Blood parameters predicted from milk spectra are candidate indicator traits of hyperketonemia—A retrospective study in the Italian Holstein population by S. Magro, M. De Marchi, M. Cassandro, R. Finocchiaro, A. Fabris, M. Marusi, A. Costa

“…Milk mid-infrared (MIR) spectroscopy has been successfully used for the prediction of several health traits in the last years, including blood metabolite concentrations, even though the model accuracy is moderate. In fact, MIR-predicted blood parameters are useful for population screening and may be used for selective breeding if they are heritable and genetically variable within a population. …”
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Quantitative analysis of targeted lipidomics in the hippocampus of APP/PS1 mice employing the UHPLC-MS/MS method by Shiyu Xiao, Xuemeng Wei, Bing Han, Xiaoqian Shi, Congzhen Wei, Rumeng Liang, Jingna Sun, Zheng Zhang, Zhengang Han, Li Shen

“…Sphingolipids (SPs), Glycerophospholipids (GPs), Glycolipids, Glycerides (GLs), Sterol Lipids (STs), and Free Fatty Acid (FA) were identified as prominent lipids exhibiting alterations in the hippocampus of AD models. Regarding glycolipid and glycerolipid composition, monogalactosyldiacylglycerols (MGDGs) and Triacylglycerols (TGs) constituted a significant proportion (p < 0.05, VIP > 1). …”
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Development and Study of Demodulators for Frequency Hopping Spread Spectrum Signals by D. I. Kaplun, V. V. Gulvanskiy, I. I. Kanatov, D. M. Klionskiy, A. B. Khachaturyan, D. N. Butusov, V. F. Lapizkiy, V. I. Bobrovskiy

“…The total error is computed for each SNR and the selected demodulation technique using the developed MATLAB/Simulink model for a communication channel. Finally, we conclude about the best demodulation technique for the selected message type for the given SNR.…”
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Factors Affecting the Ideals of Childbearing among Young People within Iranian Ethnic Groups by Zahra Ghorbani, Mohamad Aghasi

“…Given Iran's diverse ethnic composition, it is crucial to explore the relationship between ethnicity and fertility. …”
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Controls on Saturated Hydraulic Conductivity in a Degrading Permafrost Peatland Complex by Richard E. Fewster, Paul J. Morris, Graeme T. Swindles, Andy J. Baird, T. Edward Turner, Ruza F. Ivanovic

“…The multi‐site model made less skillful predictions (r2 = 0.528) than our site‐specific model, possibly due to latitudinal differences in peat compaction, floristic composition and climate. …”
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Predicting the Rheological Performance of Self-Compacting Mortar and Concrete Using Artificial Neural Network by Andreas Kounadis, Angelos Galatis, Agapoula Papakonstantinou, Efstratios Badogiannis

“…The particle size distribution of fine aggregates, along with the content and specific surface area of fine filler materials, emerged as the most significant predictive variables. This model could serve as a reliable tool for researchers and industries to design self-compacting mixtures, conserving laboratory time, as well as financial and natural resources.…”
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STATEWIDE ASSESSMENT OF WILD TURKEY HABITAT USING SATELLITE IMAGERY IN ARKANSAS by Sharon L. Goetz, William F. Porter

“…The HSI model incorporated food and cover variables into a geographic information system (GIS; ArcView Spatial Analyst) and evaluated habitat at a pixel resolution of 30 m. …”
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Multiple regression as a preventive tool for determining the risk of Legionella spp. by Enrique Gea-Izquierdo

“…Presented a significant lineal relation, withall the independent variables contributing significantly (p<0.05) to the model’s fit. …”
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The influence of environmental stability and upwelling variation on copepod diversity in the Humboldt Current System off Chile by Manuela Pérez-Aragón, Reinaldo Rivera, Vera Oerder, Carolina E. González, Cristián E. Hernández, Cristián E. Hernández, Ruben Escribano, Ruben Escribano

“…This variability has major consequences for population dynamics, community composition, and ultimately diversity patterns of planktonic copepods which dominate the bulk of zooplankton biomass. …”
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Understanding the Relationship Between Gender Representation in County Government and Perinatal Outcomes to Black, White, and Hispanic Birthing People in Georgia by Kaitlyn K. Stanhope, Pragati Kapila, Afsha Hossain, Maha Abu-Salah, Vanshika Singisetti, Amal Umerani, Sierra Carter, Sheree Boulet

