Nutritional status and body composition by bioelectrical impedance vector analysis: A cross sectional study in mild cognitive impairment and Alzheimer's disease. by Ilaria Cova, Simone Pomati, Laura Maggiore, Marica Forcella, Valentina Cucumo, Roberta Ghiretti, Giulia Grande, Fulvio Muzio, Claudio Mariani

“…<h4>Results</h4>Sociodemographic variables did not differ among the three groups (AD, MCI and HC), except for females' age, which was therefore used as covariate in a general linear multivariate model. …”
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Exploring the link between age at menarche, anthropometry and body fat composition with type II diabetes in a Singapore multi-ethnic cohort by Paula Benny, Qian Yang, Beverly Wen-Xin Wong, Cuilin Zhang, Eu-Leong Yong, Ling-Jun Li, Zhongwei Huang

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Impact of Microtopography and Neighborhood Effects on Individual Survival Across Life History Stages by Haonan Zhang, Xiao Zheng, Yi Wu, Baokun Xu, Peng Cui, Xu Zhou, Yanming Fang, Lei Xie, Hui Ding

“…Mixed-effects models were employed to assess the combined influence of these factors across life stages. …”
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The influence of whole grain products and red meat on intestinal microbiota composition in normal weight adults: a randomized crossover intervention trial. by Jana Foerster, Gertraud Maskarinec, Nicole Reichardt, Adrian Tett, Arjan Narbad, Michael Blaut, Heiner Boeing

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Landscape and climatic factors shaping mosquito abundance and species composition in southern Spain: A machine learning approach to the study of vector ecology by Martina Ferraguti, Sergio Magallanes, Carlos Mora-Rubio, Daniel Bravo-Barriga, Florentino de Lope, Alfonso Marzal

“…This study explores the interaction between environmental and climate factors, investigating their influence on the abundance and species composition of mosquitoes in southwestern Spain, a region endemic to several mosquito-borne diseases.Using comprehensive field data from 2020, we analysed mosquito abundance and species richness alongside remote sensing variables and modeling techniques, including the machine learning Random Forest. …”
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Coach-Assisted eHealth With Group or Individual Support for Employees With Obesity: Randomized Controlled Trial on Weight, Body Composition, and Health Metrics by Siniriikka A Männistö, Kirsi H Pietiläinen, Joona Muotka, Laura-Unnukka Suojanen, Raimo Lappalainen, Riitta Korpela

“…The participants were assessed for weight, body composition, blood pressure, and laboratory measurements at 0-, 6-, 12-, and 24-month time points. …”
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A novel method for predicting the geochemical composition of tailings with laboratory field and hyperspectral airborne data using a regression and classification-based approach by Yaron Ogen, Michael Denk, Cornelia Glaesser, Holger Eichstaedt

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Recovery of Carbon Fibres From Aged Epoxy Matrix Composites Using H2O2 as an Oxidant: A Thermodynamic and Technoeconomic Analysis by Paul Njeni Mabalane, Kristof Molnar, Philani Thembelihle Mazibuko, Kolos Molnár, Caroline Khoathane, Mike Masukume

“…The price of hydrogen peroxide and recovered carbon fibre are essential variables that have a high effect on the model.…”
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Physical characteristics as indicators of performance in young alpine skiers in Super-G by Stojan Puhalj, Blaž Lešnik, Črtomir Matejek, Samo Fošnarič, Tjaša Kmet, Jurij Planinšec

“…The multiple regression model explained 73% of the variance in the boys' performance and 59% in the girls', although the model itself was not statistically significant for predicting performance. …”
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Novel bio-adsorbent of alginate/HTC hydrochar &amp; alginate/HTH hydrochar composite beads for removal of basic blue 9 from water by Nayereh.S Tadayoni, Mohammad Dinari

“…Furthermore, the adsorption kinetics for both adsorbents conformed to the Elovich model. Isotherm and kinetic modeling indicate that electrostatic interactions and chemisorption are the dominant mechanisms driving dye removal.…”
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Impact of training data composition on the generalizability of convolutional neural network aortic cross-section segmentation in four-dimensional magnetic resonance flow imaging by Chiara Manini, Markus Hüllebrand, Lars Walczak, Sarah Nordmeyer, Lina Jarmatz, Titus Kuehne, Heiko Stern, Christian Meierhofer, Andreas Harloff, Jennifer Erley, Sebastian Kelle, Peter Bannas, Ralf Felix Trauzeddel, Jeanette Schulz-Menger, Anja Hennemuth

