Data-driven intelligent productivity prediction model for horizontal fracture stimulation by Qian Li, Yiyong Sui, Mengying Luo, Bin Guan, Lu Liu, Yuan Zhao

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Binarized Neural Networks for Resource-Efficient Spike Sorting by Luca M. Meyer, Majid Zamani, Andreas Demosthenous

“…This enables the generation of precise modulatory patterns of neuronal circuits. Deep learning-based spike sorting algorithms are based on power-intensive dot products, which poses challenges for on-chip processing with resource-constrained devices. …”
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Robust EEG Characteristics for Predicting Neurological Recovery from Coma After Cardiac Arrest by Meitong Zhu, Meng Xu, Meng Gao, Rui Yu, Guangyu Bin

“…This study aimed to analyze the background patterns of electroencephalogram (EEG) signals from such patients to identify the key indicators for assessing the prognosis after coma. …”
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Comprehensive Performance Comparison of Signal Processing Features in Machine Learning Classification of Alcohol Intoxication on Small Gait Datasets by Muxi Qi, Samuel Chibuoyim Uche, Emmanuel Agu

“…Convenient, unobtrusive intoxication detection methods using equipment already owned by users are desirable. Recent research has explored machine learning-based approaches using smartphone accelerometers to classify intoxicated gait patterns. …”
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Informational Approaches in Modelling Social and Economic Relations: Study on Migration and Access to Services in the European Union by Florentina-Loredana Dragomir-Constantin, Camelia Madalina Beldiman, Monica Laura Zlati

“…The applied methodology includes attribute distribution analysis, identification of hidden patterns through clustering algorithms (K-Means and Expectation-Maximisation) and training of classifiers using regression decision trees with linear leaf models (M5P) corresponding to interdependent data processing and integration modules, exploratory analysis module, machine learning and decision-making modules, oriented to support public policies through explainable scenarios and predictive-evaluative structures. …”
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A Flexible Constrained ICA Approach for Multisubject fMRI Analysis by Hanlu Yang, Trung Vu, Ehsan Ahmed Dhrubo, Vince D. Calhoun, Tülay Adali

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Robust development of data-driven models for methane and hydrogen mixture solubility in brine by Kashif Saleem, Abhinav Kumar, K. D. V. Prasad, Ahmad Alkhayyat, T. Ramachandran, Protyay Dey, Navdeep Kaur, R. Sivaranjani, I. B. Sapaev, Mehrdad Mottaghi

“…In this paper, we aim to form robust data-driven intelligent algorithms founded on various machine learning methods of Support Vector Machine, Random Forest, AdaBoost, Decision Tree, K-nearest Neighbors, Multilayer Perceptron Artificial Neural Network and Convolutional Neural Network to model solubility of hydrogen/methane blend in brine under realistic conditions of underground hydrogen storage projects by utilizing an experimental dataset collected from the existing body of published research. …”
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Layer-by-Layer Multifractal Scanning of Optically Anisotropic Architectonics of Blood Plasma Films: Fundamental and Applied Aspects by Alexander Ushenko, Natalia Pavlyukovich, Oksana Khukhlina, Olexander Pavlyukovich, Mykhaylo Gorsky, Iryna Soltys, Alexander Dubolazov, Yurii Ushenko, Olexander Salega, Ivan Mikirin, Jun Zheng, Zhebo Chen, Lin Bin

“…The laser-based Jones-matrix layer-by-layer theziography relies on polarization filtration and the digital recording of interference patterns from microscopic images of blood plasma facies. …”
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A novel stemness-related lncRNA signature predicts prognosis, immune infiltration and drug sensitivity of clear cell renal cell carcinoma by Jia Liu, Lin Yao, Yong Yang, Jinchao Ma, Ruijian You, Ziyi Yu, Peng Du

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Editorial by Bulent Cavas

“…This issue features 11 original research articles that highlight contemporary developments, challenges, and opportunities in science education. …”
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AI Driven Fraud Detection Models in Financial Networks: A Comprehensive Systematic Review by Nusrat Jahan Sarna, Farzana Ahmed Rithen, Umme Salma Jui, Sayma Belal, Al Amin, Tasnim Kabir Oishee, A. K. M. Muzahidul Islam

