Urban Heat Island Effect: Remote Sensing Monitoring and Assessment—Methods, Applications, and Future Directions by Lili Zhao, Xuncheng Fan, Tao Hong

“…The paper first analyzes the formation mechanisms and impacts of urban heat islands, then traces the evolution of remote sensing technology from early traditional platforms such as Landsat and NOAA-AVHRR to modern next-generation systems, including the Sentinel series and ECOSTRESS, emphasizing improvements in spatial and temporal resolution and their application value. At the methodological level, the study systematically evaluates core algorithms for land surface temperature extraction and heat island intensity calculation, compares innovative developments in multi-source remote sensing data integration and fusion techniques, and establishes a framework for accuracy assessment and validation. …”
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Parameterization toolbox for a physical–biogeochemical model compatible with FABM – a case study: the coupled 1D GOTM–ECOSMO E2E for the Sylt–Rømø Bight, North Sea by H. Nguyen, H. Nguyen, U. Daewel, N. Banas, C. Schrum

“…Traditionally, refining these models has involved a time-consuming trial-and-error approach to identify model parameter values that are able to reproduce observations well. …”
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Parameter identification of unmanned surface vehicle MMG model based on an improved extended Kalman filter by Pengbo SUN, Zaopeng DONG, Wei LIU, Jinliang SHENG, Zhihao LI

“…MethodsFirst, based on the traditional EKF algorithm, in order to fully utilize the valuable information hidden in the historical data, an improved EKF algorithm integrating multi-innovation theory and dynamic forgetting factor is proposed. …”
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Machine learning and thermodynamic modeling for optimizing hydrogen production via algae-biomass co-gasification by Thanadol Tuntiwongwat, Takashi Yukawa, Thongchai Rohitatisha Srinophakun, Kanit Manatura, Somboon Sukpancharoen, Seyedali Mirjalili

“…This study pioneers the integration of algae-biomass co-gasification with six ML algorithms to optimize H2 production and syngas quality through comprehensive thermodynamic modeling and artificial intelligence (AI). …”
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AI’s role in transforming learning environments: a review of collaborative approaches and innovations by Dwi Mariyono, Akmal Nur Alif Hd

“…By integrating thematic and content analysis, it offers novel insights into AI’s benefits and risks. …”
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Learning from the machine: is diabetes in adults predicted by lifestyle variables? A retrospective predictive modelling study of NHANES 2007–2018 by Efrain Riveros Perez, Bibiana Avella-Molano

“…The performance of five machine learning algorithms (logistic regression, support vector machine, random forest, XGBoost and CatBoost) was evaluated using accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and the area under the receiver operating characteristic curve (AUC). …”
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Comparing the Potential of Near- and Mid-Infrared Spectroscopy in Determining the Freshness of Strawberry Powder from Freshly Available and Stored Strawberry by Da Wang, Wenwen Wei, Yanhua Lai, Xiangzheng Yang, Shaojia Li, Lianwen Jia, Di Wu

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The outcome prediction method of football matches by the quantum neural network based on deep learning by Yang Sun, Hongyang Chu

“…During the model training phase, gradient descent is used to optimize weight parameters, and quantum algorithms are integrated to continuously adjust network weights to minimize prediction errors. …”
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Time-series InSAR measurement using ICOPS and estimation of along-track surface deformation using MAI during the 2021 eruption of Fagradalsfjall Volcano, Iceland by Wahyu Luqmanul Hakim, Muhammad Fulki Fadhillah, Seulki Lee, Sungjae Park, Won-Kyung Baek, Chang-Ki Hong, Hyun-Cheol Kim, Chang-Wook Lee

“…The improved combined scatterers interferometry with optimized point scatterers (ICOPS) algorithm is the time-series method that utilizes both PS and DS MPs and optimizes those combined MPs using a deep learning algorithm over different temporal intervals and using a statistical clustering approach to optimize the MPs spatially. …”
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SA3C-ID: a novel network intrusion detection model using feature selection and adversarial training by Wanwei Huang, Haobin Tian, Lei Wang, Sunan Wang, Kun Wang, Songze Li

“…Next, the network intrusion detection process is modeled as a Markov decision process and integrated with the Soft Actor-Critic (SAC) reinforcement learning algorithm, with a view to constructing agents; In the context of adversarial training, two agents, designated as the attacker and the defender, are defined to perform asynchronous adversarial training. …”
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GARMT: Grouping-Based Association Rule Mining to Predict Future Tables in Database Queries by Peixiong He, Libo Sun, Xian Gao, Yi Zhou, Xiao Qin

