A Novel PNDA-MMNet Model for Evaluating Dynamic Changes in the Brain State of Patients with PTSD During Neurofeedback Training by Peng Ding, Lei Zhao, Anmin Gong, Wenya Nan, Yunfa Fu

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Teenagers on TikTok: Play, Mimesis, and “Digital Authority” by N.K. Radina

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Presentating a multi-objective optimization model for resource-constrained project scheduling regarding financial costs, time delays and the reliability function by Saeideh Naderi, Mohsen Vaez-Ghasemi, Farzad Movahedi Sobhani

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Identification and mechanistic insights of cell senescence-related genes in psoriasis by Guiyan Deng, Cheng Xu, Dunchang Mo

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Development of an Internet of Things (IoT) embedded open-source gamma-ray detector using CMOS image sensor technology by D. L. Corzi, D. L. Corzi, J. Lipovetzky, J. Lipovetzky, J. Lipovetzky, M. Gómez Berisso, M. Gómez Berisso, M. Gómez Berisso

“…The detector uses simple, physics-based processing algorithms to allow for particle detection using CMOS image sensors on boards with limited processing capabilities. …”
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A New Perspective on Overfeeding in the Intensive Care Unit (ICU): Challenges, Dangers and Prevention Methods by Vlad-Dimitrie Cehan, Alina-Roxana Cehan, Mihai Claudiu Pui, Alexandra Lazar

“…Clinicians must be proficient in interpreting metabolic data, understanding the principles of energy balance, and implementing appropriate feeding algorithms. Interdisciplinary collaboration among critical care teams, including dieticians, physicians, and nurses, is crucial for ensuring consistent and effective nutritional management. …”
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Elicitation of Norwegian EQ-5D-5L values for hypothetical and experience-based health states based on the EuroQol Valuation Technology (EQ-VT) protocol by Knut Stavem, Tonya Moen Hansen, Ylva Helland, Liv Ariane Augestad, Kim Rand, Andrew Garratt

“…Introduction Norway is one of several European countries that lacks a national value set and scoring algorithm for the EuroQol five dimensions (EQ-5D). …”
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Estimating Energy Consumption During Soil Cultivation Using Geophysical Scanning and Machine Learning Methods by Jasper Tembeck Mbah, Katarzyna Pentoś, Krzysztof S. Pieczarka, Tomasz Wojciechowski

“…These data, along with soil texture, served as inputs for predicting fuel consumption and field productivity. …”
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Carbonate Seismic Facies Analysis in Reservoir Characterization: A Machine Learning Approach with Integration of Reservoir Mineralogy and Porosity by Papa Owusu, Abdelmoneam Raef, Essam Sharaf

“…To this end, this study utilizes an unsupervised comparative hierarchical and K-means ML classification of the whole 3D seismic data spectrum and a suite of spectral bands to overcome the cluster “facies” number uncertainty in ML data partition algorithms. This comparative ML, which was leveraged with seismic resolution data preconditioning, predicted geologically plausible seismic facies, i.e., seismic facies with spatial continuity, consistent morphology across seismic bands, and two ML algorithms. …”
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Research on Short-Term Load Forecasting of LSTM Regional Power Grid Based on Multi-Source Parameter Coupling by Bo Li, Yaohua Liao, Siyang Liu, Chao Liu, Zhensheng Wu

“…Traditional short-term power load-forecasting methods have certain limitations in accuracy and stability, especially when dealing with complex weather and voltage changes. To improve the prediction accuracy, this paper proposes a short-term power load-forecasting model of a regional power grid based on multi-source parameter coupling with a long short-term memory neural network (LSTM) and adopts an improved particle swarm optimization (IPSO) algorithm to optimize the LSTM network. …”
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Development of a mathematical model of dependence of specific volumetric electrical resistance of SIW-4 insulation on factors affecting its reliability by Denisov I. V.

