Rethinking Inequality: The Complex Dynamics Beyond the Kuznets Curve by Sarthak Pattnaik, Maryan Rizinski, Eugene Pinsky

“…These findings challenge the conventional Kuznets hypothesis and demonstrate that contemporary inequality patterns are influenced by factors beyond economic development, including technological change, globalization, and policy choices. …”
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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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Multichannel convolutional transformer for detecting mental disorders using electroancephalogrpahy records by Mamadou Dia, Ghazaleh Khodabandelou, Syed Muhammad Anwar, Alice Othmani

“…Our proposed model, the multichannel convolutional transformer, integrates the strengths of both convolutional neural networks and transformers. Before feeding the model as low-level features, the input is pre-processed using a common spatial pattern filter, a signal space projection filter, and a wavelet denoising filter. …”
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Design and Analysis of Plasma-Based Reconfigurable Maxwell Fish-Eye-Lens Antennas by Jafar Bazrafshan, Fatemeh Sadeghikia, Mohamed Himdi, Ali Karami Horestani, Hajar Binti Ja'afar

“…Specifically, the enhanced signal quality and dynamic beam-forming capabilities make it ideal for satellite communication, deep space missions, and interplanetary networks. The ability to dynamically adjust the radiation pattern and beam direction provides significant advantages in improving communication efficiency and reliability in challenging space environments.…”
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Trends in progress test performance of medical students at a university in Peru. by Franco Romaní-Romaní, César Gutiérrez

“…This study aimed to evaluate longitudinal trends in PT scores at a Peruvian medical school.…”
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Source Detection and Functional Connectivity of the Sensorimotor Cortex during Actual and Imaginary Limb Movement: A Preliminary Study on the Implementation of eConnectome in Motor... by Alkinoos Athanasiou, Chrysa Lithari, Konstantina Kalogianni, Manousos A. Klados, Panagiotis D. Bamidis

“…The study of functional connectivity networks (FCNs) aims at successfully modeling the dynamics of information flow between cortical areas. …”
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Smart E-Tongue Based on Polypyrrole Sensor Array as Tool for Rapid Analysis of Coffees from Different Varieties by Alvaro Arrieta Almario, Oriana Palma Calabokis, Eisa Arrieta Barrera

“…The results demonstrate that the polypyrrole sensors can generate distinct electrochemical patterns, serving as “fingerprints” for each coffee variety. …”
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Cognitive difference text classification in online knowledge collaboration based on SA-BiLSTM hybrid model by Fengjun Liu, Na Zhao, Guoqing Zhu

“…However, accurate extraction of semantic features and contextual patterns from such texts remains challenging in multi-dimensional discourse contexts. …”
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A GPT-Based Approach for Cyber Threat Assessment by Fahim Sufi

“…It utilizes a hybrid methodology combining spectral residual transformation and Convolutional Neural Networks (CNNs) to identify anomalies in time-series cyber event data, alongside regression models for evaluating the significant factors associated with cyber events. …”
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Explainable AI-based suicidal and non-suicidal ideations detection from social media text with enhanced ensemble technique by Daniyal Alghazzawi, Hayat Ullah, Naila Tabassum, Sahar K. Badri, Muhammad Zubair Asghar

“…By leveraging Explainable AI’s interpretability to analyze the features, the model elucidates the reasoning behind its classifications leading to a comprehension of hidden patterns associated with suicidal ideations. Our system is compared to cutting-edge methods on several social media datasets using experimental evaluations, demonstrating that it is superior, since it detects suicidal content more accurately than others. …”
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Robust fault detection and classification in power transmission lines via ensemble machine learning models by Tahir Anwar, Chaoxu Mu, Muhammad Zain Yousaf, Wajid Khan, Saqib Khalid, Ahmad O. Hourani, Ievgen Zaitsev

“…This research introduces a novel approach for fault detection and classification by analyzing voltage and current patterns across transmission line phases. Leveraging a comprehensive dataset of diverse fault scenarios, various machine learning algorithms—including Random Forest (RF), K-Nearest Neighbors (KNN), and Long Short-Term Memory (LSTM) networks—are evaluated. …”
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Quantification of Subsurface Hydrological Connectivity Using Wavelet Coherence Analysis by REN Ruijie, Fan Bihang, ZHANG Yaling, WANG Erqing, YANG Ruxin, HAN Xiaole, LIU Jintao, GUO Li

“…The wavelet coherence coefficient matrix successfully revealed multi-scale patterns in soil moisture dynamics, providing a robust metric for quantitatively analyzing the coupling mechanisms between soil moisture and eco-hydro-meteorological factors. …”
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Mapping the Landscape of Digital Government Transformation: A Bibliometric Analysis by Younus Muhammad, Purnomo Eko Priyo, Nurmandi Achmad, Mutiarin Dyah, Manaf Halimah Abdul, Prianto Andi Luhur, Sohsan Imron, Irawan Bambang, Salahudin Salahudin, Akbar Idil, Khairunnisa Tiara

“…The literature review makes use of citation analysis to detect patterns in the relationship between scientific papers, whereas the bibliometric analysis employs quantitative tools to evaluate published physical units. …”
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Targeting immune microenvironment in cervical cancer: current research and advances by Zhen Zhang, Miao Liu, Yu An, Chongqing Gao, Tao Wang, Zhi Zhang, Guixiang Zhang, Shuo Li, Wei Li, Mengjia Li, Gangcheng Wang

“…This review comprehensively examines the cellular and molecular components of the tumor immune microenvironment (TIME) in cervical cancer, encompassing patterns of immune cell infiltration (T cells, B cells, NK cells, DCs, TAMs), immune checkpoint molecules, and cytokine/chemokine networks. …”
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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

“…Additionally, we discuss aerobic exercise-induced changes in DNA methylation and histone modification patterns that contribute to transcriptional reprogramming and long-term cardiovascular benefits. …”
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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 superiority of CNN and LSTM in detecting more complex fall patterns aligns with previous studies emphasizing the capabilities of deep learning models in sensor data classification. …”
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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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Optimizing Energy Forecasting Using ANN and RF Models for HVAC and Heating Predictions by Khaled M. Salem, Javier M. Rey-Hernández, A. O. Elgharib, Francisco J. Rey-Martínez

“…Industry 5.0 is transforming energy demand by integrating sustainability into energy planning, ensuring market stability while minimizing environmental impact for future generations. There are several patterns for calculating energy consumption depending on whether it is measured daily, monthly, or annually through the integration of artificial intelligence approaches, particularly Artificial Neural Networks (ANNs) and Random Forests (RFs), and within the framework of Industry 5.0. …”
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A Natural Language Processing Model for Predicting Five-Star Ratings of Video Games on Short-Text Reviews by Piyush Jaiswal, Hardik Setia, Pranshu Raghuwanshi, Princy Randhawa

“…The accuracy is improved by employing different machine learning models, which enables game creators and other industry stakeholders to identify patterns about the behavior and preferences of the users.…”
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