains, perceived service quality, port digital information integration, multilateral trading maturity, and strict policy enforcement. …”
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AI-enabled obstetric point-of-care ultrasound as an emerging technology in low- and middle-income countries: provider and health system perspectives by Sara Della Ripa, Nicole Santos, Dilys Walker

“…First, AI-enabled POCUS elicited concerns around algorithmic accuracy and compromised clinical acumen due to over-reliance on AI, but an interest in gestational age automation. …”
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Carbon co-benefits of digital economy and green finance: empirical evidence from China by Yayun Ren, Xiaohang Xu, Yantuan Yu, Zhenhua Zhang

“…The study provides China and other emerging economies seeking to promote sustainable development through digital-green integration with policy-relevant implications.…”
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Learning-based locomotion control fusing multimodal perception for a bipedal humanoid robot by Chao Ji, Diyuan Liu, Wei Gao, Shiwu Zhang

“…In this paper, visual information is added to the locomotion control problem of humanoid robot, and a three-stage multi-objective constraint policy distillation optimization algorithm is innovantly proposed. …”
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GTrXL-SAC-Based Path Planning and Obstacle-Aware Control Decision-Making for UAV Autonomous Control by Jingyi Huang, Yujie Cui, Guipeng Xi, Shuangxia Bai, Bo Li, Geng Wang, Evgeny Neretin

“…To address these issues, this paper integrates DRL with the Transformer architecture to propose the GTrXL-SAC (gated Transformer-XL soft actor critic) algorithm. …”
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Collaborative carbon emission peak actions in urban agglomerations: multi-agent reinforcement learning analysis of the urban agglomerations of Beijing-Tianjin-Hebei and Yangtze Riv... by Bingbing Zhao, Min Deng, Wei-Zhen Lu, Kaiqi Chen

“…The socioeconomic actions of cities within an urban agglomeration are coordinated using the QMIX algorithm, which employs value function factorization to integrate local decisions and feedback on reduced emissions. …”
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Innovative Business Models Towards Sustainable Energy Development: Assessing Benefits, Risks, and Optimal Approaches of Blockchain Exploitation in the Energy Transition by Aikaterini Papapostolou, Ioanna Andreoulaki, Filippos Anagnostopoulos, Sokratis Divolis, Harris Niavis, Sokratis Vavilis, Vangelis Marinakis

“…Furthermore, according to the results, technological and legal risks are the most significant, followed by political, economic, and social risks, while environmental risks of blockchain integration are not as important. Strategies to address risks relevant to blockchain exploitation include ensuring policy alignment, emphasising economic feasibility, facilitating social inclusion, prioritising security and interoperability, consulting with legal experts, and using consensus algorithms with low energy consumption. …”
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A systematic review of AI-powered collaborative learning in higher education: Trends and outcomes from the last decade by Attila Kovari

“…This review aims to integrate the current state and future opportunities of AI-enhanced collaborative learning within a higher education context to inform educators, researchers, and policy makers in pursuit of improving teaching and learning practices.…”
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Secure Latency-Aware Task Offloading Using Federated Learning and Zero Trust in Edge Computing for IoMT by Waleed Almuseelem

“…Within FL, an improved on-policy temporal difference control algorithm is leveraged for local model training. …”
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Human-in-the-loop control strategy for IoT-based smart thermostats with Deep Reinforcement Learning by Payam Fatehi Karjou, Fabian Stupperich, Phillip Stoffel, Drk Müller

“…A key focus of this research is enhancing the adaptability of agents’ behavior by implementing a more generic and flexible Markov Decision Process (MDP) to promote policy generalization across diverse scenarios. The study explores the challenges of transferring control behaviors from simulation environments to real-world settings, examining the performance across different thermal zones and evaluating the integration flexibility of the control strategy within building systems. …”
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Secure Transmission for RIS-Assisted Downlink Hybrid FSO/RF SAGIN: Sum Secrecy Rate Maximization by Jiawei Li, Weichao Yang, Tong Liu, Li Li, Yi Jin, Yixin He, Dawei Wang

“…Then, an alternating iterative framework is proposed for a joint solution using the simulated annealing algorithm, semi-definite programming, and the designed deep deterministic policy gradient (DDPG) algorithm. …”
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The Impact of AI Software on Financial Transactions by Li Boyang

“…This paper explores AI’s applications in quantitative trading, risk forecasting, and intelligent customer interactions, demonstrating its ability to optimize decision-making and reduce operational costs. However, the integration of AI also raises significant concerns, including data security risks, algorithmic opacity, and increased market volatility, as evidenced by incidents like the 2010 “Flash Crash” and recent AI-driven stock fluctuations. …”
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The Gendered Well-being Assessment: addressing trauma, complex needs & social determinants of health by Denise Ruprai, Simon Pemberton, Richard Summers

“…By recognising protective factors like self-efficacy and social support, the GWA moves beyond harm mitigation to promote resilience and flourishing. Its structured, algorithm-based approach informs personalised support plans, transforming service provision and policy. …”
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Analysis of Encrypted Network Traffic for Enhancing Cyber-security in Dynamic Environments by Faeiz Alserhani

“…User selection is accomplished through robust Deep Reinforcement Learning with the Tabu Search (DRL-TS) algorithm, while channel selection is optimized through rigorous training employing Proximal Policy Optimization (PPO). …”
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Impact of the China's new energy market on carbon price fluctuation risk: Evidence from seven pilot carbon markets by Ruo-Yang Pu, Qiao-Mei Liang, Yi-Ming Wei, Song-Yang Yan, Xiang-Yu Wang, De-Hua Li, Chen Yi, Chang-Jing Ji

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Intelligent optimization method of fracturing parameters for shale oil reservoirs in Jimsar Sag, Junggar Basin, NW China by Yunjin WANG, Fujian ZHOU, Hang SU, Leyi ZHENG, Minghui LI, Fuwei YU, Yuan LI, Tianbo LIANG

“…A policy gradient-genetic-particle swarm algorithm is designed, which can adaptively adjust the inertia weights and learning factors in the iterative process, significantly improving the optimization ability of the optimization strategy. …”
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Optimization strategy of UAV‐ARIS assisted vehicular communication system by Haitao Zhao, Zhuoran Xu, Yiyang Ni, Wenxue Sun, Hongbo Zhu, Yaxuan Liu, Zhaoying Mo

“…In addition, a deep deterministic policy gradient (DDPG) algorithm is utilized for the optimization problem, and achieves convergence in continuous action space. …”
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