Characterization of biocomposite films made from carboxymethyl cellulose, okra mucilage, and black cumin seed (Nigella sativa) oil by Response Surface Methodology by Fariba Shekar, Afshin Javadi, Sodeif Azadmard-Damirchi, hamed hamishehkar

“…Statistical analysis showed that all variables significantly contribute to the model (p < 0.05). …”
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Investigation of the Boundary Value Problem for an Extended System of Stationary Nernst–Planck–Poisson Equations in the Diffusion Layer by Evgenia Kirillova, Natalia Chubyr, Roman Nazarov, Anna Kovalenko, Makhamet Urtenov

“…Dimensionless variables were introduced using characteristic parameter values. …”
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Gait speed in older adults: exploring the impact of functional, physical and social factors by Naiara Virto, Xabier Río, Iker Muñoz-Pérez, Amaia Méndez-Zorrilla, Begoña García-Zapirain

“…To assess physical function, SPPB tests (chair stand test, balance tests, gait speed test), manual grip strength, muscle quality index, and power were conducted, in addition to measuring body composition and socioeconomic status. Results: The final regression model showed that gait speed was significantly partially explained (R2=0.35; p<0.01) by the socioeconomic environment, age, balance, and relative power. …”
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Anti-aging effect of mustard and flax seed oils based nanoemulsion gel on aged rat skin through antioxidant and anti-inflammatory activity by Soha Ismail, Omar A. Ahmed-Farid, Ghada Farouk Metwally, Dina Mansour, Abeer Khattab

“…N-hexane was used to extract the oils of black mustard and flax seed from their seeds, and the oils' fatty acid composition was then determined. A full factorial design was created to assess the impact of three variables: oil type, oil concentration, and S:Cos ratio, on various responses: globule size, zeta potential, and emulsification time of the self-nanoemulsifying system. …”
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Preparation and hot compression deformation of biomedical Ni-Ti alloy by WANG Zhen, XU Xiao-wen, WANG Kuai-she, WANG Wen

“…To analyze the relationship between variables in the hot deformation process of as-cast Ni-Ti alloy, a constitutive equation based on dynamic material model was established. …”
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AI-Driven predicting and optimizing lignocellulosic sisal fiber-reinforced lightweight foamed concrete: A machine learning and metaheuristic approach for sustainable construction by Mohamed Sahraoui, Aissa Laouissi, Yacine Karmi, Abderazek Hammoudi, Mostefa Hani, Yazid Chetbani, Ahmed Belaadi, Ibrahim M.H. Alshaikh, Djamel Ghernaout

“…Statistical validation demonstrated the model's stability and reliability, evidenced by a notably low standard deviation (SD = 2.15 × 10⁻⁵), indicating minimal variability in predictions. …”
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Modifiable early life risk factors for dental calculus in dogs: a retrospective cross-sectional study in Finland by Manal B. M. Hemida, Sarah Holm, Mia Eklundh, Anna Hielm-Björkman

“…Multivariate logistic regression analyses using backward stepwise deletion were performed using data from 4771 dogs, including 2360 cases and 2411 controls, to examine the potential associations between DC in dogs and 29 distinct early life variables across five statistical models. The study incorporated a range of independent variables, including dietary, environmental, demographic, domestic, and immune-related factors. …”
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Optimization of clayey soil parameters with aeolian sand through response surface methodology and a desirability function by Ghania Boukhatem, Messaouda Bencheikh, Mohammed Benzerara, Mehmet Serkan Kırgız, N. Nagaprasad, Krishnaraj Ramaswamy, Souhila Rehab-Bekkouche, R. Shanmugam

“…Additionally, the Cc and Cs decreased by 16.15 and 54.45%, respectively, which reduced the sensitivity of the soil to volume changes. Mathematical models are developed and statistically validated using the clay and aeolian sand contents as predictive variables, while key parameters such as the maximum dry density (MDD), cohesion (C), internal friction angle (ϕ), compressibility coefficient (Cc), and swelling coefficient (Cs) serve as response metrics. …”
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Biofuel Production in Oleic Acid Hydrodeoxygenation Utilizing a Ni/Tire Rubber Carbon Catalyst and Predicting of n-Alkanes with Box–Behnken and Artificial Neural Networks by Luis A. Sánchez-Olmos, Manuel Sánchez-Cárdenas, Fernando Trejo, Martín Montes Rivera, Ernesto Olvera-Gonzalez, Benito Alexis Hernández Guerrero

“…We developed a dataset with pressure, temperature, metal content, reaction time, and catalyst composition variables as inputs. The output variables are the n-C₁₇ and n-C₁₈ alkanes obtained. …”
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Phenotypic and genetic characterisation of methane emission predicted from milk fatty acid profile of Sarda dairy ewes by F. Correddu, S. Carta, M. Congiu, A. Cesarani, C. Dimauro, N. P. P. Macciotta

