Analysis the Impact of Covid-19 on Green Accounting and Its Implications on Profitability by Reschiwati Reschiwati, Fran Sayekti, Tasia Veronica

“…The next difference is that the Performance and Environmental Disclosure variables function as both Y variables and X variables (intervening). …”
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Entropy analysis of MHD hybrid nanofluid in a rotating channel filled with porous material by Emaline Joseph Ndelwa, Michael Hamza Mkwizu, Alex Xavery Matofali, Ahmada Omar Ali

“…In addition, the increase of rotational parameter has been found to reduce skin friction to the greatest extent. These findings underscore the potential of hybrid nanofluids in optimizing thermal systems by reducing entropy generation and enhancing heat transfer efficiency.…”
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Implications of thermal stratification and radiative heat flux in blood-based ternary and dihybrid nanomaterial flow through a stretchable cylinder by Muzher Saleem, Ghada A. Khouqeer, Fazal Haq, Naglaa AbdelAll, Arshad Hussain, Mohammed Sallah

“…Non-dimensional mathematical model representing the physical phenomenon is solved through NDSolve function of Mathematica. Behavior of micropolar THNF and HNF velocity and thermal field versus influential variables are investigated. …”
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Impact of viscous dissipation, chemical reaction over a Carreau hybrid nanofluids flow across a permeable curved Riga surface by R. Mahesh, U.S. Mahabaleshwar, Basma Souayeh

“…The current work examines the significant impact of Carreau hybrid nanofluid, particularly in enhancing thermal conductivity and heat transfer efficiency, which is discussed through the integration of aluminium oxide (Al2O3) and titanium dioxide (TiO2) nanoparticles into a base fluid made of 50 % water and 50 % ethylene glycol solution. …”
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GDP per capita vs foreign direct investment: key drivers of a country's technological leadership by Aleksy Kwilinski

“…A true fixed-effects stochastic frontier model was applied to panel data, based on the Cobb-Doug- las production function and the translogarithmic function, to evaluate the determinants of technological development and identify technical efficiency. …”
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Transfer Robustness Optimization for Urban Rail Transit Timetables by Liqiao Ning, Peng Zhao, Wenkai Xu, Ke Qiao

“…Next, to improve the computational efficiency, we propose an approximate linearization approach for the EETC function and introduce two types of binary variables and auxiliary substitution variables to convert the nonlinear model to a mixed-integer linear model. …”
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Analysis of heat transfer in Casson fluid flow due to aligned flat plate with leading edge accretion and slip boundary conditions by Jaganathan Jayaprakash, Vediyappan Govindan, Haewon Byeon

“…This comparative study shows that non-Newtonian fluids improve heat retention, thermal stability, and energy efficiency. They enhance solutal mixing, reduce fouling, lower surface friction, and improve flow control, making them ideal for industrial applications. …”
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Jointed rock slope stability evaluation based on PEM-JFEM method by XIAO Shu, WU Shun-chuan, GAO Yong-tao, HAN Guang, ZHOU Yu, CHENG Ai-ping

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Cálculo de la fuerza de fricción necesaria para extraer el coque de hornos solera para el diseño de prototipos de máquinas de empuje by Oscar Manuel Duque Suarez, Marco José Duarte Márquez, Leopoldo Valero Jaimes, Elio Alarcón Suarez, Sergio Andres Davila Sepulveda

“…An experimental validation was performed using a proposed methodology to calculate the force required by the motor to extract coke, based on variables such as voltage, amperage, efficiency, and power factor. …”
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Optimal Control Problem of Converter Steelmaking Production Process Based on Operation Optimization Method by Jun Zhang

“…The optimal control indicator is determined via current state of converter smelting production process, and the set values of operation variable would control converter production. Relationship between various operating variables, current temperature, and carbon content is constructed through operation analysis of a great deal of actual production data; then, the dynamic optimal control indicator is derived from historical excellent smelting data; finally, the dynamic operation optimization model is built by taking the minimum deviation between the current data—molten steel temperature and carbon content—and optimal data which are determined by the optimal control indicator as objective function. …”
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Assessing the Effectiveness of DL-Clustering for Energy Optimization in Wireless Sensor Networks by Shailaja S. Halli, Poornima G Patil

