Optimization of Candida rugosa lipase immobilization parameters on magnetic silica aerogel using adsorption method by Jafarsadegh Moghaddas, Leila Amirkhani, Hoda Jafarizadeh- Malmiri

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Three-Dimensional Imaging of High-Contrast Subsurface Anomalies: Composite Model-Constrained Dual-Parameter Full-Waveform Inversion for GPR by Siyuan Ding, Deshan Feng, Xun Wang, Tianxiao Yu, Shuo Liu, Mengchen Yang

“…However, full-waveform inversion (FWI) for GPR data struggles to simultaneously reconstruct high-resolution 3D images of both permittivity and conductivity models. Considering the magnitude and sensitivity disparities of the model parameters in the inversion of GPR data, this study proposes a 3D dual-parameter FWI algorithm for GPR with a composite model constraint strategy. …”
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Mechanical behavior of SiC reinforced ZA63 Mg matrix composites: Experiments and 3D finite element modelling by Chong Wang, Zelong Du, Enyu Guo, Shuying Bai, Zongning Chen, Huijun Kang, Guohao Du, Yanling Xue, Tongmin Wang

“…In this work, the microstructure evolution and mechanical behavior of extruded SiC/ZA63 Mg matrix composites are investigated via combined experimental study and three-dimensional finite element modelling (3D FEM) based on the actual 3D microstructure achieved by synchrotron tomography. …”
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Sustained release biodegradable solid lipid microparticles: Formulation, evaluation and statistical optimization by response surface methodology by Hanif Muhammad, Khan Hafeez Ullah, Afzal Samina, Mahmood Asif, Maheen Safirah, Afzal Khurram, Iqbal Nabila, Andleeb Mehwish, Abbas Nazar

“…The optimized SLMs have the potential to improve nebivolol oral bioavailability.…”
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Molecular dynamics simulation and flame-retardant characterization of steel slag powder-modified styrene-butadiene rubber composites by Zhifang ZONG, Jianwen PENG, Xiaojian REN, Tianci GAO, Wenjing ZHANG, Ling ZHAO, Yurong XIA, Hao ZHANG, Yong JIA

“…The compatibility of SSP–CB/SBR is fundamental to the development of multi-component composites. In this study, molecular dynamics simulations were used to construct a steel slag-SBR interfacial model and assess the interfacial compatibility of the two components. …”
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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

“…This study developed the advanced boiler combustion control model (ABCCM) by combining the random forest (RF) and classification and regression tree (CART) algorithms to optimize the combustion of steam power boilers using steel by-product gases. …”
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Coexisting arsenate and arsenite adsorption from water using porous pellet adsorbent: Optimization by response surface methodology by B. Te, B. Wichitsathian, C. Yossapol, W. Wonglertarak

“…Central composite design under response surface methodology was applied for optimizing and observing both individual and interactive effects of four main influential adsorption factors such as contact time (24-72 h), initial solution pH (3-11), adsorbent dosage (0-20 g/L) and initial adsorbate concentration (0.25-4.25 mg/L). …”
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Optimization of Protein Extraction from Sunflower Meal Using Taguchi Design and Regression Modeling for Human Nutrition Applications by Anca Becze, Marin Senila, Lacrimioara Senila, Lucian Dordai, Oana Cadar, Vanda Liliana Fuss-Babalau, Marius Roman, Levente Levei, Paul Uiuiu, Mihai Octavian Naghiu

“…A first-order regression model was developed and validated (R² = 0.86, <i>p</i> < 0.05), identifying optimal conditions at pH 10.0, 30 °C, and 60 g per 500 mL of distilled water. …”
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An Investigation on Three-Point Bending of Foam-Filled Double Tubes and Parameter Optimization Using Response Surface Methodology by Abdolvahed Kami, Javad Shahbazi Karami

“…Finally, RSM was used to compute the best values of the parameters that result in the maximum energy absorption in bending and the lightest weight of the FFD tube. The optimization process resulted in a 141.4% increase in absorbed bending energy and a 4.63% reduction in the FFD composite tube's weight (in comparison to the initial design of the FFD tube).…”
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THERMODYNAMIC MODELING OF PHYSICAL AND CHEMICAL PROCESSES AND OPTIMIZATION OF THE TECHNOLOGY OF PLASMA COVERINGS OF THE MECHANICALLY ALLOYED THERMO-REACTIVE POWDERS by F. G. Lovshenko, G. F. Lovshenko, B. B. Hina, Z. M. Lovshenko, A. S. Fedosenko

