The objective of this research was to estimate the dose distribution delivered by radioactive gold nanoparticles (198 AuNPs or 199 AuNPs) to the tumor inside the human prostate as well as to normal tissues surrounding the tumor using the Monte-Carlo N-Particle code (MCNP-6.1. 1 code). Background Radioactive gold nanoparticles are emerging as promising agents for cancer therapy and are being investigated to treat prostate cancer in animals. In order to use them as a new therapeutic modality to treat human prostate cancer, accurate radiation dosimetry simulations are required to estimate the energy deposition in the tumor and surrounding tissue and to establish the course of therapy for the patient. Materials and methods A simple geometrical

 Eight soil samples were selected around Najaf governorate at depth levels 40-50 cm. X-Ray Fluorescence (XRF) was used to determine the concentrations of major and trace elements. Liner and mass attenuation coefficient (µ, µ_ρ) have been determined at gamma energies (662, 1172,1332) keV using NaI (Tl) detector. The range of linear attenuation coefficients for calculated samples were (0.553-1.163) cm^-1, (0.122-0.178) cm^-1 and (0.049-0.105) cm^-1 at (662, 1172,1332) keV respectively. The range of mass attenuation coefficients obtained (0.39-0.76) cm²/gm, (0.087-0.117) cm²/gm and (0.0336-0.074) cm²/gm at (662, 1172,1332) keV respectively. The result

Nowadays, cloud computing has attracted the attention of large companies due to its high potential, flexibility, and profitability in providing multi-sources of hardware and software to serve the connected users. Given the scale of modern data centers and the dynamic nature of their resource provisioning, we need effective scheduling techniques to manage these resources while satisfying both the cloud providers and cloud users goals. Task scheduling in cloud computing is considered as NP-hard problem which cannot be easily solved by classical optimization methods. Thus, both heuristic and meta-heuristic techniques have been utilized to provide optimal or near-optimal solutions within an acceptable time frame for such problems. In th

 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the others

 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the

An experiment was carried out in the fields of Agriculture College-Baghdad University during spring and autumn of 2015 by using a randomized complete blocks design with three replications. The first season hybridization was established among three pure cultivars of cowpea (Vigna uniguiculata L.) which: Ramshorn, California black eye and Rahawya in full diallel crosses according to Griffing with first method and fixed model (3 parents+ 3 diallel hybrids +3 reciprocal hybrids) and a comparison experiment was in autumn season. The result of statistical analysis showed that there was a significant difference among the parents and their hybrids for all the studied characters. The parent 1 was the higher for root nodules number , leaf number, pod

Evaporation from water bodies is important and considered a major problem in dry and semi-dry regions, in this research the evaporation has been analyzed from two approaches: engineeringly and statistically. The engineering approach deals with the calculation of evaporation rates of Mosul Dam Lake. Three methods were used: pan evaporation class A, the combined and the mass-transfer. It was found that the values ​​obtained by pan evaporation class A method was the highest among the other, while the mass transfer method achieved the lowest results. The evaporation rates during the year ranged according to the first method (0.9–5.5) mm/day, second (0.7–11.5) mm/day and the last method (1.0039×10⁶) m³/year, whi

In this article, performing and deriving te probability density function for Rayleigh distribution is done by using ordinary least squares estimator method and Rank set estimator method. Then creating interval for scale parameter of Rayleigh distribution. Anew method using   is used for fuzzy scale parameter. After that creating the survival and hazard functions for two ranking functions are conducted to show which one is beast.