Validation of Automated Somatotype Estimation Proposal Using Full-Body 3D Scanning by Bibiána Ondrejová, Lucia Bednarčíková, Norbert Ferenčík, Jozef Živčák

“…A custom-developed application processed the scanned data to compute somatotype values. The results were compared using statistical metrics, including intraclass correlation coefficients (ICCs) and Bland–Altman analysis. …”
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Acoustic Tomography of the Atmosphere: A Large-Eddy Simulation Sensitivity Study by Emina Maric, Bumseok Lee, Regis Thedin, Eliot Quon, Nicholas Hamilton

“…Unlike prior work that relied on field observations or idealized fields, the LES framework provides a ground-truth atmospheric state, enabling quantitative assessment of TDSI retrieval reliability, sensitivity to travel-time measurement noise, and dependence on covariance model parameters and temporal data integration. A detailed sensitivity analysis was conducted to determine the best-fit model parameters, identify the tolerance thresholds for parameter mismatch, and establish a maximum spatial resolution. …”
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Mapping the Main Phenological Spatiotemporal Changes of Summer Maize in the Huang-Huai-Hai Region Based on Multiple Remote Sensing Indices by Dianchen Han, Peijuan Wang, Yang Li, Yuanda Zhang, Jianping Guo

“…In conclusion, this study reveals the potential of emerging vegetation indices for extracting maize phenology, offering both data and theoretical support for regional crop adaptability assessments.…”
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Comprehensive techno-environmental evaluation of an isolated PV/wind/biomass hybrid microgrid employing various battery technologies: A comparative analysis. by Mohammed Alqahtani, Saeed Alhajri, Ahmed S Menesy, Ali Maher Mohammed, Hamdy M Sultan, Muhammad Khalid

“…This paper presents a comprehensive techno-economic analysis of an off-grid PV/wind/biomass hybrid system. …”
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Prevalence of interprofessional collaboration towards patient care and associated factors among nurses and physician in Ethiopia, 2024: a systematic review and meta-analysis by Abdulkerim Hassen Moloro, Kebede Gemeda Sabo, Begetayinoral Kussia Lahole, Beriso Furo Wengoro, Kusse Urmale Mare

“…Studies indicate that failures in interprofessional collaboration between nurses and physicians lead to adverse medical events, including hospital-acquired infections, medication administration errors, and unnecessary health-related costs. Objective This systematic review and meta-analysis aimed to investigate the pooled proportions of the interprofessional collaborations towards patient care and associated factors among nurses and physicians in Ethiopia, 2024. …”
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Genetic Variations of Three Kazakhstan Strains of the SARS-CoV-2 Virus by Bekbolat Usserbayev, Kulyaisan T. Sultankulova, Yerbol Burashev, Aibarys Melisbek, Meirzhan Shirinbekov, Balzhan S. Myrzakhmetova, Asankadir Zhunushov, Izat Smekenov, Aslan Kerimbaev, Sergazy Nurabaev, Olga Chervyakova, Nurlan Kozhabergenov, Lesbek B. Kutumbetov

“…In this study, whole-genome sequencing of three SARS-CoV-2 strains was performed using the Sanger method, which provides high accuracy in determining nucleotide sequences and avoids errors associated with multiple DNA amplification. …”
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Modeling and analysis of dynamical behavior in a fractional-order COVID-19 epidemic model with media coverage: A case study of Malaysia by Rui Hu, Muhamad Hifzhudin Noor Aziz, Nur Anisah Mohamed, Elayaraja Aruchunan

“…Finally, sensitivity analysis highlights the roles of key parameters in determining R0. …”
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State of Health Estimation of Li-Ion Battery via Incremental Capacity Analysis and Internal Resistance Identification Based on Kolmogorov–Arnold Networks by Jun Peng, Xuan Zhao, Jian Ma, Dean Meng, Shuhai Jia, Kai Zhang, Chenyan Gu, Wenhao Ding

“…The model achieved a mean absolute error of less than 0.412% in SOH prediction in the test and validation dataset. …”
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Using Social Media Platforms to Raise Health Awareness and Increase Health Education in Pakistan: Structural Equation Modeling Analysis and Questionnaire Study by Malik Mamoon Munir, Nabil Ahmed

“…MethodsThe study used two-stage structural equation modeling (SEM). Data analysis used AMOS 26.0 software, adopting scales from previous literature. …”
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The Impact of Building Level of Detail Modelling Strategies: Insights into Building and Urban Energy Modelling by Daniel Bishop, Mahdi Mohkam, Baxter L. M. Williams, Wentao Wu, Larry Bellamy

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Efficacy and safety of olanzapine for treatment of patients with bipolar depression: Chinese subpopulation analysis of a double-blind, randomized, placebo-controlled study by Wang G, Cheng Y, Wang J, Wu SH, Xue HB

“…The lack of a statistically significant difference between the olanzapine and placebo groups in this Chinese subpopulation analysis may relate to an a priori lack of study power, and underestimation of the effect of olanzapine because of a greater emergence of mania in placebo-treated patients and missing data associated with a high early discontinuation rate. …”
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Evaluation of a Computer-Based Morphological Analysis Method for Free-Text Responses in the General Medicine In-Training Examination: Algorithm Validation Study by Daiki Yokokawa, Kiyoshi Shikino, Yuji Nishizaki, Sho Fukui, Yasuharu Tokuda

