Wafer‐Scale Synthesis of Topological Insulator Sb2Te3 Thin Films by Ali Shafiei, Ahmad Fathi Hafshejani, Rehab M. G. Ahmed, Alessio Lamperti, Emanuele Longo, Lorenzo Locatelli, Christian Martella, Alessandro Molle, Graziella Tallarida, Carlo Zucchetti, Claudia Wiemer, Massimo Longo, Roberto Mantovan

“…Furthermore, comprehensive information on the variability of the functional properties of Sb2Te3 thin films with their morphological, chemical, and structural properties, as probed by scanning electron microscopy, X‐ray diffraction/reflectivity, atomic force microscopy, Raman spectroscopy, time‐of‐flight secondary ion mass spectrometry, and energy‐dispersive X‐ray analyses is reported. …”
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Research on Ship Heave Motion Compensation Control Under Complex Sea State Environment Based on Improved Reinforcement Learning by ZHANG Qin, ZHOU Jingyi, WANG Xingyue, HU Xiong

“…The TD3 algorithm approximates the value function and policy by harnessing deep neural networks, equipping it to tackle complex and nonlinear sea condition challenges. …”
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Collaborative Federated Learning of Unmanned Aerial Vehicles in Space–Air–Ground Integrated Network by Huibo Li, Peng Gong, Siqi Li, Weidong Wang, Yu Liu, Xiang Gao, Dapeng Oliver Wu, Duk Kyung Kim, Guangwei Zhang, Jihao Zhang

“…In addition, the closed-form solutions of the optimized variables are obtained. Simulation results demonstrate that the proposed collaborative training scheme based on D2D can reduce the impact of heterogeneity on FL model performance and IRA can effectively reduce energy consumption while simultaneously enhancing training efficiency of FL.…”
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SVR-Optimized ANN Model for Predicting Earthquake Risk in Electrical Substations Based on Disaster Datasets in the Aceh Region, Indonesia by Elvy Sahnur Nasution, Yuwaldi Away, Syahrial, Ira Devi Sara, Andri Novandri

“…The ANN training process uses backpropagation with sigmoid and tanh activation functions. The ANN outputs are then used as input features for the SVR model, applying a Radial Basis Function (RBF) kernel to capture the non-linear relationships between variables. …”
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Revealing the Immune Response of <i>Sitona callosus</i> Gyllenhal to Entomopathogenic Fungi <i>Beauveria bassiana</i> Infection Through Integrative Analyses of Transcriptomics and... by Nan Li, Xin Gu, Ming Xin, Xinpu Wang

“…Additionally, we utilized the Pearson correlation coefficient method to examine the relationships between differentially expressed immune-related genes and metabolites, revealing notably strong correlations between these two sets of variables. …”
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Network Analysis of Key Instrumental Activities of Daily Living and Cognitive Domains for Targeted Intervention in US Older Adults Without Dementia: Cross-Sectional Study by Jiaying Li, Rendong He, Erh-Chi Hsu, Junxin Li

“…Network analysis identified central and bridge variables. Nonparametric and case-dropping bootstrap methods checked network stability. …”
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Comparative study between the Patient Participation Culture Tool and the Hospital Survey on Patient Safety Culture using retrospective data from 2014 to 2021 by Ward Schrooten, Ann Van Hecke, Marlies Claesen, Evelyne Punnewaert, Simon Malfait, Kristof Eeckloo

“…Spearman’s rank correlation coefficient was employed to evaluate relationships between continuous variables represented by PACT domain and HSPSC dimensional scores among study participants.Results Data from 17 hospitals were analysed. …”
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The Effect of Season and Breed on Hypothalamic–Pituitary–Adrenal Axis Hormones, Metabolic Hormones, and Oxidative Markers in Ponies and Horses by Sarah Alison Vaughn, Margaret B. Lemons, Kelsey A. Hart

“…Linear mixed effects modeling with a random effect for animal was used to determine the effects of season and breed. Correlation coefficients were calculated for relevant variables. …”
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Identification of an additive interaction using parameter regularization and model selection in epidemiology by Chanchan Hu, Zhifeng Lin, Zhijian Hu, Shaowei Lin

“…Background In epidemiology, indicators such as the relative excess risk due to interaction (RERI), attributable proportion (AP), and synergy index (S) are commonly used to assess additive interactions between two variables. However, the results of these indicators are sometimes inconsistent in real world applications and it may be difficult to draw conclusions from them. …”
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Relationship between Communication Skills and General Health in Nursing Students of Hamadan University of Medical Sciences by Roya Amini, Fariba Soleimani, Nahid Mohammadi, Tapak Leili

