Dynamics of Acculturation and Enculturation of Languages to Socio-Economic Development in Nigeria: Implication for Poverty Reduction by Khadijah Ashiru Abdulrahman

“… Every group and society has cultures constituting frameworks for their lives and behavioral patterns. Cultural factors affect socio-economic behavior in at least four ways: its impact on organization and production, attitudes towards consumption and work, the ability to create and manage institutions, and the creation of social networks. …”
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Deep learning to promote health through sports and physical training by Xinyue Li

“…Recent advancements in deep learning and time-series analysis offer an opportunity to develop more personalized and accurate predictive models for assessing health improvement trends.MethodsThis study proposes a Health Improvement Score (HIS) prediction model based on a sequence-to-sequence deep learning architecture with Long Short-Term Memory (LSTM) networks and an attention mechanism. The model integrates heterogeneous time-series data, including physiological parameters (heart rate, blood oxygen levels, respiration rate), activity metrics (steps, distance, calories burned), sleep patterns, and body measurements. …”
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Multistage Training of Fuzzy Cognitive Maps to Predict Preeclampsia and Fetal Growth Restriction by William Hoyos, Rodrigo Garcia, Jose Aguilar

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Comparison of alternative approaches for analysing multi-level RNA-seq data. by Irina Mohorianu, Amanda Bretman, Damian T Smith, Emily K Fowler, Tamas Dalmay, Tracey Chapman

“…It enables the description of genome-wide patterns of expression and the identification of regulatory interactions and networks. …”
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Machine learning based insights into cardiomyopathy and heart failure research: a bibliometric analysis from 2005 to 2024 by Muhammad Junaid Akram, Muhammad Junaid Akram, Asad Nawaz, Asad Nawaz, Yuan Yuxing, Yuan Yuxing, Jinpeng Zhang, Jinpeng Zhang, Huang Haixin, Huang Haixin, Lingjuan Liu, Lingjuan Liu, Xu Qian, Jie Tian, Jie Tian

“…Key metrics examined included top institutions, countries, journals, keywords, co-authorship networks, and keyword co-occurrence patterns. Additionally, the analysis evaluated publication counts, citation trends, H-index, and collaboration metrics to identify research trends and emerging themes in the field.ResultsA total of 2,110 publications retrieved from the last 20 years were included in the analysis. …”
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Enhanced visibility graph for EEG classification by Asma Belhadi, Pedro G. Lind, Pedro G. Lind, Pedro G. Lind, Youcef Djenouri, Youcef Djenouri, Anis Yazidi, Anis Yazidi

“…Our framework offers a holistic approach for capturing both frequency-domain characteristics and temporal dynamics of EEG signals. We evaluate four DL architectures, namely multilayer perceptron (MLP), long short-term memory (LSTM) networks, InceptionTime and ChronoNet, applied to several datasets and in different experimental conditions. …”
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Leaf Development and Its Interaction with Phyllospheric Microorganisms: Impacts on Plant Stress Responses by Huanhuan Yang, Jing Liu, Mei Ma, Zilong Tan, Kaiyue Zhang, Ruiqi Sun, Xinxin Zhan, Dayong Cui

“…Leaf development is regulated by intricately genetic and hormonal networks, which are further modulated by environmental inputs. …”
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A deep reinforcement learning approach for wind speed forecasting by Shahab S. Band, Ting Jia Lin, Sultan Noman Qasem, Rasoul Ameri, Danyal Shahmirzadi, Muhammad Shamrooz Aslam, Hao-Ting Pai, Ely Salwana, Amir Mosavi

“…The conventional wind forecasting methods often struggle to handle the non-stationary and inconsistent wind patterns. This paper presents a hybrid method of  Empirical Wavelet Transform (EWT) and Deep Reinforcement Learning (DRL) for wind speed modeling to overcome the forecasting challenges. …”
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Linking Satellite and Ground Observations of NO₂ in Spanish Cities: Influence of Meteorology and O₃ by Carlos Morillas, Sergio Álvarez, José C. M. Pires, Adrián Jesús García, Sara Martínez

“…Differences between in situ and satellite data were more pronounced in coastal cities, influenced by wind patterns and urban morphology (Madrid: r = 0.86, v = 1.34 m/s; Valencia: r = 0.68, v = 2.97 m/s; Barcelona: r = 0.65, v = 8.04 m/s). …”
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A meta-analysis of resting-state fMRI in postherpetic neuralgia using AES-SDM by Guanzuan Wu, Yurou Luo, Danling Guo, Sangying Lv, Jianfeng Yang