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Variation in the Phenolic Profile and Antioxidant, Antihyperglycemic, and Anti-Inflammatory Activity in Leaves of <i>Cotoneaster zabelii</i> during Growing Season by Agnieszka Kicel, Anna Magiera, Monika Anna Olszewska

“…In the course of optimizing the harvest time for <i>C. zabelii</i> cultivated in Poland, the leaf samples were collected monthly during the annual plant vegetation season, and the hydromethanolic leaf extracts were evaluated for their phenolic composition and model biological activities, including antioxidant, antihyperglycemic, and anti-inflammatory effects in vitro. …”
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Integrating piecewise and symbolic regression with remote sensing data for spatiotemporal analysis of surface water total dissolved solids in the Karun River, Iran by Javad Zahiri, Mohammad Reza Nikoo, Adell Moradi-Sabzkouhi, Mitra Cheraghi, Nazmi Mat Nawi

“…The innovative use of a fuzzy-based uncertainty analysis, coupled with AHP weighting, allowed for a comprehensive assessment of TDS estimation accuracy and uncertainty. The Composite Uncertainty Index (CUI) approach revealed that the Multivariate Adaptive Regression Splines (MARS) and M5 models performed better than other models, with CUI values of 0.83 and 0.72, respectively. …”
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Uncertainty and Stochasticity in Modelling of Microstructure Evolution During Hot Rolling of Steels Uncertainty and Stochasticity in Modelling of Microstructure Evolution During Ho... by D. Szeliga, J. Foryś, J. Kusiak, R. Kuziak, R. Nadolski, M. Pietrzyk, Ł. Rauch

“…Models based on stochastic internal variables meet this requirement. …”
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Lis State of the Greenland and Barents Sea ice cover in the context of current climate change by Ye. U. Mironov, E. S. Egorova, N. A. Lis

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Experimental and Statistical Investigations for Tensile Properties of Hemp Fibers by Peyman Sadeghi, Quang Cao, Ragab Abouzeid, Mohammad Shayan, Meensung Koo, Qinglin Wu

“…To further understand the variability and reliability of the tensile properties, statistical models were developed. …”
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Fine-scale landscape characteristics, vegetation composition, and snowmelt timing control phenological heterogeneity across low-Arctic tundra landscapes in Western Alaska by Dedi Yang, Wouter Hantson, Daniel J Hayes, Jin Wu, Shawn P Serbin

“…Deciduous tall shrubs (e.g. alder and willow) had a later SOS (∼7 d behind the mean of other PFTs), but completed leaf expansion (within 2 weeks) considerably faster compared to other PFTs. We modeled the landscape-scale variation in SOS and SOF using Random Forest, which showed that plant phenology can be accurately captured by a suite of variables related to vegetation composition, topographic characteristics, and snowmelt timing (variance explained: 53%–68% for SOS and 59%–82% for SOF). …”
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Causality among landscape characteristics, seasonality and stream water quality in the Paraopeba river basin by Fernando Arão Bila Júnior, Fernando António Leal Pacheco, Renato Farias do Valle Junior, Maytê Maria Abreu Pires de Melo Silva, Teresa Cristina Tarlé Pissarra, Marília Carvalho de Melo, Carlos Alberto Valera, Luís Filipe Sanches Fernandes, João Paulo Moura

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Performance Evaluation and Optimization of Binder-Toner and Mixing Efficiency Ratios in an E-Waste Toner-Modified Composite Mixture Using Response Surface Methodology by Syyed Adnan Raheel Shah, Sabahat Hussan, Nabil Ben Kahla, Muhammad Kashif Anwar, Mansoor Ahmad Baluch, Ahsan Nawaz

“…The study utilized a central composite design (CCD) together with the response surface methodology (RSM) to optimize the mix design variables, specifically the binder-toner ratio (BT) and mixing efficiency ratio (MER). …”
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Review: Preclinical Models of Large‐Vessel Occlusion Stroke by Alexander Keister, Arianna Carfora, Mayur S. Patel, Amanda S. Zakeri, Lillian Mannix, Debra G. Wheeler, Paco S. Herson, Shahid M. Nimjee

“…Thus, variables including size and region of the occlusion, composition of the clot, and degree of reperfusion can be controlled. …”
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