Beyond Linearity: Uncovering the Complex Spatiotemporal Drivers of New-Type Urbanization and Eco-Environmental Resilience Coupling in China’s Chengdu–Chongqing Economic Circle with... by Caoxin Chen, Shiyi Wang, Meixi Liu, Ke Huang, Qiuyi Guo, Wei Xie, Jiangjun Wan

“…These findings enrich existing research and offer policy insights to enhance coordinated development in the Chengdu–Chongqing Economic Circle.…”
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SankeyNetwork: A clear and concise visualization tool for bibliometric data by Sher-Wei Lim, Willy Chou, Lifan Chen

“…Slope graphs showed upward trends in four core elements over the past four years.The study concludes that these methods provide clearer insights while reducing visual complexity, and recommends combining performance sheets, Sankey diagrams, and slope graphs in future bibliometric analyses to better detect hotspots and evolving research patterns. • Sankey diagrams to enhance traditional bibliometric visualization methods. • Analyzing 2252 articles from Journal of METHODSX (2020–2024) to highlight author collaborations. • Key insights include the prominence of U.S., and Symbiosis International (India) in author collaborations.…”
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DECONSTRUCTING NARRATIVE STRUCTURE: A LINGUISTIC FRAMEWORK FOR CT-BASED SHORT STORY WRITING by Fransiska Marta Sari, Mudhar, Riyati, Sri Utami

“…Computational Thinking (CT) is presented as a potential solution, to be implemented in the story outlining process by breaking down the complex story ideas into smaller parts (decomposition), identifying patterns in narratives (pattern recognition), focusing on important elements (abstraction), and designing structured writing steps (algorithm). …”
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MODELING THE BEHAVIOR OF ENTERTAINMENT CONTENT CONSUMERS TAKING INTO ACCOUNT DIGITAL TECHNOLOGIES by Olga Zyma

“…Based on recent studies from Gradus Research, the Digital Global Overview Report, and other sources, the shift in media consumption patterns among the youth audience towards entertainment and visual content is demonstrated. …”
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Analysis and Application of Grey-Markov Chain Model in Tax Forecasting by Huidi Zhang, Yimao Chen

“…Grey-Markov chain model formed by the combination of grey forecasting and Markov chain forecasting can not only reveal the general developmental trend of time series data, but also predict their state change patterns. Based on the summary and analysis of previous research works, this paper expounds the current research status and significance of tax forecasting, elaborates the development background, current status, and future challenges of the Grey-Markov chain model, introduces the basic principles of grey forecasting model and Markov chain model, constructs the Grey-Markov chain model, analyzes the model’s residual error and posteriori error tests, conducts the analysis of Grey-Markov chain model, performs grey forecasting model construction and its state division, implements the calculation of transition probability matrix and the determination of tax forecasting value, discusses the application of the Grey-Markov chain model in tax forecasting, and finally carries out a simulation experiment and its result analysis. …”
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Deciphering the complex links between inflammatory bowel diseases and NAFLD through advanced statistical and machine learning analysis by Deepak Kumar, Brijesh Bakariya, Chaman Verma, Zoltán Illés

“…There is an urgent need for non-invasive methods to diagnose various stages of liver dysfunction and uncover hidden pattern based on individual disease characteristics. …”
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The Role of Immunohistochemistry as a Surrogate Marker in Molecular Subtyping and Classification of Bladder Cancer by Tatiana Cano Barbadilla, Martina Álvarez Pérez, Juan Daniel Prieto Cuadra, Mª Teresa Dawid de Vera, Fernando Alberca-del Arco, Isabel García Muñoz, Rocío Santos-Pérez de la Blanca, Bernardo Herrera-Imbroda, Elisa Matas-Rico, Mª Isabel Hierro Martín

“…We discuss the practical advantages of IHC for subtyping, including its cost effectiveness and feasibility in standard pathology laboratories, alongside ongoing challenges such as the requirement for standardised protocols and external validation across diverse clinical settings; Conclusions: While IHC has limitations, it offers a viable alternative for laboratories lacking access to advanced molecular techniques. Further research is required to determine the optimal combination of markers, establish a consensus diagnostic algorithm, and validate IHC through large-scale trials. …”
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Marine Soundscape Monitoring Enabled by Artificial Intelligence-Aided Integrated Distributed Sensing and Communications by Juan M. Marin, Wahyu Hendra Gunawan, Alaaeddine Rjeb, Islam Ashry, Baoshi Sun, Talha Ariff, Chun Hong Kang, Tien Khee Ng, Shinkyu Park, Carlos M. Duarte, Boon S. Ooi

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Artificial Surface Water Construction Aggregated Water Loss Through Evaporation in the North China Plain by Ziang Wang, Yan Zhou, Wenge Zhang, Shimin Tian, Yaoping Cui, Haifeng Tian, Xiaoyan Liu, Bing Han

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Quantifying Spatiotemporal Changes in Supraglacial Debris Cover in Eastern Pamir from 1994 to 2024 Based on the Google Earth Engine by Hehe Liu, Zhen Zhang, Shiyin Liu, Fuming Xie, Jing Ding, Guolong Li, Haoran Su

