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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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

“…These outputs are fused into a combined feature vector, which is then used by a meta-classifier for final predictions. …”
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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

“…Gene Ontology analysis revealed both general cancer processes, such as wound healing and epithelial cell proliferation, as well as cancer-specific processes, such as “angiogenesis” in the kidney and “ossification” in the lung. …”
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Predicting Three-Dimensional (3D) Printing Product Quality with Machine Learning-Based Regression Methods by Ahmet Burak Tatar

“…Within this framework, prediction models including Linear Regression (LR), Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), Gaussian Process Regression (GPR), and Multi-Layer Perceptron (MLP) were developed, and their performances were assessed using metrics such as accuracy (R²), error rates (RMSE, MSE, MAE), and computational time. …”
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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 can be of value for predicting the spread of contaminants and changes in the bottom topography, both under an anthropogenic impact and due to the natural processes in the coastal area.…”
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Branched-chain amino acids modulate the proteomic profile of Trypanosoma cruzi metacyclogenesis induced by proline. by Janaina de Freitas Nascimento, Flávia Silva Damasceno, Sabrina Marsiccobetre, Francisca Natália de Luna Vitorino, Renan Weege Achjian, Julia Pinheiro Chagas da Cunha, Ariel Mariano Silber

“…Trypanosoma cruzi, the causative agent of Chagas disease, has a complex life cycle that involves triatomine insects as vectors and mammals as hosts. The differentiation of epimastigote forms into metacyclic trypomastigotes within the insect vector is crucial for the parasite's life cycle progression. …”
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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

“…Five ML algorithms were evaluated, with Gradient Boosting and Support Vector Regression demonstrating superior performance in capturing complex, non-linear relationships. …”
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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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«Smart City» in Socio-Political Projection (The Case of Barcelona) by A. V. Baranov, L. N. Garas

“…It is emphasized that information and communication technologies led to the transformation of a rigidly vertical bureaucratic system of exercising power and set the vector of its transition to a horizontal (network model) based on the effects of high technologies.It is noted that the modern model of exercising power in Barcelona presupposes the active involvement of citizens in the processes of city management, based on the use of technological platforms that simplify coworking processes.As a result of the study, the authors come to the conclusion that the contemporary paradigm of the “smart city” involves the involvement of citizens as active participants in decisionmaking and planning. …”
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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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Comparative transcriptomics of transgenic tobacco plants overexpressing Miscanthus sinensis BTF3 by Ji Won Seo, Da Ye Ham, Jae Geun Lee, Hee Young Kim, Ik Young Choi, Myong Jo Kim, Eun Soo Seong

“…Gene ontology (GO) analysis of up-regulated transcripts showed that the most expressed transcripts were involved in biological processes. Analysis of down-regulated differentially expressed genes (DEGs) showed that they were involved in metabolic processes that corresponded to biological processes. …”
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Prediction of breast cancer Invasive Disease Events using transfer learning on clinical data as image-form. by Annarita Fanizzi, Samantha Bove, Maria Colomba Comes, Erika Francesca Di Benedetto, Agnese Latorre, Francesco Giotta, Annalisa Nardone, Alessandro Rizzo, Clara Soranno, Alfredo Zito, Raffaella Massafra

“…After transforming each patient, represented by a vector of clinical information, to an image form, we extracted low-level quantitative imaging features by means of a pre-trained Convolutional Neural Network, namely, AlexNET. …”
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Method for Solving the Problem of Load Movement over the Ice Cover of a Reservoir along a Complex Trajectory by A. V. Galaburdin

“…The development of the polar regions of the World Ocean contributed to an increased interest in studying wave processes in water bodies with ice cover caused by the action of a mobile load. …”
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A novel signal peptide toolbox for optimized heterologous expression of yeast pheromones in Bacillus subtilis by Tomislav Vološen, Henri Max Deda, Anica Walther, Philipp F. Popp, Thorsten Mascher, Diana Wolf

“…We developed an integrative evaluation vector in which the promoter, SPs, and a coding sequence (CDS) of the POI are easily exchangeable. …”
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Homogeneous difference schemes for the coupled problems of hydrodynamics and elasticity by I.P. Tsygvintsev, A.Yu. Krukovskiy, Yu.A. Poveshchenko, V.A. Gasilov, D.S. Boykov, S.B. Popov

“…Taking into account the energy balance of the medium, the families of integral consistent approximations of the vector analysis operators, which are sufficient for the discrete modeling of these processes considering the space curvature caused by the cylindrical geometry of the system, were built. …”
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What Can DKIST/DL-NIRSP Tell Us about Quiet-Sun Magnetism? by Jiayi Liu, Xudong Sun, Peter W. Schuck, Sarah A. Jaeggli

“…In this paper, we assess the diagnostic capability of the Diffraction Limited Near Infrared Spectropolarimeter (DL-NIRSP) instrument on DKIST for the energy transport processes in the quiet-Sun photosphere. To this end, we synthesize high-resolution, high-cadence Stokes profiles of the Fe i 630 nm lines using a realistic magnetohydrodynamic simulation, degrade them to emulate the DKIST/DL-NIRSP observations, and subsequently infer the vector magnetic and velocity fields. …”
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Effective Machine Learning Techniques for Dealing with Poor Credit Data by Dumisani Selby Nkambule, Bhekisipho Twala, Jan Harm Christiaan Pretorius

“…Data are vital at the core of the credit decision-making processes. Decision-making depends heavily on accurate, complete data, and failure to harness high-quality data would impact credit lenders when assessing the loan applicants’ risk profiles. …”
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Comparison of zero-shot approach and retrieval-augmented generation for analyzing the tone of comments in the Ukrainian language by M. Prytula, O. Sinkevych, I. Olenych

“…To implement RAG, Qdrant was utilized as a vector database, while the LangChain library enabled the integration of a large language model with external data sources. …”
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