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Here we investigate the irreversibility aspects in magnetohydrodynamics flow of viscous nanofluid by a variable thicked surface. Viscous dissipation, Joule heating and heat generation/absorption in energy expression is considered. Behavior of Brownian diffusion and thermophoresis are also discussed. The nanoliquid is considered electrical conducting under the behavior of magnetic field exerted transverse to the sheet. Using similarity variables the nonlinear PDEs are altered to ordinary one. The obtained system are computed through Newton built in shooting method. Significant behavior of various involving parameters on entropy generation rate, velocity, concentration, Bejan number and temperature are examined. Gradient of velocity and heat transfer rate are numerically computed through tabulated form. Velocity field is augmented versus power index (n). Temperature and velocity profiles have opposite characteristics for larger approximation of Hartmann number. Concentration profile has similar impact against Brownian diffusion variable and Lewis number. Entropy optimization is boost up via rising values of Brinkman and Hartmann numbers. Bejan number is declined for increasing value of Hartmann number.

Here we investigate the irreversibility aspects in magnetohydrodynamics flow of viscous nanofluid by a variable thicked surface. Viscous dissipation, Joule heating and heat generation/absorption in energy expression is considered. Behavior of Brownian diffusion and thermophoresis are also discussed. The nanoliquid is considered electrical conducting under the behavior of magnetic field exerted transverse to the sheet. Using similarity variables the nonlinear PDEs are altered to ordinary one. The obtained system are computed through Newton built in shooting method. Significant behavior of various involving parameters on entropy generation rate, velocity, concentration, Bejan number and temperature are examined. Gradient of velocity and heat transfer rate are numerically computed through tabulated form. Velocity field is augmented versus power index (n). Temperature and velocity profiles have opposite characteristics for larger approximation of Hartmann number. Concentration profile has similar impact against Brownian diffusion variable and Lewis number. Entropy optimization is boost up via rising values of Brinkman and Hartmann numbers. Bejan number is declined for increasing value of Hartmann number.

Acute ingestion of ethanol impairs memory, an effect which might be related to ethanol-induced inhibition of vasopressin release. This was studied using tests of memory and cognitive function in 26 normal subjects before and after ethanol ingestion. Equal numbers of subjects received randomly, by double-blind intranasal administration, placebo or 1-desamino-8-D-arginine vasopressin prior to ethanol ingestion. Administration of the vasopressin analog did not reverse the ethanol-induced deficits in memory and cognitive function.

Acute ingestion of ethanol impairs memory, an effect which might be related to ethanol-induced inhibition of vasopressin release. This was studied using tests of memory and cognitive function in 26 normal subjects before and after ethanol ingestion. Equal numbers of subjects received randomly, by double-blind intranasal administration, placebo or 1-desamino-8-D-arginine vasopressin prior to ethanol ingestion. Administration of the vasopressin analog did not reverse the ethanol-induced deficits in memory and cognitive function.

Abstract In designing a parallel resonant induction heating system, selecting a suitable capacitor for its parallel circuit is very important. To properly select this capacitor, several solutions have been proposed such as using Lagrange method, standard bacterial foraging and genetic algorithms. Although some of these methods have been performed well, they have not considered either some restrictions or a multi-objective function in their design. To obtain an optimal value for the capacitor, this paper utilizes a bio-inspired optimization method called smart bacterial foraging algorithm (SBFA). SBFA is modeled based upon the foraging behavior of bacteria including the individual and social intelligences. SBFA uses a multi-objective optimization function including efficiency, power output and difference between power loss and output by taking the voltage and resonant frequency limitations into consideration. In order to demonstrate the efficiency and performance of the proposed approach, this paper simulates it using MATLAB. Then, the simulation results are compared with two existing algorithms: standard bacterial foraging and genetic algorithms. Based upon the results, SBFA is outperformed in comparison with the aforementioned algorithms in selecting the optimum capacitance. Results point to the fact that there can be different resonant frequencies with respect to the different capacitances of the heater as well as that for one of these frequencies the objective function has a minimum value. In addition, findings show a Pareto-Efficient situation for efficiency and power output value in an induction heating system.