“…ResultsOf the 104 responses collected—63 for postgraduate year 1 and 41 for postgraduate year 2—39 cases remained for final analysis after excluding invalid responses. The authors found discrepancies between human and machine scoring in 14 questions (7.2%); some were due to shortcomings in machine scoring that could be resolved by maintaining a list of correct words and dictionaries, whereas others were due to human error. …”
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Use of artificial neural network for optimization of irreversibility analysis in radiative Cross nanofluid flow past an inclined surface with convective boundary conditions by Ali Farhan, Zaib Aurang, Zafar Syed Sohaib, Khan Umair, Ahmed Muhammad Faizan, Elattar Samia, Khashi’ie Najiyah Safwa

“…To evaluate the correctness of the proposed model, the results of training, testing, and validation are analyzed using the performance charts, error histograms, transition state analysis, comparisons between bvp4c and ANN, and regression plots. …”
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A comprehensive analysis of digital inclusive finance’s influence on high quality enterprise development through fixed effects and deep learning frameworks by Dedai Wei, Zimo Wang, Hanfu Kang, Xinye Sha, Yiran Xie, Anqi Dai, Kaichen Ouyang

“…Then, based on the results of these tests, we selected deep learning features and combined Kolmogorov–Arnold Neural Network (KAN), Graph Neural Network (GNN) models with classic time series deep learning models (Transformer, LSTM, BiLSTM, GRU) to capture the latent nonlinear features in the data for prediction. The results show that, compared to traditional time series forecasting methods, the improved deep learning models perform better in capturing the nonlinear relationships of economic variables, improving prediction accuracy, and reducing prediction errors. …”
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Spatiotemporal Analysis and Anomalous Trends of Asia AOD (2001–2024): Insights from a Deep Learning Fusion Model and EOF Decomposition by Yu Ding, Wenjia Ni, Jiaxin Dong, Jie Yang, Shiyao Meng, Siwei Li

“…The fused dataset demonstrates significant improvements over the original MERRA-2 AOD, with an increase in the coefficient of determination (R²) by 0.1065 and a reduction in root mean square error (RMSE) by 0.0369. Spatio-temporal analysis, conducted using Empirical Orthogonal Function (EOF) decomposition, reveals that AOD concentrations across Asia are strongly influenced by anthropogenic factors, including industrial activities, transportation emissions, and biomass burning. …”
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Handling of missing component information for common composite score outcomes used in axial spondyloarthritis research when complete-case analysis is unbiased by Christos Polysopoulos, Stylianos Georgiadis, Lykke Midtbøll Ørnbjerg, Almut Scherer, Daniela Di Giuseppe, Merete Lund Hetland, Michael John Nissen, Gareth T. Jones, Bente Glintborg, Anne Gitte Loft, Johan Karlsson Wallman, Karel Pavelka, Jakub Závada, Ayten Yazici, Maria José Santos, Adrian Ciurea, Burkhard Möller, Brigitte Michelsen, Pawel Mielnik, Johanna Huhtakangas, Heikki Relas, Katja Perdan Pirkmajer, Ziga Rotar, Ross MacDonald, Bjorn Gudbjornsson, Irene van der Horst-Bruinsma, Marleen van de Sande, Myriam Riek

“…Abstract Background Observational data on composite scores often comes with missing component information. …”
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A Calculating Method for the Height of Multi-Type Buildings Based on 3D Point Cloud by Yuehuan Wang, Shuwen Yang, Ruixiong Kou, Zhuang Shi, Yikun Li

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Interpretable multi-horizon time series forecasting of cryptocurrencies by leverage temporal fusion transformer by Arslan Farooq, M. Irfan Uddin, Muhammad Adnan, Ala Abdulsalam Alarood, Eesa Alsolami, Safa Habibullah

“…The study demonstrates that the ADE-TFT model outperforms its lower-layer counterparts in terms of forecasting accuracy, with reduced Mean Absolute Percentage Error (MAPE), Mean Squared Error (MSE), and Root Mean Square Error (RMSE) values, particularly when using a higher hidden layer configuration (h=8). …”
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Research on Monthly Runoff Forecast in Dry Seasons Based on GEO-RVM Model by ZHANG Yajie, CUI Dongwen

“…To improve the accuracy of monthly runoff forecasts during dry seasons,this study proposes a forecasting method that combines the golden eagle optimization (GEO) algorithm and the relevance vector machine (RVM).On the basis of the runoff data of 67 a from a hydrological station in Yunnan Province,the monthly runoff with good correlation before the forecast month is selected as the influencing factor of forecasts,and the influencing factor is reduced in dimension by principal component analysis (PCA).The kernel width factor and hyperparameters of RVM are optimized by the GEO algorithm,and the GEO-RVM model is built to forecast the monthly runoff of the station during the dry season from November to April of the following year.Moreover,the forecast results are compared with those of the GEO-based support vector machine (SVM) model (GEO-SVM).The results demonstrate that the average relative errors of the GEO-RVM model for the monthly runoff forecasts from November to April of the following year are 8.59%,7.34%,5.97%,6.07%,5.99%,and 5.04%,respectively,which means the accuracy is better than that of the GEO-SVM model.The GEO algorithm can effectively optimize the kernel width factor and hyperparameters of RVM,and the GEO-RVM model has better forecast accuracy,which can be used for monthly runoff forecasting during dry seasons.…”
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A Distributed Machine Learning-Based Scheme for Real-Time Highway Traffic Flow Prediction in Internet of Vehicles by Hani Alnami, Imad Mahgoub, Hamzah Al-Najada, Easa Alalwany

“…However, these detection systems do not support real-time analysis. Centralized machine learning methods face a number of challenges due to the sheer volume of traffic data that needs to be processed in real-time. …”
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