Opportunities and challenges of quantum computing for climate modeling by Mierk Schwabe, Lorenzo Pastori, Inés de Vega, Pierre Gentine, Luigi Iapichino, Valtteri Lahtinen, Martin Leib, Jeanette Miriam Lorenz, Veronika Eyring

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Groundwater estimation and determination of its probable recharge source in the Lower Swat District, Khyber Pakhtunkhwa, Pakistan, using analytical data and multiple machine learni... by Imran Ahmad, Ibrar Ul Haq, Mansoor Ahmad, Iram Gul, Mursaleen Khan, Khushnuma Khushnuma, Ubaid Ullah, Maqsood Ur Rehman, Mohamed Metwaly

“…It aims to identify recharge sources using a combination of analytical data and advanced machine learning (ML) algorithms. …”
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Methods and reliability study of moral education assessment in universities: A machine learning-based approach by Ting Jin

“…The objective is to employ data-driven methodologies to enhance ethical assessment frameworks through improved objectivity, scalability, and consistency. …”
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Applicability Evaluation of Provincial Precipitation Real-time Analysis Product in Beijing by Zhao Wenfang, Wang Huiying, Meng Huifang, Miao Yupeng, Huang Mingming, Fan Min, Tang Wei

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Spatial Gap-Filling of Himawari-8 Hourly AOD Products Using Machine Learning with Model-Based AOD and Meteorological Data: A Focus on the Korean Peninsula by Youjeong Youn, Seoyeon Kim, Seung Hee Kim, Yangwon Lee

“…However, optical remote sensing encounters difficulties in detecting Aerosol Optical Depth (AOD) over cloud-covered regions, creating data gaps that limit comprehensive environmental analysis. …”
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Dynamic Workload Management System in the Public Sector: A Comparative Analysis by Konstantinos C. Giotopoulos, Dimitrios Michalopoulos, Gerasimos Vonitsanos, Dimitris Papadopoulos, Ioanna Giannoukou, Spyros Sioutas

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Quantitative Estimation of Net Primary Productivity by an Improved tCASA Model Using Landsat Time Series Data: A Case Study of Central Plains, China by Lida Xu, Zongze Zhao, Cheng Wang, Hongtao Wang, Chao Ma

“…To address this issue, an adaptive temperature stress coefficient for the CASA model (tCASA) is proposed to estimate the NPP of the Central Plains Urban Agglomeration (CPUA) using Landsat time-series data spanning from 2002 to 2022. Based on the Theil-Sen Median Estimators, the Mann–Kendall test, and partial correlation analysis, this article delves into the impact of climate and human activities on NPP. …”
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Assessment of Racial Misclassification Among American Indian and Alaska Native Identity in Cancer Surveillance Data in the United States and Considerations for Oral Health: A Syste... by Amanda J. Llaneza, Alex Holt, Julie Seward, Jamie Piatt, Janis E. Campbell

“…Studies involving the racial misclassification of AI/AN identity among cancer surveillance data were screened for eligibility. Data were analyzed in terms of the discussion of racial misclassification, methods to reduce this error, and the reporting of research involving Indigenous peoples. …”
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A patient-centric benefit-risk assessment of daridorexant for the treatment of insomnia disorder using patient preference data collected in two phase 3 clinical trials by Sebastian Heidenreich, Melissa Ross, Bruno Flamion, Andrea Phillips-Beyer

“…Sensitivity analyses accounted for uncertainty in both clinical trial and patient preference data. Results: Preferences of 602 trial participants (68.1 % female, mean age 58.6 years) were used in the qBRA analysis. …”
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Comparison of Neural Network, Ordinary Kriging, and Inverse Distance Weighting Algorithms for Seismic and Well-Derived Depth Data: A Case Study in the Bjelovar Subdepression, Croat... by Ana Brcković, Tomislav Malvić, Jasna Orešković, Josipa Kapuralić

“…OK is the relative winner, showing the flexibility of variogram analysis regarding the number of data points and possible clustering. …”
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The Development of Digital Twin Baby Incubators for Fault Detection and Performance Analysis by Hatice Kabaoğlu, Emine Uçar, Fecir Duran

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Comparative Analysis of LSTM and GRU Models for Ethereum (ETH) Price Prediction by Moch Panji Agung Saputra, Riza Andrian Ibrahim, Renda Sandi Saputra

“…Therefore, this study aims to compare the performance of LSTM and GRU in predicting Ethereum prices using a hyperparameter tuning approach. The data used is historical data of Ethereum (ETH) shares from 2020 to 2025. …”
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Garbage prediction using regression analysis for municipal corporations of Indian cities by Raj Kumar Sharma, Manisha Jailia

“…The mean square error and the mean absolute error in the analysis and the Taylor plot show that the RFR model is best suited for predicting daily garbage production in a city. …”
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Meta-analysis of Genetic Parameters for Productive and Reproductive Traits in Laying Hens by Maryam Sokhan, Sheida Varkoohi, Ali Hossein Piray

“…The I2 index showed that the heterogeneity in all investigated traits for heritability and genetic and phenotypic correlations was more than 70%, so random effects model was used for data analysis. The software package Comprehensive Meta-Analysis (version 2) was used to perform statistical analysis and estimation of weighted means of heritability and genetic and phenotypic correlations for sexual maturity age, sexual maturity weight, egg number and egg weight, standard error and 95% confidence interval. …”
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Enhancing Large-Area DEM modeling of GF-7 stereo imagery: Integrating ICESat-2 data with Multi-characteristic constraint filtering and terrain matching correction by Kai Chen, Wen Dai, Fayuan Li, Sijin Li, Chun Wang

“…However, owing to the discrepancies between these two data platforms and the systematic errors of their sensors, errors arise in the BA fusion outcomes during the matching process of the two datasets. …”
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Analysis and research on the impact of medium voltage power line carrier communication by ZHAO Tonghan, SU Yuzhong

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DETERMINING KEY DETERMINANTS OF DEMAND FOR INTERNATIONAL RESERVES IN UKRAINE: COINTEGRATION ANALYSIS by M. I. Makarenko, D. V. Gordieieva

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Assessing and adjusting for bias in ecological analysis using multiple sample datasets by Qingfeng Li

“…The effectiveness of these adjustments is evaluated through formal mathematical derivations, simulations, and empirical analysis using data from the 2014 Kenya Demographic and Health Survey. …”
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Analysis of corn price forecast in China based on Lasso-XGBoost-SHAP by Wenming Cheng, Fangyuan Li

“…Results demonstrate that the Lasso-XGBoost model outperforms traditional linear models (LM) and other algorithms, including SVM (Support Vector Machine) and MLP (Multilayer Perceptron), with root mean squared error (RMSE) of 0.094, coefficient of determination (R2) of 0.973, mean absolute error (MAE) of 0.072, representing a 7.84% reduction in RMSE compared to standalone XGBoost. …”
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Artificial Neural Network Analysis for Cost Estimation of Building Projects in India by Ankita Gupta, Piyali Debnath

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