Biodiversity is one of the important biological factors in determining water quality and maintaining the
ecological balance. In this study, there are 223 species of phytoplankton were identified, and they are as
follows: 88 species of Bacillariophyta and were at 44%,70 species of Chlorophyta and they were at 29 %, 39
species of Cyanophyta and they were at 16 %, 12 species of Euglenozoa and they were at 4 %, four species of
Miozoa and they were at 3 %, and, Phylum Charophyta and Ochrophyta were only eight and two species,
respectively and both of them were at 2%. The common phytoplankton recorded in the sites studied
include Nitzschia palea, Scenedesmus quadricauda, Oscillatoria princeps, and Peridinium

The present study was conducted in the Tigris River within Baghdad (University of Baghdad campus). The study included some physicochemical parameters and qualitative of epiphytic algae on the host plant (Ceratophyllum demersum) during summer season 2013. The results revealed that the study area was alkaline, hard and oxygenated water. A total of 105 taxa of epiphytic algae was identified. Bacillariophyceae diatoms composed 44.7% of the total and were represented by 42.4% of the order Pennales and 1.9 %of the order Centrales. Chlorophyceae composed 32.3%, followed by Cyanophyceae composed 22.8 % of the total. The total number of epiphytic algae was fluctuated among the study period. Most of the identified algae were benthos type and a few

The study aims to predict Total Dissolved Solids (TDS) as a water quality indicator parameter at spatial and temporal distribution of the Tigris River, Iraq by using Artificial Neural Network (ANN) model. This study was conducted on this river between Mosul and Amarah in Iraq on five positions stretching along the river for the period from 2001to 2011. In the ANNs model calibration, a computer program of multiple linear regressions is used to obtain a set of coefficient for a linear model. The input parameters of the ANNs model were the discharge of the Tigris River, the year, the month and the distance of the sampling stations from upstream of the river. The sensitivity analysis indicated that the distance and discharge

The paper aims to measure and analysis the impact Public Spending on Iraq economy (Kaldor Variables).

 (variables of the magic square Kaldor) and them in after 2003.

The paper adopted econometric Methods to test the stationarity of the Variables under consideration. For the period (2005-2016) by using multiple regression and estimation the Impulse response function (IRF), by adopting Eviews 10 program.

The results of Impulse response function for the following five-years after the period under consideration reflexes that public expenditure (PEX) was fluctuating between positive and negative in all the variables of the research and this shows the fragility of the performance of fiscal policy in Iraq.

T

Background: changing in lifestyle like displacing place could cause depression which is a common mental disorder that change general health that affect dental caries incidence and severity. The aims of this study were to assess the relation of depression status on prevalence and severity of dental caries among internally displaced people. Material and Method: The sample include 121 internally displaced people aged from 13-17 years. Method for depression measuring is by using Children Depression Inventory (CDI2) questionnaire. Dental caries is measured by using caries experience (DMFs) and caries severity D1-4. Result: the mean value for decayed and missing surfaces were higher in high depression grade as compering with low and medium dep

هذا البحث يتحدى الافتراض القائل أن العراق بعد عام 2003 يجب دراسته بمعزل عن ديناميات التي سبقت عام 2003، اذ تبرهن هذه الدراسة على ان الشعبوية هي احدى الديناميات التي تمظهرت بصورة شعبوية استبدادية في النظام الديكتاتوري، نظرًا لأنه كان زعيم حزب علماني وعربي على نطاق واسع، لكنه استخدم الدين والقومية بشكل استراتيجي وانتقائي في ظروف معينة، مما خلق سياق الشعبوية الحديثة. الموجة الثانية هي الشعبوية العرقية والطائف

Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD