Evaluation of the performance of ERA5, ERA5-Land and MERRA-2 reanalysis to estimate snow depth over a mountainous semi-arid region in Iran by Faezehsadat Majidi, Samaneh Sabetghadam, Maryam Gharaylou, Reza Rezaian

“…Additionally, the study highlights the challenges MERRA-2 faces in capturing snow depth in mountainous regions. Future research could benefit from integrating additional datasets and employing machine learning algorithms to improve snow depth assessments, as these approaches may reduce estimation uncertainties and enhance the understanding of snow dynamics across various regions, ultimately contributing to more reliable hydrological assessments.…”
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Economic approach for optimal allocation of irrigation water in water-scarce region by Xueliang Zhang, Li Ren, Jianshi Zhao

“…Optimizing irrigation water allocation is critical for maximizing grain yields in water-scarce regions. Traditional algorithms face challenges such as lack of interpretable criteria, the curse of dimensionality, and instability. …”
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Dual-hybrid intrusion detection system to detect False Data Injection in smart grids. by Saad Hammood Mohammed, Mandeep S Jit Singh, Abdulmajeed Al-Jumaily, Mohammad Tariqul Islam, Md Shabiul Islam, Abdulmajeed M Alenezi, Mohamed S Soliman

“…This study presents a practical dual-hybrid IDS framework for detecting FDIAs in smart grids, addressing the limitations of existing IDS techniques. Future research should focus on integrating real-world smart grid data for validation, developing adaptive learning mechanisms, exploring other bio-inspired optimization algorithms, and addressing real-time processing and scalability challenges in large-scale deployments.…”
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Improved YOLOv8 Model for Phenotype Detection of Horticultural Seedling Growth Based on Digital Cousin by Yuhao Song, Lin Yang, Shuo Li, Xin Yang, Chi Ma, Yuan Huang, Aamir Hussain

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Model Development for Estimating Sub-Daily Urban Air Temperature Patterns in China Using Land Surface Temperature and Auxiliary Data from 2013 to 2023 by Yuchen Guo, János Unger, Tamás Gál

“…., maximum and minimum Tair), with few focusing on sub-daily urban Tair at high spatial resolution. In this study, we integrated MODIS-based land surface temperature (LST) data with 18 auxiliary data from 2013 to 2023 to develop a Tair estimation model for major Chinese cities, using random forest algorithms across four diurnal and seasonal conditions: warm daytime, warm nighttime, cold daytime, and cold nighttime. …”
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Evaluating the performances of SVR and XGBoost for short-range forecasting of heatwaves across different temperature zones of India by Srikanth Bhoopathi, Nitish Kumar, Somesh, Manali Pal

“…This research aims to forecast maximum temperatures and the frequency of heatwave days across four different temperature zones (Zone 1, 2, 3 and 4) in India. …”
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Efficient Identification and Classification of Pear Varieties Based on Leaf Appearance with YOLOv10 Model by Niman Li, Yongqing Wu, Zhengyu Jiang, Yulu Mou, Xiaohao Ji, Hongliang Huo, Xingguang Dong

“…To address the issue of low recognition precision in Yuluxiang, the Spatial and Channel reconstruction Convolution (SCConv) module is introduced on the basis of YOLOv10 to improve the model. …”
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Urban Heat Island Effect: Remote Sensing Monitoring and Assessment—Methods, Applications, and Future Directions by Lili Zhao, Xuncheng Fan, Tao Hong

“…At the methodological level, the study systematically evaluates core algorithms for land surface temperature extraction and heat island intensity calculation, compares innovative developments in multi-source remote sensing data integration and fusion techniques, and establishes a framework for accuracy assessment and validation. …”
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Impact of Subjective and Objective Green Space Characteristics on Mental Health Benefits: An Explainable Machine Learning Approach by Ke LI, Yipei MAO, Yongjun LI

“…By combining field measurements, questionnaire surveys, and advanced machine learning algorithms, the research explores the impact of green space characteristics on emotional restoration, cognitive enhancement, and stress relief. …”
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A rapid-application emissions-to-impacts tool for scenario assessment: Probabilistic Regional Impacts from Model patterns and Emissions (PRIME) by C. Mathison, C. Mathison, E. J. Burke, G. Munday, C. D. Jones, C. D. Jones, C. J. Smith, C. J. Smith, C. J. Smith, C. J. Smith, N. J. Steinert, N. J. Steinert, A. J. Wiltshire, A. J. Wiltshire, C. Huntingford, E. Kovacs, L. K. Gohar, R. M. Varney, D. McNeall, D. McNeall

