In this study, multi-objective optimization of nanofluid aluminum oxide in a mixture of water and ethylene glycol (40:60) is studied. In order to reduce viscosity and increase thermal conductivity of nanofluids, NSGA-II algorithm is used to alter the temperature and volume fraction of nanoparticles. Neural network modeling of experimental data is used to obtain the values of viscosity and thermal conductivity on temperature and volume fraction of nanoparticles. In order to evaluate the optimization objective functions, neural network optimization is connected to NSGA-II algorithm and at any time assessment of the fitness function, the neural network model is called. Finally, Pareto Front and the corresponding optimum points are provided and introduced. Optimal results showed that the optimum viscosity and thermal conductivity occurs at maximum temperature.
Background: This study aimed to examine the efficacy of methylene blue (MB) and toluidine blue O (TBO) photodynamic therapy (PDT) as adjuncts to root surface debridement (RSD). Methods: This split-mouth, randomized, controlled clinical trial included eighteen patients, and a total of 332 sites (control = 102, MB = 124 and TBO = 106) were examined. Two sessions of PDT were completed at baseline and two weeks after RSD. Clinical parameters of bleeding on probing (BOP), plaque index (PI), probing pocket depth (PPD), and clinical attachment level (CAL) were measured pre- and post-treatment. Results: PPD and BOP reductions in sites treated by RSD with adjunctive photosensitizers (MB and TBO) were significantly higher than in control site
... Show MoreIn this paper, a cognitive system based on a nonlinear neural controller and intelligent algorithm that will guide an autonomous mobile robot during continuous path-tracking and navigate over solid obstacles with avoidance was proposed. The goal of the proposed structure is to plan and track the reference path equation for the autonomous mobile robot in the mining environment to avoid the obstacles and reach to the target position by using intelligent optimization algorithms. Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) Algorithms are used to finding the solutions of the mobile robot navigation problems in the mine by searching the optimal paths and finding the reference path equation of the optimal
... Show MoreA series of new coumarin and N-amino-2-quinolone derivatives have been synthesized. The reaction of coumarin (1) with excess of Hydrazine hydrate 98% yielded 1-amino-2-quinolone (2), Compound (2) was reacted with different Sulfonyl chloride to yield Sulfonamides [ N-(2-oxoquinolin-1(2H)-yl) methane sulfonamide (3), N-(2-oxoquinolin-1(2H)-yl) Benzene sulfonamide (4) and 4-methyl-N-(2-oxoquinolin-1(2H)-yl) benzene sulfonamide (5) ], while reaction of 2-(4-methyl-2-oxo-2H-chromen-7-yloxy) acetic acid (8) with different amines yielded compounds [ 2-(4-methyl-2-oxo-2H-chromen-7-yloxy)-N-(2-oxoquinolin-1(2H)-yl) acetamide (9) and N-(5-methyl-1,3,4-thiadiazol-2-yl)-2-(4-methyl-2-oxo-2H-chromen-7-yloxy)acetamide (10) ] th
... Show MoreThe pharmacophore 2-aminothiazole has an interesting role in pharmaceutical chemistry as this led to the synthesis of many types of compounds with diverse biological activity. Schiff base derivatives at the same time contribute to drug evolution importantly. In this review, the Schiff base derivatives of 2-aminothiazole formed and some of their metal complexes are being focused on, and the antimicrobial and anticancer activity of them is being illustrated.
The pharmacophore 2-aminothiazole has an interesting role in pharmaceutical chemistry as this led to the synthesis of many types of compounds with diverse biological activity. Schiff base derivatives at the same time contribute to drug evolution importantly. In this review, the Schiff base derivatives of 2-aminothiazole formed and some of their metal complexes are being focused on, and the antimicrobial and anticancer activity of them is being illustrated.
It is well known that drilling fluid is a key parameter for optimizing drilling operations, cleaning the hole, and managing the rig hydraulics and margins of surge and swab pressures. Although the experimental works represent valid and reliable results, they are expensive and time consuming. In contrast, continuous and regular determination of the rheological fluid properties can perform its essential functions during good construction. The aim of this study is to develop empirical models to estimate the drilling mud rheological properties of water-based fluids with less need for lab measurements. This study provides two predictive techniques, multiple regression analysis and artificial neural networks, to determine the rheological
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