Spectral optical properties of soot: laboratory investigation of propane flame particles and their link to composition by J. Heuser, C. Di Biagio, J. Yon, M. Cazaunau, A. Bergé, A. Bergé, E. Pangui, M. Zanatta, M. Zanatta, L. Renzi, A. Marinoni, S. Inomata, C. Yu, V. Bernardoni, S. Chevaillier, D. Ferry, P. Laj, P. Laj, M. Maillé, D. Massabò, D. Massabò, F. Mazzei, F. Mazzei, G. Noyalet, H. Tanimoto, B. Temime-Roussel, R. Vecchi, V. Vernocchi, P. Formenti, B. Picquet-Varrault, J.-F. Doussin

“…The established relationship can provide a useful parameterisation for models to estimate the absorption from combustion aerosols and their BC and BrC contributions.…”
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Multivariate Data Analysis to Assess Process Evolution and Systematic Root Causes Investigation in Tablet Manufacturing at an Industrial Scale—A Case Study Focused on Improving Tab... by Rita Mathe, Tibor Casian, Ioan Tomuta

“…The purpose of this work was to identify the root causes for the low and variable hardness of core tablets prepared using high-shear wet granulation through batch statistical modeling and to verify the short- and long-term effectiveness of the improvement actions. …”
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Inverse Association of Longitudinal Variations in Fat Tissue Radiodensity and Area by Giulia Besutti, Marta Ottone, Efrem Bonelli, Simone Canovi, Roberto Farì, Francesco Farioli, Annarita Pecchi, Guido Ligabue, Massimo Pellegrini, Pierpaolo Pattacini, Paolo Giorgi Rossi

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Machine learning prediction of metabolic dysfunction-associated fatty liver disease risk in American adults using body composition: explainable analysis based on SHapley Additive e... by Yan Hong, Xinrong Chen, Ling Wang, Fan Zhang, ZiYing Zeng, Weining Xie

“…This study aimed to develop and validate machine learning (ML) models for predicting MAFLD using detailed body composition metrics and to explore the relative contributions of adipose tissue features through explainable ML techniques.MethodsData from the 2017–2018 National Health and Nutrition Examination Survey (NHANES) were used to construct predictive models based on anthropometric, demographic, lifestyle, and clinical variables. …”
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Nutritional quality of Piptocoma discolor and Cratylia argentea as a non-timber forest products for animal feed in the Caquetá province by Faver Álvarez Carrillo, Fernando Casanoves, Yolanda Cuellar Medina, Jhoyner Felipe Ortiz Meneses, Victor Julio Balanta Martinez, Gustavo Adolfo Celis Parra

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A statistical and machine learning approach for monthly precipitation forecasting in an Amazon city by Ewerton Cristhian Lima de Oliveira, Eduardo Costa de Carvalho, Edmir dos Santos Jesus, Rafael de Lima Rocha, Rafael de Lima Rocha, Helder Moreira Arruda, Ronnie Cley de Oliveira Alves, Ronnie Cley de Oliveira Alves, Renata Gonçalves Tedeschi

“…Additionally, we use meteorological data from a set of sensors installed at a meteorological station located in Belém to train multivariate statistical and machine learning (ML) models to predict precipitation. Besides the use of algorithms, another evaluation was conducted on Feature Composition based on statistical methods to investigate the impact of variables on the prediction.ResultsThe results obtained in our investigation indicate that the vector autoregressive moving average with exogenous regressors (VARMAX) model achieved the best performance in rainfall forecasting, with an average root mean square error (RMSE) of 9.1833 in time series cross-validation, outperforming the other models.DiscussionThe climate-driven patterns directly influenced the performance of the rainfall forecasting models evaluated in this study. …”
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Fish fauna and its environmental relationship in an endorheic basin of Zacatecas, Mexico by Fernando Solís-Carlos, Gorgonio Ruiz-Campos, María de Lourdes Lozano-Vilano, Juana Claudia Leyva-Aguilera

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Preliminary analysis of patient assessment within a study on the impact of hydrokinetotherapy on body composition and metabolic disease risk in an adult population segment by Claudiu Cobuz, Sînziana Călina Silișteanu, Maricela Cobuz, Andrei-Ioan Costea, Elena Vizitiu Lakhdari

