Background : Shoulder pain is a common problem that can pose difficult diagnostic and therapeutic challenges for the family physician It is the third most common musculoskeletal complaint in the general population, and account for 5% of all general practitioners musculoskeletal consults Objective: To determine the diagnostic performance of ultrasonography compared with the physical examination for detection of rotator cuff tears in painful shoulder syndrome. Method: Prospective study was done on seventy patients (48 male, 22 female), age ranged between 30-70 years (mean age 50 years), From February 2007 to July 2011, were subjected to comparative study in Al-Kindy teaching hospital with rotator cuff tears, including physical and ultrasonographic examination. Result: Ultrasound examination confirmed the presence of rotator cuff tear in 58 patients (82.8%), about two third of them below age 40 (65.7%) and male gender (68.6%). Conclusion: Ultrasonography which is noninvasive, safe; cheap with no known risk like radiation is a sensitive and accurate method of identifying patients with rotator cuff tears, and should be used wherever possible to improve diagnosis and treatment of painful shoulder disorders
Sol-gel method was use to prepare Ag-SiO2 nanoparticles. Crystal structure of the nanocomposite was investigated by means of X-ray diffraction patterns while the color intensity was evaluated by spectrophotometry. The morphology analysis using atomic force microscopy showed that the average grain sizes were in range (68.96-75.81 nm) for all samples. The characterization of Ag-SiO2 nanoparticles were investigated by using Scanning Electron Microscopy (SEM). Ag-SiO2 NPs are highly stable and have significant effect on both Gram positive and negative bacteria. Antibacterial properties of the nanocomposite were tested with the use of Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli) bacteria. The results have shown antibacteri
... Show MoreAbstract The research aims to identify the psychological and health risks that a child might be exposed to by playing with hazardous toys such as pellet guns. To this end, the researcher has visited Ian Al-Haytham Eye Hospital in Baghdad, the emergency department to figure out the rate of injuries in Children for the consecutive years (2017-2018) and the first Month of (2019). The psychological risks as a result of disability are represented by the inability to accommodate the surrounding environment well. Additionally, the child experiences a kind of tension, conflict, and going in psychological crises through introversion, isolation, withdrawal tendencies,
... Show MoreThe combination of wavelet theory and neural networks has lead to the development of wavelet networks. Wavelet networks are feed-forward neural networks using wavelets as activation function. Wavelets networks have been used in classification and identification problems with some success.
In this work we proposed a fuzzy wavenet network (FWN), which learns by common back-propagation algorithm to classify medical images. The library of medical image has been analyzed, first. Second, Two experimental tables’ rules provide an excellent opportunity to test the ability of fuzzy wavenet network due to the high level of information variability often experienced with this type of images.
&n
... Show MoreThis paper deals with the F-compact operator defined on probabilistic Hilbert space and gives some of its main properties.
The main purpose of this paper is to study some results concerning reduced ring with another concepts as semiprime ring ,prime ring,essential ideal ,derivations and homomorphism ,we give some results a bout that.
Let R be a commutative ring with identity 1 and M be a unitary left R-module. A submodule N of an R-module M is said to be approximately pure submodule of an R-module, if for each ideal I of R. The main purpose of this paper is to study the properties of the following concepts: approximately pure essentialsubmodules, approximately pure closedsubmodules and relative approximately pure complement submodules. We prove that: when an R-module M is an approximately purely extending modules and N be Ap-puresubmodulein M, if M has the Ap-pure intersection property then N is Ap purely extending.
Let R be associative ring with identity and M is a non- zero unitary left module over R. M is called M- hollow if every maximal submodule of M is small submodule of M. In this paper we study the properties of this kind of modules.
In this paper, we consider a new approach to solve type of partial differential equation by using coupled Laplace transformation with decomposition method to find the exact solution for non–linear non–homogenous equation with initial conditions. The reliability for suggested approach illustrated by solving model equations such as second order linear and nonlinear Klein–Gordon equation. The application results show the efficiency and ability for suggested approach.
The global food supply heavily depends on utilizing fertilizers to meet production goals. The adverse impacts of traditional fertilization practices on the environment have necessitated the exploration of new alternatives in the form of smart fertilizer technologies (SFTs). This review seeks to categorize SFTs, which are slow and controlled-release Fertilizers (SCRFs), nano fertilizers, and biological fertilizers, and describes their operational principles. It examines the environmental implications of conventional fertilizers and outlines the attributes of SFTs that effectively address these concerns. The findings demonstrate a pronounced environmental advantage of SFTs, including enhanced crop yields, minimized nutrient loss, improved nut
... Show MoreIn this paper, integrated quantum neural network (QNN), which is a class of feedforward
neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that
... Show More