A Review of Reinforcement Learning for Fixed-Wing Aircraft Control Tasks by David J. Richter, Ricardo A. Calix, Kyungbaek Kim

“…Reinforcement learning (RL) has seen an uptick in research interest in recent years, with many papers published in a plethora of different fields, topics and applications. …”
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Use of Levosimendan in Cardiac Anesthesiology by L. A. Krichevsky, V. Yu. Rybakov, O. G. Guseva, I. E. Kharlamova, A. Yu. Lyamin

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Potential biomarkers and immune infiltration linking endometriosis with recurrent pregnancy loss based on bioinformatics and machine learning by Jianhui Chen, Qun Li, Xiaofang Liu, Fang Lin, Yaling Jing, Jiayan Yang, Lianfang Zhao

“…These findings may provide new mechanistic insights or therapeutic targets for further research of EMs and RPL.…”
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Corn Plant In-Row Distance Analysis Based on Unmanned Aerial Vehicle Imagery and Row-Unit Dynamics by Marko M. Kostić, Željana Grbović, Rana Waqar, Bojana Ivošević, Marko Panić, Antonio Scarfone, Aristotelis C. Tagarakis

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Intercomparison and Validation of MIRS, MSPPS, and IMS Snow Cover Products by Jessica Chiu, Stephany Paredes-Mesa, Tarendra Lakhankar, Peter Romanov, Nir Krakauer, Reza Khanbilvardi, Ralph Ferraro

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Diagnostic efficacy of serological and epigenetic methods of screening diagnostics of colorectal cancer by O. I. Kit, D. V. Burtsev, A. Yu. Maksimov

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COMPARISON OF THE METHOD OF ELECTROMETRIC DETERMINATION OF ROOT CANAL PARAMETERS AND THE METHOD OF THRESHOLD SEGMENTATION OF RADIOGRAPHS by Oleksii Perepelytsia, Oleg Avrunin

“…Radiological is the most promising for research because of its painlessness to the patient, low radiation dose during intraoral radiography and the possibility of using image processing algorithms to refine the measurement results. …”
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Investigation and Application of Water-Saving Monitoring Technology in Public Institutions by WANG Kang, ZHENG Yongjie, ZHANG Zhen, TANG Yanping, SONG Wenhao, GUO Xiaoming

“…Considering the characteristics of water use and the current situation of water facilities in public institutions,this study comprehensively employs the Internet of Things (IoT),cloud deployment,databases,three-dimensional (3D) visualization,and other advanced techniques to create a water-saving reconstruction scheme with integrated software and hardware for public institutions.Therefore,a smart water management platform for public institutions is built to implement advanced water-saving concepts and improve the water management level.The main research results are as follows:① By intelligent remote monitoring equipment,the multiclass water measurement network is designed to realize the fine collection of zonal water use data;② this study designs a reconstruction scheme of water facilities and explores the utilization mode of unconventional water sources to improve the utilization efficiency of water resources;③ multiple algorithms and statistical methods are used to analyze the time series of water use data,and thus this study realizes the analysis of pipeline network leakage and damage,identification of water use anomalies,and water-saving statistical analysis,and the investigation of water use laws;④ the platform with functions of monitoring and early warning is established to achieve real-time remote monitoring of water use,statistical analysis of historical water use,and identification and warning of pipe network leakage,so as to detect water anomalies in time and save water.The research results are first applied to the construction of the water-saving institution of the Pearl River Water Resources Commission to build a benchmark for the construction of water-saving institutions in the southern region.On the basis of application experience,the comprehensively integrated monitoring technology for water-saving in public institutions is developed,which provides a new idea for public institutions to save water.…”
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Responsible artificial intelligence in Africa: towards policy learning by Paul Plantinga, Kristophina Shilongo, Oarabile Mudongo, Angelique Umubyeyi, Michael Gastrow, Gabriella Razzano

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Automatic Detection for Mining Subsidence Areas Using the CBAM-Enhanced VGG-UNet Model With Long Time Series InSAR Interferograms by Kegui Jiang, Keming Yang, Mengting Gao, Liuguo Zhu, Chuang Jiang

“…The technical theories of monitoring and preventing mining subsidence have long been key challenges and research priorities in the mining field. The rapid advancements in remote sensing technology and deep learning algorithms have enabled significant breakthroughs in monitoring and accurately identifying mining subsidence. …”
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Advanced Learning Technologies for Intelligent Transportation Systems: Prospects and Challenges by Ruhul Amin Khalil, Ziad Safelnasr, Naod Yemane, Mebruk Kedir, Atawulrahman Shafiqurrahman, NASIR SAEED

“…Intelligent Transportation Systems (ITS) operate within a highly intricate and dynamic environment characterized by complex spatial and temporal dynamics at various scales, further compounded by fluctuating conditions influenced by external factors such as social events, holidays, and weather. …”
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Epidemiological Features of Chronic Lung Infection in Patients with Cystic Fibrosis by I. A. Shaginyan, M. Yu. Chernukha, L. R. Avetisyan, E. A. Siyanova, D. G. Kulyastova, O. S. Medvedeva, T. B. Priputnevich, D. Yu. Trofimov, A. V. Gordeev, E. I. Kondratieva, E. L. Amelina, S. A. Krasovskiy