Abstract In designing a parallel resonant induction heating system, selecting a suitable capacitor for its parallel circuit is very important. To properly select this capacitor, several solutions have been proposed such as using Lagrange method, standard bacterial foraging and genetic algorithms. Although some of these methods have been performed well, they have not considered either some restrictions or a multi-objective function in their design. To obtain an optimal value for the capacitor, this paper utilizes a bio-inspired optimization method called smart bacterial foraging algorithm (SBFA). SBFA is modeled based upon the foraging behavior of bacteria including the individual and social intelligences. SBFA uses a multi-objective optimization function including efficiency, power output and difference between power loss and output by taking the voltage and resonant frequency limitations into consideration. In order to demonstrate the efficiency and performance of the proposed approach, this paper simulates it using MATLAB. Then, the simulation results are compared with two existing algorithms: standard bacterial foraging and genetic algorithms. Based upon the results, SBFA is outperformed in comparison with the aforementioned algorithms in selecting the optimum capacitance. Results point to the fact that there can be different resonant frequencies with respect to the different capacitances of the heater as well as that for one of these frequencies the objective function has a minimum value. In addition, findings show a Pareto-Efficient situation for efficiency and power output value in an induction heating system.

Adaptive transparent system (ATS) is an aspiring and effective building system that can adapt itself through environmental changes in spontaneous and reversible ways. It proposes an automatic and real-time response to indoor and outdoor conditions by increasing building energy efficiency and user comfort. This research presents a critical analysis to provide a preference order of the smart materials being used in the adaptive transparent systems. The approach of using smart material technologies in the building façades is discussed as the promising research direction for the future. A comprehensive literature review is conducted to identify the smart materials used in adaptive transparent systems along with their properties. Seven types of smart materials that are aerogel (AG), phase change material (PCM), photovoltaic (PV), electrochromic (EC), thermo-chromic (TC), thermo-tropic (TT), and liquid crystal polymers (LCP) are selected based on evaluation criteria determined by the literature. The identified criteria are bulk density (BD), thermal conductivity (TCd), sound insolation (SI), fire retardation (FR), heat transfer coefficient (HTC), solar transmittance (ST), air purification (AP), annual energy saving (AES), cost saving (CS), ultraviolet (UV)/near infrared (NIR) control (UNC), and embodied carbon (EC). The identified seven smart materials are investigated with the help of two multi-criteria decision-making (MCDM) techniques named analytical hierarchical process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) for analysis and ranking of materials. Results of the analysis demonstrate that PV is the most optimum material for adaptive transparent systems while others are ranked according to their performance.

Adaptive transparent system (ATS) is an aspiring and effective building system that can adapt itself through environmental changes in spontaneous and reversible ways. It proposes an automatic and real-time response to indoor and outdoor conditions by increasing building energy efficiency and user comfort. This research presents a critical analysis to provide a preference order of the smart materials being used in the adaptive transparent systems. The approach of using smart material technologies in the building façades is discussed as the promising research direction for the future. A comprehensive literature review is conducted to identify the smart materials used in adaptive transparent systems along with their properties. Seven types of smart materials that are aerogel (AG), phase change material (PCM), photovoltaic (PV), electrochromic (EC), thermo-chromic (TC), thermo-tropic (TT), and liquid crystal polymers (LCP) are selected based on evaluation criteria determined by the literature. The identified criteria are bulk density (BD), thermal conductivity (TCd), sound insolation (SI), fire retardation (FR), heat transfer coefficient (HTC), solar transmittance (ST), air purification (AP), annual energy saving (AES), cost saving (CS), ultraviolet (UV)/near infrared (NIR) control (UNC), and embodied carbon (EC). The identified seven smart materials are investigated with the help of two multi-criteria decision-making (MCDM) techniques named analytical hierarchical process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) for analysis and ranking of materials. Results of the analysis demonstrate that PV is the most optimum material for adaptive transparent systems while others are ranked according to their performance.

Abstract This study presents an overview of footprints as defined indicators that can be used to measure sustainability. An overview of the definitions and units of measurement associated with environmental, social, and economic footprints is important because the definitions of footprints vary and are often expressed unclearly. Composite footprints combining two or more individual footprints are also assessed. These combinations produce multi-objective optimisation problems. Several tools for footprint(s)' evaluation are presented, including some of the numerous carbon footprint calculators, available calculators for other footprints, some ecological footprints-based, graph-based, and mathematical programming tools. A comprehensive overview is offered of footprint-based sustainability assessment.