“…This meta-analysis used the anisotropic effect size-signed differential mapping (AES-SDM) approach to evaluate rs-fMRI studies on PHN and to provide more robust insights into the brain networks involved in processing PHN pain.Materials and methodsA systematic search of PubMed, Embase, Web of Science, and the Cochrane Database was performed for rs-fMRI studies comparing PHN patients with healthy controls, up until 1 November 2024. …”
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Rethinking Inequality: The Complex Dynamics Beyond the Kuznets Curve by Sarthak Pattnaik, Maryan Rizinski, Eugene Pinsky

“…Forecasts using ARIMA and neural networks indicate continued fluctuations in inequality through 2030, with the U.S. and Germany showing upward trends while France and the UK demonstrate relative stability. …”
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Sentiment Analysis of ChatGPT on Indonesian Text using Hybrid CNN and Bi-LSTM by Vincentius Riandaru Prasetyo, Mohammad Farid Naufal, Kevin Wijaya

“…This study explores sentiment analysis on Indonesian text using a hybrid deep learning approach that combines Convolutional Neural Networks (CNN) and Bidirectional Long Short-Term Memory (Bi-LSTM). …”
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Non-invasive detection of Parkinson’s disease based on speech analysis and interpretable machine learning by Huanqing Xu, Wei Xie, Mingzhen Pang, Ya Li, Luhua Jin, Fangliang Huang, Xian Shao

“…Several machine learning algorithms, including K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Decision Trees, Random Forests, and Neural Networks, were implemented and evaluated. Model performance was assessed using accuracy, recall, F1 score, and area under the receiver operating characteristic curve (AUC-ROC) metrics. …”
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GeoBM: A Python-based tool for integrated visualization of global bibliometric data by Chun Chong Fu, Jorge Fleta-Asín, Fernando Muñoz, Carlos Sáenz-Royo, Loo Keat Wei

“…By providing a dual-focus representation of publication density and collaborative strength, GeoBM offers a powerful tool for the spatial analysis of global research networks, contributing to more nuanced evaluations in science policy, research management, and innovation studies.…”
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Energy Efficiency in Smart Buildings through Prediction modeling and Optimization Using a Modified Whale Optimization Algorithm by El Assri Nasima, Ennejjar Mohammed, Jallal Mohammed Ali, Chabaa Samira, Zeroual Abdelouhab

“…The primary focus is on evaluating the performance of two prominent and widely-used machine learning algorithms: Artificial Neural Networks (ANN) and Random Forest (RF). …”
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Cardioepigenetics in action: aerobic exercise-induced modulation of miRNAs, lncRNAs, and chromatin remodeling in cardiovascular disease by Shoudu Yuan, Qi Ye, Ran Qin

“…Emerging evidence highlights the central role of epigenetic modifications and non-coding RNAs including microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) in the regulation of gene expression networks underlying cardiovascular homeostasis and disease. …”
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Machine Learning-Based Diabetes Risk Prediction Using Associated Behavioral Features by Ayodeji O. J. Ibitoye, Joseph D. Akinyemi, Olufade F. W. Onifade

“…With different uncertainties in human lifestyles, it is difficult to predict diabetes while assuming that the risk patterns are the same for all. The likelihood of diabetes in a patient is mostly predicted using machine learning (ML) models on features explicitly available in datasets, while the intrinsic relationship between features viz-a-viz their potential relevance to the presence of diabetes is oftentimes neglected. …”
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A comparative study of machine learning algorithms for fall detection in technology-based healthcare system: Analyzing SVM, KNN, decision tree, random forest, LSTM, and CNN by Afuan Lasmedi, Isnanto R. Rizal

“…The research utilizes a dataset consisting of 1,428 training samples and 573 testing samples, evaluated using a 10-fold cross-validation technique. …”
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Modeling the Impact of Climate Change on Soil Health Using Predictive Analytics by Alsalami Zaid, Mandapati A. H. A. Hussein, Sundari Venkata Rama

“…Reliable methods for predicting and managing changes in soil properties in response to increasing temperature fluctuations, shifting precipitation patterns, and extreme weather events are needed, as these changes are occurring in the face of soil properties. …”
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Pose estimation for health data analysis: advancing AI in neuroscience and psychology by Juan Yu, Daoyu Zhu

“…IntroductionThe integration of artificial intelligence (AI) with health data analysis offers unprecedented opportunities to advance research in neuroscience and psychology, particularly in extracting meaningful patterns from complex, heterogeneous, and high-dimensional datasets. …”
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