“…Determining the fitness function allows us to estimate the player's stability over these variables. …”
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Estimation of micro-extraction process hippuric acid for toluene exposure monitoring in urine samples by Behnaz Sarani, Mashaallah Rahmani, Ahmad Reza Abbasian

“…The independent variables for the micro-extraction process of hippuric acid were examined, while the response from the HA monitoring acted as the dependent variable. …”
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Analysis of the Influence of Tension on the Fluctuation of iMCVT by Feng Nenglian, Huang Hongyin, Wang Xiaofeng, Chen Longke, Zhang Xingyu

“…The Innovative Movable-teeth CVT（ iMCVT） is a new type of non-friction continuously variable transmission,in the process of transmission,there will be fluctuations in rotational speed and torque. …”
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Domain knowledge-driven decomposition-based large-scale optimization for ship cabin structures by Puyu JIANG, Jun LIU, Qiangjun LUO, Yuansheng CHENG

“…Each girder size variable is separately grouped, and the corresponding subproblem's objective function is the weight of the cabin structure. …”
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Thermal performance prediction of a V-trough solar water heater with a modified twisted tape using ANFIS, G.L.R., R.T. and SVM models of machine learning by A. Saravanan, S. Rama Sree, M. Sreenivasa Reddy, Elumalai PV, Krishnasamy Karthik, Ashok Kumar Cheeli, Nasim Hasan

“…The dependent variables in this study are the Nusselt number (Nu), friction factor (FF), and efficiency (η). 130 datasets were chosen for training purposes, while 32 were used for testing. …”
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Pareto Optimal Solutions for Stochastic Dynamic Programming Problems via Monte Carlo Simulation by R. T. N. Cardoso, R. H. C. Takahashi, F. R. B. Cruz

“…Instead of using the expected values of the objective function, the randomness nature of the decision variables is kept along the process, while Pareto fronts weighted by all quantiles of the objective function are determined. …”
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Comparison and System Development of a Two-Coil and Three-Coil Inductive Link for Transcutaneous Power Transfer by Maarten Schelles, Ward Lievens, Laurens Goyvaerts, Frederik Ceyssens, Rikky Muller, Michael Kraft

“…For devices with a relatively high power consumption and located right under the skin, wireless power transfer through an inductive link is the most reliable method to ensure robust and long-term functionality. However, the efficiency of these inductive links highly depends on the size, location and variable power consumption of the implant. …”
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The Influence of Wind Speed on Pneumatic Conveying Characteristics of Solid Feed in Horizontal Pipe by Simulation and Experiment by Chengming Wang, Shihui Jiao, Zhuoyao Wang, Pengfei Guo, Hao Ma, Baojun Li, Weiwei Zhang, Wei Lv, Xingyuan Fu, Shuaihao Wang, Chenkai Dong, Ge Guo, Hongyang Wang

“…The results show that when the conveying wind speed increases from 18 m/s to 20.6 m/s, the solid feed changes from sedimentary flow to suspended flow, the particle accumulation gradually decreases and the conveying efficiency is significantly improved. The particle slug greatly reduces the collision and friction between the internal particles and the pipe and reduces the crushing rate to a certain extent. …”
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Evaluation of Multiparameter Likelihoods through Iteration of Two-dimensional Slices by Joel S. Jayson

“…Markov Chain Monte Carlo (MCMC) computation has been the dominant instrument for evaluating multiparameter functions. For applications with a quasi-linear variable such as, A _s , the 2D iterative method is orders of magnitude more efficient than MCMC.…”
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Analysis Method of Agricultural Total Factor Productivity Based on Stochastic Block Model (SBM) and Machine Learning by Yanzi Li, Cai Chen, Fuqiang Liu, Jian Wang

“…It uses the SBM direction distance function and the Luenberger productivity index to measure the agricultural efficiency, total factor productivity, and their components. …”
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