“…We fit multilevel log binomial models with generalized estimating equations, with percent female as the primary independent variable. …”
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Utilization of plastic and glass waste mixed with sand as an alternative brick materials by Badiea A. Mahyoub, Amer H. Abdu, Adel A. Ahmed, Ibtisam M. Kamal

“…Optimization of the two effective variables (plastic/sand and galas ratios) has been made and correlating the results obtained using Box-Wilson statistical method to create a model for describing the predictable properties of a new product.…”
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Numerous Multi-Wave Solutions of the Time-Fractional Boussinesq-like System via a Variant of the Extended Simple Equations Method (SEsM) by Elena V. Nikolova, Mila Chilikova-Lubomirova

“…Based on the applied SEsM variant, we assume that each system variable in the studied model supports multi-wave dynamics, which involves combined propagation of two distinct waves traveling at different wave speeds. …”
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Optimization of Parameters of Two-Beam Laser Twelding of Quartz Raw Materials by V. A. Emelyanov, E. B. Shershnev, Y. V. Nikitjuk, S. I. Sokolov, I. Y. Aushev

“…Using the face-centered version of the central compositional plan of the experiment, a regression model of two-beam cleaning of quartz raw materials was obtained. …”
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Analysis of factors affecting employee performance by Yusuf Ronny Edward, Nagian Toni, Erina Alimin

“…This study aims to examine the variables that affect employees' productivity at PT Z. …”
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Machine learning-driven benchmarking of China's wastewater treatment plant electricity consumption by Minjian Li, Chongqiao Tang, Junhan Gu, Nianchu Li, Ahemaide Zhou, Kunlin Wu, Zhibo Zhang, Hui Huang, Hongqiang Ren

“…The findings not only enhance understanding of WWTP electricity consumption patterns and provide a scalable model for wider application, but also demonstrate a novel methodology for addressing multi-variable problems.…”
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A multi-source combined operation low carbon economy dispatch considering flexible participation of nuclear power in peaking by WU Xi, CHEN Kangwen, GUO Qisheng, LIU Yichen, YUE Fuchang

“…Firstly, 0-1 variables are used to accurately linearize the flexible address to nonlinear output of nuclear power. …”
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Optimizing Boride Coating Thickness on Steel Surfaces Through Machine Learning: Development, Validation, and Experimental Insights by Selim Demirci, Durmuş Özkan Şahin, Sercan Demirci, Armağan Gümüş, Mehmet Masum Tünçay

“…In this study, a comprehensive machine learning (ML) model was developed to predict and optimize boride coating thickness on steel surfaces based on boriding parameters such as temperature, time, boriding media, method, and alloy composition. …”
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Investigating the Affecting Factors of Speed Dispersion for Suburban Arterial Highways in Nanjing, China by Yongfeng Ma, Xin Gu, Jaeyoung Lee, Qiaojun Xiang

“…The results from the two models showed substantial differences. The road condition factor was not significant in the cross-sectional speed dispersion model, but was interpretive in the segmented speed dispersion model. …”
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Thermodynamical Theory of Inelastic Single Crystals by Piotr Perzyna

“…A general constitutive model is developed within the thermodynamic framework of the rate-type covariance constitutive structure with finite set of the internal state variables, and takes account of the effects as follows: (i) thermomechanical coupling; (ii) influence of covariance terms, lattice deformations and rotations and plastic spin; (iii) evolution of the dislocation substructure; (iv) deviation from the Schmidt rule of a critical resolved shear stress for slip; (v) rate sensitivity (viscosity). …”
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Association between the nutritional inflammation index and mortality among patients with sepsis: insights from traditional methods and machine learning-based mortality prediction by Yuanshuo Ge, Ding Hu, Zhe Wang, Cheng Zhang

“…The association between ANLR and mortality was investigated through Kaplan-Meier survival analysis, Cox regression, and restricted cubic spline (RCS) modeling. Furthermore, the contribution of ANLR relative to other predictors was evaluated by developing machine learning models, with SHapley Additive exPlanations (SHAP) employed to determine variable importance. …”
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