Comprehensive analysis of mRNA and lncRNA expression for predicting lymph node metastasis in cervical cancer: a novel seven-gene signature approach by Jiahui Wei, Ming Wang, Yumei Wu

“…Our work bridges molecular insights with clinical practice and provides a foundation for further research into the management of CC.…”
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Graph Neural Network With Hessian-Based Locally Linear Embedding for Cancer Metastasis Analysis in Lymph Nodes Using DeepLab Segmentation by Senthil Jayapal, R. Annamalai

“…To accomplish better preservation of the geometry of high-dimensional data and more effective feature extraction, the HLLE algorithm is applied. These features are then inputted into a GNN, which utilizes the graph structure to identify and analyze metastatic patterns. …”
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Improving Fall Classification Accuracy of Multi-Input Models Using Three-Axis Accelerometer and Heart Rate Variability Data by Seunghui Kim, Jae Eun Ko, Seungbin Baek, Daechang Kim, Sungmin Kim

“…To solve this problem, a fall prevention algorithm using an acceleration sensor has been developed, and research is being conducted to enable continuous monitoring using a Holter electrocardiograph. …”
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Enhancing Fake Review Detection Using Linguistic Exaggeration, BERT Embeddings, and Fuzzy Logic by Mohammed Ennaouri, Ahmed Zellou

“…Our method first preprocesses reviews and extracts key linguistic features based on extravagant words using a fuzzy logic-based membership function that highlights extreme linguistic patterns. Simultaneously, BERT embeddings capture the deep semantic meaning of the text. …”
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PFVnet, a feature enhancement network for low recognition coal and rock images by Cai Han, Zhenwen Liu, Shenglei Zhao, Yubo Li, Yanwei Duan, Xinzhou Yang, Chuanbo Hao

“…We characterized the grayscale and texture feature patterns of coal-rock media under varying degrees of interference and established a comprehensive multi-element image training sample library. …”
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Correlation and Prediction Analysis of Cyanobacteria with Water Environment Data by Sang-Leen Yun

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PSYCHOLOGICAL ASPECTS OF INVOLVEMENT OF YOUNG PEOPLE IN EXTREMIST GROUPS IN THE INTERNET ENVIRONMENT by Olga V. Kruzhkova, Irina V. Vorobyeva, Darya M. Nikiforova

“…Consideration of the main motivational reasons, taking into account the specifics of building human interaction with the environment made it possible to identify and describe the main types of behavioural patterns exhibited by young people on the Internet. …”
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Hydroecological limitations of the use of water resources of transboundary rivers of the steppe zone (through the example of the Ural and Tobol Rivers, Russia) by Zh. T. Sivohip, V. M. Pavleichik, A. A. Chibilev, Yu. A. Padalko, M. A. Kozlova, O. B. Popova

“…To identify the main types of hydroecological restriction on the use of water resources and their spatial patterns in the Ural and Tobol river basins within the steppe zone.A comprehensive assessment of the water‐environmental situation in the regions of the studied basins studied was carried out on the basis of the calculation of water‐environmental stress – the ratio of water intake and free flow (average long‐term flow minus ecological). …”
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A Three-Dimensional Feature Space Model for Soil Salinity Inversion in Arid Oases: Polarimetric SAR and Multispectral Data Synergy by Ilyas Nurmemet, Yilizhati Aili, Yang Xiang, Aihepa Aihaiti, Yu Qin, Bilali Aizezi

“…Spatial analysis revealed distinct salinity distribution patterns: (1) Mildly salinized areas clustered in the central oasis region, and (2) severely salinized zones predominated in northern low-lying margins. …”
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INTEGRATED ASSESSMENT AND MAPPING OF ANTHROPOGENIC IMPACT ON THE NATURAL ENVIRONMENT OF RUSSIAN REGIONS by V. S. Tikunov, S. K. Belousov

“…These matrices allow not only to identify spatial patterns of distribution of the level of anthropogenic impact, but also to study the dynamics of this phenomenon in relation to the regions of Russia. …”
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Exploring Passengers’ Dependency Variety on Stations’ Functions in Urban Subway by Xia Zhao, Pengpeng Jiao, Yong Zhang, Chenjing Zhou

