Sex-specific associations between body composition and depression among U.S. adults: a cross-sectional study by Yijing Li, Juan Li, Tianning Sun, Zhigang He, Cheng Liu, Zhixiao Li, Yanqiong Wu, Hongbing Xiang

“…After accounting for confounding variables, the associations between fat mass index (FMI), appendicular skeletal muscle mass index (ASMI), body fat percentage (BFP), body composition phenotypes, and depression risk were assessed using restricted cubic spline (RCS) curves and multivariable logistic regression models. …”
Get full text

Development of Durian Rind/Polypyrrole Composite and Its Application in Removing of Anionic Dyes by Yan Wang, Zijing Dai, Jiaqi Zha, Wenqing Wei

“…Then, the removing performance of the DR/PPy material for anionic dyes was explored. The impact of key variables such as the amount of adsorbent, initial dye concentration, pH, adsorption temperature, and contacting time on the adsorption efficiency was examined. …”
Get full text

Dynamic Properties of Concrete Composite Panels under Eccentric Compression Loading Tests by Max De Castro MAGALHAES, Roberto Marcio da SILVA

“…The main aim of this paper is to examine the variability of some dynamic properties of concrete composite panels to in-plane eccentric compression loads via static and dynamic impact testing. …”
Get full text

Resin-based adhesives, composites, and luting agents: Investigation of article citations and altmetrics by Fernanda LAUER, Rodrigo Rohenkohl SILVA, Leticia Regina SARTORI, Kauê COLLARES, Rafael SARKIS-ONOFRE, Clóvis FAGGION JUNIOR, Rafael Ratto de MORAES

“…Data were analyzed using stepwise backward quasi-Poisson regression models (p < 0.05). A total of 707 articles were included, which evaluated restorative composites (58.3%), adhesives (27.2%), and luting agents (19.5%). …”
Get full text

Soil Reflectance Composite for Digital Soil Mapping in a Mediterranean Cropland District by Monica Zanini, Uta Heiden, Leonardo Pace, Raffaele Casa, Simone Priori

“…The procedure to obtain the SRC was carried out following the Soil Composite Mapping Processor (SCMaP) methodology. The Sentinel-2 bands of the SRC showed strong correlations with soil features, making them very suitable explicative variables for regression kriging. …”
Get full text

Resistance training as a modulator of inflammation and cognition by Jacqueline Goodrich, Jamie L. Tartar, Jonathan Banks, Francesca Leon, Jose Antonio

“…Pearson correlations were also conducted to explore the relationship between biomarkers (CRP, IL-6, cortisol) and cognitive outcomes, with secondary analysis examining the impact of PSQI and lifestyle variables on the study’s results through within-subjects Pearson correlations.Results Paired t-tests revealed significant improvements in cognitive performance: Flanker (t(14) = 5.27, p < .001), Stroop (t(14) = -4.61, p < .001), and composite cognition (t(14) = -5.11, p < .001), along with increased muscle mass (t(14) = -4.21, p < .001). …”
Get full text

Impact of a 15-week ability-based training program on body composition and physical fitness in university-based fire academy recruits by Annette Zapp, Kyla Schults, Krissy Sanchez, Paige Sutton, Amanda Ehlrich, Jay Dawes

“…No multivariate outliers were detected in the model; significance was set at p < 0.05.Results Significant improvements (p ≤ 0.001) in sKM and BF% were observed between testing sessions 1 and 2, with statistically insignificant improvements between testing sessions 2 and 3, suggesting the overall program was impactful in providing positive body composition changes. …”
Get full text

A Numerical-Experimental Method for Drop Impact Analysis of Composite Landing Gear by Yongliang Guan, Zhipeng Xue, Ming Li, Hongguang Jia

“…Therefore, variability in mechanical properties must be considered in a mechanical response analysis of composite structures. …”
Get full text

Non-Invasive Composition Identification in Organic Solar Cells via Deep Learning by Yi-Hsun Chang, You-Lun Zhang, Cheng-Hao Cheng, Shu-Han Wu, Cheng-Han Li, Su-Yu Liao, Zi-Chun Tseng, Ming-Yi Lin, Chun-Ying Huang

