Designing an entrepreneurial ecosystem model in a university with a knowledge-based approach by Nahid Mir, Amin Rahimi Kia, Mehry Daraei

“…The results in the qualitative part showed that 67 primary codes, 11 basic themes, and 5 constructive themes are identified in most infrastructure and support clusters (2 themes), integration of technology and knowledge (2 themes), education and culture (3 themes), policy and planning. (2 themes), and integrated management (2 themes); and relationships between them were drawn and presented in the form of a paradigmatic model. The results of the quantitative part showed that 5 indicators and 11 components with factor load, average extracted variance, and convergent validity are higher than (0.4), Cronbach's alpha coefficient and composite reliability are higher than (0.7), significant t coefficients is higher than (1.96); all were confirmed, and the model has a strong fit.ConclusionThe purpose of this research was to design an entrepreneurship ecosystem model in a university. …”
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Integrated neural network and AspenPlus model for entrained flow gasification kinetics investigation by Balaban Dario, Lubura Jelena, Kojić Predrag

“…The obtained results were used in ANN development for each output variable (syngas composition, efficiency, heating value, and carbon conversion). …”
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Quantitative control of interfacial structure and thermal conductivity between diamond and copper via thermal diffusion of alloying element by Yizhe Cao, Bo Li, Lei Liu, Shaolong Li, Dongxu Hui, Shaodi Wang, Huiying Liu, Xin Li, Xin Zhang, Shengyin Zhou, Shufeng Li

“…Here, systematic experiments of diamond/Cu–Cr composites have been conducted to unravel the effects of two important variables for thermal diffusion, temperature (800–1025 °C) and holding time (5–60 min), on the growth of chromium carbide interfaces and the resulting thermal conductivity. …”
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Research on real time measurement model and measurement system for gas concentration in extraction drilling by Dayang Yu, Junhao Zhu, Xing Li, An He, Huaiqian Liu, Changjiang Chen, Yong Liu

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Complex system modeling reveals oxalate homeostasis is driven by diverse oxalate-degrading bacteria by Sromona D Mukherjee, Carlos Batagello, Ava Adler, Jose Agudelo, Anna Zampini, Mangesh Suryavanshi, Andrew Nguyen, Terry Orr, Denise Dearing, Manoj Monga, Aaron W Miller

“…Using multiple, independent molecular, rodent, and in vitro experimental models, we found that microbiome composition influenced multiple oxalate-microbe-host interfaces. …”
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MATHEMATICAL MODELS OF CREATION OF A SUBSYSTEM OF ENSURING SAFETY OF INFORMATION IN THE DISTRIBUTED INFORMATION SYSTEMS by D. O. Esikov, R. N. Akinshin, P. I. Abramov, L. E. Loutina

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Advanced machine learning models for the prediction of ceramic tiles’ properties during the firing stage by V. Vasic, Milica, Awoyera, Paul O., Fadugba, Oladlu George, Barisic, Ivana, Nettinger Grubeša, Ivanka

“…A robust dataset of 312 ceramic samples was analyzed, including variables such as particle size distribution, chemical and mineralogical composition, and firing temperatures ranging from 1000 to 1300 °C. …”
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Presenting the model of managerial competencies of women in the industry (case study: Sabah Food Company) by masoomeh samadi, mohammad mohammadi, Hamid Rezaei Far, hossein hakimpour

“…Abstract The purpose of this research is to provide a model of managerial competencies of women in the industry (case study: Sabah Food Company). …”
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Modeling biogeochemical processes in the Azov Sea using statistically processed data on river flow by A. I. Sukhinov, Y. V. Belova, A. V. Nikitina, A. M. Atayan

“…River flow, varying in volume and chemical composition, affects significantly the variability of hydrophysical and biogeochemical parameters of the processes occurring in the coastal environment. …”
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Predictive Modeling of Functional and Physical Properties of Extrusion Cooked Ready-To-Eat Corn Meal by Adeyemi Adio Aderele, Adewumi Babatunde, Adeniyi Olayanju, Adekojo Waheed

“…A second-degree polynomial equation was fitted for each response variable as a function of extrusion cooking process factors. …”
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Modeling the Production Process of Lignin Nanoparticles Through Anti-Solvent Precipitation for Properties Prediction by Victor Girard, Laurent Marchal-Heussler, Hubert Chapuis, Nicolas Brosse, Nadia Canilho, Isabelle Ziegler-Devin

