Background: Blood vessels injury is one of the most
common causes of medical emergencies that admitted to
hospitals and at the same time it regarded as one of the
most important causes of death. They may represent less
than 15% of all injuries; they deserve special attention
because of their severe complications.
Objective: The aim of the present study is to assess
anatomically the injures of major arteries and veins in the
lower limb with their management.
Methods: The present study extended from April 2006 to
February 2007, in which 65 patients with lower limb
vascular injury were examined in Emergency Department
and Forensic Medicine Department of Tikrit Teaching
Hospital in Salah-Aldin governora

    The aim of the research was to assess effects of short and long-period exposure to radiation from mobile phone on blood indices in experimental rats. In this study forty mature female rats were used; the animals were divided into two experimental group, each group consists of twenty animals. Short-period group of rats were exposed to cell phone radiation for different duration 30 m, 60 m, and 90 m per day for six weeks. Long-period group of rats were exposed to radiation from mobile phone for different duration 2h, 4h, and 6h per day for three months. The study noticed that there was significant (P≥0.05) elevation in total white blood cells and the study demonstrated significant increment (P≥0.05) in percentage of

Isolation and identification of bacterial isolates were carried out according to the morphology and biochemical characteristics on one hundred and twenty stool specimens collected from children under five years old via using biochemical tests and Api 20E compact system for further confirmation. Bacterial isolates were distributed as (34.48, 20.68, 5.17,0.86) % for Escherichia coli, Salmonella typhi ,Enterobacter aerogenos, Citrobacter freundii and Hafnia alvei respectively and 9.48 % for each Proteus mirabilis, Pseudomonas aeruginosa and Klebsiella Pneumonia. As well as, 2.58% for both Shigella sonnei and Serratia marcescens. Antibiotic susceptibility test for 116 bacterial isolates was performed towards 20 antibiotics types using disk d

This study discussed the effects of doping with silver (Ag) on the optical and structural properties of
CdO nanoparticles at different concentrations 0, 1, 2, 3, 4, 5 wt% prepared by the precipitation method. The
materials were annealed at 550˚C for 1 h. The structural, topographical, and optical properties were
diagnosed by X-ray diffraction analysis, atomic force instrument, and visible and ultraviolet spectrometers.
The results show that the average diameter of the grains depends on the percentage of added silver to the
material, as the diameter decreased from 88.8 to 59.7 nm, and it was found that the roughness increased from
5.56 to 26.5. When studying the optical properties, it was noted that th

The coefficient of performance of a window type Air-Conditioner system can be improved if a reduction in the work of compressor can be achieved by a suitable technique. The present study investigates the effect of dispersing a low concentration of TiO2 nanoparticles in the mineral oil based lubricant, as well as on the overall performance of a window type Air-Conditioner system using R22 as the working fluid. An enhancement in the COP of the refrigeration system has been observed and the existence of an optimum volume fraction noticed, with low concentrations of nanoparticles suspended in the mineral oil. Results showed that the average compressor work reduced by 13.3%, which ultimately resulted in an increase of 11.99% in the COP due to

Researchers employ behavior based malware detection models that depend on API tracking and analyzing features to identify suspected PE applications. Those malware behavior models become more efficient than the signature based malware detection systems for detecting unknown malwares. This is because a simple polymorphic or metamorphic malware can defeat signature based detection systems easily. The growing number of computer malwares and the detection of malware have been the concern for security researchers for a large period of time. The use of logic formulae to model the malware behaviors is one of the most encouraging recent developments in malware research, which provides alternatives to classic virus detection methods. To address the l

Many carbonate reservoirs in the world show a tilted in originally oil-water contact (OOWC) which requires a special consideration in the selection of the capillary pressure curves and an understanding of reservoir fluids distribution while initializing the reservoir simulation models.
An analytical model for predicting the capillary pressure across the interface that separates two immiscible fluids was derived from reservoir pressure transient analysis. The model reflected the entire interaction between the reservoir-aquifer fluids and rock properties measured under downhole reservoir conditions.
This model retained the natural coupling of oil reservoirs with the aquifer zone and treated them as an explicit-region composite system

In this paper, new brain tumour detection method is discovered whereby the normal slices are disassembled from the abnormal ones. Three main phases are deployed including the extraction of the cerebral tissue, the detection of abnormal block and the mechanism of fine-tuning and finally the detection of abnormal slice according to the detected abnormal blocks. Through experimental tests, progress made by the suggested means is assessed and verified. As a result, in terms of qualitative assessment, it is found that the performance of proposed method is satisfactory and may contribute to the development of reliable MRI brain tumour diagnosis and treatments.

Recently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. Combating this phenomenon and detecting misleading information manually is rather boring, takes a long time, and impractical. It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. This dataset contains news articles covering multiple fields such as politics, economy, culture, sports and others. A Hybrid Deep Neural Network has been proposed to improve accuracy. This network focuses on the properties of both the Text-Convolution Neural