“…By analyzing vast datasets, AI can uncover hidden fraud patterns and dynamically adapt to emerging threats. …”
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Identification and validation of hub genes related to neutrophil extracellular traps-mediated cell damage and immune recruitment during abdominal aortic aneurysm by Chuanlong Lu, Heng Wang, Maolin Qiao, Runze Chang, Jinshan Chen, Lizheng Li, Keyi Fan, Sheng Yan, Ruijing Zhang, Honglin Dong

“…We performed an analysis on the infiltration of immune cells within the AAA transcriptome dataset, employing CIBERSORT and ssGSEA algorithms (GSE183464). Next, the gene expression patterns associated with NETs formation (GSE178883) were utilized to examine the physiological processes in peripheral blood neutrophils post-PMA (Phorbol 12-myristate 13-acetate) induction. …”
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Predicting and Preventing School Dropout with Business Intelligence: Insights from a Systematic Review by Diana-Margarita Córdova-Esparza, Juan Terven, Julio-Alejandro Romero-González, Karen-Edith Córdova-Esparza, Rocio-Edith López-Martínez, Teresa García-Ramírez, Ricardo Chaparro-Sánchez

“…The results highlight a wide range of predictive tools and methodologies, notably data visualization platforms (e.g., Power BI) and algorithms like decision trees, Random Forest, and logistic regression, demonstrating effectiveness in identifying dropout patterns and at-risk students. …”
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FLNA, a disulfidptosis-related gene, modulates tumor immunity and progression in colorectal cancer by Qiong Li, Renhong Huang, Lingling Lv, Haifeng Ying, Yuan Wu, YuQing Huang, Yuxi Li, Wen Ma, Xiaoshuang Liu, Qinghui Meng, Fengying Xing, Yan Shen, Lan Zheng

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Lipid-Metabolism-Related Gene Signature Predicts Prognosis and Immune Microenvironment Alterations in Endometrial Cancer by Zhangxin Wu, Yufei Nie, Deshui Kong, Lixiang Xue, Tianhui He, Kuaile Zhang, Jie Zhang, Chunliang Shang, Hongyan Guo

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A quantum machine learning framework for predicting drug sensitivity in multiple myeloma using proteomic data by M. Priyadharshini, B. Deevena Raju, A. Faritha Banu, P. Jagdish Kumar, V. Murugesh, Oleg Rybin

“…QSVM employs quantum kernels to map data into a higher-dimensional Hilbert space, so that the model can detect complex patterns in MM drug resistance. qPCA reduces dimensionality without loss of important variance, and thus improves computation efficiency. …”
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Data-driven EV charging infrastructure with uncertainty based on a spatial–temporal flow-driven (STFD) models considering batteries by Talal Alharbi, Ahmed Abdalrahman, Mostafa H. Mostafa

“…Incorporating energy storage systems (ESS) can help address these challenges by improving overall system efficiency. This research proposes a comprehensive planning methodology that optimizes the placement of EV charging stations by considering traffic flow patterns over space and time. …”
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Identification of gene signatures and potential pharmaceutical candidates linked to COVID-19-related depression based on gene expression profiles by Shaojun Chen, Yiyuan Luo, Lihua Zhang

“…The underlying mechanisms responsible for the coexistence of COVID-19 and depression remain unclear, and more research is needed to find hub genes and effective therapies. …”
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Mapping the use of artificial intelligence in medical education: a scoping review by Erwin Hernando Hernández Rincón, Daniel Jimenez, Lizeth Alexandra Chavarro Aguilar, Juan Miguel Pérez Flórez, Álvaro Enrique Romero Tapia, Claudia Liliana Jaimes Peñuela

“…Data were analyzed using thematic analysis to identify patterns in AI curriculum development and implementation. …”
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PlantGaussian: Exploring 3D Gaussian splatting for cross-time, cross-scene, and realistic 3D plant visualization and beyond by Peng Shen, Xueyao Jing, Wenzhe Deng, Hanyue Jia, Tingting Wu

“…Observing plants across time and diverse scenes is critical in uncovering plant growth patterns. Classic methods often struggle to observe or measure plants against complex backgrounds and at different growth stages. …”
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