“…Using first a parametric and then a Fractional Factorial Design, predictions of LNP sizes and size distribution, as well as zeta-potential, were derived from a model over beech by-products organosolv lignin, depending on initial lignin concentration (x₁, g/L), solvent flow rate (x₂, mL/min), antisolvent composition (x₃, H2O/EtOH <i>v</i>/<i>v</i>), antisolvent ratio (x₄, solvent/antisolvent <i>v</i>/<i>v</i>), and antisolvent stirring speed (x₅, rpm). …”
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Assessing the multi-scale predictive ability of ecosystem functional attributes for species distribution modelling. by Salvador Arenas-Castro, João Gonçalves, Paulo Alves, Domingo Alcaraz-Segura, João P Honrado

“…Here we describe a modelling framework to assess the predictive ability of EFAs as Essential Biodiversity Variables (EBVs) against traditional datasets (climate, land-cover) at several scales. …”
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Non-linear association of a novel inflammation-lipid composite marker CRP/HDL with insulin resistance and type 2 diabetes: findings from a comprehensive national cross-sectional st... by Kun Xue, Meijun Sun, Chao Zong, Shanshan Xing, Hang Xue

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Designing model of place branding based on brand attachment (Kish Island case study) by khadigeh Ghaemmaghami Tabrizi, Asghar Moshabaki Esfahaniَ, Abdolah Naami, Naser Azad

“…Qualitative data were analyzed by Maxqda software. Using extracted Variables for designing the questionnaire and gathering data from tourism by Simple Random Sample and quantitative data analyzed by Structural Equation Modeling by SMART-PLS. …”
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Application of RSM- CCD methodology and image J. for modeling and optimization of orchid protocorm encapsulation by Zahra Mahdavi, Shirin Dianati Daylami, Ali Fadavi, Mandana Mahfeli

“…A device was designed to control the dripping of alginate for a given temperature in order to wrap the protocorm. The central composite design has been used to investigate the effect of encapsulation variables on the physical properties of orchid synthetic seed such as volume, sphericity Index (SI) and Concentricity Index (CI). …”
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Modeling the Higher Heating Value of Spanish Biomass via Neural Networks and Analytical Equations by Anbarasan Jayapal, Fernando Ordonez Morales, Muhammad Ishtiaq, Se Yun Kim, Nagireddy Gari Subba Reddy

“…The optimized ANN achieved strong predictive accuracy (validation R² ≈ 0.81; mean squared error ≈ 1.33 MJ/kg; MAE ≈ 0.77 MJ/kg), representing a substantial improvement over 54 analytical models despite the known complexity and variability of biomass composition. …”
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Evaluating the Wound Healing Activity of Fabricated Stingless Bee Honey Hydrogels in an Animal Model by Mohd Azri Abd Jalil, Hazrina Hadi, Muhammad Lokman Md Isa, Umar Azhan, Kamarul Ariffin Khalid, Md Abul Barkat

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THE COMPATIBILITY OF MODEL FOR LOW SHEAR FLOW ANALYSIS IN DEVELOPING PLASTICIZED HTPB-BASED BINDER by Afni Restasari, Luthfia Hajar Abdillah, Retno Ardianingsih, Bagus Wicaksono, Rika Suwana Budi

“…In developing flow behavior of plasticized prepolymer as liquid content of composite solid propellant, zero shear viscosity (ZSV) is a critical parameter that Goh-Wan equation is developed to model it recently [1]. …”
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Design of bond strength testing method of concrete layers for creating a material model by Marek Kříž, Michaela Frantová, Václav Wudi, Petr Štemberk

“… The need to determine the bond strength of concrete layers in structural modeling is quite frequent and often encounters a lack of relevant experimental data due to the large number of variables which affect the bond strength. …”
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Label dependency modeling in Multi-Label Naïve Bayes through input space expansion by PKA Chitra, Saravana Balaji Balasubramanian, Omar Khattab, Mhd Omar Al-Kadri

“…The innovation of improved multi-label Naïve Bayes (iMLNB) lies in its strategic expansion of the input space, which assimilates meta information derived from the label space, thereby engendering a composite input domain that encompasses both continuous and categorical variables. …”
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