“…To address this research gap, this study employed Landsat remote sensing images within the Google Earth Engine platform, leveraging the Random Forest algorithm to classify the supraglacial debris cover. …”
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Evaluating the effectiveness of using the intelligent adaptive training system for design modules based on printed circuit boards by K. K. Hoang, Yu. V. Donetskaya

“…Method. The parameters, algorithm and patterns of building intelligent adaptive learning systems for designing modules based on PCB of ship integrated control systems for future specialists are disclosed. …”
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Population Structure of the Invasive Asian Tiger Mosquito, Aedes albopictus, in Europe by Margaret K. Corley, Luciano Veiga Cosme, Peter A. Armbruster, Nigel Beebe, Anna Bega, Sebastien Boyer, Beniamino Caputo, Chun‐Hong Chen, Jacob E. Crawford, Alessandra dellaTorre, Roger Eritja, Michael C. Fontaine, Richard J. Gill, Trang Huynh, Perparim Kadriaj, Kevin Maringer, Ademir Jesus Martins, Andrew Maynard, Shomen Mukherjee, Leonard E. Munstermann, Verena Pichler, Maria Sharakhova, Sinnathamby Noble Surendran, Sandra Urbanelli, Enkelejda Velo, Isra Wahid, Muhammet Mustafa Akiner, Georgios Balatsos, Gilles Besnard, Maria Louise Borg, Daniel Bravo‐Barriga, Rubén Bueno Marí, Francisco Collantes, Cintia Horvath, Mihaela Kavran, Raquel Medialdea‐Carrera, Tanya Melillo, Antonios Michaelakis, Ognyan Mikov, Arianna Puggioli, Elton Rogozi, Francis Schaffner, Kayleigh Hackett, Thomas Johnson, Tina Wu, João Pinto, Vera Valadas, Adalgisa Caccone

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Exploring the Impact of Negative Words Used in Online Feedback in Hotel Industry: A Sentiment Analysis, N-gram, and Text Network Analysis Approach by DOI: 10.7172/2449-6634.jmcbem.2023.1.3 Journal of Marketing and Consumer Behaviour in Emerging Markets 1(16)2023 39 (39–50) © 2023 Authors. This is an open access journal distributed under the Creative Commons BY 4.0 license (https://creativecommons.org/licenses/by/4.0/) Exploring the Impact of Negative Words Used in Online Feedback in Hotel Industry: A Sentiment Analysis, N-gram, and Text Network Analysis Approach Daniel Dan

“…Behavioural marketing researchers might want to use these results to confirm the existence of such patterns in different datasets or situations.…”
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Validation of salivary uric acid remote self-monitoring for early prediction of hypertensive disorders of pregnancy: study protocol for a prospective, observational, multicentre co... by Isabel Reading, Amarnath Bhide, Ramesh Ganapathy, Baskaran Thilaganathan, Basia Chmielewska

“…We will validate a predictive algorithm that analyses colour data from several consecutive samples to detect patterns that predict whether HDP is likely to occur. …”
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N6-methyladenine identification using deep learning and discriminative feature integration by Salman Khan, Islam Uddin, Sumaiya Noor, Salman A. AlQahtani, Nijad Ahmad

“…A multilayer DNN serves as the classification algorithm to identify N6-methyladenine sites accurately. …”
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Convolutional neural network approach for fault detection and characterization in medium voltage distribution networks by Atefeh Pour Shafei, J.Fernando A. Silva, J. Monteiro

“…However, recent advances in artificial intelligence (AI) are enabling researchers to create alternative approaches for fault detection and location strategies. …”
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Sparse support path generation for multi-axis curved layer fused filament fabrication by Tak Yu Lau, Dong He, Yamin Li, Yihe Wang, Danjie Bi, Lulu Huang, Pengcheng Hu, Kai Tang

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Behavior Analysis With Integrated Visual-Motor Tracking for Developmental Coordination Disorder by Ruimin Li, Hong Fu, Yang Zheng, Shuiping Gou, Jane Jie Yu, Xiaowei Kong, Hongmin Wang

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Machine Learning-Enhanced Attribute-Based Authentication for Secure IoT Access Control by Jibran Saleem, Umar Raza, Mohammad Hammoudeh, William Holderbaum

“…Traditional authentication systems struggle to balance security, privacy and computational efficiency, particularly in resource-constrained environments such as Industry 4.0. This research presents the SmartIoT Hybrid Machine Learning (ML) Model, a novel integration of Attribute-Based Authentication and a lightweight machine learning algorithm designed to enhance security while minimising computational overhead. …”
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Graphlet decomposition dataset of Tallinn’s road network from January 2020 OpenStreetMap dataGithub by Mahdi Rasoulinezhad, Nasim Eslamirad, Jenni Partanen

“…The resulting dataset enables researchers to identify recurring patterns in urban street networks, study urban morphology, and compare structural similarities between different urban areas. …”
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