Predicting Landslide Deposit Zones: Insights from Advanced Sampling Strategies in the Ilopango Caldera, El Salvador by Laura Paola Calderon-Cucunuba, Abel Alexei Argueta-Platero, Tomás Fernández, Claudio Mercurio, Chiara Martinello, Edoardo Rotigliano, Christian Conoscenti

“…Additionally, the Multivariate Adaptive Regression Splines (MARS) algorithm was used for modeling. Our findings revealed that models developed using the deposition area dataset were more effective compared with those based on the source area dataset. …”
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Alternative method for determining API degrees of petroleum in contaminated soil by FTIR by F.J. Guzmán-Osorio, R.H. Adams, V.I. Domínguez-Rodríguez, C.E. Lobato-García, A. Guerrero-Peña, J.R. Barajas-Hernández, E. Baltierra-Trejo

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Single-Frame Infrared Target Detection Based on Fast Content-Related Modeling by Zipeng Zhang, Xidong Zhao, Wenzheng Wang, Yuqi Han, Chenwei Deng, Zhuokai Li, Linbo Tang

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Standards of specialized diabetes care. Edited by Dedov I.I., Shestakova M.V., Mayorov A.Yu. 10th edition by Ivan I. Dedov, Marina V. Shestakova, Alexander Yu. Mayorov, Natalya G. Mokrysheva, Olga K. Vikulova, Gagik R. Galstyan, Tamara L. Kuraeva, Valentina A. Peterkova, Olga M. Smirnova, Elena G. Starostina, Elena V. Surkova, Olga Y. Sukhareva, Alla Y. Tokmakova, Minara S. Shamkhalova, Ivona Renata Jarek-Martynova, Ekaterina V. Artemova, Diana D. Beshlieva, Olga N. Bondarenko, Natalya N. Volevodz, Irina S. Gomova, Olga R. Grigoryan, Zera N. Dzhemilova, Roza M. Esayan, Liudmila I. Ibragimova, Viktor Y. Kalashnikov, Irina V. Kononenko, Dmitry N. Laptev, Dmitry V. Lipatov, Olga G. Melnikova, Margarina S. Mikhina, Marina S. Michurova, Oleg G. Motovilin, Tatiana V. Nikonova, Roman V. Rozhivanov, Igor A. Sklyanik, Ekaterina A. Shestakova

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The Intracluster Light Analysis of the Most Evolved Systems of Galaxies: Fossil Groups by Nícolas O. L. de Oliveira, Yolanda Jiménez-Teja, Renato A. Dupke, Eleazar R. Carrasco, Anton M. Koekemoer, Yuanyuan Su, Jose Manuel Vilchez, Jimmy A. Irwin, Eric D. Miller, Lucas E. Johnson

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YOLOv8n-WSE-Pest: A Lightweight Deep Learning Model Based on YOLOv8n for Pest Identification in Tea Gardens by Hongxu Li, Wenxia Yuan, Yuxin Xia, Zejun Wang, Junjie He, Qiaomei Wang, Shihao Zhang, Limei Li, Fang Yang, Baijuan Wang

“…The integration of the Efficient Multi-Scale Attention Module with Cross-Spatial Learning enables the model to have more flexible global attention. The research results demonstrate that compared to the original YOLOv8n model, the improved YOLOv8n-WSE-pest model shows increases in the precision, recall, mAP50, and F1 score by 3.12%, 5.65%, 2.18%, and 4.43%, respectively. …”
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Joint Optical Performance Monitoring and Modulation Format/Bit-Rate Identification by CNN-Based Multi-Task Learning by Xiaojie Fan, Yulai Xie, Fang Ren, Yiying Zhang, Xiaoshan Huang, Wei Chen, Tianwen Zhangsun, Jianping Wang

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Resource allocation for coexistence of eMBB and bursty URLLC based on queueing with preemption by Wei Guo, Kai Liang, Yuewen Song, Xiaoli Chu, Gan Zheng, Kai-Kit Wong

“…We decompose this problem into three sub-problems and solve them alternately using a block coordinate descent algorithm. Numerical results show that our proposed method reduces the outage probability and average delay of URLLC compared to the existing works.…”
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Use of Data Mining for Intelligent Evaluation of Imputation Methods by David Red, Carlos R. Primorac

