Isothermal crystallization kinetics of poly(ethylene terephthalate) and poly(methyl methacrylate) blends

“…Different kinetic models like the Avrami, Tobin and Urbanovici-Segal models have been applied for determining the isothermal crystallization kinetics of virgin poly(ethylene terephthalate) (PET) and PET/poly(methyl methacrylate) (PMMA) blends. …”
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Emotional intelligence, support, and organizational culture’s impact on decision-making: mediation and moderation analysis in academia by Saqib Munir, Muhammad Khalid Anser, Syed Tahir Hussain Shah, Talat Islam, Khalid Zaman

“…Abstract Academic decision-making is composite, involving a number of players with various points of view and frequently conflicting interests. …”
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Detecting fish community structure in open waters using environmental DNA: a case study from the central South China Sea by Ting Chen, Ting Chen, Shuai Zhang, Shuai Zhang, Shuai Zhang, Peiwen Jiang, Zuozhi Chen, Zuozhi Chen, Jun Zhang, Jun Zhang, Shannan Xu, Shannan Xu, Shannan Xu, Min Li, Min Li, Min Li

“…Additionally, generalized additive models (GAMs) were applied for the 5 m and 200 m depth layers to assess the influence of environmental variables on fish communities. …”
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Optimization and Multimachine Learning Algorithms to Predict Nanometal Surface Area Transfer Parameters for Gold and Silver Nanoparticles by Steven M. E. Demers, Christopher Sobecki, Larry Deschaine

“…However, the expansion and testing of this model for nanoparticles of different metal composition is needed to develop a greater variety of nanosensors for medical and commercial applications. …”
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Sex-Dependent Effects of Body Fat on Cardiac Function and Outcomes in Community-Dwelling Older Adults by Haowen Jiang, MBBS, Jie Jun Wong, MBBS, Glades H.M. Tan, BEng, Louis L.Y. Teo, MBBS, See Hooi Ewe, MBBS, PhD, Ru-San Tan, MBBS, Fei Gao, PhD, Angela S. Koh, MBBS, MPH, PhD

“…Correlations between baseline or interval changes (Δ) of WHR, BFM and PBF with follow-up or Δ values of outcomes were analyzed, with multivariable linear regression model adjustments for significant variables. Results: Among 409 older adults (mean age 61 ± 12.7 years, 214 women) with median follow-up of 4.9 (4.5, 5.2) years, baseline BFM predicted echocardiographic diastolic dysfunction at follow-up in women (OR: 1.059; 95% CI: 1.051-1.115; P = 0.002). …”
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Prevalence and Associated Factors of Sarcopenic Obesity Among Nursing Home Residents: A Cross‐Sectional Multi‐Centre Study by Doris Eglseer, Hristo Hristov, Sanja Krušič, Nadan Gregorič, Irena Hren, Igor Pravst, Živa Lavriša

“…The multivariable logistic regression model shows that higher age (OR 1.07; CI 1.02, 1.11), male sex (OR 2.3; CI 1.22, 4.5) and higher energy intake (OR 1.13; CI 1.04, 1.22) were significantly associated with sarcopenic obesity. …”
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Biological maturation determines the beneficial effects of high-intensity functional training on cardiorespiratory fitness in male adolescents by Jarosław Domaradzki, Cristian Alvarez, Rafał Szafraniec, Dawid Koźlenia

“…Background During adolescence, between 15–18 years of age, biological maturation is associated with changes in body composition, blood pressure (BP), and cardiorespiratory fitness (CRF). …”
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Intestinal permeability of N-acetylcysteine is driven by gut microbiota-dependent cysteine palmitoylation by Yu-Hang Zhang, Chen-Shu Dai, Ya-Jie Wang, Wen-Yu Wang, Tian-Tian Qi, Man-Cheng Xia, Gan Zhou, Yi-Min Cui

“…However, identifying microbial-drug interactions remains challenging due to the highly variable composition of intestinal flora among individuals. …”
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Predicting the sport level in elite male motorcycle speedway riders based on physical profile and experience. by Stefan Szczepan, Zofia Wróblewska, Faye Perkins, Maciej Markowski, Kamil Michalik

“…The strongest predictive variable of sport level in the regression model (R2 = 0.28) was body height (p = 0.043) and sport experience (p < 0.001). …”
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Predicting Strength Properties of High-Performance Concrete Modified with Natural Aggregates and Ferroslag under Varied Curing Conditions by Muthumani Soundararajan, Sridhar Jayaprakash, S. K. Maniarasan, Ravindran Gobinath