“…Heritability of eMI and eMY estimated using a single trait model was 0.13 ± 0.05 and 0.05 ± 0.04, respectively. …”
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Functional and internalizing disorders co-aggregate with cardiometabolic and immune-related diseases within families: a population-based cohort study by Olivier D. Steen, Martje Bos, Sonja L. van Ockenburg, Yiling Zhou, Ilja M. Nolte, Harold Snieder, Kenneth Kendler, Judith G. M. Rosmalen, Hanna M. van Loo

“…We used logistic regression to model the prevalence of these disorders in the general population and in participants with affected relatives. …”
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Surface Defect Detection for Small Samples of Particleboard Based on Improved Proximal Policy Optimization by Haifei Xia, Haiyan Zhou, Mingao Zhang, Qingyi Zhang, Chenlong Fan, Yutu Yang, Shuang Xi, Ying Liu

“…The method integrates the variable action space and the composite reward function and achieves the balanced optimization of different types of defect detection performance by adjusting the scaling and translation amplitude of the detection region. …”
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Enhancing Agricultural Futures Return Prediction: Insights from Rolling VMD, Economic Factors, and Mixed Ensembles by Yiling Ye, Xiaowen Zhuang, Cai Yi, Dinggao Liu, Zhenpeng Tang

“…Additionally, previous studies have lacked a comprehensive consideration of key economic variables that influence agricultural prices. To address these issues, this study proposes the “Rolling VMD-LASSO-Mixed Ensemble” forecasting framework and compares its performance with “Rolling VMD” against univariate models, “Rolling VMD-LASSO” against “Rolling VMD”, and “Rolling VMD-LASSO-Mixed Ensemble” against “Rolling VMD-LASSO”. …”
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Smart furniture using radar technology for cardiac health monitoring by Ali Gharamohammadi, Mohammad Omid Bagheri, Serene Abu-Sardanah, Michael M. Y. R. Riad, Hajar Abedi, Ahmad Ansariyan, Kang Wang, Ashish Saragadam, Dmytro Chumachenko, Shahabeddin Abhari, Plinio Pelegrini Morita, Amir Khajepour, George Shaker

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Machine learning study on magnetic structure of rare earth based magnetic materials by Dan Liu, Jiahe Song, Zhixin Liu, Jine Zhang, Weiqiang Chen, Yinong Yin, Jianfeng Xi, Xinqi Zheng, Jiazheng Hao, Tongyun Zhao, Fengxia Hu, Jirong Sun, Baogen Shen

“…In this work, 11 machine learning algorithms were trained to predict the material magnetic structure. Material composition and crystal structure are used to classify the dataset, and the relationship between multi-feature variables is constructed in a small sample space. …”
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Bio-Organic Fertilizer Application Enhances Silage Maize Yield by Regulating Soil Physicochemical and Microbial Properties by Ying Tang, Lili Nian, Xu Zhao, Juan Li, Zining Wang, Liuwen Dong

“…Random forest and structural equation modeling (SEM) identified soil carbon storage and bacterial diversity as key drivers of EMF, which integrates soil functions such as nutrient cycling, decomposition, enzyme activity, and microbial diversity. …”
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Dynamic response of twin parallel tunnels in unsaturated soil under metro train loadings by Yiyang Liu, Guocai Wang, Yonger Ji, Siyu Jin, Tianshi Wan

“…The analytical generalized solutions were deduced by solving the governing equations for the coupled tunnel-soil system using the separation of variables method and the Helmholtz decomposition method combined with the Fourier transform technique. …”
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Tree community, vegetation structure and aboveground carbon storage in Atlantic tropical forests of Cameroon by Jean Louis Fobane, Jules Christian Zekeng, Cédric Djomo Chimi, Jean Michel Onana, André Paul Ebanga, Léonnel Djoumbi Tchonang, Ameline Clarance Talla Makoutsing, Marguerite Marie Mbolo

“…Additionally, multiple regression models were used to examine the effects of environmental variables and stand size structure on non-destructive carbon stock assessments. …”
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Exploring individual differences in fear extinction in male and female mice: insights from HPA axis, microbiota, and transcriptomics by Marc Ten-Blanco, María Ponce-Renilla, Inmaculada Pereda-Pérez, Cristina Izquierdo-Luengo, Carlo Bressa, Olga Zafra, Rosa María Tolón, Fernando Berrendero

“…This model allowed us to stratify the mice population into two extreme phenotypic subgroups (resilient and susceptible), based on their individual fear extinction behavior. …”
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Applicability of Machine Learning and Mathematical Equations to the Prediction of Total Organic Carbon in Cambrian Shale, Sichuan Basin, China by Majia Zheng, Meng Zhao, Ya Wu, Kangjun Chen, Jiwei Zheng, Xianglu Tang, Dadong Liu

“…Accurate Total Organic Carbon (TOC) prediction in the deeply buried Lower Cambrian Qiongzhusi Formation shale is constrained by extreme heterogeneity (TOC variability: 0.5–12 wt.%, mineral composition Coefficient of Variation > 40%) and ambiguous geophysical responses. …”
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