Background: Prolapsed intervertebral disc is an important and common cause of low backache. MRI has now become universally accepted investigation for prolapsed intervertebral disc. We, however, regularly come across situations, when MRI shows diffuse disc bulges, even at multiple levels, which cannot be correlated clinically and when such cases are operated, no significant disc prolapse is found resulting in negative exploration. Objective: To evaluate the role of M.R.I. finding not only for diagnosis of disc herniation at lumbar region but also for localization the level of herniation Methods: A prospective study on seventy five symptomatic low backache and MRI confirmed prolapsed intervertebral disc patients at lumbo-sacral region were op

This research aims to removes dyes from waste water by adsorption using banana peels. The conduct experiment done by banana powder and banana gel to compare between them and find out which one is the most efficient in adsorption. Studying the effects different factors on adsorption material and calculate the best removal efficiency to get rid of the methylene blue dye (MB).

Three isolates of  P. aeruginosa were isolated from burnt patients. The ability of these isolates for adhesion and formation of slime layer were tested, the result showed that all isolates were able to adherence on the smooth surface. The sensitivity of  P. aeruginosa isolates for antibiotics were tested , all isolates were sensitive  to Gentamycin, Piperacillin and Amikacin Ciprofloxacin, and  resist to Tetracyclin, Amoxicillin, Cephalexine , Ceftriaxone. Ciprofloxacin and Amikacin were found effective against P. aeruginosa isolates with MIC values of 3.8 μg/ ml for  Ciprofloxacin  and 0.244 μg/ ml for Amikacin The antibacterial effect of Different concentrations of Aloe

The coagulation and flocculation process using coated magnetic nanoparticles is considered one of the effective technologies for turbidity removal. This study investigates an application of magnetic nanoparticles coated with citric acid in the coagulation and flocculation process on Tigris River water in Baghdad, Iraq. Magnetic nanoparticles (MNP1) were synthesized by the co-precipitation method and coated with citric acid (MNP2). The prepared MNP1 and MNP2 were characterized by XRD, FTIR, AFM, FE-SEM, EDS, and zeta potential analysis. For coagulation process, the effect of different types of coagulants (alum, FeCl3, MNP1, MNP2), coagulant dosage (10–110 mg/l), and initial pH (3–9) were examined in this work. The best coagulant was MNP2

Generally, statistical methods are used in various fields of science, especially in the research field, in which Statistical analysis is carried out by adopting several techniques, according to the nature of the study and its objectives. One of these techniques is building statistical models, which is done through regression models. This technique is considered one of the most important statistical methods for studying the relationship between a dependent variable, also called (the response variable) and the other variables, called covariate variables. This research describes the estimation of the partial linear regression model, as well as the estimation of the “missing at random” values (MAR). Regarding the

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