Long-Term (2015–2024) Daily PM_2.5 Estimation in China by Using XGBoost Combining Empirical Orthogonal Function Decomposition by Jiacheng Jiang, Jiaxin Dong, Yu Ding, Wenjia Ni, Jie Yang, Siwei Li

“…First, we utilize the machine learning algorithm XGBoost (EXtreme Gradient Boosting) to address gaps in the daily MAIAC (Multi-Angle Implementation of Atmospheric Correction) AOD (Aerosol Optical Depth), with R²/RMSE (coefficient of determination/Root Mean Square Error) of 0.67/0.2678 compared to AERONET (Aerosol Robotic Network) AOD. …”
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Mapping the Carrier Phase of a Propagating Wave by Wireless Two-Way Interferometry Scanned by a Mobile Robot by Takaaki Nara, Yoshito Okada, Shotaro Kojima, Ranulfo Bezerra, Kazunori Ohno, Suguru Kameda, Nobuyasu Shiga, Satoshi Yasuda, Kenichi Takizawa, Satoshi Tadokoro

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Novel oxygen optode sensor with fast response time: an in-depth characterization and assessment of the HydroFlash O2, applicable for several ocean observing platforms by Tobias Hahn, Arne Körtzinger, Arne Körtzinger

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The possibility of using the DKS-AT1123 dosimeter for radiation monitoring of medical electron accelerators with the energy of more than 10 MeV by A. N. Barkovsky, S. A. Ogorodnikov

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Evaluating reservoir permeability from core data: Leveraging boosting techniques and ANN for heterogeneous reservoirs by Amad Hussen, Tanveer Alam Munshi, Minhaz Chowdhury, Labiba Nusrat Jahan, Abu Bakker Siddique, Mahamudul Hashan

“…According to the results, boosting strategies with a root mean squared error (RMSE) of less than 32.24 and a coefficient of determination (R2) of more than 0.95 are good enough and meet the study's objectives. …”
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El Nino Southern Oscillation and Indian Ocean Dipole teleconnection to the wetness and drought trend of Bhutan using time series (1983-2022) PERSIANN rainfall data by Dibyendu Dutta, Manoj Kumar Nanda, Ramprasad Kundu, Saurabh Tewari, Pragyan Jain, Bidyut Kumar Bhadra, Tanmay Khemka, Ankur Naik, Angshu Chakraverty

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Clinical Features of Juvenile Open-angle Glaucoma by A. V. Malyshev, A. S. Apostolova, A. A. Sergienko, A. F. Teshev, G. Yu. Karapetov, M. K. Ashhamahova, B. N. Hatsukova

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Phase equilibrium and kinetic studies of choline chloride-based deep eutectic solvents in water system for the inhibition of methane gas hydrate formation by Aliyu Adebayo Sulaimon, Ali Qasim, Mohamad Athif, Asiah Nusaibah Masri, Pearl Isabellah Murungi, Aneel Jordan Atthi Tasan Singh

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A hybrid slime mold enhanced convergent particle swarm optimizer for parameter estimation of proton exchange membrane fuel cell by Mohammad Aljaidi, Sunilkumar P. Agrawal, Anil Parmar, Pradeep Jangir, Arpita, Bhargavi Indrajit Trivedi, G. Gulothungan, Ali Fayez Alkoradees, Reena Jangid, Mohammad Khishe

“…In all cases, SCPSO consistently outperformed all competitors with the lowest mean sum of squared error (SSE) and minimal standard deviation (e.g., [10−16, 10−18]), thus confirming its robustness and reliability. …”
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Enhancing water balance simulations in SWAT for paddy-dominated catchments through refined soil moisture dynamics by Meng Xiang, Di Wu, Qianan Yu, Haitao Wu, Tianchi Cai, Yuanlai Cui

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Effect of Intramuscular Injection of Vitamin D on 25-Hydroxyvitamin D Levels, Glycaemic Control, and Liver Enzymes in Libyan Patients with Type 2 Diabetes Mellitus by Hafsa M. Alemam, Mouna M. ElJilani, Abdulla M. Bashein

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Dynamic Closed-Loop Validation of a Hardware-in-the-Loop Testbench for Parallel Hybrid Electric Vehicles by Marc Timur Düzgün, Christian Heusch, Sascha Krysmon, Christian Dönitz, Sung-Yong Lee, Jakob Andert, Stefan Pischinger

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Dose prediction of CyberKnife Monte Carlo plan for lung cancer patients based on deep learning: robust learning of variable beam configurations by Yuchao Miao, Jiwei Li, Ruigang Ge, Chuanbin Xie, Yaoying Liu, Gaolong Zhang, Mingchang Miao, Shouping Xu

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Process-based modeling of solar-induced chlorophyll fluorescence with VISIT-SIF version 1.0 by T. Miyauchi, T. Miyauchi, M. Saito, H. M. Noda, A. Ito, T. Kato, T. Matsunaga

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Can machine-learning algorithms improve upon classical palaeoenvironmental reconstruction models? by P. Sun, P. B. Holden, H. J. B. Birks, H. J. B. Birks

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Volunteering of students: Social meaning and basis of motivated refusal by M. V. Pevnaya, A. N. Tarasova, D. F. Telepaeva, M. Cernicova-Bucă

“…The article is based on the materials of the authors’ research projects implemented in 2017–2020 in the Sverdlovsk region. …”
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Psychometric properties of the Chinese version of scales of knowledge, attitude, and practice of self-care for patients with arteriovenous fistula: a translation and verification s... by Chuang Li, Chuang Li, Youbei Lin, Jiaxin Cheng, Danfeng Xu, Danfeng Xu, Lan Zhang

“…Confirmatory factor analysis (CFA) demonstrated good model fit, with fit indices such as the chi-square value, Comparative Fit Index (CFI), Tucker–Lewis Index (TLI), and Root Mean Square Error of Approximation (RMSEA) meeting acceptable standards. …”
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Drying kinetics and mathematical modeling of coconut meat slices: Insight into pretreatment and drying synergic effect by Daniel Kwabena Fordjour, Frederick Sarpong, James Owusu-Kwarteng, Evans Frimpong Boateng

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A hybrid approach to predicting and classifying dental impaction: integrating regularized regression and XG boost methods by Asok Mathew, Pradeep K. Yadalam, Ahmed Radeideh, Shrouk Hady, Rona Swed, Reyyan Cheema, Majd Mousa AL-Mohammad, Mohammed Alsaegh, SR Shetty

“…The study improved impaction prediction accuracy to a rate of 78%, with horizontal class predictions achieving a precision of 0.72 and an error rate of 28.1%. Additionally, the regularized logistic regression model attained 75% accuracy for classification and prediction.ConclusionThe study aims to improve dental research by predicting the eruption behavior of lower molars, enabling dental practitioners to make more concise treatment plans. …”
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Raman evaluation of graphene oxide dispersed in naphthenic oil by ALAN PASSERO, TAYNARA A. DE CARVALHO, NATALIA B. SANCHES, LIDIA M.S. MURAKAMI, JORGE CARLOS N. DUTRA, RITA DE CÁSSIA L. DUTRA

“…The results contribute to the state of the art of researching industrial aerospace solutions for polymeric systems containing graphene oxide.…”
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