Heterogeneity in the Driver Behavior: An Exploratory Study Using Real-Time Driving Data by Jahnavi Yarlagadda, Digvijay S. Pawar

“…Driver behavior heterogeneity is a significant aspect to understand the individual behavioral variations and develop driver assistance systems. This study characterizes the heterogeneity in driving behavior using real-time driving performance features. …”
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Mapping Urban Villages in Beijing–Tianjin–Hebei Core Cities Through a Dual-Stage Fusion of Individual Building Footprints and Glimmer Imagery by Jianqiang Hu, Yuheng Fu, Chaoqun Zhang, Manchun Li, Bingbo Gao, Qiancheng Lv, Jing Yang, Ziyue Chen

“…Accelerated urbanization has led to the widespread emergence of informal urban settlements, particularly urban villages (UVs), posing significant challenges to social equity, public welfare, and sustainable urban development. Current research on UV identification often relies solely on high-resolution satellite imagery, neglecting the unique spatial patterns and socioeconomic characteristics of UVs, thus limiting the effective distinction between UVs and other confusing land-use types. …”
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Enhancing prediction of crop yield and soil health assessment for sustainable agriculture using machine learning approach by Kapil Netaji Vhatkar, Shweta Ashish Koparde, Sonali Kothari, Jayesh Sarwade, Kishor Sakur

“…The goal of this research is • to make sophisticated models for precise crop production forecasting and thorough evaluation of soil health, • to improve sustainability by optimize farming methods, and • to assist farmers in making well-informed decisions.Iterative Partitioning-Ensemble Filter (IP-EF) is a technique used for feature selection, enhancing model performance by iteratively partitioning data and refining feature subsets. …”
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Representation of Feminism in Russian Media Space: Authors and Narratives by Nikita A. Argylov, Ksenia A. Khramtsovskaya

“…The authors examine the features of media representation of feminism as a topical phenomenon and study related stories in Russian news and mass media over recent years. …”
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Forecasting Temperature Time Series Data Using Combined Statistical and Deep Learning Methods: A Case Study of Nairobi County Daily Temperature by John Kamwele Mutinda, Amos Kipkorir Langat, Samuel Musili Mwalili

“…In addition, the high R-squared value of 0.779234 indicates that approximately 77.92% of the variance in the observed data is explained by the model, showcasing its robustness and effectiveness in capturing the underlying patterns in temperature time series data. Overall, this study underscores the importance of VMD in preprocessing data to enhance feature representation and forecasting accuracy. …”
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Surface Damage Detection in Hydraulic Structures from UAV Images Using Lightweight Neural Networks by Feng Han, Chongshi Gu

“…The developed DL-based model integrates an enhanced Fast-SCNN backbone for efficient feature extraction, a Lightweight Feature Pyramid Attention (LFPA) module for multi-scale context enhancement, and an Edge Attention Module (EAM) for refined boundary localization. …”
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Frequency and Determinants of Flare and Persistently Active Disease in a Large Multinational Prospective Lupus Cohort by Yanjie Hao, Dylan Hansen, Worawit Louthrenoo, Yi‐Hsing Chen, Jiacai Cho, Aisha Lateef, Laniyati Hamijoyo, Shue Fen Luo, Yeong‐Jian Wu, Sandra Navarra, Leonid Zamora, Zhanguo Li, Sargunan Sockalingam, Yasuhiro Katsumata, Masayoshi Harigai, Lanlan Ji, Zhuoli Zhang, Madelynn Chan, Jun Kikuchi, Tsutomu Takeuchi, Sang‐Cheol Bae, Fiona Goldblatt, Sean O'Neill, Kristine (Pek Ling) Ng, B. M. D. B. Basnayake, Nicola Tugnet, Naoaki Ohkubo, Yoshiya Tanaka, Cherica Tee, Michael Tee, C. S. Lau, Ning Li, Vera Golder, Alberta Hoi, Rangi Kandane‐Rathnayake, Eric Morand, Shereen Oon, Mandana Nikpour, for the Asia Pacific Lupus Collaboration

“…Conclusion Both flare and PAD are common disease activity patterns in SLE; both predict organ damage accrual but differ in disease features and predictive factors. …”
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Profiling antivaccination channels in Telegram: early efforts in detecting misinformation by Aelita Skarzauskiene, Monika Maciuliene, Aiste Dirzyte, Gintare Guleviciute

“…This study addresses the methodological gap in capturing and analysing misinformation on Telegram, with a particular focus on the anti-vaccination community.MethodsThe research was conducted in three phases: (1) a structured review of literature on misinformation dissemination via Telegram, (2) development of a conceptual framework incorporating features of message creators, message content, intended targets and broader social context, and (3) application of this framework to anti-vaccination Telegram channels using latent profile analysis (LPA). …”
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"Quattuor sanctissimi episcopi": not just St. Patrick by O. A. Kuchtenkova