“…Data of thermodynamic modeling of balanced structure of powders of the mechanically alloyed thermo-reactive compositions, dependences of powders heating and structure of coverings on temperature of plasma stream, and also the results of optimization of spatter process are given.…”
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Modeling and Solving the Knapsack Problem with a Multi-Objective Equilibrium Optimizer Algorithm Based on Weighted Congestion Distance by Ziqian Wang, Xin Huang, Yan Zhang, Danju Lv, Wei Li, Zhicheng Zhu, Jian’e Dong

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Process Optimization and Mathematical Modeling of Cartridge Filter Cleanup Using Pulse Jet Air Ring (PJAR) Technology by Abdolreza Ansari, Alireza Pardakhti, Naser Mehrdadi

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Optimization Design of Body-in-White Stiffness Test Rig Based on the Global Adaptive Algorithm of the Hybrid Element Model by Zhaohui Hu, Shuai Mo, Huang Liu, Fuhao Mo

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Optimized Design and Test of Geometrically Nonlinear Static Aeroelasticity Model for High-Speed High-Aspect-Ratio Wing by Xing Li, Wei Qian, Ling Xiao, Xinyu Ai, Jun Liu

“…In this study, in order to study the static aeroelastic characteristics of the transonic flow of a high-aspect-ratio airfoil, a new design method of the scaled similar optimization model is described, and the change in the model lift coefficient due to geometrically nonlinear static aeroelasticity effects when the angle of attack is changed was investigated by using simulation and wind tunnel test methods. …”
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Effect of horizontal shift between fabric layers on the meso-scale-void formation in liquid composite molding by B. Yang, C. Y. Zhao, F. Y. Bi, S. B. Wang, C. Ma, S. L. Wang

“…Accurate prediction of void content is the foundation of process optimization for Liquid Composite Molding (LCM). During mold filling, void formation is a three-dimensional flow process, while at present the void formation is treated as a result of in-plane air entrapment, the resin and air flows on the thickness direction are totally neglected. …”
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MATHEMATICAL MODELING OF OAT BISCUITS FORMULA ENRICHED WITH PRODUCTS OF TOPINAMBUR PROCESSING by N. T. Shamkova, M. Y. Tamova, A. A. Varivoda, N. S. Shelest

“…The disadvantage of oat biscuits as well as wheat flour cookies, is the imbalance in micronutrient composition against the background of high energy value and sugar content. …”
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Seed Protein Content Estimation with Bench-Top Hyperspectral Imaging and Attentive Convolutional Neural Network Models by Imran Said, Vasit Sagan, Kyle T. Peterson, Haireti Alifu, Abuduwanli Maiwulanjiang, Abby Stylianou, Omar Al Akkad, Supria Sarkar, Noor Al Shakarji

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Modelling of Separation and Air Classification Processes of Aerodisperse Systems in the Shelving Device by Varukha D. A., Smirnov V. А., Edl M., Demianenko M. M., Yukhymenko M. P., Pavlenko I. V., Liaposhchenko O. O.

“…Based on the obtained data as a result of numerical modelling, the possibility of increasing gas flow influence to the polydispersed material were found, as well as organization along the walls of coarse fraction downward flow by dint of the optimizing the devise design (specifically through the organization of additional inlets for airflow) were obtained.…”
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Spatiotemporal Land Use Change Detection Through Automated Sampling and Multi-Feature Composite Analysis: A Case Study of the Ebinur Lake Basin by Yi Yang, Liang Zhao, Ya Guo, Shihua Liu, Xiang Qin, Yixiao Li, Xiaoqiong Jiang

“…This study proposes an innovative technical framework that integrates automated sample generation, multi-feature optimization, and classification model refinement to enhance the accuracy of land use classification and enable detailed spatiotemporal analysis in the Ebinur Lake Basin. …”
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A mineral-strength conversion model based on LIBS technology and rapid batch testing and application of uniaxial compressive strength by Qinghe ZHANG, Xiaorui WANG, Chuanbing WANG, Weiguo LI, Fengqiang GONG, Xinsheng ZHANG, Jingguo LI

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