From emissions to emotions: Exploring the impact of climate change on happiness across 140 countries by Jeremy Ko, Chun Kai Leung, Xiaoxian Chen, David A. Palmer

“…Robustness checks, including two-stage least squares (2SLS) regression and panel-corrected standard errors (PCSE), confirm the stability of the findings. …”
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A Sparse Representation-Based Reconstruction Method of Electrical Impedance Imaging for Grounding Grid by Ke Zhu, Donghui Luo, Zhengzheng Fu, Zhihang Xue, Xianghang Bu

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A Hybrid Vector Autoregressive Model for Accurate Macroeconomic Forecasting: An Application to the U.S. Economy by Faridoon Khan, Hasnain Iftikhar, Imran Khan, Paulo Canas Rodrigues, Abdulmajeed Atiah Alharbi, Jeza Allohibi

“…The multi-step-ahead out-of-sample forecast results (root mean square error and mean absolute error) for the considered data suggest that the proposed hybrid model yields a highly accurate and efficient gain. …”
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A robust quantification of H2O in silicate glasses through micro-Raman spectroscopy: insights on the compositional effect by Filippo Ridolfi, Diego González-García

“…A robust and reproducible method for baseline subtraction and measurement of the water and silicate areas and their ratio (Rw/s) is proposed. Rw/s data show an average error of ±0.07 confirming the high potential of Raman spectroscopy of accurately determining the water content. …”
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Simulation and Experimental Study on the Shrub-Cutting Performance of Quasi-Planetary Cutter by Zikai Song, Xibin Dong, Chi Teng, Ben Guo, Jiawang Zhang, Yuchen Zhang

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Deep learning to promote health through sports and physical training by Xinyue Li

“…It achieves 22.8% lower Mean Absolute Error (MAE), 19.3% lower Root Mean Squared Error (RMSE), 6.5% higher R2, and 7.9% higher Explained Variance Score (EVS) compared to competitive models.ConclusionThe proposed HIS prediction model effectively captures complex temporal dependencies and improves the accuracy of health improvement predictions.…”
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Artificial Intelligence-Based Techniques for Fouling Resistance Estimation of Shell and Tube Heat Exchanger: Cascaded Forward and Recurrent Models by Ikram Kouidri, Abdennasser Dahmani, Furizal Furizal, Alfian Ma’arif, Ahmed A. Mostfa, Abdeltif Amrane, Lotfi Mouni, Abdel-Nasser Sharkawy

“…Model performance is assessed based on mean squared error (MSE), regression values (R), and statistical error analysis. …”
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Comparative Numerical Solution of Fractional Spline with Continuity Equations by Faraidun K. Hamasalh, Seaman S. Hamasalh

“…For the provided spline function, error bounds were studied and a stability analysis was completed. …”
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CONSTRUCTION AND RESEARCH OF RADIAL CONTACT PRESSURE DISTRIBUTION MODEL FOR HEAVY-DUTY ENGINEERING WHEELS by YE Haozhe, WU Chaohua, QUAN Yongzhi, SHI Xiaoliang, LUO Wei

“…The outcomes demonstrate the calculation error of mere-approximately 1.943% in relation to the measured data for the key calibration points. …”
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Linear Average Yield Criterion and Its Application in Failure Pressure Evaluation of Defect-Free Pipelines by Jian-Hong Ji, Ming-Ming Sun, Jie Zhang

“…Analysis of internal pressure failure is a crucial aspect of assessing pipeline integrity. …”
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Adaptive Symmetry Self-Matching for 3D Point Cloud Completion of Occluded Tomato Fruits in Complex Canopy Environments by Wenqin Wang, Chengda Lin, Haiyu Shui, Ke Zhang, Ruifang Zhai

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Statistical Modeling to Improve Time Series Forecasting Using Machine Learning, Time Series, and Hybrid Models: A Case Study of Bitcoin Price Forecasting by Moiz Qureshi, Hasnain Iftikhar, Paulo Canas Rodrigues, Mohd Ziaur Rehman, S. A. Atif Salar

“…Various hybrid models are then proposed utilizing these models, which are based on simple averaging of these models. The data-splitting technique, commonly used in comparative analysis, splits the data into training and testing data sets. …”
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A framework for upscaling aboveground biomass from an individual tree to landscape level and qualifying the multiscale spatial uncertainties for secondary forests by Ye Ma, Jungho Im, Zhen Zhen, Yinghui Zhao

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Initial stiffness of integrally-formed GFRP T-joint in GFRP transmission tower by Jinyi Xu, Jian Ma, Yong Chen, Xu Cui, Bing Feng, Wending Mou, Feng Pan

“…In terms of the top displacement, the result obtained via the structural analysis is close to the measured data, indicating an error of 9.03%. …”
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Flexible movement kernel estimation in habitat selection analyses with generalized additive models by Rafael Arce Guillen, Jennifer Pohle, Florian Jeltsch, Manuel Roeleke, Björn Reineking, Natasha Klappstein, Ulrike Schlägel

“…This offers greater flexibility and makes the analysis of real data more reliable.…”
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Advancing Nutritional Status Classification With Hybrid Artificial Intelligence: A Novel Methodological Approach by Md. Moddassir Alam, Asif Irshad Khan, Aasim Zafar, Mohammad Sohail, Mohammad Tauheed Ahmad, Rezaul Azim

“…Method This study utilizes the fire hawk optimizer‐based k‐means (FHO‐K‐Means) clustering method to identify key physiological indicators associated with under nutrition in children. The analysis is conducted using the UNICEF dataset, encompassing data from Afghanistan, Albania, Algeria, and Zimbabwe. …”
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Health-related quality of life implications of plantar ulcers resulting from neuropathic damage caused by leprosy: An analysis from the trial of autologous blood products (TABLE tr... by Naomi Kate Gibbs, Jessica Ochalek, Indra Bahadur Napit, Dilip Shrestha, Pedro Saramago Goncalves, Richard J Lilford, Mark Sculpher

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Permanent terrestrial laser scanning for near-continuous environmental observations: Systems, methods, challenges and applications by Roderik Lindenbergh, Katharina Anders, Mariana Campos, Daniel Czerwonka-Schröder, Bernhard Höfle, Mieke Kuschnerus, Eetu Puttonen, Rainer Prinz, Martin Rutzinger, Annelies Voordendag, Sander Vos

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Augmenting Fatigue Datasets for Improved Multiaxial Fatigue Strength Prediction with Neural Networks by Napon Opasanon, Leon Josef Stahr, Lukas Suchy, Alexander Hasse

“…This research underscores the potential of data augmentation techniques to enhance machine learning models for fatigue analysis.…”
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Multi-Criteria Assessment of Flood Risk on Railroads Using a Machine Learning Approach: A Case Study of Railroads in Minas Gerais by Fernanda Oliveira de Sousa, Victor Andre Ariza Flores, Christhian Santana Cunha, Sandra Oda, Hostilio Xavier Ratton Neto

“…In the meantime, historical precipitation, flow, and hydrological balance data will be used to calibrate and validate hydrological models. …”
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