Machine learning applications for chloride ingress prediction in concrete: insights from recent literature by Quynh-Chau Truong, Anh-Thu Nguyen Vu

“…Various algorithms, such as Artificial Neural Networks (ANNs), Gene Expression Programming (GEP), Extreme Gradient Boosting (XGBoost), Support Vector Machine (SVM) and Ensemble Learning, have shown potential in estimating corrosion processes, predicting material properties, and evaluating structural durability. …”
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Investigating the dynamics and uncertainties in portfolio optimization using the Fourier-Millen transform. by Muhammad Hilal Alkhudaydi, Aiedh Mrisi Alharthi

“…Many investors and financial managers view portfolio optimisation as a critical step in the management and selection processes. This is due to the fact that a portfolio fundamentally comprises a collection of uncertain securities, such as equities. …”
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Periodical Press of Kurgan City, Tobolsk Province of Late XIX — Early XX Centuries by A. A. Mironova

“…The processes of development of mass media in the county city Kurgan, a large agricultural center of the Tobolsk province, in the late 19th — early 20th centuries are analyzed. …”
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State of communication regimes in the area of the Greater Caspian Sea by V. G. Golovin, E. E. Golovina

“…This format is determined by two interrelated processes: the state of the geopolitical landscape, as well as the friendliness of communication regimes. …”
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Reconciling flexibility and efficiency: medial entorhinal cortex represents a compositional cognitive map by Payam Piray, Nathaniel D. Daw

“…Here, we propose a novel computational model for efficiently creating and planning with compositional predictive maps, which successfully reproduces response fields in the medial entorhinal cortex, particularly object vector cells and grid cells. The model treats each object as an alteration to a baseline map linked to open space, creating predictive maps by combining object-related representations compositionally, providing insights into brain processes supporting efficient, flexible planning.…”
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The use of cytokines in the treatment of cornea inflammatory and dystrophic diseases (review) by M. S. Denisko, O. I. Krivosheina

“…At the same time, the main properties of cytokines are pleiotropy, lack of antigenic specificity, and the ability to form a cascade chain, that allows versatile correction of the spectrum of reparative processes. There are evidences of the possibility of using cytokines in the regeneration of damaged tissues in recent decades. …”
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A novel double machine learning approach for detecting early breast cancer using advanced feature selection and dimensionality reduction techniques by Suganya Athisayamani, Tamilazhagan S, A. Robert Singh, Jae-Yong Hwang, Gyanendra Prasad Joshi

“…XGBoost optimizes decision tree ensembles and provides class probabilities, while the ANN processes numerical data to learn deeper representations. …”
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Characterizing the pan-cancer role of exosomal miRNAs in metastasis across cancers by Piyush Agrawal, Gulden Olgun, Arashdeep Singh, Vishaka Gopalan, Sridhar Hannenhalli

“…Exosomal microRNAs (exomiRs) play a critical role in intercellular communication, especially in cancer, where they regulate key cellular processes like proliferation, angiogenesis, and metastasis, highlighting their significance as potential diagnostic and therapeutic targets. …”
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Application of Closed Reconstruction Method in Error Detection of RV Cycloidal Gear by Meng Tian, Tianxing Li, Yulong Li, Jinfan Li

“…Due to the sensitive direction of one-dimensional probe is inconsistent with the definition direction of tooth profile normal error， the error calculation process is tedious， and even the error result is inaccurate， which can not truly reflect the machining shape of the actual tooth profile. …”
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The Implementation of Machine Learning in Lithofacies Classification using Multi Well Logs Data by Sudarmaji Saroji*, Ekrar Winata, Putra Pratama Wahyu Hidayat, Suryo Prakoso, Firman Herdiansyah

“…This research presents an automated lithofacies classification using a machine learning method to increase computational power in shortening the lithofacies classification process's time consumption. The support vector machine (SVM) algorithm has been applied successfully to the Damar field, Indonesia. …”
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FORMATION OF PROFESSIONAL COMPETENCE OF A CARDIOLOGIST AND A HIGHER SCHOOL TEACHER by Александр Константинович Вахрушев, Ксения Владимировна Комарова, Егор Сергеевич Филимонов

“…The article proves that the professional competence of a doctor is developed on the basis of mastering the method of examining a patient in combination with a purposeful selection of literature, accompanied by lectures, seminars and practical classes. In the educational process, it is advisable to change the vector from an informative approach to direct medical and methodological work (activity approach).…”
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Intelligent System for Reducing Waste and Enhancing Efficiency in Copper Production Using Machine Learning by Bagdaulet Kenzhaliyev, Timur Imankulov, Aksultan Mukhanbet, Sergey Kvyatkovskiy, Maral Dyussebekova, Nurdaulet Tasmurzayev

