Modeling the weaning diet of piglets with fermented feed material: effects on growth performance and health parameters by Sarunas Badaras, Vytaute Starkute, Vytaute Starkute, Ernestas Mockus, Modestas Ruzauskas, Modestas Ruzauskas, Dovile Klupsaite, Erika Mozuriene, Jurgita Dailidaviciene, Agila Dauksiene, Agila Dauksiene, Laurynas Vadopalas, Barbara U. Metzler-Zebeli, Elena Bartkiene, Elena Bartkiene

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Optimal Selection Criterion for Runoff Component Models Based on Benefit-Risk Balance by DING Xiao-ling, HU Wei-zhong, TANG Hai-hua, LUO Bin, FENG Kuai-le

“…[Conclusions] A novel approach is proposed in this study for selecting component models of variable-length runoff sequences by balancing identification accuracy (benefit) and stability (risk). …”
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Modeling creep for a closed cylindrical shell under hydrostatic pressure by M. A. Magomedov, V. V. Kuznetsov, B. M. Yazyev, S. V. Litvinov

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Viscosity modelling of chlorinated brines in three-component systems with a continuously variable temperature range between 293-323 K by Andrés Soto-Bubert, Rashmi Bhardwaj, Satheeshkumar Rajendran, Roberto Acevedo

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Multidisciplinary Design Optimization of the NASA Metallic and Composite Common Research Model Wingbox: Addressing Static Strength, Stiffness, Aeroelastic, and Manufacturing Constr... by Odeh Dababneh, Timoleon Kipouros, James F. Whidborne

“…This study explores the multidisciplinary design optimization (MDO) of the NASA Common Research Model (CRM) wingbox, utilizing both metallic and composite materials while addressing various constraints, including static strength, stiffness, aeroelasticity, and manufacturing considerations. …”
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Intelligent multi-modeling reveals biological relationships and adaptive phenotypes for dairy cow adaptation to climate change by Robson Mateus Freitas Silveira, Angela Maria de Vasconcelos, Concepta McManus, Luiz Paulo Fávero, Iran José Oliveira da Silva

“…Biological analysis formed seven distinct mechanisms, each associated with specific biological functions and climate-driven effects on physiological and productive traits. 1) Blood traits were related to all milk components; 2) Lipid and energy metabolism, as well as kidney function, are related to the regulation of body temperature and milk composition; 3) Immunity and thyroid hormones are related to radiant thermal load; and 4) Homeostasis is the organic balance maintained between thermoregulatory, hormonal, hematological, productive, and biochemical functions, which are influenced by environmental variables. …”
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Mechanical constitutive model of stand off damping composites layered rubber core under wide strain rates by Zhangda Zhao, Wenjun Meng, Bijuan Yan, Guansen Qiao, Yuan Qin, Yao Wang, Tao Yang, Hong Ren

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Impact of Different Regimens of Fluoridated Dentifrice Application on the pH and Inorganic Composition in an Oral Microcosm Biofilm Model by Patrícia de Lourdes Budoia de Carvalho, Juliano Pelim Pessan, Bruna do Amaral, Amanda Costa Troncha, Samuel Campos Sousa, Douglas Roberto Monteiro, Thayse Yumi Hosida, Alberto Carlos Botazzo Delbem, Caio Sampaio

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Modeling and prediction of tribological properties of copper/aluminum-graphite self-lubricating composites using machine learning algorithms by Huifeng Ning, Faqiang Chen, Yunfeng Su, Hongbin Li, Hengzhong Fan, Junjie Song, Yongsheng Zhang, Litian Hu

“…Correlation of friction coefficients and wear rates of copper/aluminum-graphite (Cu/Al-graphite) self-lubricating composites with their inherent material properties (composition, lubricant content, particle size, processing process, and interfacial bonding strength) and the variables related to the testing method (normal load, sliding speed, and sliding distance) were analyzed using traditional approaches, followed by modeling and prediction of tribological properties through five different ML algorithms, namely support vector machine (SVM), K-Nearest neighbor (KNN), random forest (RF), eXtreme gradient boosting (XGBoost), and least-squares boosting (LSBoost), based on the tribology experimental data. …”
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Modeling of the Physicochemical and Nutritional Composition of <i>Musa paradisiaca</i> (Williams Variety) at Different Ripening Stages in Ecuador by María Fernanda Garcés-Moncayo, Fabricio Guevara-Viejó, Juan Diego Valenzuela-Cobos, Purificación Galindo-Villardón, Purificación Vicente-Galindo

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Robust Design Optimization of Viscoelastic Damped Composite Structures Integrating Model Order Reduction and Generalized Stochastic Collocation by Tianyu Wang, Chao Xu, Teng Li

