Energy-efficient blockchain-IIoT with mobile edge computing: optimizing resource allocation and multi-hop offloading by Yiyi Zhang, Xueyue Xue, Xianfu Lin, Wenchang Wei, Zhicheng Su

“…Finally, a Multi-Agent Hybrid Trust Region Policy Optimization (MAHTRPO) algorithm is proposed to optimally solve the formulated problem. …”
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Spatial (Mis)Matches Between Biodiversity and Habitat Quality Under Multi-Scenarios: A Case Study in Shandong Province, Eastern China by Xiaoyin Sun, Ruifeng Shan, Qingxin Luan, Yuee Zhang, Zhicong Chen

“…The results of this study can be integrated by ecological managers and planners for biodiversity conservation.…”
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Leveraging machine learning for data-driven building energy rate prediction by Nasim Eslamirad, Mehdi Golamnia, Payam Sajadi, Francesco Pilla

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Mapping 1-km soybean yield across China from 2001 to 2020 based on ensemble learning by Min Zhang, Xinlei Xu, Junji Ou, Zengguang Zhang, Fangzheng Chen, Lijie Shi, Bin Wang, Meiqin Zhang, Liang He, Xueliang Zhang, Yong Chen, Kelin Hu, Puyu Feng

“…The integration of these diverse datasets allows for a nuanced understanding of the factors influencing soybean yield at a 1-km resolution. …”
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Developing a semi-automated technique of surface water quality analysis using GEE and machine learning: A case study for Sundarbans by Sheikh Fahim Faysal Sowrav, Sujit Kumar Debsarma, Mohan Kumar Das, Khan Mohammad Ibtehal, Mahfujur Rahman, Noshin Tabassum Hridita, Atika Afia Broty, Muhammad Sajid Anam Hoque

“…This study presents a semi-automated approach for assessing water quality in the Sundarbans, a critical and vulnerable ecosystem, using machine learning (ML) models integrated with field and remotely-sensed data. Key water quality parameters—Sea Surface Temperature (SST), Total Suspended Solids (TSS), Turbidity, Salinity, and pH—were predicted through ML algorithms and interpolated using the Empirical Bayesian Kriging (EBK) model in ArcGIS Pro. …”
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Unveiling new insights into migraine risk stratification using machine learning models of adjustable risk factors by Yu-Chen Liu, Ye-Hai Liu, Hai-Feng Pan, Wei Wang

“…Second, we trained ensemble machine learning (ML) algorithms that incorporated these factors, with Shapley Additive exPlanations (SHAP) value analysis quantifying predictor importance. …”
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System aspects of management technology for scientific and educational services by A. A. Zatsarinnyy, A. P. Shabanov

“…Topicality. The state policy in the sphere of national security and socio-economic development of the Russian Federation, carried out in the face of new threats requires correcting structural imbalances in the economy. …”
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Unveiling the sociodemographic and socioeconomic determinants of antenatal care utilization in Bangladesh: insights from the 2017–18 BDHS by Md. Mojammel Haque Sakib, Muhammad Khairul Alam, Nilufar Yasmin, Rumana Rois

“…Addressing these disparities and making relevant policy implications such as expanding community-based ANC programs, integrating services into primary healthcare, and increasing awareness through mass media are required to enhance ANC accessibility and utilization in underserved populations.…”
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Advancing GIS-based suitability analysis of BtX, PtX, PBtX, and eBtX facilities using the fuzzy analytic hierarchy process by Marcel Dossow, Mengxi Chen, Hartmut Spliethoff, Sebastian Fendt

“…The proposed approach offers a robust, quantitative framework for spatial optimization in the siting of sustainable fuel production facilities with significant applications for policy-makers, industry, and researchers involved in BtX, PtX, and e-/PBtX scale-up.The methodology encompasses a comprehensive suitability analysis, … • Providing a recommended list of suitability and exclusion criteria, categorized into ``requisite,'' ``infrastructure,'' and ``environmental'' criteria, tailored for sustainable fuel production site selection. • Offering a structured workflow for deriving suitability maps through a combination of GIS-based FAHP with exclusion analysis. • Providing a practical, replicable algorithm that can guide users through the process, making it easier to apply in various geographic and project contexts.…”
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Livestock production losses attributable to brucellosis in northern and central Tanzania: Application of an epidemiological-economic modelling framework. by Ângelo J F Mendes, Daniel T Haydon, William A de Glanville, Rebecca F Bodenham, AbdulHamid S Lukambagire, Paul C D Johnson, Gabriel M Shirima, Sarah Cleaveland, Emma McIntosh, Nick Hanley, Jo E B Halliday

“…This study aimed to develop an integrated epidemiological-economic modelling framework to estimate production losses attributable to livestock brucellosis, using Tanzania as a case study. …”
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A visualized bibliometric analysis on remote sensing monitoring of methane emissions in coal mines by CUI Ximin, GUO Wei, SHI Guobin, LI Qingqing, YAO Hansi, ZHANG Yuhuan, ZHAO Yuling, RIENOW Andreas