“…In real-world situations, researchers frequently face the difficulty of missing values (MV), i.e., values not observed in a data set. …”
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Advantages and potentials of SuperDove imagery for fine monitoring of suspended particulate matter in estuaries and tidal channels by Peng Li, Shenliang Chen, Congliang Xu, Wenjuan Wu, Jiarui Qi, Yinghai Ke, Hongyu Ji, Shihua Li, Xiaojing Zhong

“…Suspended particulate matter (SPM) concentration is an essential biogeochemical parameter for water quality evaluation and morphodynamic researches. As the newest satellite in Planet family, SuperDove (SD) with eight spectral bands achieves observation to Earth with unprecedented temporal and spatial resolution. …”
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An Approach to Predicting Urban Carbon Stock Using a Self-Attention Convolutional Long Short-Term Memory Network Model: A Case Study in Wuhan Urban Circle by Zhi Zhou, Xueling Wu, Bo Peng

“…This paper introduces a long- and short-term memory network algorithm called the Self-Attention Convolutional Long and Short-Term Memory Network (SA-ConvLSTM). …”
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Towards Secure IoT Authentication System Based on Fog Computing and Blockchain Technologies to Resist 51% and Hijacking Cyber-Attacks by Muwafaq Jawad, Ali A. Yassin, Hamid Ali Abed Al-asadi, Zaid Ameen Abduljabbar, Vincent Omollo Nyangares, Zaid Alaa Hussien, Husam A. Neamah

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Analysis of the Strength Development, CO₂ Emissions, and Optimized Low-Carbon Design of Fly-Ash-Enhanced Composite Concrete by Bo Yang, Yu Dong, Xiao-Yong Wang

“…Fly ash is commonly used as a partial replacement for cement. Although extensive research has been conducted on mixed design schemes for fly ash concrete, these studies commonly overlook carbonation durability, which may lead to an insufficient service life. …”
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Explainable machine learning model for predicting furosemide responsiveness in patients with oliguric acute kidney injury by Meng Jiang, Chun-qiu Pan, Jian Li, Li-gang Xu, Chang-li Li

“…It outperformed the logistic regression and other ML models in correctly predicting furosemide diuretic response, achieved 92.43% sensitivity (95% CI: 90.88–93.73%) and 95.12% specificity (95% CI: 93.51–96.3%).Conclusion A boosted ensemble algorithm can be used to accurately differentiate between patients who would and would not respond to furosemide in oliguric AKI. …”
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Can the adherence to quality of care indicators for early rheumatoid arthritis in clinical practice reduce risk of hospitalisation? Retrospective cohort study based on the Record L... by Carlo Alberto Scirè, Antonella Zambon, Greta Carrara, Anna Zanetti, Lisa Argnani

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Prospects of application of artificial neural networks for forecasting of cargo transportation volume in transport systems by D. T. Yakupov, O. N. Rozhko

“…The purpose of research – to identify the prospects for the use of neural network approach in relation to the tasks of economic forecasting of logistics performance, in particular of volume freight traffic in the transport system promiscuous regional freight traffic, as well as to substantiate the effectiveness of the use of artificial neural networks (ANN), as compared with the efficiency of traditional extrapolative methods of forecasting. …”
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A new method for determining factors Influencing productivity of deep coalbed methane vertical cluster wells by HUANG Li, XIONG Xianyue, WANG Feng, SUN Xiongwei, ZHANG Yixin, ZHAO Longmei, SHI Shi, ZHANG Wen, ZHAO Haoyang, JI Liang, DENG Lin

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Clustering Credit Card Holder Berdasarkan Pembayaran Tagihan Menggunakan Improved K-Means dengan Particle Swarm Optimization by Farhanna Mar'i, Ahmad Afif Supianto

“…However, the K-Means method can not provide the optimum solution because of its limitation in determining the optimal centroid point, so to improve the K-Means method in this research is used one of the evolution algorithm namely Particle Swarm Optimization (PSO) to generate optimum centroid point used in k-means calculation process. …”
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Estimation of the Potential Benefits of Meningococcal Vaccination in Children at 9 and 12 Months of Age Using a Predictive Mathematical Model by N. I. Briko, O. I. Volkova, I. S. Korolyova, E. O. Kurilovich, L. D. Popovich, I. V. Feldblum

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Towards an automated protocol for wildlife density estimation using camera‐traps by Andrea Zampetti, Davide Mirante, Pablo Palencia, Luca Santini

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