This paper aims to identify the contents of the advertisements of the (Take the Vaccine .. to Protect Yourself) campaign that was carried out by the Iraqi Ministry of Health for the period from (11/19/2020) to (4/1/2022), to raise awareness of the anti-Covid 19 virus vaccines, which it published on its official page on Facebook. The researcher used a comprehensive inventory method for the research community, and used the content analysis tool.                                                                             

The study aims to identify the degree of appreciation for the level of digital citizenship of a sample of Palestinian university students in the governorates of Gaza, and its relationship to the level of health awareness about the emerging coronavirus (covid-19). To achieve the objectives of the study, the researcher followed a descriptive approach by applying two questionnaires; the first, which consists of 30 items, was used  to measure the level of digital citizenship.  The second, which consists of 19 items, was used to measure the level of health awareness. Both questionnaires  were applied on a sample of 367 students who were electronically selected using the manner simple randomness. Results have shown that the degr

Hematological malignancies remain one of the leading causes of death worldwide despite advances in cancer therapeutics. Newcastle disease virus (NDV) is a member of Paramyxoviridae that elicits considerable interest as an anticancer agent because it can replicate up to 10 000 times faster in human cancer cells than in most normal cancer cells. Several NDV strains reportedly induce the cytolysis of cancerous cell lines. The attenuated Iraqi strain (AMHA1) of NDV is a novel oncolytic agent with promising antitumor characteristics, including apoptosis induction. This study aimed to evaluate the ability of the AMHA1 NDV strain to induce apoptotic cell death in hematological tumors through caspase-dependent or independent apoptotic pathways. The

Seventy four Iraqi breast cancer paraffin blocks were collected from patients were attended to center health laboratory, histopathology department, Bagdad, Iraq. The patients information’s which included: name, age, and the pathological stage, grade, tumor size were obtained from the clinical records of the patients also relation with sex hormones was recorded. The cases which has been taken included invasive ductal and invasive lobular carcinoma type Women age were ranged from 24-80 years peak age frequency of tumor occurred in the category of more than 40 years old. Immunohistochemical expression of her-2/neu was from total 74 cases of infiltrative ductal carcinoma cases, 27(36.49%)were positive for Her-2/neu expression, 47(63.51%) were

We have studied Bayesian method in this paper by using the modified exponential growth model, where this model is more using to represent the growth phenomena. We focus on three of prior functions (Informative, Natural Conjugate, and the function that depends on previous experiments) to use it in the Bayesian method. Where almost of observations for the growth phenomena are depended on one another, which in turn leads to a correlation between those observations, which calls to treat such this problem, called Autocorrelation, and to verified this has been used Bayesian method.

The goal of this study is to knowledge the effect of Autocorrelation on the estimation by using Bayesian method. F

This study uses load factor and loss factor to determine the power losses of the electrical feeders. An approach is presented to calculate the power losses in the distribution system. The feeder’s technical data and daily operation recorded data are used to calculate and analyze power losses.

This paper presents more realistic method for calculating the power losses based on load and loss factors instead of the traditional methods of calculating the power losses that uses the RMS value of the load current which not consider the load varying with respect to the time. Eight 11kV feeders are taken as a case study for our work to calculate load factor, loss factor and power losses. Four of them (F40, F42, F43 and F