“…This study therefore suggests areas for future research, such as the precision and efficiency of remote sensing monitoring, intelligent data processing and algorithms, multi-platform integration and fusion, and international collaboration and data sharing.…”
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Spatial Prediction of Soil Continuous and Categorical Properties Using Deep Learning Approaches for Tamil Nadu, India by Thamizh Vendan Tarun Kshatriya, Ramalingam Kumaraperumal, Sellaperumal Pazhanivelan, Nivas Raj Moorthi, Dhanaraju Muthumanickam, Kaliaperumal Ragunath, Jagadeeswaran Ramasamy

“…The validation and test results obtained for each of the soil attributes for both the algorithms were most comparable with the DL-MLP algorithm depicting the attributes’ most intricate spatial organization details, compared to the 1D-CNN model. …”
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Achieving comprehensive water productivity improvement: A multi-objective simulation-optimization model for water productivity-oriented irrigation water management by Gang Li, Chenglong Zhang, Zailin Huo, Yanqi Liu

“…Moreover, the Environmental Policy Integrated Climate (EPIC) crop growth model and water-salt balance equations are incorporated to readily simulate daily physical processes of crop growth and dynamic water and salt movement. …”
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Zonal Estimation of the Earliest Winter Wheat Identification Time in Shandong Province Considering Phenological and Environmental Factors by Jiaqi Chen, Xin Du, Chen Wang, Cheng Cai, Guanru Fang, Ziming Wang, Mengyu Liu, Huanxue Zhang

“…To address this issue, we proposed a zonal-based early-season mapping framework for winter wheat by integrating phenological and environmental factors. …”
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Multi-Agent Reinforcement Learning in Games: Research and Applications by Haiyang Li, Ping Yang, Weidong Liu, Shaoqiang Yan, Xinyi Zhang, Donglin Zhu

“…Building upon stochastic game and extensive-form game-theoretic frameworks, we establish a methodological taxonomy across three dimensions: value function optimization, policy gradient learning, and online search planning, thereby clarifying the evolutionary logic and innovation trajectories of algorithmic advancements. …”
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Fast optimization of the emission reduction pathways of major air pollutants in China: From the perspective of different decision preferences by Yihao Wang, Xuying Wang, Yixuan Zheng, Zeyuan Liu, Yu Zhang, Jiani Kang, Wenbo Xue, Jing Zhang, Yu Lei

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Evaluation of the shielding initiative in Wales (EVITE Immunity): protocol for a quasiexperimental study by Stephen Jolles, Ashley Akbari, Andrew Carson-Stevens, Helen Snooks, Alan Watkins, Adrian Edwards, Ann John, Alison Porter, Victoria Williams, Bridie Angela Evans, Ronan Lyons, Bernadette Sewell, Mark Rhys Kingston, Tony Whiffen, Jane Lyons, Rowena Bailey, Catherine A Thornton, Lesley Bethell, Samantha Bufton, Lucy Dixon

“…This study will generate a logic model of the intervention and evaluate the effects and costs of shielding to inform policy development and delivery during future pandemics.Methods and analysis This is a quasiexperimental study undertaken in Wales where records for people who were identified for shielding were already anonymously linked into integrated data systems for public health decision-making. …”
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Improving agricultural commodity allocation and market regulation: a novel hybrid model based on dual decomposition and enhanced BiLSTM for price prediction by Lihua Zhang, Fushun Wang, Fushun Wang, Kejian Wang, Kejian Wang, Zhenxue He, Zhenxue He, Chen Chen, Chen Chen, Jiahao Liu, Jiahao Liu, Chao Wang, Chao Wang, Zhe Wang

“…The ability to scientifically and effectively predict agricultural commodity prices is of great significance for the rational deployment of market mechanisms, the timely adjustment of supply chains, and the promotion of food policy adjustments. This paper proposes a sustainable hybrid model SV-PSO-BiLSTM which integrates Seasonal-Trend decomposition procedure based on Loess (STL), Variational Mode Decomposition (VMD), Particle Swarm Optimization (PSO), and Bidirectional Long Short-Term Memory (BiLSTM) neural networks. …”
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Bayesian Q-learning in multi-objective reward model for homophobic and transphobic text classification in low-resource languages: A hypothesis testing framework in multi-objective... by Vivek Suresh Raj, Ruba Priyadharshini, Saranya Rajiakodi, Bharathi Raja Chakravarthi

“…To address this, we propose a Bayesian Q-Learning framework with a convolutional neural network policy. The policy outputs action logits, integrated with Q-value estimates sampled via Thompson Sampling from a Gaussian posterior. …”
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Decoupled Reinforcement Hybrid PPO–Sliding Control for Underactuated Systems: Application to Cart–Pole and Acrobot by Yi-Jen Mon

“…In the Cart–Pole task, the method achieves long-term balance with high stability, outperforming traditional RL algorithms such as the Proximal Policy Optimization (PPO) in average episode length and robustness to environmental disturbances. …”
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