Integrating Hyperspectral, Thermal, and Ground Data with Machine Learning Algorithms Enhances the Prediction of Grapevine Yield and Berry Composition by Shaikh Yassir Yousouf Jewan, Deepak Gautam, Debbie Sparkes, Ajit Singh, Lawal Billa, Alessia Cogato, Erik Murchie, Vinay Pagay

“…These data, together with the canopy state variable data, were then used as inputs for the modelling. …”
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Utilizing Circadian Heart Rate Variability Features and Machine Learning for Estimating Left Ventricular Ejection Fraction Levels in Hypertensive Patients: A Composite Multiscale E... by Nanxiang Zhang, Qi Pan, Shuo Yang, Leen Huang, Jianan Yin, Hai Lin, Xiang Huang, Chonglong Ding, Xinyan Zou, Yongjun Zheng, Jinxin Zhang

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Evaluation and modelling of the buckling behaviour of SRC composite columns under simultaneous off-axis and lateral loading by Kabir Sadeghi, Javad Royaei, Fatemeh Nouban

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Multi-function composite data generation and PIMamba model for fault diagnosis in sucker-rod pumping wells by Senhao Ren, Wenqiang Tang, Chao Ma, Li Hou, Xiaodong Chen, Jiashan Lin, Jie Yang, Yun Yang, Xiao Huo, Guoxin Li, Daowei Zhang

“…To overcome these challenges, we propose a multi-function composite data generation paradigm that integrates diverse functional characteristics, generating 11 classes of highly interpretable single-condition images as training data for a prior model. …”
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Novel composite health assessment risk model for older allogeneic transplant recipients: BMT-CTN 1704 by Mohamed L. Sorror, Wael Saber, Brent Logan, Nancy Geller, Anna Bellach, Jianqun Kou, William Wood, John M. McCarty, Thomas G. Knight, Lyndsey Runaas, Laura Johnston, Jeremy Walston, Ryotaro Nakamura, Lori Jarrett, Asmita Mishra, Joseph Uberti, Parastoo B. Dahi, Jennifer N. Saultz, Shannon R. McCurdy, Lawrence E. Morris, Philip H. Imus, William J. Hogan, Kalyan Nadiminti, Vijaya Raj Bhatt, Rebecca Olin, Joseph Maakaron, Ronald Sobecks, Sarah A. Wall, Deborah Mattila, Bailey Protz, Steven M. Devine, Mary M. Horowitz, Andrew S. Artz

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An Analytical Solution for Variable Viscosity Flow in Fractured Media: Development and Comparative Analysis With Numerical Simulations by Anis Younes, Mohammad Mahdi Rajabi, Fatemeh Rezaiezadeh Roukerd, Marwan Fahs

“…Our study, recognizing these discrepancies, abandons this uniform viscosity assumption for a more realistic model of variable viscosity flow, focusing on viscous displacement scenarios. …”
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The impact of soil physical properties on combine harvester efficiency: a composite model from correlation trends by Mohd. Saifur Rahman, Nafis Shahid Fahim, Bodruzzaman Khan, Md. Fahad Jubayer, Tariqul Islam, Md Altaf Hossain

“…The findings reveal that sandy loam soils provide optimal conditions for harvesting efficiency, while loamy sands lead to reduced performance due to lower bearing capacity and increased slippage. The developed composite model accounts for 82.2% of the variability in field efficiency, offering a predictive tool for improving mechanized farming practices. …”
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A predictive model for biomass waste pyrolysis yield: Exploring the correlation of proximate analysis and product composition by Sabah Mariyam, Mohammad Alherbawi, Gordon McKay, Tareq Al-Ansari

“…In-depth examination of bio-oil compositions (based on carbon number classifications, and bonding arrangements) and gas composition (carbon monoxide, carbon dioxide, hydrogen, and methane) at varying operating conditions elucidates substantial yield differences, emphasizing the nuanced nature of product compositions. …”
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Study on the Damage Behavior of Engineered Cementitious Composites: Experiment, Theory, and Numerical Implementation by Tingting Ding, Zhuo Wang, Yang Liu, Xinlong Wang, Tingxin Sun, Shengyou Yang

“…It then introduces the concepts of damage energy release rate and energy equivalent strain, and constructs a three-dimensional constitutive model of ECCs by introducing the damage variable function. …”
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Characterization of EAF and LF Slags Through an Upgraded Stationary Flowsheet Model of the Electric Steelmaking Route by Ismael Matino, Alice Petrucciani, Antonella Zaccara, Valentina Colla, Maria Ferrer Prieto, Raquel Arias Pérez

“…In this paper, a stationary flowsheet model of the electric steelmaking route is presented; this model enables joint monitoring of key variables related to process, steel and slags. …”
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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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