“…Meanwhile, passengers in the rest three groups possess a low dependency on urban subway and display extreme travel patterns in time and frequency, greatly increasing management difficulties for transit operators. …”
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Transformer attention fusion for fine grained medical image classification by Danyal Badar, Junaid Abbas, Raed Alsini, Tahir Abbas, Wang ChengLiang, Ali Daud

“…This model uses self-attention mechanics to improve spatial connections between single scales and cross-attention to automatically match feature patterns across multiple scales, thereby developing a comprehensive information structure. …”
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Two Decades of Coastal Development across the Arabian Gulf: Insights from Remote Sensing and Machine Learning by B. Dahy, R. Sousa, M. Sultan, J. A. Burt

“…These findings emphasize the complex interactions between urbanization and environmental processes, underscoring the need for sustainable planning strategies. Future research will focus on detailed analyses of vegetation, urbanization trends, and long-term inundation patterns to better support climate adaptation and regional resilience planning in the Arabian Gulf.…”
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Arrears behavior prediction of power users based on BP neural network and multi-scale feature learning: a refined risk assessment framework by Liang Yu, Yuanshen Hong, Hua Lin, Xu Jiang, Ziming Song

“…These results indicate that the proposed method offers significant improvements in capturing user behavior patterns and enhancing prediction accuracy. The study concludes that the effective fusion of multi-scale features not only enhances the model’s prediction performance but also strengthens its generalization ability. …”
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Understanding acceptance and resistance toward generative AI technologies: a multi-theoretical framework integrating functional, risk, and sociolegal factors by Priyanka Shrivastava

“…Additionally, the manuscript now highlights demographic diversity, including variations in age, gender, and academic discipline, as relevant to AI adoption patterns. Ethical concerns, including algorithmic bias, data ownership, and the labor market impact of AI, are addressed to offer a more holistic understanding of resistance behavior. …”
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An enhanced integrated fuzzy logic-based deep learning techniques (EIFL-DL) for the recommendation system on industrial applications by Yasir Rafique, Jue Wu, Abdul Wahab Muzaffar, Bilal Rafique

“…Deep learning techniques, on the other hand, excel at extracting complex patterns and features from large-scale data. By integrating fuzzy logic with deep learning, the EIFL-DL framework harnesses the strengths of both approaches to overcome the limitations of traditional RSs. …”
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Evaluation of future land use change impacts on soil erosion for holota watershed, Ethiopia by Abebe Chala Guder, Worku Firomsa Kabeta

“…In the Holota watershed of Ethiopia, rapid population growth and urbanization have accelerated unplanned land use and land cover (LULC) changes, significantly affecting soil erosion patterns. This study aims to assess the spatiotemporal changes in LULC and their impact on soil erosion from 2000 to 2050. …”
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Association of white matter hyperintensity burden and infarct volume in the anterior choroidal artery territory with early neurological progression: a dual-center retrospective stu... by Weiwei Gao, Weiwei Gao, Lixue Wang, Junyi Huang, Yitao Yu, Jingjing She, Jingjing She, Jingjing She, Mingyang Wang, Lijuan Cai, Lijuan Cai, Taishan Kang, Xingyu Chen, Xingyu Chen, Jianzhong Lin, Renjing Zhu, Renjing Zhu, Renjing Zhu

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Releasing the octoPus, an open-source digital tool to promote Integrated Pest Management by Simone Bregaglio, Eugenio Rossi, Lorenzo Ascari, Gabriele Mongiano, Eleonora Del Cavallo, Sofia Bajocco, Luisa Maria Manici, Antonio Gerardo Pepe, Chiara Bassi, Rocchina Tiso, Fabio Pietrangeli, Giovanna Cattaneo, Camilla Nigro, Marco Secondo Gerardi, Simone Bussotti, Angela Sanchioni, Danilo Tognetti, Mariangela Sandra, Irene De Lillo, Paolo Framarin, Sandra Di Ferdinando, Riccardo Bugiani

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Penerapan Feature Engineering dan Hyperparameter Tuning untuk Meningkatkan Akurasi Model Random Forest pada Klasifikasi Risiko Kredit by Nadea Putri Nur Fauzi, Siti Khomsah, Aditya Dwi Putra Wicaksono

“…This research aims to improve the accuracy of the Random Forest algorithm classification model by implementing parameter tuning and feature engineering. …”
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