The present study was implemented in the period from January to December 2017, to assess the assemblage of fish, with the effects of some environmental factors and knowledge the impacts of annual periodic fluctuations between drowning and drought on the abundance and size-spectrum on the fish community in Al-Cibyaish marsh. Water temperature ranged between 13 ͦ C in January to 35 ͦ C in July, salinity from 2.90 PSU (Practical salinity unite) in February to 4.14 PSU in August. Hydrogen ion ranged between 7.60 in July to 8.30 in February. The present study appears contribution of environmental variables in the distribution, widespread and occurrence of fish assemblage in the Al-Chibyaish marsh. A total of 3294 specimens were collected represented 15 fish species affiliated to 15 genera, six families and five orders. Three fish species in present area were formed 72.38% of the total number of species in the marsh. Planiliza abu was the most abundant species formed 35.43%, Alburnus mossulensis, 19.22% and Oreochromis aureus, 17.73%. The ecological indices were within the range of previous studies and described as poor for diversity index ranged between1.38 in June to 1.96 in November. Richness index fluctuated from 0.96 in May and July to 1.96 in April and can express as half integrated. The evenness index values ranged from 0.68 in September to 0.85 in November and December indicate to semi-balanced or slightly balanced. Fish size revealed dominance of the small size due to high mortality in the dry season. The present study affirms prevalence and dominates of historical small native species P. abu and some of the small invasive species, which possess various functional characteristics, enable it to inhabit the marsh.
Objective(s): The study aims at evaluating pregnancy-related health behaviors for pregnant women, and to identify the association between pregnancy-related health behaviors and their demographic characteristics of pregnant woman’s age, education, employment, residential area and monthly income.
Methodology: A descriptive study is carried out for the period from December 14th, 2020 to June 20th, 2021. This study was conducted through a non-probability (convenience) sample of 150 pregnant women attending, Abo Ghareeb primary health care sector in Abo Ghareeb spend. The sample has been collected by using the instrument to gather data and accomplish the study's objectives. A questionnaire is composed of (29) items and it is divided into
This study offers numerical simulation results using the ABAQUS/CAE version 2019 finite element computer application to examine the performance, and residual strength of eight recycle aggregate RC one-way slabs. Six strengthened by NSM CFRP plates were presented to study the impact of several parameters on their structural behavior. The experimental results of four selected slabs under monotonic load, plus one slab under repeated load, were validated numerically. Then the numerical analysis was extended to different parameters investigation, such as the impact of added CFRP length on ultimate load capacity and load-deflection response and the impact of concrete compressive strength value on the structural performance of
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This study was done to evaluate a new technique to determine the presence of methamphetamine in the hair using nano bentonite-based adsorbent as the filler of extraction column. The state of the art of this study was based on the presence of silica in the nano bentonite that was assumed can interact with methamphetamine. The hair used was treated using methanol to extract the presence of methamphetamine, then it was continued by sonicating the hair sample. Qualitative analysis using Marquish reagent was performed to confirm the presence of methamphetamine in the isolate.The hair sample that has been taken in a different period confirmed that this current developing method can be used to analyzed methamphetamine. This m
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Objective This research investigates Breast Cancer real data for Iraqi women, these data are acquired manually from several Iraqi Hospitals of early detection for Breast Cancer. Data mining techniques are used to discover the hidden knowledge, unexpected patterns, and new rules from the dataset, which implies a large number of attributes. Methods Data mining techniques manipulate the redundant or simply irrelevant attributes to discover interesting patterns. However, the dataset is processed via Weka (The Waikato Environment for Knowledge Analysis) platform. The OneR technique is used as a machine learning classifier to evaluate the attribute worthy according to the class value. Results The evaluation is performed using
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The current issues in spam email detection systems are directly related to spam email classification's low accuracy and feature selection's high dimensionality. However, in machine learning (ML), feature selection (FS) as a global optimization strategy reduces data redundancy and produces a collection of precise and acceptable outcomes. A black hole algorithm-based FS algorithm is suggested in this paper for reducing the dimensionality of features and improving the accuracy of spam email classification. Each star's features are represented in binary form, with the features being transformed to binary using a sigmoid function. The proposed Binary Black Hole Algorithm (BBH) searches the feature space for the best feature subsets,
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