Arsenic is a prevalent and pervasive environmental contaminant with varied amounts in drinking water. Arsenic exposure causes cancer, cardiovascular, liver, nerve, and ophthalmic diseases. The current study aimed to find the best conditions for eliminating arsenic from simulated wastewater and their effect on biomarkers of hepatic in mice. Adsorption tests including pH, contact duration, Al-kheriat dosage, and arsenic concentrations were evaluated. Seventy-two healthy albino mice (male) were accidentally allocated into nine groups (n = 8), the first group was considered as healthy control, the second group (AL-Kheriat), and other groups received AL-Kheriat and arsenic 25, 50, 75, 100, 125, 150 and 175 mg/kg, respectively. Next 10 days, the

Mixed Kirkuk and Sharki-Baghdad crude oils were distilled into narrow fractions. The range of these narrow fractions were 10oC, starting from IBP to 350oC. The total distillates from mixed Kirkuk and Sharki-Baghdad crude oils were 58.25 vol % and 44.65 vol %, respectively.The hydrocarbons compositions (paraffin, naphthene, aromatic) in light fractions starting from IBP to 250oC were determined by using PONA analysis method. The results show that the paraffin content decreases with increasing mid percent boiling point of the fraction, while the naphthene, and aromatic increase with the increase of mid percent boiling point of mixed Kirkuk and Sharki-Baghdad crude oils. Three groups of empirical equations were developed for the prediction

In a connected graph , the distance function between each pair of two vertices from a set vertex  is the shortest distance between them and the vertex degree  denoted by  is the number of edges which are incident to the vertex  The Schultz and modified Schultz polynomials of  are have defined as:

 respectively, where the summations are taken over all unordered pairs of distinct vertices in  and  is the distance between  and  in  The general forms of Schultz and modified Schultz polynomials shall be found and indices of the edge – identification chain and ring – square graphs in the present work.

This research depends on the relationship between the reflected spectrum, the nature of each target, area and the percentage of its presence with other targets in the unity of the target area. The changes occur in Land cover have been detected for different years using satellite images based on the Modified Spectral Angle Mapper (MSAM) processing, where Landsat satellite images are utilized using two software programming (MATLAB 7.11 and ERDAS imagine 2014). The proposed supervised classification method (MSAM) using a MATLAB program with supervised classification method (Maximum likelihood Classifier) by ERDAS imagine have been used to get farthest precise results and detect environmental changes for periods. Despite using two classificatio

A common approach to the color image compression was started by transform
the red, green, and blue or (RGB) color model to a desire color model, then applying
compression techniques, and finally retransform the results into RGB model In this
paper, a new color image compression method based on multilevel block truncation
coding (MBTC) and vector quantization is presented. By exploiting human visual
system response for color, bit allocation process is implemented to distribute the bits
for encoding in more effective away.
To improve the performance efficiency of vector quantization (VQ),
modifications have been implemented. To combines the simple computational and
edge preservation properties of MBTC with high c

This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.