Reproductive failure is the hallmark of brucellosis in animals. An uncommon but important complication in pregnant women who become acutely infected withBrucella melitensisis spontaneous pregnancy loss or vertical transmission to the fetus. Unfortunately, the mechanism behind reproductive failure is still obscure, partially due to the lack of a proper study model. Recently, it was demonstrated that intratracheal (IT) inoculation of nonpregnant guinea pigs would replicate features of clinical disease in humans.

Sustainable development is longer that meet the needs of the present generation without compromising the ability of future generations to meet their own needs as it seeks to harmonize economic, social, Why research aims to check the availability of a proposed program takes into account the evidence and scrutiny of financial commitment and performance audit in accordance with the dimensions of sustainable development (economic, environmental, social and institutional) to measure the extent of the province on the needs of current and future generations, The problem with research that there is no audit program ensures the audit of financial statements, commitment and performance of health services in order to achieve sustainable development

The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par

Abstract
The current research aims to identify mental health and its role in promoting self-confidence and positive behavior of female university students. The researcher adopted the descriptive analytical approach in this research. The researcher depended on the availability of sources and references, literature, and previous field studies to analyze and study all aspects related to mental health and its role in promoting self-confidence and positive behavior of university students and then expand its importance and identify the areas of mental health, self-confidence, positive behavior, and university. The second chapter included the concept of mental health, the importance of the study, the most important factors of health and psyc

Background Solar irradiance is a nonlinear and intermittent function, which makes accurate forecasting of solar power generation a challenge. The high variability of meteorological conditions is not well represented by conventional atmospheric models, thus hampering forecasting skill and model robustness. In this work, an advanced hybridization of multi-population cuckoo search (HMPCS) algorithm with machine learning (ML) methods is developed to enhance the prediction performance of photovoltaic (PV) power forecasting with more reliability. Methods In this study, a hybrid modeling framework is proposed, called HMPCS–ML framework which captures the global search capacity of HMPCS and predictive power of sophisti

With a goal to identify, and ultimately removing from the oil fraction, the carcinogenic components, an oil fraction oil has been analyzed into a main three hydrocarbon groups, paraffins, aromatics, and polycyclic saturates. A multi-stage adsorption apparatus has been used. Four units of 300 g alumina each seems to be sufficient for removing the polynuclear aromatics from 75 g of an oil fraction boiling between 365-375 °C from Qurna crude oil. The usefulness of the ternary diagram for analyzing the oil fraction to the three hydrocarbons groups has been studied and verified. An experimentally based linear relationship of density and refractive index was established to enable of identifying the composition of an oil fraction using th

              The current paper proposes a new estimator for the linear regression model parameters under Big Data circumstances.  From the diversity of Big Data variables comes many challenges that  can be interesting to the  researchers who try their best to find new and novel methods to estimate the parameters of linear regression model. Data has been collected by Central Statistical Organization IRAQ, and the child labor in Iraq has been chosen as data. Child labor is the most vital phenomena that both society and education are suffering from and it affects the future of our next generation. Two methods have been selected to estimate the parameter

   A new nano-sized NiMo/TiO₂-γ-Al₂O₃ was prepared as a Hydrodesulphurization catalyst for Iraqi gas oil with sulfur content of 8980 ppm, supplied from Al-Dura Refinery. Sol-gel method was used to prepare TiO₂- γ-Al₂O₃ nano catalyst support with 64% TiO_2, 32% Al₂O₃, Ni-Mo/TiO-γ-Al₂O₃ catalyst was prepared under vacuum impregnation conditions to loading metals with percentage 3.8 wt.% and 14 wt.% for nickel and molybdenum respectively while the percentage for alumina, and titanium became 21.7, and 58.61 respectively. The synthesized TiO₂- γ-Al₂O₃ nanocomposites and Ni-Mo /TiO₂