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Data fusion-based improvements in empirical regression and machine learning for global daily ∼ 8 km resolution sea surface nitrate estimation and interpretation by Aifen Zhong, Difeng Wang, Fang Gong, Jingjing Huang, Zhuoqi Zheng, Xianqiang He, Qing Zhang, Qiankun Zhu

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VGGBM-Net: A Novel Pixel-Based Transfer Features Engineering for Automated Coffee Bean Diseases Classification by Muhammad Shadab Alam Hashmi, Azam Mehmood Qadri, Ali Raza, Saleem Ullah, Aseel Smerat, Changgyun Kim, Muhammad Syafrudin, Norma Latif Fitriyani

“…These enhanced features are then used as inputs for advanced machine-learning algorithms. Unlike traditional models, this feature extraction enhances classification accuracy and robustness. …”
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GPS-based street-view greenspace exposure and wearable assessed physical activity in a prospective cohort of US women by Li Yi, Jaime E. Hart, Grete Wilt, Cindy R. Hu, Marcia Pescador Jimenez, Pi-I Debby Lin, Esra Suel, Perry Hystad, Steve Hankey, Wenwen Zhang, Jorge E. Chavarro, Francine Laden, Peter James

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Predicting the passive control of fluid forces over circular cylinder in a time dependent flow using neuro-computing by Atif Asghar, Rashid Mahmood, Afraz Hussain Majeed, Hammad Alotaibi, Ahmed Refaie Ali

“…The objective of this research is to combine Artificial Neural Networks (ANNs) and Computational Fluid Dynamics (CFD) approaches to leverage the advantages of both methods. …”
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Co-benefits for cropland yield, nitrogen emissions, and climate impact through multi-objective optimization agricultural manure solutions by Yinghua Yin, Shufang Guo, Qiyu Xu, Jian Liu, Hongyuan Wang, Yanhua Zhuang, Zhen Wang, Lingling Hua, Hongbin Liu, Limei Zhai

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Architecture and Field Operation of a Portable Digital Holographic Microscope for In Situ Measurements of Bacterial Motility by J. Kent Wallace, Manuel Bedrossian, Stephanie Rider, Dylan McKeithen, Felipe Fregoso, Frank Loya, Scott M. Perl

“…Future developments of this platform will focus on refining data reduction algorithms and operational methodologies for Earth-based and space-based applications.…”
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An optimized approach for predicting water quality features and a performance evaluation for mapping surface water potential zones based on Discriminant Analysis (DA), Geographical... by Abhijeet Das

“…To achieve this goal, this investigation relies on Drinking (Dr)-Water Quality Index (WQI) and multivariate statistical techniques including discriminant analysis (DA), to assess the variations of surface water quality in the selected region. Again, this research used a strong methodology by incorporating Machine learning (ML) algorithms, such as: Artificial Neural Network (ANN), Gaussian Process Regression (GPR), Support Vector Machine (SVM), and Linear Regression Model (LRM), were applied to forecast and confirm the quality of the water. …”
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Development of a circadian-related prognostic signature highlights RBM17 as a stemness regulator in liver cancer by Jingsong Yan, Xiao Yang, Jiabin Lu, Shasha Wu, Yanchen Wang, Yuyang Du, Jingyi Zheng, Fenfen Wang, Han Gao, Hui Yang, Shaoyan Xi, Yan Li

“…Employing machine learning algorithms, we pinpointed four pivotal dysregulated LCGs. …”
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Improving Distribution Prediction by Integrating Expert Range Maps and Opportunistic Occurrences: Evidence From Japanese Sea Cucumber by Bingqing Xiao, Songxi Yuan, Ákos Bede‐Fazekas, Jinxin Zhou, Xingyu Song, Qiang Lin, Lei Cui, Zhixin Zhang

“…To overcome this limitation, researchers have proposed improving predictions of SDMs by integrating different types of distribution data, but this idea has rarely been explored in the marine realm. …”
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Developing a semi-automated technique of surface water quality analysis using GEE and machine learning: A case study for Sundarbans by Sheikh Fahim Faysal Sowrav, Sujit Kumar Debsarma, Mohan Kumar Das, Khan Mohammad Ibtehal, Mahfujur Rahman, Noshin Tabassum Hridita, Atika Afia Broty, Muhammad Sajid Anam Hoque

“…Comparative analyses showed that ML-based models effectively captured spatial and temporal variations, aligning closely with field measurements. …”
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