Urban-rural inequality in soil heavy metal health risks: Insights from Baoding, China by Lingzhi Luo, Liang Wang, You Li, Hongying Cao, Yanling Guo, Xiaoyong Liao

“…This is the first study to combine high-resolution machine learning mapping, source apportionment, and multi-scale risk assessment in an urban–rural context. …”
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Analysis of fault detection and defect categorization in photovoltaic inverters for enhanced reliability and efficiency in large-scale solar energy systems by Malik Stephanie, Daßler David, Patel Dharm, Klute Carola, Klengel Robert, Dietrich Andreas, Kaufmann Kai, Hennig Carsten, Wehnert Danny, Ebert Matthias

“…A root cause analysis identified the failure pattern through material diagnostics of several power modules from inverters previously installed in the field. …”
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Automated inflammatory bowel disease detection using wearable bowel sound event spotting by Annalisa Baronetto, Annalisa Baronetto, Sarah Fischer, Sarah Fischer, Markus F. Neurath, Markus F. Neurath, Oliver Amft, Oliver Amft

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RAILWAY VEHICLES PANTOGRAPH FAULT DIAGNOSIS BASED ON VARIATIONAL MODE DECOMPOSITION DISPERSION ENTROPY AND SVM by PAN Ning

“…Finally, SVM was used as pattern recgnition method to identified the fault features and the diagnosis results are obtained. …”
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Citrus quality grading based on statistical complexity measurement and multifractal spectrum method by Cao Leping, Wen Zhiyuan

“…It can also make huge economic and social benefits and increase farmers income and agricultural productivity so as to promote the sustained and healthy development of the citrus industry.For the purpose of precise measurement of citrus quality grading, the complexity measurement of Bingtang orange defective fruit damaged by diseases and insect pest patterns were studied by machine recognition, along with the navel orange fruit perimeter-area fractal dimension and the shape, color grading and sugar acid nondestructive detection of section tone unit coordinates multifractal spectrum height and width.Physiological boron deficiency, Eriophyes oleivorus and rind oil spotting disease were very common in Bingtang orange fruits. …”
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Sliding Window-Based Randomized K-Fold Dynamic ANN for Next-Day Stock Trend Forecasting by Jaykumar Ishvarbhai Prajapati, Raja Das

“…The integration of machine learning and stock forecasting is attracting increased curiosity owing to its growing significance. …”
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Zebrafish identification with deep CNN and ViT architectures using a rolling training window by Jason Puchalla, Aaron Serianni, Bo Deng

“…To understand the success of the CNN classifier and inform future real-time identification of zebrafish, we analyzed the impact of shape, pattern, and color by modifying the images of the training set and compared the test results with other prevalent machine learning models.…”
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High-Impedance Fault Detection in DC Microgrid Lines Using Open-Set Recognition by Ivan Grcić, Hrvoje Pandžić

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Optimization of sports injury treatment through artificial intelligence: Methods for effective prevention, diagnosis and rehabilitation by Kimi Milić Marko, Sinanović Šćepan, Jestrović Vladimir

“…Additionally, models for automated injury pattern recognition have been examined, which can significantly contribute to preventative measures and reduce injury incidence. …”
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Predictiveness and drivers of highly pathogenic avian influenza outbreaks in Europe by Michael Rogo Opata, Andrea Lavarello-Schettini, Jan C. Semenza, Joacim Rocklöv

“…Combining these drivers, the outbreak pattern is predicted with an accuracy of 94% for model two (M2). …”
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Estimating Fault Friction From Seismic Signals in the Laboratory by Bertrand Rouet‐Leduc, Claudia Hulbert, David C. Bolton, Christopher X. Ren, Jacques Riviere, Chris Marone, Robert A. Guyer, Paul A. Johnson

“…In a classic laboratory experiment of repeating earthquakes, we find that the seismic signal follows a specific pattern with respect to fault friction, allowing us to determine the fault's position within its failure cycle. …”
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Application of physics-informed neural networks for two-phase flow model with variable diffusion and experimental validation by Daulet Kalesh, Timur Merembayev, Sagyn Omirbekov, Yerlan Amanbek

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Skew Logistic Distribution Applied as Activation Function in Artificial Neural Networks by Eder Silva Dos Santos, Altemir da Silva Braga, Ana Beatriz Alvarez, Thuanne Paixao

“…In recent years, Artificial Neural Networks (ANNs) have stood out among machine learning algorithms in many applications, such as image and video pattern recognition. …”
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Fetal health classification with predictive algorithm by using Ensemble Model by Devi V. Sowmya, Kancharakuntla Manoj Reddy, Paleti Goutam Nayudu, Madhunala Akash

“…Cardiotocography (CTG) is a widely used technique that monitors fetal heart rate (FHR) patterns and uterine contractions, providing critical insights into fetal health. …”
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ANALYSIS AND MINIMIZATION OF THE RISKS OF HARMFUL DEPENDENCIES IN THE PROCESS OF CONTINUOUS INTEGRATION AND IMPLEMENTATION OF SOFTWARE CODE by Danil N. Alekseev, Renat M. Khamitov

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Exploration and validation of the prognostic value of mitophagy and mitochondrial dynamics-related genes in cervical cancer by Jiankui Li, Xi Chen, Juan Li

“…Mendelian randomization (MR) and 101 machine learning models were employed to identify mitophagy- and MD-associated prognostic genes in CC. …”
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AI-driven precision diagnosis and treatment in Parkinson’s disease: a comprehensive review and experimental analysis by Bhekisipho Twala

“…Additionally, we developed and tested a hybrid machine learning model combining deep learning, computer vision, and natural language processing techniques for PD assessment using motor symptom analysis, voice pattern recognition, and gait analysis.ResultsThe systematic review identified 127 relevant studies demonstrating significant advances in AI-driven PD diagnosis, with accuracy rates ranging from 78 to 96%. …”
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Deep and hybrid learning of MRI diagnosis for early detection of the progression stages in Alzheimer’s disease by Ibrahim Abunadi

“…The first proposed system is to classify a data set using artificial neural networks (ANNs) and feed-forward neural networks (FFNN) based on the features extracted in a hybrid manner by using a combination of Local Binary Pattern (LBP), Discrete Wavelet Transform (DWT), and Gray Level Co-occurrence Matrix (GLCM) algorithms. …”
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Long-Term Spatiotemporal Information Extraction of Cultivated Land in the Nomadic Area: A Case Study of the Selenge River Basin by Yifei Sun, Juanle Wang, Kai Li, Sonomdagva Chonokhuu

“…Traditional nomadic areas showed a spatial pattern of reconstruction, characterized by a significant transformation to agricultural land. …”
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A Novel Electromagnetic Induction-Based Approach to Identify the State of Shallow Groundwater in the Oasis Group of the Tarim Basin in Xinjiang During 2000–2022 by Fei Wang, Yang Wei, Rongrong Li, Hongjiang Hu, Xiaojing Li

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