“…These databases ensure data integrity through strongly typed schema definitions and support complex transaction management and efficient query processing capabilities. …”
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Development and clinical application of an automated machine learning-based delirium risk prediction model for emergency polytrauma patients by Zhenyi Liu, Yihao Huang, Long Li, Yisha Xu, Peng Wu, Zhigang Zhang, Tingyong Han, Liangjie Zhang, Ming Zhang

“…To address high-dimensional clinical heterogeneity, an Improved Flood Algorithm (IFLA)—enhanced with sine mapping initialization and Cauchy mutation perturbations—was integrated into an automated machine learning (AutoML) framework for simultaneous feature selection and hyperparameter optimization. …”
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The 3D tooth model segmentation method based on GAC+PointMLP network by Jianjun Chen, Liyuan Zheng, Huilai Zou, Jiafa Mao, Weiguo Sheng

“…Compared to other traditional segmentation algorithms, the proposed method shows improvements of 1.1, 2.04, 1.06, 2.2, and 1.8 percentage points in Overall Accuracy (OA), Sensitivity (SEN), Positive Predictive Value (PPV), and Intersection Over Union (IoU), respectively. …”
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Self-Sensing Approach for Semi-Active Control of Variable Damping Electromagnetic Suspension System by Chao Fu, Pengfei Liu, Jianqiang Yu, An Qin, Donghong Ning

“…This paper combines the Kalman filter observer with self-sensing technology and integrates it into the electromagnetic damper (EMD), estimating the displacement and velocity of the EMD based on the three-phase voltage generated by the permanent magnet synchronous motor (PMSM). …”
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Detecting Botrytis Cinerea Control Efficacy via Deep Learning by Wenlong Yi, Xunsheng Zhang, Shiming Dai, Sergey Kuzmin, Igor Gerasimov, Xiangping Cheng

“…The innovations include (1) combining channel attention mechanism, multi-head self-attention mechanism, and multi-scale feature extractor to improve prediction accuracy and (2) introducing the Shapley value algorithm to achieve a precise quantitative analysis of environmental variables’ contribution to colony growth. …”
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Learning atomic forces from uncertainty-calibrated adversarial attacks by Henrique Musseli Cezar, Tilmann Bodenstein, Henrik Andersen Sveinsson, Morten Ledum, Simen Reine, Sigbjørn Løland Bore

“…We propose the Calibrated Adversarial Geometry Optimization (CAGO) algorithm to discover adversarial structures with user-assigned errors. …”
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Machine Learning Applications in Gray, Blue, and Green Hydrogen Production: A Comprehensive Review by Xuejia Du, Shihui Gao, Gang Yang

“…Despite promising results, real-world deployment remains limited due to data sparsity, model integration challenges, and economic barriers. Nonetheless, this review identifies significant opportunities for ML to accelerate innovation across the hydrogen value chain. …”
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Challenges and Applications of Artificial Intelligence in Education: A Systematic Review by Saeid Arifnejad, Asadolah khadivi, Farhad Alipour

“…Additionally, it facilitates efficient teaching methodologies, automates grading and assessment, and optimizes resource allocation. The integration of AI can significantly improve the quality of education.Value: This research contributes to bridging the knowledge gap regarding AI applications in education while identifying key challenges for educators and policymakers.…”
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Presepsin in Hepatic Pathology: Bridging the Gap in Early Sepsis Detection by Dana-Maria Bilous, Mihai Ciocîrlan, Cătălina Vlăduț, Carmen-Georgeta Fierbințeanu-Braticevici

“…While preliminary evidence is compelling, further prospective, multicenter studies are required to validate its integration into standard care algorithms. Presepsin may become a valuable addition to clinical decision-making tools, particularly in hepatology-focused sepsis management.…”
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Optimization of thermoelectric temperature control systems by A. I. Semilyak, T. E. Sarkarov, D. V. Evdulov, K. K. Nazarov

“…The resulting control algorithm provides an increase in the heating current on the Peltier until the temperature rises to a predetermined high temperature value, and then by changing the direction of the current, a cooling current is created on the Peltier element until the temperature of the copper plate drops to a predetermined low temperature. …”
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