“…The growing environmental impact of copper production necessitates innovative approaches for optimizing metallurgical processes and minimizing waste. This study addresses this challenge by leveraging advanced machine learning (ML) techniques to enhance the efficiency of pyrometallurgical operations such as slag optimization, composition prediction, and waste minimization. …”
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Synthesis and properties of 3-(ethylthio)-9-methyl-6-(alkylthio)pyrazolo[1,5-d][1,2,4]triazolo[3,4-f][1,2,4]triazines by S. O. Fedotov, A. S. Hotsulia

“…Various factors contribute to this process. Among them, we can note the significant possibilities of chemical transformation involving these cycles, the simplicity, and reliability of methods, the creation of molecules with a certain level of bioavailability and the ability to influence a number of biochemical processes. …”
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Development and correctness analysis of the mathematical model of transport and suspension sedimentation depending on bottom relief variation by A. I. Sukhinov, V. V. Sidoryakina

“…The model considers the following processes: advective transfer caused by the aquatic medium motion, micro-turbulent diffusion, and gravity sedimentation of suspended particles, as well as the bottom geometry variation caused by the particle settling or bottom sediment rising. …”
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Ways to increase the competitiveness of an enterprise in human capital management by V. V. Kruglikova, O. A. Kulabnieva

“…It is noted that in Ukrainian enterprises there are active processes of human capital transformation, which are associated with the external and internal environment digitalization. …”
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Machine learning reveals distinct gene expression signatures across tissue states in stony coral tissue loss disease by Kelsey M. Beavers, Daniela Gutierrez-Andrade, Emily W. Van Buren, Madison A. Emery, Marilyn E. Brandt, Amy Apprill, Laura D. Mydlarz

“…This approach identifies genes with high classification accuracy and reveals processes associated with SCTLD resistance, such as immune regulation and lipid biosynthesis, as well as processes involved in disease progression, such as inflammation, cytoskeletal disruption and symbiosis breakdown. …”
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Data efficient prediction of excited-state properties using quantum neural networks by Manuel Hagelueken, Marco F Huber, Marco Roth

“…We show that, in many cases, the procedure is able to outperform various classical models (support vector machines, Gaussian processes, and NNs) that rely solely on classical features, by up to two orders of magnitude in the test mean squared error.…”
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A Two-Branch ResNet-BiLSTM Deep Learning Framework for Extracting Multimodal Features Applied to PPG-Based Cuffless Blood Pressure Estimation by Zenan Liu, Minghong Qiao, Yezi Liu, Jing Zhang, Ling He

“…To address this problem, we propose a novel two-branch deep learning framework combining Residual Networks (ResNet) and Bidirectional Long Short-Term Memory (BiLSTM) for photoplethysmography (PPG)-based cuffless blood pressure estimation. The ResNet branch processes 60 features selected by Support Vector Machine-Recursive Feature Elimination (SVM-RFE) from manually extracted features, including our newly proposed trend features, while the BiLSTM branch processes complete PPG waveforms. …”
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Rickettsia parkeri hypothetical protein RPATATE_1266, a homolog of exopolyphosphatase/guanosine pentaphosphate phosphohydrolase, regulates tick cell apoptosis by Dattatray V. Sawant, Nicole Y. Burkhardt, Haritha Katasani, Benjamin Cull, Ulrike G. Munderloh, Xin-Ru Wang

“…Advancing knowledge of the molecular mechanisms that regulate R. parkeri infection and replication is important for the field of vector-pathogen interactions. This study identifies the RPATATE_1266 gene (a hypothetical protein with homology to exopolyphosphatase/guanosine pentaphosphate phosphohydrolase [Ppx/Gppa] family proteins) as a key regulator of mitochondrial-dependent apoptosis in tick cells, a process critical for rickettsial intracellular survival. …”
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METHODOLOGY OF EVALUATING THE EFFICIENCY OF INFORMATION SUPPORT FOR DECISION-MAKING IN THE MANAGEMENT OF COMPLEX DYNAMIC OBJECTS by Yuriy V. Silenok, Vadim L. Yakovlev

“…Abstract. Objectives The process of managing complex dynamic objects and systems is inevitably connected with the problem of the effectiveness of providing qualitative support information for making managerial decisions. …”
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