“…To account for fabrication-related variability, the active-layer thickness varied by over ±15% around the optimal value, creating a realistic and diverse training dataset. …”
Get full text

Uncertainty analysis in the design of Type-IV composite pressure vessels for hydrogen storage by Yao Koutsawa, Lyazid Bouhala

“…Sobol’ indices were used to assess the direct and total influence of the uncertain parameters on the BP variability, guiding optimization in composite pressure vessel design. …”
Get full text

Analysis of Mineral Composition and Isotope Ratio as Part of Chemical Profiles of Apples for Their Authentication by Boris Krška, Martin Mészáros, Tomáš Bílek, Aleš Vávra, Jan Náměstek, Jiří Sedlák

“…However, their high variability within particular districts complicates the resolution of the LDA model. …”
Get full text

High Spatial Resolution in Total Water Storage Variations Inferred From GPS: Case Study in the Great Lakes Watershed, US by Shuo Zheng, Zizhan Zhang, Bridget R. Scanlon, Haoming Yan, Alexander Y. Sun, Ashraf Rateb, Yan Li

“…The average annual amplitude of TWSGPS on land reaches 82.0 mm, greatly exceeding estimates from GRACE/GFO (∼48.0 mm) and composite hydrological model outputs (∼62.0 mm). The seasonal groundwater fluctuations inferred from GPS have peak‐to‐peak amplitudes of ∼40 km3 with the maximum around September. …”
Get full text

Turbidity and suspended sediment relationship based on sediment composition and particle size distribution by Jongmin Kim, Siyoon Kwon, Sewoong Chung, Young Do Kim

Get full text

Multi-objective optimization of dual-stator permanent magnet motor based on composite algorithm by Xiaoguang Kong, Zhuo Yang

Get full text

Absorbent material composition prediction based on multi-objective regression with value stacking and selection by Shi He, Jiaying Chen, Kai Huang, Jian Mao, Kexun Li, Taikang Liu

“…Traditional multi-objective regression methods often fail to provide accurate component predictions, limiting their performance.MethodWe propose a multi-objective predictive model for absorbent compositions. Using single-variable predictions as cumulative features in a regression chain improves feature representation. …”
Get full text

Multiple Characteristics Criterion Based Incipient Fault Detection of Distribution Systems by Anning WANG, Rongqi FAN, Yang ZHANG, Jiachao LIU, Wei HU, Shimin ZHONG, Ke JIA

“…The fault characteristics of the new distribution system have changed significantly under the high proportion of new energy access, with variable operation modes and limited short-circuit currents. …”
Get full text

Data-driven assessment of corrosion in reinforced concrete structures embedded in clay dominated soils by Shahbaz Ahmad, Siraj Ahmad, Sabih Akhtar, Faraz Ahmad, Mujib Ahmad Ansari

“…Abstract The integration of Artificial Intelligence techniques, particularly Artificial Neural Networks (ANNs), has transformed predictive modeling in structural and durability engineering. …”
Get full text

Machine Learning Approach for Predicting Hypertension Based on Body Composition in South Korean Adults by Jeong-Woo Seo, Sanghun Lee, Mi Hong Yim

“…In the hypertension prediction model, the most important variables for men were age, skeletal muscle mass (SMM), and body fat mass (BFM), in that order. …”
Get full text

Epoxy/Silicone Blend Loaded with N-Doped CNT Composites: Study on the Optoelectronic Properties by Younes Ziat, Hamza Belkhanchi, Maryama Hammi, Ousama Ifguis

Get full text

Mechanical Performance of Group Stud Connectors in Steel–Concrete Composite Beams with Straddle Monorail by Lei-Ting Jiao, Zhen-Hao Wu, Yong-Fei Zhao, Ji-Zhi Zhao, Shu-Ke Wang

“…This study investigates the behavior of group stud connectors by conducting push-out tests on four specimens, comprising three full-scale models and one 1:3 scaled model. Variables such as the number of connectors, arrangement, and specimen size were explored. …”
Get full text