Analysis of Peculiarities of Epidemiological Situation on Cholera in the World and in the Russian Federation in 2024 and Forecast of its Development in 2025 by V. D. Kruglikov, N. E. Gaevskaya, E. V. Monakhova, E. A. Moskvitina, V. V. Agafonova, I. V. Savina, O. A. Podoynitsyna, N. A. Selyanskaya, A. S. Vodop’yanov, O. V. Duvanova, E. A. Men’shikova, M. I. Ezhova, E. S. Shipko, A. V. Evteev, V. S. Kaz’mina, P. V. Bodraya, E. N. Sokirkina

“…A special feature was the import of a polyantibiotic-resistant Vibrio cholerae O1 El Tor strain from Tanzania to Island Mayotte. …”
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Understanding Software Defect Prediction Through eXplainable Neural Additive Models by Ruiqi He, Yong Li, Chi Sun

“…Furthermore, feature interaction analysis is conducted to uncover nonlinear interactions between different features. …”
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An adaptive dual distillation framework for efficient remaining useful life prediction by Xiang Cheng, Jun Kit Chaw, Shafrida Sahrani, Mei Choo Ang, Saraswathy Shamini Gunasekaran, Moamin A. Mahmoud, Halimah Badioze Zaman, Yanfeng Zhao, Fuchen Ren

“…Soft-target distillation refines predictive distributions to provide robust supervision and our correlation-based feature alignment preserves inter-feature relationships and prevents information loss. …”
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A deep dive into artificial intelligence with enhanced optimization-based security breach detection in internet of health things enabled smart city environment by S Jayanthi, Sodagudi Suhasini, N. Sharmili, E. Laxmi Lydia, V. Shwetha, Bibhuti Bhusan Dash, Mrinal Bachute

“…For the selection of the feature process, the proposed SADDBN-AMOA model designs a slime mould optimization (SMO) model to select the most related features from the data. …”
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Enhanced Blade Fault Diagnosis Using Hybrid Deep Learning: A Comparative Analysis of Traditional Machine Learning and 1D Convolutional Transformer Architecture by Syed Asad Imam, Meng Hee Lim, Ahmed Mohammed Abdelrhman, Iftikhar Ahmad, Mohd Salman Leong

“…By investigating blade fault patterns and using appropriate diagnostic techniques, it becomes possible to predict potential failures and schedule maintenance proactively. This approach reduces operational failure and extends the lifespan of the equipment. …”
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Research on the Application of Deep Learning Algorithm in the Damage Detection of Steel Structures by Qingyun Ge, Caimei Li, Fulian Yang

“…The model combines three key innovations: multi-scale convolutional layers for spatial feature extraction, bidirectional LSTM units for temporal dependency modeling, and an attention mechanism for adaptive sensor data fusion. …”
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Taking into account developing character of projects in nanoindustry at the stage of their planning

“…Approach to accounting of developing character of the projects, based on allocation of zones of development is offered. Features of the project’s proactive development zone and problem of its size choice, and also the variant of the solution of this problem are described.…”
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From Lab to Life: Self‐Powered Sweat Sensors and Their Future in Personal Health Monitoring by Nan Gao, Guodong Xu, Gang Chang, Yuxiang Wu

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Real-Time Pipeline Leak Detection: A Hybrid Deep Learning Approach Using Acoustic Emission Signals by Faisal Saleem, Zahoor Ahmad, Jong-Myon Kim

“…The methodology transforms acoustic emission (AE) signals from the time domain into scalogram images using continuous wavelet transform (CWT) to enhance leak-related features. A Gaussian filter minimizes background noise and clarifies these features further. …”
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Rolling Bearing Reliability Assessment via Kernel Principal Component Analysis and Weibull Proportional Hazard Model by Fengtao Wang, Xutao Chen, Bosen Dun, Bei Wang, Dawen Yan, Hong Zhu

“…Successful reliability assessment, which is dependent on selecting features that accurately reflect performance degradation as the inputs of the assessment model, allows for the proactive maintenance of equipment. …”
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The Impact of Chatbot Response Strategies and Emojis Usage on Customers’ Purchase Intention: The Mediating Roles of Psychological Distance and Performance Expectancy by Hua Meng, Xinyuan Lu, Jiangling Xu

