Analysis of Vulnerability of the Population of the Sary-Dzhas Natural Plague Focus in Kyrgyzstan by G. E. Sarieva, R. Kh. Yusupov, G. Dzh. Bazarkanova, R. K. Maimulov, N. K. Moldakunova, N. N. Bekbolotova

“…The aim of the work was to assess the forecast of epidemiological vulnerability of the population of the Sary-Dzhas natural plague focus based on the current data on the population size, pasture area and development of tourism. …”
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High-speed threat detection in 5G SDN with particle swarm optimizer integrated GRU-driven generative adversarial network by R. Shameli, Sujatha Rajkumar

“…Moreover, the performance of this model is evaluated using the InSDN dataset and compared with existing DL model-based intrusion detection approaches and the results demonstrate a significantly higher accuracy rate of 98.4%, precision rate of 98%, recall rate of 98.5%, less detection time of 2.464 s, lesser Log loss rate of 1.0 and more metrics instilling confidence in the effectiveness of the proposed method.…”
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Diagnostic value of a novel automated simultaneous amplification and testing method in pulmonary tuberculosis and extrapulmonary tuberculosis by Xichao Ou, Peilei Hu, Xundi Bao, Zhou Liu, Chong Teng, Jingwei Guo, Dongfang Xu, Yue Li, Bing Zhao, Ruida Xing, Hui Xia, Ling Ma, Yang Zhou, Yang Zheng, Yuanyuan Song, Shengfen Wang, Yanlin Zhao, Yunhong Tan, Huiwen Zheng

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Exploring Machine Learning Methods for Aflatoxin M1 Prediction in Jordanian Breast Milk Samples by Abdullah Aref, Eman Omar, Eman Alseidi, Nour Elhuda A. Alqudah, Sharaf Omar

“…The presence of aflatoxin M1 in breast milk poses a serious risk to the health of infants because of its potential to cause cancer and have negative effects on development. Detecting AFM1 in milk samples using conventional methods is often time-consuming and may not provide real-time monitoring capabilities. …”
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Detecting sub-instability before three Mw > 6.0 earthquakes on Chinese mainland in 2020–2022 with load/unload response ratio by Huaizhong Yu, Donghui Jia, Chieh-Hung Chen, Yue Liu, Haitao Wang, Jie Liu, Rui Yan, Binbin Zhao, Jianming Liu, Yuchuan Ma, Guihong Han, Wen Yang, Zhengyi Yuan, Zeping Li

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Exploring Different Dynamics of Recurrent Neural Network Methods for Stock Market Prediction - A Comparative Study by Ajit Mohan Pattanayak, Aleena Swetapadma, Biswajit Sahoo

“…The intricate and unpredictable nature of stock markets underscores the importance of precise forecasting for timely detection of downturns and subsequent rebounds. …”
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The VMD-Informer-BiLSTM-EAA Hybrid Model for Predicting Zenith Tropospheric Delay by Zhengdao Yuan, Xu Lin, Yashi Xu, Ruiting Dai, Cong Yang, Lunwei Zhao, Yakun Han

“…Furthermore, our model reduces the training time by 8.2% compared to the Transformer model, demonstrating superior prediction performance and robustness in long-term ZTD forecasting. This study introduces a novel approach for high-accuracy ZTD modeling, which is significantly beneficial for precise GNSS positioning and the detection of water vapor content.…”
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Methodology for Estimating the Cost of Construction Equipment Based on the Analysis of Important Characteristics Using Machine Learning Methods by Nataliya Boyko, Oleksii Lukash

“…The study pays additional attention to the specific characteristics of heavy machinery by the sector of the economy. The existing methods and tools for price forecasting, depending on the specific characteristics of the equipment, were analyzed. …”
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One-pot, uracil-DNA-glycosylase-aided, and multi-indicator nanobiosensor detection platform for identifying Brucella melitensis from the Brucella spp by Xinggui Yang, Yue Wang, Sha Mao, Ying Liu, Fengming Chen, Junfei Huang, Xiaoyan Zeng, Hai Jiang, Shijun Li

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Lightning Prediction in the Tehran Region Using the WRF Model With Multiple Physical Parameterizations and an Ensemble Approach by Sakineh Khansalari, Maryam Gharaylou

“…Based on these findings, we recommend the ensemble method as the most reliable approach for more accurate lightning simulations in future studies.…”
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Anthropogenic influence has intensified the severity of summer compound hot and drought events over xinjiang, China by Xiaolu Zhang, Botao Zhou, Xiaoxin Wang, Wenxin Xie, Huixin Li

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A Deep Learning-Based Echo Extrapolation Method by Fusing Radar Mosaic and RMAPS-NOW Data by Shanhao Wang, Zhiqun Hu, Fuzeng Wang, Ruiting Liu, Lirong Wang, Jiexin Chen

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Effect of senile asthenia syndrome on cardiovascular mortality within 12 months in patients over 70 years of age with myocardial infarction by O. Yu. Aydumova, Yu. V. Shchukin, M. V. Piskunov

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Dynamical systems theory approach in oceanography: a review on achievements, limitations, verification and validation of Lagrangian methods by S. V. Prants

“…The modern LA explores dynamical systems theory (DST) methods to detect locations of geometric structures hidden in chaotic fluid flows and organizing transport, stirring and mixing in the ocean. …”
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Development and Future Perspectives of Air Pollution Research Using Artificial Intelligence-Based Methods: A Bibliometric Review by Olgu Aydın, Hatice Kılar

“…The findings indicate that after 2014, AI-based methods have led to a paradigm shift, playing a critical role in air pollution forecasting and modeling. …”
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Modification of IPI Method for Extraction of Short-Term and Imminent OLR Anomalies and Case Study of Two Large Earthquakes by Maoning Feng, Pan Xiong, Weixi Tian, Yue Liu, Changhui Ju, Cheng Song, Yongxian Zhang

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Does syndromic surveillance assist public health practice in early detecting respiratory epidemics? Evidence from a wide Italian retrospective experience by Giovanni Corrao, Andrea Stella Bonaugurio, Giorgio Bagarella, Mauro Maistrello, Olivia Leoni, Danilo Cereda, Andrea Gori

“…Electronic resources may facilitate enhanced early detection of epidemics. Here, we aimed to retrospectively explore whether examining trends in the use of emergency and healthcare services and the Google search engine is useful in detecting Severe Acute Respiratory Syndrome Coronavirus outbreaks early compared with the currently used swab-based surveillance system. …”
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An Improved Pattern Informatics Method for Extracting Ionospheric Disturbances Related to Seismicity Based on CSES Data: A Case Study of the Mw7.3 Maduo Earthquake by Weixi Tian, Yongxian Zhang, Changhui Ju, Shengfeng Zhang, Maoning Feng, Fengli Liu

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Genomics vs. AI-enhanced electrocardiogram: predicting atrial fibrillation in the era of precision medicine by Jean-Marie Grégoire, Cédric Gilon, François Marelli, Hugues Bersini, Stéphane Carlier

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Adaptive Early Wildfire Monitoring Based on Spatiotemporal Prediction and Himawari 8/9 by Zekun Xu, Zhaoming Zhang, Guojin He, Shuaizhang Zhang, Tengfei Long, Guizhou Wang

“…This model integrates Stacking ConvLSTM to forecast mid-infrared brightness temperatures and employs a nonparametric dynamic thresholding method based on Otsu's algorithm for spatiotemporal anomaly detection, facilitating the identification of potential hotspots. …”
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