“…The aim of the article is to place the aforementioned Saints within the life of the Irish society and Church; distill their distinctive features, spiritual, and social role within the early Medieval Church of Ireland (by analysing narrative patterns, genealogies, and mentions); and describe the development of their modern-day cult. …”
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A Novel Chaotic Neural Network Using Memristive Synapse with Applications in Associative Memory by Xiaofang Hu, Shukai Duan, Lidan Wang

“…The proposed memristive CNN has four significant features: (1) nanoscale memristors can simplify the synaptic circuit greatly and enable the synaptic weights update easily; (2) it can separate stored patterns from superimposed input; (3) it can deal with one-to-many associative memory; (4) it can deal with many-to-many associative memory. …”
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On the role of knowledge graphs in AI-based scientific discovery by Mathieu d’Aquin

“…Indeed, the ability of such models to extrapolate from data, seemingly finding unknown patterns relating implicit features of the objects under study to their properties can, at the very least, help accelerate and scale up those studies as demonstrated in fields such as molecular biology and chemistry. …”
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Coastal environmental changes in Ninh Thuan Province, South-Central Vietnam. by Bijeesh Kozhikkodan Veettil, Siham Acharki, Vikram Puri, Vanna Teck

“…This study investigated five critical coastal environmental features (shoreline dynamics, drought conditions, soil salinity trends, mangrove deforestation, and reforestation, as well as spatiotemporal variations in aquaculture and salt farming areas) using satellite data and geospatial analysis. …”
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CIRCUIT-DESIGN SOLUTIONS AND INFORMATION SUPPORT OF CITY ELECTRIC NETWORKS IN THE CONDITIONS OF THE SMART GRID by M. I. Fursanov

“…Therefore, the present article presents and features the main directions of development of automatic control modes of the SMART GRID.…”
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Designed for safety: characteristics and trends in crime prevention through environmental design research by Yu Wen, Hong Qi, Tao Long, Xinjia Zhang

“…This helps to propose crime prevention strategies for new social issues and crime patterns, thereby providing strong support for the sustainable development of cities.…”
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Monitoring paddy rice cultivation adjustments in Northeast China through time series remote sensing and deep learning by Shihao Wang, Chong Huang, Lingxiao Huang, Xinliang Xu, Huading Shi, Qingbao Gu, Qiang Xue, Shiai Liu, Chenchen Zhang

“…To these, in this study, we developed a paddy rice mapping framework that integrates automatically generated training samples, time series features from key cultivation stages, and a deep learning model to improve paddy rice identification accuracy in Northeast China, which is a typical rice-wetland coexisting area. …”
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Optical thermometry and fingerprint detection in SrLa1−xEuxLiTeO6 phosphors with abnormal thermal quenching effect by Zheng-Rong Xia, Rong-Qing Li, Qing-Hua Zheng, Fang-Fang Liu, Wei-Wei Zhou, Kai-Xuan Yuan, Yue Tong, Wang Zhao

“…Moreover, the fluorescence images of fingerprints developed by SrLa0.5Eu0.5LiTeO6 phosphors were clearly visible, and level I–III detail features were highlighted. …”
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Detecting heavy trucks from mobile phone trajectories using image-based behavioral representations and deep learning models by Franco Basso, Félix des Rotours, Tomás Maldonado, Raúl Pezoa, Mauricio Varas

“…By employing Call Detail Records (CDR) and introducing an image-inspired architecture, the study uses Convolutional Neural Networks (CNN) to model the microscopic behavioral patterns of mobile devices. Our numerical results show that our proposed approach outperforms more classical machine learning methods that rely only on aggregated features. …”
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No genetic structure detected in multiple Brazilian marine fish species by Julia Tovar Verba, Adam Stow, Priscila F. M. Lopes, Maria Grazia Pennino, Antonio Sole-Cava, Sergio Maia Queiroz Lima

“…Consequently, identifying evolutionarily significant genetic lineages within exploited species can benefit the development of conservation management strategies. With the absence of genetic data life history traits are sometimes assumed to be good predictors of genetic patterns in natural populations. …”
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Detection and Localization of Stationary Waves on Venus Using a Self‐Supervised Anomaly Detection Model by Husnu Baris Baydargil, Jose Eduardo Oliveira Silva, Yeon Joo Lee, Meeyoung Cha

“…To address this, we propose a self‐supervised anomaly detection model based on a vector‐quantized generative adversarial network to identify and localize stationary atmospheric waves in spacecraft images of Venus. Our model is developed over Akatsuki images of Venus and is trained on smaller cropped images containing features other than stationary waves, allowing it to learn the underlying patterns of normal cloud features. …”
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Water quality caracterization of Drean-Annaba aquifer (NE Algeria): using hydrochemical and isotopic tools by Abderahmane Yahi, Larbi Djabri, Rania Remmani, Hamza Bouguerra, Salah Eddine Tachi, Fehdi Chemseddine, Hadji Rihab, Naziha Mokadem, Younes Hamed, Salem Bouri

“…As a result, hydrochemical changes in groundwater and surface water, such as wadis, have a predictable pattern. To demonstrate these chemical effects statistically, principal component analysis (PCA) tools and a nickel diagram were used. …”
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