“…It also opens up the possibility of developing the second stage of the study, associated with the construction of an algorithm for the method of predictive assessment of the residual life of the insulation material of the conductor under study.…”
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Patient perspectives on the use of digital medical devices and health data for AI-driven personalised medicine in Parkinson’s Disease by Ivana Paccoud, Ivana Paccoud, Mayca Marín Valero, Laura Carrasco Marín, Noémi Bontridder, Alzhraa Ibrahim, Alzhraa Ibrahim, Jüergen Winkler, Jüergen Winkler, Messaline Fomo, Messaline Fomo, Stefano Sapienza, Stefano Sapienza, Fouad Khoury, Jean-Christophe Corvol, Holger Fröhlich, Holger Fröhlich, Jochen Klucken, Jochen Klucken, Jochen Klucken

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A PCC-Ensemble-TCN model for wind turbine icing detection using class-imbalanced and label-missing SCADA data by Shenyi Ding, Zhijie Wang, Jue Zhang, Fang Han, Xiaochun Gu, Guangxiao Song

“…Temporal convolutional networks are trained to extract features and make predictions on each subset. The final prediction result is obtained by ensembling the prediction results of all temporal convolutional network models. …”
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Artificial intelligence (machine learning) in the psychology of learning: Unveiling new insights and directions by Nora Darjazini, Mohammad Hossein Zarghami, Reza Ghorban Jahromi, Leila Shobeiry

“…Results: 260 features were extracted from the computer texts prepared from the speech and writing learners responses by natural language processing (NLP) algorithms. We used learning models of decision tree, nearest neighbor, support vector method, neural network and regularized linear method to predict reading comprehension using extracted linguistic features. …”
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Estimation of the High-Frequency Feature Slope in Gravitational Wave Signals from Core Collapse Supernovae Using Machine Learning by Alejandro Casallas-Lagos, Javier M. Antelis, Claudia Moreno, Ramiro Franco-Hernández

“…We evaluated the efficiency and performance of the ML algorithms using a set of metrics to measure their ability to accurately predict the HFF slope within the data set. …”
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Recent Results on the Use of Artificial Intelligence Techniques Applied to Wireless Power Transfer Systems by Federico Amadei, Michele Quercio, Francesco Riganti Fulginei

“…We explore how ML can optimize the geometric and structural design of WPT coils, predict the optimal parameters for inductive couplers, and enhance coupling efficiency under varying conditions. …”
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Pharmacological potential of 3,5-dimethyl-4-(3-(5-nitrofuran-2-yl)allylidenamino)-1-alkyl-1,2,4-triazolium bromides by A. S. Hotsulia, O. I. Panasenko, T. S. Brytanova

“…A molecular docking method that uses a variety of computational algorithms to predict and analyze interactions, including determining the presence of possible binding sites, estimating binding energies, and the spatial arrangement of molecules. …”
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Improved Key Microbial Biomarker Discovery Using Ensemble Statistical Methods by Walter Pirovano, Yashjit Gangopadhyay, Mirna Lilian Baak, Christiaan Arie de Leeuw, Radhika Bongoni, Eline Suzanne Klaassens

“…However, advanced biostatistical analysis is required to properly combine microbiome taxonomic abundance data with phenotypical metadata and reliably predict disease states. While differential abundance analysis and machine-learning techniques are widely used to perform such analyses, selecting the best method is not trivial due to the complexity and specific characteristics of both the data and the algorithms. …”
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Mathematical Modelling and Optimisation of Operating Parameters for Enhanced Energy Generation in Gas Turbine Power Plant with Intercooler by Anthony O. Onokwai, Udochukwu B. Akuru, Dawood A. Desai

“…The RSM, being the initial model, was able to predict but lacked precision when compared with the nonlinear influences that were modelled by ANFIS PSO and ANFIS GA, with power output, thermal efficiency and specific fuel consumption (sfc) having corresponding R² values of 0.979, 0.987 and 0.972. …”
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Two General Data Protection Regulation (GDPR) Compliant Approaches to Scoring Firm Financial Frailty in Business Litigation by A. E Rodriguez, Gazi Murat Duman, Ron Kuntze

“…We then map the scores onto bivariate classes using Fisher-Jenks clustering. Each algorithm’s accuracy is obtained by comparing its predictions of either failure of viability to those of the labeled data in O'Haver (1993). …”
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