“…The findings suggest that proactive response strategies by chatbots are more effective in strengthening users’ purchase intention compared to reactive strategies. …”
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UAV deployment and caching scheme based on user preference prediction by Jiazhi REN, Hui TIAN, Shaoshuai FAN, Yuanzhuo LIN, Gaofeng NIE, Jilong LI

“…In order to design an efficient edge caching policy considering spatial heterogeneity and temporal fluctuations of users’ content requests,a proactive caching scheme was proposed with UAV’s deployment location design based on user preference prediction.Firstly,each user’s preference characteristics were predicted based on file similarity and user similarity,and the request time and user location were also predicted when a content request occurs.Thereafter,on the basis of the predicted geographical location,request time and user preference,each UAV’s deployment location and the corresponding content placement were determined by virtue of clustering method based on SOM and AGNES.Simulation results show that the proposed scheme outperforms other three comparison schemes in terms of hit ratio and transmission delay.Furthermore,the results also reveal that content preference is correlated with different user features by different weights.Accordingly,different impact weights should be matched with different user features.…”
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TFBlender: a hybrid time series attention model with data-driven macroeconomic perspectives for ELS Knock-In prediction by Kyungjun Lee, Juyeob Lee, Eunil Park

“…Furthermore, to refine the work on these macroeconomic signals, we introduce a Time-Feature Blender (TFBlender). Built on attention mechanisms, the TFBlender operates along two paths: time and features. …”
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Encouraging Safety 4.0 to enhance industrial culture: An extensive study of its technologies, roles, and challenges by Abid Haleem, Mohd Javaid, Ravi Pratap Singh

“…This study-based article emphasises real-time, proactive solutions and the revolutionary influence of Safety 4.0 technologies on industrial safety. …”
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Predictive Modeling of Long-Term Care Needs in Traumatic Brain Injury Patients Using Machine Learning by Tee-Tau Eric Nyam, Kuan-Chi Tu, Nai-Ching Chen, Che-Chuan Wang, Chung-Feng Liu, Ching-Lung Kuo, Jen-Chieh Liao

“…The DeLong test revealed no significant differences among the best predictive models under various feature combinations. SHAP analysis illustrated a similar distribution of feature importance for the top 11 features in XGBoost, with 27 features, and Random Forest with 11 features. …”
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Real-World Steam Powerplant Boiler Tube Leakage Detection Using Hybrid Deep Learning by Salman Khalid, Muhammad Muzammil Azad, Heung Soo Kim

“…The data of each sensor are independently processed by a dedicated CNN model, allowing for the autonomous extraction of sensor-specific features. These features are then fused to create a comprehensive feature representation of the system’s condition, which is analyzed by an SVM classifier to accurately identify leakages. …”
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Flexible monitoring of mechatronic technological machines by Andrew K. Tugengold, Roman N. Voloshin

“…The basis of such a system is considered the abandonment of the response strategy to failure in favor of a flexible proactive and predictive maintenance. A variant of the flexible system implementation based on the intelligent technologies is proposed. …”
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THE USE OF AN ADAPTIVE APPROACH TO IMPROVE THE MECHANISM OF MANAGEMENT OF THE FUNCTIONING OF ENTERPRISES OF THE CONSTRUCTION COMPLEX by Alexander S. Tarasov

“…Using this approach provides an opportunity for a more proactive and collaborative approach during changes caused by construction problems. …”
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Ada-GCNLSTM: An adaptive urban crime spatiotemporal prediction model by Miaoxuan Shan, Chunlin Ye, Peng Chen, Shufan Peng

“…Accurate crime prediction is crucial for the proactive allocation of law enforcement resources and ensuring urban safety. …”
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Radiation enteritis associated with temporal sequencing of total neoadjuvant therapy in locally advanced rectal cancer: a preliminary study by Chen-ying Ma, Yi Fu, Lou Liu, Jie Chen, Shu-yue Li, Lu Zhang, Ju-ying Zhou

“…Four delta feature strategies were defined (absolute difference, percent change, ratio, and feature fusion) by concatenating pre- and post-RT features. …”
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