Nile Red Staining for Oil Determination in Microalgal Cells: A New Insight through Statistical Modelling by Ronald Halim, Paul A. Webley

“…In its first phase, this study examined the dependence of microalgal Nile red fluorescence (Tetraselmis suecica) in terms of its most pertinent staining variables. A quadratic surface model that successfully described the Nile red fluorescence intensity as a composite function of its variables was generated (r2=0.86). …”
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Integrating observational and modelled data to advance the understanding of heat stress effects on pregnant subsistence farmers in the gambia by Carole Bouverat, Jainaba Badjie, Tida Samateh, Tida Saidy, Kris A. Murray, Andrew M. Prentice, Neil Maxwell, Andy Haines, Ana Maria Vicedo Cabrera, Ana Bonell

“…Associations between physiological and environmental variables were assessed through Pearson correlation coefficient analysis, mixed effect linear models with random intercepts per participant and confirmatory composite analysis. …”
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Numerical Modeling of the Impact of Natural Tropical Oscillations on the Amplitudes of Atmospheric Tides During Sudden Stratospheric Warming by Koval' Andrey Vladislavovich, Vargin Pavel, Gavrilov Nikolai Mihaylovich, Didenko Kseniia Andreevna, Ermakova Tatiana, Efimov Matvey Maksimovich, Sokolov Arseniy

“…In order to study the evolution of atmospheric tides, model simulations of the general atmospheric circulation were carried out using a 3-dimensional nonlinear mechanistic model “MUAM”. …”
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Establishing strength prediction models for low-carbon rubberized cementitious mortar using advanced AI tools by Fu Limei, Xu Feng

“…Rubberized cementitious composites have emerged as a sustainable alternative in the construction sector by promoting circular economy principles. …”
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Hybrid Gaussian Process Regression Models for Accurate Prediction of Carbonation-Induced Steel Corrosion in Cementitious Mortars by Teerapun Saeheaw

“…Four Gaussian Process Regression (GPR) variants were systematically developed: Baseline GPR with manual optimization, Expert Knowledge GPR employing domain-driven dual-kernel architecture, GPR with Automatic Relevance Determination (GPR-ARD) for feature selection, and GPR-OptCorrosion featuring specialized multi-component composite kernels. The models were trained and validated using 180 carbonated mortar specimens with 15 systematically categorized variables spanning mixture, material, environmental, and electrochemical parameters. …”
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The Ecological Impacts and Modeling of the Beaver Dam Distribution: A Study on Habitat Characteristics and Environmental Factors in Romania by Alexandru Gridan, Ovidiu Ionescu, Georgeta Ionescu, Ancuta Fedorca, Elena Ciocirlan, Claudiu Pașca, Darius Hardalau

“…This study aimed to (i) characterize the physical and compositional features of beaver dams in the Râul Negru basin, Romania, (ii) model the environmental variables influencing the dam distribution using MaxEnt, and (iii) evaluate the implications for broader conservation strategies. …”
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Predicting the role of socio-economic indices for the Human Development Index based on a multivariate regression model by Zainab Alimoradi, Mark D. Griffiths, Mehran Alijanzadeh

“…The multivariate regression model showed IMR and the MPI were significant predictors of HDI and explained 84.7% of variance. …”
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A validated multivariable machine learning model to predict cardio-kidney risk in diabetic kidney disease by James L. Jr. Januzzi, Naveed Sattar, Muthiah Vaduganathan, Craig A. Magaret, Rhonda F. Rhyne, Yuxi Liu, Serge Masson, Javed Butler, Michael K. Hansen

“…We sought to develop an accurate means by which to stratify risk in DKD. Methods Clinical variables and biomarkers were evaluated for their ability to predict the adjudicated primary composite endpoint of CREDENCE (Canagliflozin and Renal Events in Diabetes with Established Nephropathy Clinical Evaluation) by 3 years. …”
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A vascular endothelial cell, neuron, and microglia tri-culture model to study hypertension-related depression by Hongxia Zhao, Hongxia Zhao, Lingge Huang, Jian Liu, Min Feng, Yeqian Liu, Hong Li, Shan Gong, Chunming Chen, Shuiqing Zeng, Weiqiong Ren

“…However, in vivo animal models are often limited by the complexity of intrinsic systems, high inter-individual variability, and stringent ethical regulations. …”
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On the Nonlinear Forced Vibration of the Magnetostrictive Laminated Beam in a Complex Environment by Nicolae Herisanu, Bogdan Marinca, Vasile Marinca