“…Communication skills had a significant relationship with most aspects of general health, except social function (p<0.001). There was no correlation between demographic variables and communication skills (p<0.05). …”
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Objective Measures of Spatial Effects in Spanish Concert Halls by Sara GIRÓN, Teófilo ZAMARRENO, Pedro BUSTAMANTE

“…The paper concludes with a discussion on the relationships of hall-average data of the five parameters with eight geometric and acoustic variables.…”
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RELATIONSHIP BETWEEN PRIVATE DOMESTIC INVESTMENT AND ECONOMIC GROWTH IN NIGERIA (1986-2018): AUTO-REGRESSIVE DISTRIBUTED LAG APPROACH by Isiaka Kareem JIMBA, Rosemary Bukola AJALA

“…The study incorporated other investment measures like foreign direct investment and public investment into the model, while inflation and exchange rate were taken as control variables. Secondary data was sourced from CBN statistical bulletin of various editions and was estimated using autoregressive distributed lag bound test and its coefficients. …”
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Enhancer chip: detecting human copy number variations in regulatory elements. by Marco Savarese, Giulio Piluso, Daniela Orteschi, Giuseppina Di Fruscio, Manuela Dionisi, Francesca del Vecchio Blanco, Annalaura Torella, Teresa Giugliano, Michele Iacomino, Marcella Zollino, Giovanni Neri, Vincenzo Nigro

“…Validation experiments have demonstrated that Enhancer Chip efficiently detects duplications and deletions covering enhancer loci, demonstrating that it is a powerful instrument to detect and characterize copy number variable enhancers.…”
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Impact of viscous dissipation, chemical reaction over a Carreau hybrid nanofluids flow across a permeable curved Riga surface by R. Mahesh, U.S. Mahabaleshwar, Basma Souayeh

“…Subsequently, the original partial differential equations are transformed using boundary layer approximations and similarity variables to produce a dimensionless ordinary differential equation. …”
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Detecting and reducing heterogeneity of error in acoustic classification by Oliver C. Metcalf, Jos Barlow, Yves Bas, Erika Berenguer, Christian Devenish, Filipe França, Stuart Marsden, Charlotte Smith, Alexander C. Lees

“…We recommend assessing—and if necessary correcting for—heterogeneity of precision error when using automated classification on acoustic data to quantify species presence as a function of an environmental, spatial or temporal predictor variable.…”
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Resilience for activity engagement among frail older adults: moderated mediation effect of social support by Eunna Oh, Nayoung Kim, Lkhagvajav Gansukh, Rhayun Song

“…Resilience has been identified as a protective factor that supports physical function, cognitive health, and independence in daily activities. …”
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Unsupervised selective labeling for semi-supervised industrial defect detection by Jian Ge, Qin Qin, Shaojing Song, Jinhua Jiang, Zhiwei Shen

“…This has motivated a shift towards semi-supervised learning (SSL), which leverages labeled and unlabeled data to improve learning efficiency and reduce annotation costs. This work proposes the unsupervised spectral clustering labeling (USCL) method to optimize SSL for industrial challenges like defect variability, rarity, and complex distributions. …”
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Cost-effective process design for methanol synthesis from carbon dioxide hydrogenation by Sheng-Zhong Huang, Chih-Yao Lin, Chianghui Wang, Akhmat Fauzan Saputra, Henggar Yudha Hananto, Nicolas Justin Sutanto, Anggit Raksajati, Vincentius Surya Kurnia Adi

“…Accordingly, this research introduces an optimization framework capable of handling diverse process configurations, operating variables, and their interactions. This approach enables effective optimization using total annual cost (TAC) as the objective function and significantly enhances process design efficiency. …”
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Multi-Objective Optimal Design of 200 kW Permanent Magnet Synchronous Motor Based on NSGA-II by Chengxu Sun, Qi Li, Tao Fan, Xuhui Wen, Ye Li, Hongyang Li

“…Interior permanent magnet synchronous motors (IPMSMs) are widely applied as drive motors in electric vehicles because they have the advantages of high power density, high efficiency, and excellent dynamic performance. This paper introduces a framework for multi-objective optimization, tailored for the demands of V-Shaped IPMSMs, which involves high-dimensional variables. …”
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Predicting and Mapping of Soil Organic Matter with Machine Learning in the Black Soil Region of the Southern Northeast Plain of China by Yiyang Li, Gang Yao, Shuangyi Li, Xiuru Dong

“…The models were trained by using 1554 surface soil samples and 19 auxiliary variables. Recursive feature elimination was used as a feature selection method to identify effective variables. …”
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