The objective of this study is to evaluate the bacterial count and heavy metal concentration of river water on fish micronuclei. Fish and water samples are carried out in 1 May to 1 June 2013 from Tigris River. A total of fifty three fish sample are studied. The bacteriological quality of water showed that the total viable count is ranged from 150×103 to 352×103 cfu/ml and fecal coliform counts was 1250 cell/100ml during the study period. All the metals (Cu, Hg, Pb, and Zn) are within the normal limit, but Cd was slightly elevated in river water samples. The appearance of micronuclei in red blood cells of all fish species is detect , by recording a larger number of it, in ( Abu Alsomere , Hishne , Bannini Kaber al fam & Karkoor

The rivers are the main source of fresh water for many countries and the great development which is considered as one of the sustainable development elements in its various agricultural, industrial, domestic and environmental fields .The countries of the world seek food security and water security in order to ensure the basic needs of citizens .Because their distribution is uneven in many regions of the world with different human needs, which leads to conflicts over water sources, especially those located in one international river basin .This has led to the emergence of internationallegal rules governing the management of The problem revolves around the dialectic between limited water resources and increased need for water use b

An integrated GIS-VBA (Geographical Information System – Visual Basic for Application), model is developed for selecting an optimum water harvesting dam location among an available locations in a watershed. The proposed model allows quick and precise estimation of an adopted weighted objective function for each selected location. In addition to that for each location, a different dam height is used as a nominee for optimum selection. The VBA model includes an optimization model with a weighted objective function that includes beneficiary items (positive) , such as the available storage , the dam height allowed by the site as an indicator for the potential of hydroelectric power generation , the rainfall rate as a source of water . In a

Modeling forward kinematics with neural networks allows for efficient handling of nonlinear relationships and realistic error correction in time-critical applications by relying on accurate training data. This paper presents a Multi-Layer Feed-Forward Neural Network (MLFFNN) to solve the forward kinematics of a 3-DOF robot. The proposed MLFFNN consists of 50 hidden neurons and was trained using 628319 samples to find only the position (x, y, z) of the end-effector. Data were generated by MATLAB, assuming an incremental motion of joints. The joint variables ( , , and ) are the inputs of the NN, which outputs the positions of the end effector (x, y, z) calculated using the Denavit-Hartenberg (DH) method. The results demonstrate that t

In this paper, an algorithm is suggested to train a single layer feedforward neural network to function as a heteroassociative memory. This algorithm enhances the ability of the memory to recall the stored patterns when partially described noisy inputs patterns are presented. The algorithm relies on adapting the standard delta rule by introducing new terms, first order term and second order term to it. Results show that the heteroassociative neural network trained with this algorithm perfectly recalls the desired stored pattern when 1.6% and 3.2% special partially described noisy inputs patterns are presented.

Finger vein recognition and user identification is a relatively recent biometric recognition technology with a broad variety of applications, and biometric authentication is extensively employed in the information age. As one of the most essential authentication technologies available today, finger vein recognition captures our attention owing to its high level of security, dependability, and track record of performance. Embedded convolutional neural networks are based on the early or intermediate fusing of input. In early fusion, pictures are categorized according to their location in the input space. In this study, we employ a highly optimized network and late fusion rather than early fusion to create a Fusion convolutional neural network

Smart water flooding (low salinity water flooding) was mainly invested in a sandstone reservoir. The main reasons for using low salinity water flooding are; to improve oil recovery and to give a support for the reservoir pressure.

In this study, two core plugs of sandstone were used with different permeability from south of Iraq to explain the effect of water injection with different ions concentration on the oil recovery. Water types that have been used are formation water, seawater, modified low salinity water, and deionized water.

The effects of water salinity, the flow rate of water injected, and the permeability of core plugs have been studied in order to summarize the best conditions of low salinity

Introduction: This study aimed to evaluate the impact of ozonated water on water sorption and solubility of heat-cure acrylic resin. Methods: Thirty-three samples of heat-cured acrylic resin were manufactured and divided into three groups: control, immersion for 10 and 20 minutes in ozonated water. Water sorption and water solubility tests were carried out in line with ADA Standard No. 12 for denture-base acrylic resin. Data were analyzed using one-way ANOVA at a significance level of 5%. Results: There was a nonsignificant difference between the control and experimental groups regarding water sorption (P