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Adaptation of the process‐based CSM‐CROPGRO model to simulate the growth and development of industrial hemp for seed and fiber production by Alwin Hopf, Kenneth J. Boote, Yogendra Upadhyaya, Hardeep Singh, Michael J. Mulvaney, Navdeep Kaur, Lakesh K. Sharma, Zachary Brym, Jonathan A. Watson, Gerrit Hoogenboom

“…A seasonal analysis using the adapted model showed the impact of variable planting dates on hemp phenology, biomass, and grain production. …”
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Travel Patterns Analysis Using Tensor-Based Model from Large-Scale License Plate Recognition Data by Zhaoxin Liu, Xiaolu Wang, Yufeng Bi, Jun Kong, Run Xu, Yuanpei Chen, Jinjun Tang

“…As travel patterns are influenced by many variables, a method framework based on the tensor model is proposed to explore the influence of variables on travel characteristics. …”
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A dengue fever predicting model based on Baidu search index data and climate data in South China. by Dan Liu, Songjing Guo, Mingjun Zou, Cong Chen, Fei Deng, Zhong Xie, Sheng Hu, Liang Wu

“…Firstly, the time series dengue fever data were decomposed into seasonal, trend and remainder components by the seasonal-trend decomposition procedure based on loess (STL). Secondly, the time lag of variables was determined in cross-correlation analysis and the order of autocorrelation was estimated using autocorrelation (ACF) and partial autocorrelation functions (PACF). …”
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METHODS AND MODELS OF RESEARCH OF INVESTMENT ATTRACTIVENESS AND COMPETITIVENESS OF PROJECT-ORIENTED ENTERPRISE IN THE PROCESS OF CREATING INNOVATIVE HIGH-TECH by Oleg Fedorovich, Viktor Kosenko, Liudmyla Lutai, Iaroslav Zamirets

“…The qualitative assessments of experts for the main indicators of the component composition of the product in the form of linguistic variables are proposed. …”
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Development of a river dissolved oxygen prediction model integrating spatial effects and multiple deep learning algorithm by Yubo Zhao, Mo Chen

“…The model is benchmarked against several baselines and evaluated using RMSE, MAE, R2, and PICP, which are recorded as 0.2935, 0.2053, 0.9852, and 98.9 %, respectively—outperforming all competing models. …”
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Artificial Intelligence-Driven Approach to Optimizing Boiler Power Generation Efficiency: The Advanced Boiler Combustion Control Model by Kyu-Jeong Lee, So-Won Choi, Eul-Bum Lee

“…The by-product gases generated during steel manufacturing processes, including blast furnace gas, coke oven gas, and Linz–Donawitz gas, exhibit considerable variability in composition and supply. Consequently, achieving stable combustion control of these gases is critical for improving boiler efficiency. …”
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Advanced generalized machine learning models for predicting hydrogen–brine interfacial tension in underground hydrogen storage systems by Ahmed Farid Ibrahim

“…This study applies machine learning (ML) techniques to predict IFT between H2 and brine across various salt types, concentrations, and gas compositions. A dataset was used with variables such as temperature, pressure, brine salinity, and gas composition (H2, CH4, CO2). …”
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Improvement of the inflammation-damaged intestinal barrier and modulation of the gut microbiota in ulcerative colitis after FMT in the SHIME® model by Anna Kamlárová, Monika Kvaková, Ľuboš Ambro, René Link, Izabela Bertková, Zdenka Hertelyová, Martin Janíčko, Emília Hijová, Jana Štofilová

“…In summary, this study confirmed that a single dose of FMT beneficially modulated the composition and metabolic activity of the UC microbiota in the SHIME® model. …”
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Evaluation of long-term carbon dynamics in a drained forested peatland using the ForSAFE-Peat model by D. Escobar, D. Escobar, S. Manzoni, J. Tapasco, P. Vestin, S. Belyazid

“…Model simulations aligned well with observed groundwater levels (<span class="inline-formula"><i>R</i>²=0.78</span>) and soil temperatures (<span class="inline-formula"><i>R</i>²≥0.76</span>) and captured seasonal and annual net ecosystem production patterns, although daily variability was not always well represented. …”
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Optimization of extrusion parameters for low-cost alumina–kaolin ceramic membranes via CCD by Mahmoud Moharrami, Mohammadreza Omidkhah, Mohammad Salehi Maleh

“…These findings confirm that the RSM-based design model, incorporating porosity, average pore size, and flexural strength as response variables, is a robust tool for optimizing the fabrication of alumina-kaolin ceramic membranes. …”
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