“…Further, natural aggregate, ferro slag, and duration of curing were considered as basic variables to suggest the model. Regression models for response data were evaluated using analysis of variance (ANOVA) and Pareto charts. …”
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Enhancing concrete strength for sustainability using a machine learning approach to improve mechanical performance by Amir Khan, Aneel Manan, Muhammad Umar, Mudassir Mehmood, Kennedy C. Onyelowe, Krishna Prakash Arunachalam

“…Three ML models Extreme Gradient Boosting (XGBoost), Decision Tree, and K-Nearest Neighbors (KNN) were developed and evaluated using metrics such as R2, RMSE, MAE, and MAPE. …”
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Statistical Optimization of Culture Conditions for Enhanced Biomass Yield of Lactobacillus acidophilus CM1 Using Plackett–Burman and Response Surface Methodology by Khushboo Rajput, Amar Yasser Jassim, Ameer Abbas Mohammed, Abdel Rahman Mohammad Said Al-Tawaha, Arun Karnwal, Tabarak Malik

“…This approach offers a scalable model for bioprocess optimization in industrial fermentation.…”
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Energy expenditure compared to physical activity measured by accelerometry and self-report in adolescents: a validation study. by Pedro C Hallal, Felipe F Reichert, Valerie L Clark, Kelly L Cordeira, Ana M B Menezes, Simon Eaton, Ulf Ekelund, Jonathan C Wells

“…By incorporating fat and fat-free mass in the model, we were able to explain 58% of the variability in TEE.…”
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Dynamic Analysis and Scale Optimization of Prefabricated Building Wall Panel Installation by Jiang Mingyang, Zhang Lin, Liu Hongbin, Sima Mingyang, Yu Ningtao

“…The scale optimization model of the landing mechanism, based on the composite shape method and iterative calculation through Matlab software, the optimal scale parameters of each component of the boom lift chain are obtained, and the maximum load of the boom lift cylinder is reduced by about 11%, effectively improving the dynamic performance of the mechanism. …”
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Optimization of Drying Parameters for Total Phenolic Content of Papaya Using Response Surface Methodology by Ferdusee Akter, Shireen Akther, Afroza Sultana, Md. Motiur Rahman, Ujjwal Kumar Deb

“…In order to fit the experimental data, a quadratic polynomial model is created for the output variable, and an analysis of variance is carried out to determine whether or not the model is compatible to determine the optimal drying conditions. …”
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Development and external validation of a risk prediction score (DASHI) for cardiovascular events following acute respiratory infections: derivation and validation retrospective coh... by Joseph J. Lee, Constantinos Koshiaris, Cynthia Wright-Drakesmith, Jennifer A. Davidson, Charlotte Warren-Gash, F.D. Richard Hobbs, James P. Sheppard

“…We derived two logistic regression models, one with the top ranked variables, and another including additional lower ranked variables. …”
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Optimization of ultrasound-assisted extraction of glycyrrhizic acid from licorice using response surface methodology by Seol Jang, A. Yeong Lee, A. Reum Lee, Goya Choi, Ho Kyoung Kim

“…Conclusion: The experimental values agreed with those predicted by RSM models, thus indicating the suitability of the model employed and the success of RSM in optimizing the extraction conditions. …”
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Stiffness Characteristics of High-Speed Railway Turnout and the Effect on the Dynamic Train-Turnout Interaction by Jingmang Xu, Ping Wang, Xiaochuan Ma, Yuan Gao, Rong Chen

“…Track stiffness in railway turnouts is variable due to differences in structural composition along the longitudinal direction, which will lead to severe dynamic interaction between train and turnout. …”
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The Role of Cognitive Performance in Older Europeans’ General Health: Insights from Relative Importance Analysis by Eleni Serafetinidou, Christina Parpoula

“…Participants were classified into good or poor health status, and logistic regression models assessed the predictive significance of cognitive variables on general health, supplemented by a relative importance analysis to estimate relative effect sizes. …”
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Spatiotemporal Multivariate Weather Prediction Network Based on CNN-Transformer by Ruowu Wu, Yandan Liang, Lianlei Lin, Zongwei Zhang

“…After that, in order to ensure that the model has better prediction ability for global and local hotspot areas, we designed a composite loss function based on MSE and SSIM to focus on the global and structural distribution of weather to achieve more accurate multivariate weather prediction. …”
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