“…This study presents a novel approach that integrates model order reduction (MOR) and generalized stochastic collocation (gSC) to enhance robust design optimization (RDO) of viscoelastic damped composite structures under material and geometric uncertainties. …”
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Development of objective test functions for modeling and sensitivity analysis of the mechanical behaviour of aluminum-agro-marine waste composites by Obinna Onyebuchi Barah, Stephen Ndubuisi Nnamchi, Milon Dennison Selvam, Mustafah Muhamad Mundu, Abubakar Abdulkarim

“…Objective Test Functions (OTFs) were derived using physical modeling and sensitivity analysis to filter impactful variables. …”
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Defining critical quality attributes and composition parameters for burn wound dressings: Antibiotic-anesthetic films as a model by María Florencia Sanchez, Laura Carolina Luciani-Giacobbe, Fiamma Barbieri, María Eugenia Olivera

“…This underscores the imperative need to establish precise critical quality attributes, a task undertaken within this study using an antibiotic-anesthetic film as a model. The aim was to establish the influence of critical composition and process parameters and optimize the formula.First, the quality target product profile was defined, and critical quality attributes were identified. …”
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Antiviral Activity of Double-Stranded Ribonucleic Acid and Interferon Alpha Composition in the Model of Experimental Influenza Infection of Mice by S. G. Gamaley, М. O. Skarnovich, E. V. Makarevich, О. Yu. Mazurkov, L. N. Shishkina, О. S. Ivanova, G. M. Levagina, Е. D. Danilenko

“…The aim of this work was to study antiviral activity of intranasal forms of the pharmaceutical compositions containing yeast dsRNA and recombinant human interferon-alpha-2b in a model of lethal influenza infection in mice. …”
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Impact of chemical composition on metabolizable energy and its prediction models in brewer's spent grains for broilers at different ages by Mingqiang Song, Kai Tian, Cong Ren, Youyou Liu, Xiaomeng Ye, Yuming Wang, Jingjing Xie, Feng Zhao

“…This study aimed to investigate the relationship between chemical composition and metabolizable energy (ME) in brewer’s spent grains (BSG), and to develop ME prediction models for fast-growing white feathered broilers at different ages. …”
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A multidimensional machine learning framework for LST reconstruction and climate variable analysis in forest fire occurrence by Hatef Dastour, Quazi K. Hassan

“…Land Surface Temperature (LST) datasets play a crucial role in understanding the complex interplay between forest fires, climate variables, and vegetation dynamics. This study is divided into two primary parts: the first part investigates the predictive performance of a machine learning framework based on CatBoost and XGBoost models in estimating LST across different land cover classes in Alberta, Canada. …”
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Intra-Site Variability in the Still Bay Fauna at Blombos Cave: Implications for Explanatory Models of the Middle Stone Age Cultural and Technological Evolution. by Emmanuel Discamps, Christopher Stuart Henshilwood

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Predicting 3-year all-cause mortality in rectal cancer patients based on body composition and machine learning by Xiangyong Li, Zeyang Zhou, Xiaoyang Zhang, Xinmeng Cheng, Chungen Xing, Yong Wu

“…SHAP values revealed that subcutaneous adipose tissue index (SAI), visceral adipose tissue index (VAI), skeletal muscle density (SMD), visceral-to-subcutaneous adipose tissue ratio (VSR), and subcutaneous adipose tissue density (SAD) were the five most important variables influencing all-cause mortality post-LaTME.ConclusionBy integrating body composition, multiple ML predictive models were developed and validated for predicting all-cause mortality after rectal cancer surgery, with the XGBoost model exhibiting the best performance.…”
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A Panchromatic Characterization of the Evening and Morning Atmosphere of WASP-107 b: Composition and Cloud Variations, and Insight into the Effect of Stellar Contamination by Matthew M. Murphy, Thomas G. Beatty, Everett Schlawin, Taylor J. Bell, Michael Radica, Thomas D. Kennedy, Nishil Mehta, Luis Welbanks, Michael R. Line, Vivien Parmentier, Thomas P. Greene, Sagnick Mukherjee, Jonathan J. Fortney, Kazumasa Ohno, Lindsey Wiser, Kenneth Arnold, Emily Rauscher, Isaac R. Edelman, Marcia J. Rieke

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A predictive model for body water and fluid balance using 3D smartphone anthropometry by Austin J. Graybeal, Abby T. Compton, Sydney H. Swafford, Caleb F. Brandner, Molly F. Johnson, Maria G. Kaylor, Hunter Haynes, Jon Stavres

“…Fluid overload and imbalance were determined using ECF/TBW and ECF/ICF, respectively, and subsequently predicted from the retained variables using receiver operating characteristic curve analyses and logistic regression.ResultsEstimates from each of the newly-developed prediction models were not significantly different from the estimates produced using BIS (all p ≥ 0.70) and revealed acceptable agreement (TBW: R2 = 0.91, RMSE = 3.24 L; ECF: R2 = 0.94, RMSE = 1.10 L; ICF: R2 = 0.87, RMSE = 2.29 L) when evaluated in the testing sample (n = 66), although proportional bias was observed (p &lt; 0.001). …”
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