Breast cancer is the most common cause of death among women worldwide (1)
. Breast self-exam (BSE) is considered
an important public health procedure; primary prevention should be given the highest priority in the fight against
cancer.
Cancer is considered the second leading cause of death in developed countries there was some 6.2 million cancer
related deaths, accounƟng for 12% of all deaths globally (5).Patients perception toward this disease and preference
concerning the types and aims of their treatment are vary they may loss hopes and become devastated and crippled
or even dies earlier, if told about the diagnosis (13). The study aimed to assess knowledge of female students regarding
BSE, and to find out rel

    In this survey, there are 14 species belonging to 14 genera, nine families and two orders, collected on Macrofungi from Tikrit city, Salahadin Governorate, North Central of Iraq. The members of Coleoptera were more abundant than flies on Macrofungi.

    The family of Ciidae and Leiodidae (Order, Coleoptera), Mycetophilidae (Order, Diptera), and 6 species are recorded for the first time for insect fauna of Iraq.

Objectives of the study: Assess pregnant women's knowledge about tetanus toxoid vaccination, to find out the
relationship between pregnant women's knowledge and some variables which included: (age, level of
education, occupational status, socio-economic level, gravidity, parity, following visits of antenatal care,
tetanus toxoid vaccination coverage).
Methods and Materials: Descriptive analytic study conducted on multistage probabilistic sample of 130
pregnant women during period from 30th January 2012 to the 24th April 2013 was carried out in the six primary
health care centers at Karbala city. The questionnaire was consisted of four parts which include of: sociodemographic
characteristics, reproductive information,

This study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperatur

Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration

A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twenty four samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

Solar energy is one of the immeasurable renewable energy in power generation for a green, clean and healthier environment. The silicon-layer solar panels absorb sun energy and converts it into electricity by off-grid inverter. Electricity is transferred either from this inverter or from transformer, consumed by consumption unit(s) available for residential or economic purposes. The artificial neural network is the foundation of artificial intelligence and solves many complex problems which are difficult by statistical methods or by humans. In view of this, the purpose of this work is to assess the performance of the Solar - Transformer - Consumption (STC) system. The system may be in complete breakdown situation due to failure of both so