“…Similarly, the BMI data for men aged 40-60 indicated notable variability in body composition, consistent with the findings for men aged 61-80. …”
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Continental Orientation and the Climate of Land-dominated, Arid Planets by Donald M. Glaser, Igor Aleinov, Anthony Leboissetier, M. J. Way

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Optical Detection of the X-Ray Flash in the Very Fast Nova V1674 Her: Optical Contribution of the Irradiated Accretion Disk by Izumi Hachisu, Mariko Kato

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Theoretical and computational investigations on estimation of viscosity of ionic liquids for green adsorbent: Effect of temperature and composition by Zhaoxiong Han

“…The dataset comprises categorical information on Cation and Anion, along with numeric variables T(K) and xIL (mol%), serving as inputs for the models, while Viscosity (Pa.s) represents the output variable. …”
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Analysis of Control Characteristics and Design of Control System Based on Internal Parameters in Doubly Fed Variable-Speed Pumped Storage Unit by Guopeng Zhao, Yongxin Zhang, Jiyun Ren

“…The composition of doubly fed variable-speed pumped storage unit is introduced, and the mathematical model of every component is proposed. …”
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Assessment of Melon Fruit Nutritional Composition Using VIS/NIR/SWIR Spectroscopy Coupled with Chemometrics by Dimitrios S. Kasampalis, Pavlos Tsouvaltzis, Anastasios S. Siomos

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EFFECT OF BIOFERTILIZATION OF NOPAL VEGETABLE CROPS (Opuntia ficus-indica) ON PHYSICOCHEMICAL, PHYTOCHEMICAL AND MORPHOLOGICAL VARIABLES AND ITS RELATIONSHIP WITH BIOMASS PRODUCTIO... by Ruy Ortiz-Rodriguez, Manuel Galvan-Aguilar, Manuel Lopez-Rodriguez, Rosa Elena Pérez Sánchez, Alfonso Luna-Cruz, Gerardo Ordaz-Ocho

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White Coat: Origins, Composition, Semantics, Pragmatics, and Word-Formation Potential of Russian Phraseological Unit by T. V. Leontyeva

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Analytical investigation on resolution calculation method for nonlinear temperature load of steel-concrete composite girders by Chun-Ming Zhang, Wei-Hong Wu, Wei Xian, Wei Xian

“…The analysis encompasses temperature-induced self-restraint stresses, secondary stresses, and axial deformation in variable-section continuous composite girders. Key findings reveal that code-specified thermal stresses exhibit opposing polarity characteristics at specific locations compared to other models. …”
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Learning compositional sequences with multiple time scales through a hierarchical network of spiking neurons. by Amadeus Maes, Mauricio Barahona, Claudia Clopath

“…The hierarchical model redistributes the variability: it achieves high motif fidelity at the cost of higher variability in the between-motif timings.…”
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Low-noise optimization design for underwater series-connected multi-sphere composite shell structure by Hefan LI, Guanjun ZHANG, Yuzhao KE

“…The radial basis function (RBF) neural network was used to establish a multidimensional mapping model between the design variables and the optimization objective. …”
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Dynamic changes in AI-based analysis of endometrial cellular composition: Analysis of PCOS and RIF endometrium by Seungbaek Lee, Riikka K. Arffman, Elina K. Komsi, Outi Lindgren, Janette Kemppainen, Keiu Kask, Merli Saare, Andres Salumets, Terhi T. Piltonen

“…In conclusion, the AI model can potentially improve endometrial histology assessment by accelerating the analysis of the cellular composition of the tissue and by ensuring maximal objectivity for research and clinical purposes.…”
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Association between Serum Uric Acid Levels and Sleep Variables: Results from the National Health and Nutrition Survey 2005–2008 by R. Constance Wiener, Anoop Shankar

“…We found that snoring more than 5 nights per week, daytime sleepiness, and an additive composite score of sleep variables were associated with high serum uric acid in the age- , sex-adjusted model and in a multivariable model adjusting for demographic and lifestyle/behavioral risk factors. …”
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