Exploding wire Technique is a way for production metal and its compound nanoparticle that is capable of production of bulk amount at low cost semiconductor. In this work a copper iodine nanoparticles were fabricate by exploding copper wires with different currents in iodine solution. The produced samples were examined by XRD, FTIR, SEM and TEM to characterize their properties. The XRD proved the Nano-size for producer. The crystalline size increases with increasing current. FTIR measurements show a peaks located at 638.92 for Cu-I stretch bond indicate on formation of copper iodide compound and the peaks intensities increase with increasing current. The SEM and TEM measurements show that the thin films have nanostructures.

The present study was conducted to determine histopathological changes caused by chronic effect of Nitrofurantoin(NFT) in The albino mice Testes. The Study included 40 mice were divided on the five groups: the first group taken distilled water and become control group . the remaining group which are exposure with NFT drug in concentration (100-150-200-250) mg / kg, respectively, Doses were given orally for a period (month and two months). The results of histopathological changes included occurrence of congestion in the blood vessel and degeneration of spermatogonia and aggregation of spermatids in the lumen of semineferous tubules and inhibition of spermatogensis process and decrease of sperm inside the lumen

We have studied the effect of applying an external magnetic field on the characteristics of iron oxide (IO) nanoparticles (NPs) synthesized by pulsed laser ablation in dimethylformamide (DMF). The NPs synthesized with and without applying of magnetic field were characterized by Fourier transformation infrared spectroscopy (FT-IR), UV–Vis absorption, scanning electron microscope (SEM), atomic force microscope (AFM), and X-ray diffraction (XRD). SEM results confirmed that the particle size was decreased after applying magnetic field.

A Strength Pareto Evolutionary Algorithm 2 (SPEA 2) approach for solving the multi-objective Environmental / Economic Power Dispatch (EEPD) problem is presented in this paper. In the past fuel cost consumption minimization was the aim (a single objective function) of economic power dispatch problem. Since the clean air act amendments have been applied to reduce SO2 and NOX emissions from power plants, the utilities change their strategies in order to reduce pollution and atmospheric emission as well, adding emission minimization as other objective function made economic power dispatch (EPD) a multi-objective problem having conflicting objectives. SPEA2 is the improved version of SPEA with better fitness assignment, density estimation, an

The convergence speed is the most important feature of Back-Propagation (BP) algorithm. A lot of improvements were proposed to this algorithm since its presentation, in order to speed up the convergence phase. In this paper, a new modified BP algorithm called Speeding up Back-Propagation Learning (SUBPL) algorithm is proposed and compared to the standard BP. Different data sets were implemented and experimented to verify the improvement in SUBPL.

This paper develops a fuzzy multi-objective model for solving aggregate production planning problems that contain multiple products and multiple periods in uncertain environments. We seek to minimize total production cost and total labor cost. We adopted a new method that utilizes a Zimmermans approach to determine the tolerance and aspiration levels. The actual performance of an industrial company was used to prove the feasibility of the proposed model. The proposed model shows that the method is useful, generalizable, and can be applied to APP problems with other parameters.

Data centric techniques, like data aggregation via modified algorithm based on fuzzy clustering algorithm with voronoi diagram which is called modified Voronoi Fuzzy Clustering Algorithm (VFCA) is presented in this paper. In the modified algorithm, the sensed area divided into number of voronoi cells by applying voronoi diagram, these cells are clustered by a fuzzy C-means method (FCM) to reduce the transmission distance. Then an appropriate cluster head (CH) for each cluster is elected. Three parameters are used for this election process, the energy, distance between CH and its neighbor sensors and packet loss values. Furthermore, data aggregation is employed in each CH to reduce the amount of data transmission which le