In this research we prepared nanofibers by electrospinning from
poly (Vinyl Alcohol) /TiO2. The spectrum of the solution (Emission)
was studied and found to be at 772 nm, several process parameters
were such as concentration of TiO2 , and the effect of distance from
nozzle tip to the grounded collector (gap distance). The result of the
lower concentration of, the smaller the diameter of nanofiber is.
Increasing the gap distance will affect nanofibers diameter

Chemical pesticides have an impact on other living organisms in addition to their intended target organisms. Any chemical pesticide is therefore made safe for use by examining its biological characteristics and side effects. The present study was aimed at determining the resistance efficiency of six bacterial isolates obtained from malathion-contaminated soils. Bacteria were isolated from soil samples collected in Adhamiya, Baghdad, Iraq. Biochemical tests and VITEK 2 compact equipment were used to identify the bacterial isolates. Primary and secondary screening tests were conducted on the bacterial isolates for resistance against malathion pesticides. The optimal bacterial growth conditions were determined in malathion-contaminated media.

Introduction: Rheumatoid arthritis (RA) is one of the most prevalent systemic inflammatory diseases worldwide. Cardiac complications present the most common mortality cause among RA patients. One of the most important comorbid conditions with RA is diabetic hyperglycemia mainly type 2 diabetes mellitus (T2DM). Aim of the study: The present study was conducted to assess prevalence of T2DM among patients diagnosed with RA from Iraq. Methodology: We included a randomly selected 100 rheumatoid arthritis. All included patients were subjected to anthropometric measurements, diabetic profile assessment and ESR, CRP and rheumatoid factor measurement. Results: Among the included RA patients, 28 patients were diagnosed with new-onset DM. Our

In this research, an analysis for the standard Hueckel edge detection algorithm behaviour by using three dimensional representations for the edge goodness criterion is presents after applying it on a real high texture satellite image, where the edge goodness criterion is analysis statistically. The Hueckel edge detection algorithm showed a forward exponential relationship between the execution time with the used disk radius. Hueckel restrictions that mentioned in his papers are adopted in this research. A discussion for the resultant edge shape and malformation is presented, since this is the first practical study of applying Hueckel edge detection algorithm on a real high texture image containing ramp edges (satellite image).

 This project introduces a prospective material for photonic laser applications. The material is olive oil which is classified as organic compound, having a good nonlinear optical properties candidate to be used in photonic applications. A high purity sample of olive oil has been used. The theoretical calculation to generate third harmonic wave using olive oil has been determine using MATLAB program. THG (λ=355nm) intensity has been determined at two cases of sample thicknesses 1mm and 10mm. The minimum threshold incident intensity to obtain THG intensity are equal I_ω=7530 mW/cm² at L=1mm and I_ω= 6220 mW/cm² at L=10mm. The possibility of generation of third harmonic in olive oil inside

The main objective of this study is to determine the suitable excitation wavelengths for
urine components reaching to select the suitable lasers to execute the auto fluorescence due to their
high intensities. The auto fluorescence was measured at 305, 325 and 350 nm excitation wavelengths
for eleven urine samples which were also analyzed by conventional methods (chemical and
microscopic examination). Data manipulation using Matlab package programming language showed
that urine sample with normal chemical and biological components have emission peaks which are
different from the infected urine samples. Despite the complexity of the composition of urine,
fluorescence maxima can be observed. Most likely, the peaks obser

Diabetic retinopathy is an eye disease in diabetic patients due to damage to the small blood vessels in the retina due to high and low blood sugar levels. Accurate detection and classification of Diabetic Retinopathy is an important task in computer-aided diagnosis, especially when planning for diabetic retinopathy surgery. Therefore, this study aims to design an automated model based on deep learning, which helps ophthalmologists detect and classify diabetic retinopathy severity through fundus images. In this work, a deep convolutional neural network (CNN) with transfer learning and fine tunes has been proposed by using pre-trained networks known as Residual Network-50 (ResNet-50). The overall framework of the proposed