Background : The kidneys may be injured in abdominal trauma, both blunt & penetrating. Renal trauma may manifest in a dramatic fashion for both the patient and the clinician. Objectives: To evaluate the incidence, management, morbidity &mortality of renal injury in blunt & penetrating abdominal trauma.
Results:The majority o f patients were males (35= 77.8%), the rest were females (10= 22.2%). The average age was 37 years (range= 18-56 years). The most common grades were grade1, grade2 and grade3 (40=88.9%), while 5 patients (11.1%) were grades 4 and 5.The most common associated injuries were liver, spleen, small & large bowels and diaphragm. The mortality was 20% (9 patients). The most common cause of death was multip

Safe drinking water is essential for the present and future generations' health. This study aims to assess drinking water quality in Baghdad's Al-Rusafa neighborhood. Water samples were taken from 32 neighborhoods on this side. The quality of the examined potable water samples differed depending on the water source. This investigation's pH, chlorine, EC, TDS, TSS, Cd, and Pb levels were below acceptable ranges. TDS levels in Al-Mada'in are more significant than acceptable (>600ppm) water levels. Bacteria have polluted six communities (Shigella, Salmonella, Escherichia coli, and Klebsiella). Bacterial quality of drinking water and gram-negative bacteria resistant to chlorine in Baghdad's municipal water supply. Regarding pH, the w

Aerial Robot Arms (ARAs) enable aerial drones to interact and influence objects in various environments. Traditional ARA controllers need the availability of a high-precision model to avoid high control chattering. Furthermore, in practical applications of aerial object manipulation, the payloads that ARAs can handle vary, depending on the nature of the task. The high uncertainties due to modeling errors and an unknown payload are inversely proportional to the stability of ARAs. To address the issue of stability, a new adaptive robust controller, based on the Radial Basis Function (RBF) neural network, is proposed. A three-tier approach is also followed. Firstly, a detailed new model for the ARA is derived using the Lagrange–d’A

   الضاد والظاء موطن تفرد العربية وفخرها ، الفت فيهما العشرات والعشرات من المصنفات الثرّة لكثرة ذرائع تلابسهما والخلط بينهما ، فهما متشابهان في هيكل البناء ، وإخراجهما متداخل على اللسان ، وألفاظهما متناظرة برحابة في الإملاء ، فضلاعن  اشكالهما  إلى حدّ الآن ، مما حثني على التفكير في وسائل تسهل المطروح وتمد جسراً بين أجزائه عسى أن تدنو قطافه في دفع الشبهة ومواراتها ، فتحصلت لي امور ادرتها بكلمتين مف

Sesame crop, one of the very important oily, industrial, and summer crops that is economically important, has been investigated. The plantation and production of this crop has been studied in Al-Qadisiyah governorate during 2003-218. This is because this governorate is well-known by sesame plantation. Such a study helps to know the geographical distribution of sesame agricultural season in 2017-2018, and explore the most important natural factors that affect its plantation. Different research approaches have been adopted based on that facts that need to be met. A field study approach has been used in studying sesame crop descriptively and conceptually, shedding light on its nutritional and economic importance. Moreover, a descriptive com

Aims: This study aimed to assess complications of caesarean section among pregnant women attending AL Diwaniyah Maternity and Pediatric Hospital; and find out relationship between complications of caesarean section and socio-demographic data of women. Methods: A descriptive cross-sectional study design is conducted for the period of December 26th 2020 to June 1st 2021. The validity of the questionnaire is determine through a panel of experts and reliability was achieved through a pilot study. By a purposive sample is selected among pregnant women who undergo caesarean section, data was collected through the use of questionnaire and interview techniques; and analyzed through the descriptive and inferential statistic. Results: Findings indica

The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices

The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices