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 model of a human prostate was used, and the dose deposited by 198 AuNPs or 199 AuNPs to the tumor within the prostate as well as to the healthy tissue surrounding the prostate was calculated using the MCNP code. Water and A-150 TEP phantoms were used to simulate the soft and tumor tissues. Results The results showed that the dose due to 198 AuNPs or 199 AuNPs, which are distributed homogenously in the tumor, had a maximal value in the tumor region and then rapidly decreased toward the prostate–tumor interface and surrounding organs. However, the dose deposited by 198 Au is significantly higher than the dose deposited by 199 Au in the tumor region as well as normal tissues. Conclusions According to the MCNP results, 198 AuNPs are a promising modality to treat prostate cancer and other cancers and 199 AuNPs could be used for imaging purposes. Abstract
Physiological status and litter size can indeed have a significant impact on ewes' hematological parameters, which are essential indicators of their health. Therefore, this study examined the hematological profiles of ewes during pregnancy with single and twins in the Awassi ewes. The present study involved 232 ewes in good health and at sexual maturity. Among them, 123 ewes had single pregnancies, while 109 ewes had twin pregnancies. The age range of the ewes included in the study was between 3.5 and 4.5 years. Hematological tests were conducted on the sheep's blood samples promptly following collection. The findings demonstrated variations in hematological parameters among pregnant
... Show MoreIn data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.
The research deals with Iraq's position of the Lebanese civil war and the Efforts made by Iraq in order to stop the bleeding of this war, the research also deals with the nature of regime in Lebanon and the developments that preceded the war and the positions of the internal and external competing forces, as weu as handling the Iraqi Syrian disagreement and it's impaet on the situation of Lebanon and the war developments.
The research focused on the Iraq's position towards the externd proposed solutions to solve the Lebanese civil war.
Lithology identification plays a crucial role in reservoir characteristics, as it directly influences petrophysical evaluations and informs decisions on permeable zone detection, hydrocarbon reserve estimation, and production optimization. This paper aims to identify lithology and minerals composition within the Mishrif Formation of the Ratawi Oilfield using well log data from five open hole logs of wells RT-2, RT-4, RT-5, RT-6, and RT-42. At this step, the logging lithology identification tasks often involve constructing a lithology identification model based on the assumption that the log data are interconnected. Lithology and minerals were identified using three empirical methods: Neutron-Density cross plots for lithology id
... Show MoreMercifulness is a trait of civilization, humanity, and a moral value in society, because it has an impact on social life and its role in spreading interdependence, joint liability, and solidarity among people. Mercifulness means spreading mercy, synergy, sympathy, and cooperation. Generally, a society that enjoys strong ties tends to have a kind of stability and development, as well as, is able to face the economic, political, and security crises. Conversely, a weak society leads to weak social cohesion and weak community infrastructure that is more vulnerable to social, economic, and political instability. Thus, this is the aim of the research that has used a social survey method applied to a sample of respondents who have reached (300)
... Show MoreIn the present work the clathrate hydrate dissociation enthalpies of refrigerant R134a+ water system, and R134a + water + salt system were determined. The heat of dissociation of three types of aqueous salts solutions of NaCl, KBr and NaF at three concentrations (0.09, 0.17and 0.26) mol·kg−1 for each salt type, were enthalpy measured. The Clapeyron equation was used tocalculate heat of dissociation of experimental data for binary and ternary system.In order to find the effect of compressibility factor on heat dissociation enthalpy, the study was conducted by using equation of state proposed by Peng and Robinson Stryjek-Vera (PRSV). The obtained results of dissociation enthalpy for binary system were (143.8) kJ.mol-1
... Show MoreEmpirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F
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