Magnetic Mixed Hemimicelles Solid-Phase Extraction of Three Food Colorants from Real Samples

Introducing a specific clean extraction procedure with a minimal matrices effect for food colorant determination is still a challengeable topic and highly recommended. Mixed hemimicelle solid-phase extraction method, based on cetyltrimethylammonium bromide-coated Fe₃O₄/SiO₂ nanoparticles as a novel, simple, and fast preconcentration method, was applied for preconcentration and fast isolation of three synthetic food colorants in foodstuff matrices prior to HPLC-UV-vis determination. The influence of different parameters on extraction efficiency such as surfactant amount, sample pH, time of extraction, desorption condition, and nanoparticles concentration was optimized. Under the optimized conditions, a preconcentration factor of 100 was achieved by extracting 10 mL sample. The limit of detection for the three synthetic food colorants including Tartrazine, Sunset yellow FCF, and Quinoline yellow is 2.50, 1.25, and 2.12 μg/L, respectively. The proposed method was applicable for extraction and preconcentration of three food colorants in various food samples with the food dye contents in the range of 13–105 μg/L.     

Modeling metallurgical responses of coal Tri-Flo separators by a novel BNN:a "Conscious-Lab" development

Tri-flo cyclone,as a dense-medium separation device,is one of the most typical environmentally friendly industrial techniques in the coal washery plants.Surpris...     

Fluid Flow and Mixing in Non-Isothermal Water Model of Continuous Casting Tundish

Fluid flow and mixing of molten steel in a twin-slab-strand continuous casting tundish were investigated using a mixing model under non-isothermal conditions.This model led to a set of ordinary differential equations that were solved with a Runge-Kutta algorithm.Steady state water modeling was carried out under non-isothermal conditions.Experimental data obtained from the water model were used to calibrate the mixing model.Owing to the presence of a mixed convection in the non-isothermal conditions,a channelizing flow would be created in the fluid inside the tundish.A mixing model was designed that was capable of predicting RTD（residence time distribution）curves for different cases in non-isothermal conditions.The relationship between RTD parameters and the Tu（tundish Richardson number）was obtained for various cases under non-isothermal conditions.The results show that the RTD parameters were completely different under isothermal and non-isothermal conditions.The comparison of the RTD curves between the isothermal and non-isothermal conditions presents that the extent of mixing in the tundish in non-isothermal conditions is lower than the mixing extent in isothermal conditions.     

A Sliding Mode Controller Based on Robust Model Reference Adaptive Proportional-integral Control for Stand-alone Three-phase Inverter

This paper proposes a sliding mode controller based on robust model reference adaptive proportional-integral (RMRA-PI) control for a stand-alone voltage source inverter (SA-VSI). The proposed controller has two control loops where the coefficients of PI controller are regulated by the adaptive sliding law. This method is used to regulate the output voltage of the inverter under different load conditions and uncertainty, and adapts the output to the reference model to reduce the total harmonic distortion (THD). In this paper, the stability of the proposed controller is proven by using Lyapunov’s theory and Barbalet’s lemma. The proposed controller performs well in voltage regulation such as low THD under sudden load change and uncertainty. Also, the results of the proposed controller are compared with PI controller to show the effectiveness of the presented control system.     

Using correlation coefficients for locating partial discharge in power transformer

Most serious failure of power transformers is due to the insulation breakdown. Partial discharge (PD) that damages insulation by gradual erosion is major source of insulation failure. The effective ability of the wavelet packets analysis as a tool for disk-to-disk partial discharge faults detection and localization in transformer windings is shown in this paper. Techniques for locating a PD source are of the major importance in both the maintenance and repair of a transformer. One of the most well-known methods of PD localization in transformers is based on winding modeling and current of neutral point analysis. Since the impedance between PD location and neutral point of winding depends on the PD location in respect to neutral point, the frequency spectrum of neutral point current varies when the PD location changes. In the other word, the current components of neutral points vary according to the place where PD occurs. So in this paper, detailed model of transformer winding is modeled and the neutral point current is studied for locating PD. The used method is validated by the simulated model of transformer windings. This model produces a very acceptable current when compared to the experimental data. In this paper for locating partial discharge (PD) in transformer windings, a simulated model is developed for the transformer winding and the PD phenomenon mechanism. The impulse current test and wavelet packets transformation are used to locate PD. It is shown that the neutral current measurement of the transformer winding has useful information about PD location.     

Isogeometric level set topology optimization for elastoplastic plane stress problems

International Journal of Mechanics and Materials in Design - This article aims to utilize IsoGeometric analysis (IGA) and Level set method for topology optimization of elastoplastic plane stress...     

Non-prespecified Starting Depot Formulations for Minimum-Distance Trajectory Optimization in Patrolling Problem

In this paper, two new formulations are presented for trajectory optimization in the patrolling problem. It is assumed that the starting depot is not prespecified; an assumption that distinguishes the present work from the existing literature. A number of viewpoints are assigned to be visited in a certain sequence to minimize the total travel distance. The problem turns out to be a variant of the well-known Traveling Salesmen Problem (TSP), namely the Single depot multiple Traveling Salesmen Problem (mTSP). Comparisons between the commonly-used prespecified starting depot approach and the proposed formulations are performed and the efficacy of the results is presented through simulations. It is noted that by using the new approach, the total travel distance can be improved by an average of about 20 % compared to the case where the starting depot is prespecified, and by about 40 % in the worst-case scenario (in terms of the starting depot).     

CCFinder: using Spark to find clustering coefficient in big graphs

Networks with billions of vertices introduce new challenges to perform graph analysis in a reasonable time. Clustering coefficient is an important analytical measure of networks such as social networks and biological networks. To compute clustering coefficient in big graphs, existing distributed algorithms suffer from low efficiency such that they may fail due to demanding lots of memory, or even, if they complete successfully, their execution time is not acceptable for real-world applications. We present a distributed MapReduce-based algorithm, called CCFinder, to efficiently compute clustering coefficient in very big graphs. CCFinder is executed on Apache Spark, a scalable data processing platform. It efficiently detects existing triangles through using our proposed data structure, called FONL, which is cached in the distributed memory provided by Spark and reused multiple times. As data items in the FONL are fine-grained and contain the minimum required information, CCFinder requires less storage space and has better parallelism in comparison with its competitors. To find clustering coefficient, our solution to triangle counting is extended to have degree information of the vertices in the appropriate places. We performed several experiments on a Spark cluster with 60 processors. The results show that CCFinder achieves acceptable scalability and outperforms six existing competitor methods. Four competitors are those methods proposed based on graph processing systems, i.e., GraphX, NScale, NScaleSpark, and Pregel frameworks, and two others are the Cohen’s method and NodeIterator++, introduced based on MapReduce.