“…To define epidemiologic characteristics of chronic lung infection caused by the most common agents (S. aureus, P. aeruginosa, B. cepacia-like bacteria (Bcc) and Achromobacter spp.) using a novel chronic lung infection in cystic fibrosis patients microbiological diagnosis algorithm. Materials and methods. Over a period of 7 years (2008-2016) 300 children with cystic fibrosis living in Moscow, Moscow region and several other regions of Russian Federation have been checked-up. 260 sputum samples from 100 adult patients, who were under care at the Pulmonology Research Institute, were studied. …”
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A novel smart surveillance approach to strengthen health facility-based disease surveillance in Tanzania by Ms Happy Mkali, MD Alix Miauton, Dr. Alexandra Kulinkina, Ms. Magreth Joram, MD Caroline Enos, Mr. Lazar Pavicevic, Mr. Vincent Faivre, Dr. MD Rainer Tan, Dr. Sabine Renggli, Ms. Theopista Lotto, Mr. Sinamgoda Ngailla, MD Godfrey Kavishe, Mr. Ibrahim Mtebene, Mr. Peter Agrea, MD Lameck Luwanda, Mr Geofrey Ashery, MD Chacha Mangu, Dr. MD Nyanda Ntinginya, Prof. Dr. Honorati Masanja, Prof. Dr. MD Isabella Eckerle, Prof. Dr. MD Valerie D'Acremont

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Evaluation of the performance of ERA5, ERA5-Land and MERRA-2 reanalysis to estimate snow depth over a mountainous semi-arid region in Iran by Faezehsadat Majidi, Samaneh Sabetghadam, Maryam Gharaylou, Reza Rezaian

“…Additionally, the study highlights the challenges MERRA-2 faces in capturing snow depth in mountainous regions. Future research could benefit from integrating additional datasets and employing machine learning algorithms to improve snow depth assessments, as these approaches may reduce estimation uncertainties and enhance the understanding of snow dynamics across various regions, ultimately contributing to more reliable hydrological assessments.…”
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Economic approach for optimal allocation of irrigation water in water-scarce region by Xueliang Zhang, Li Ren, Jianshi Zhao

“…Optimizing irrigation water allocation is critical for maximizing grain yields in water-scarce regions. Traditional algorithms face challenges such as lack of interpretable criteria, the curse of dimensionality, and instability. …”
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Model Development for Estimating Sub-Daily Urban Air Temperature Patterns in China Using Land Surface Temperature and Auxiliary Data from 2013 to 2023 by Yuchen Guo, János Unger, Tamás Gál

“…., maximum and minimum Tair), with few focusing on sub-daily urban Tair at high spatial resolution. In this study, we integrated MODIS-based land surface temperature (LST) data with 18 auxiliary data from 2013 to 2023 to develop a Tair estimation model for major Chinese cities, using random forest algorithms across four diurnal and seasonal conditions: warm daytime, warm nighttime, cold daytime, and cold nighttime. …”
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Evaluating the performances of SVR and XGBoost for short-range forecasting of heatwaves across different temperature zones of India by Srikanth Bhoopathi, Nitish Kumar, Somesh, Manali Pal

“…This research aims to forecast maximum temperatures and the frequency of heatwave days across four different temperature zones (Zone 1, 2, 3 and 4) in India. …”
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Urban Heat Island Effect: Remote Sensing Monitoring and Assessment—Methods, Applications, and Future Directions by Lili Zhao, Xuncheng Fan, Tao Hong

“…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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Adaptive Control and Market Integration: Optimizing Distributed Power Resources for a Sustainable Grid by Josue N. Otshwe, Bin Li, Songsong Chen, Feixiang Gong, Bing Qi, Ngouokoua J. Chabrol

“…To handle the complexity of DPR interactions, we offer a strong, hierarchical control architecture encompassing main, secondary, and tertiary levels. System performance is improved using advanced control strategies together with real-time market-responsive changes and predictive algorithms. …”
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Machine Learning in Maritime Safety for Autonomous Shipping: A Bibliometric Review and Future Trends by Jie Xue, Peijie Yang, Qianbing Li, Yuanming Song, P. H. A. J. M. van Gelder, Eleonora Papadimitriou, Hao Hu

“…Through the review, we found that maritime safety machine learning methods are evolving toward a systematic and comprehensive direction, and the integration with AI and human interaction may be the next bellwether. Future research will concentrate on three main areas: evolving safety objectives towards proactive management and autonomous coordination, developing advanced safety technologies, such as bio-inspired sensors, quantum machine learning, and self-healing systems, and enhancing decision-making with machine learning algorithms such as generative adversarial networks (GANs), hierarchical reinforcement learning (HRL), and federated learning. …”
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