In this research, the effect of reinforcing epoxy resin composites with a filler derived from chopped agriculture waste from oil palm (OP). Epoxy/OP composites were formed by dispersing (1, 3, 5, and 10 wt%) OP filler using a high-speed mechanical stirrer utilizing a hand lay-up method. The effect of adding zinc oxide (ZnO) nanoparticles, with an average size of 10-30 nm, with different wt% (1,2,3, and 5wt%) to the epoxy/oil palm composite,  on the behavior of an epoxy/oil palm composite was studied with different ratios (1,2,3, and 5wt%) and an average size of  10-30 nm.  Fourier Transform Infrared (FTIR) spectrometry and mechanical properties (tensile, impact, hardness, and wear rate) were used to examine the composites. The FTIR

The aim of the study is to assess the risk factors which lead to myocardial infarction and relation to some variables. The filed study was carried out from the 1st of April to the end of Sept. 2005. The Sample of the study consisted of (100) patients in lbn-Albeetar and Baghdad Teaching Hospital. The result of the study indicated the following; 45% of patients with age group (41-50) were more exposed to the disease and there is no significant difference was seen in the level of education, Martial status, weight and height. The result shows that there are significant difference in risk factors like hypertension, cholesterol level in blood and diabetes. When analyzed by T.test at level of P < 0.01 and there are significant difference in smoki

Asthma is a chronic disease characterized by inflammatory events in the airways, that makes breathing a hard process in these patients. Angiotensin II (AngII) is important regulator for aldosterone production. Also, it participates in inducing reactive oxygen species (ROS) and inflammatory events. Angiotensin-converting enzyme (ACE) is responsible for the production of AngII. We hypothesised that ACE and AngII participate in the progression of asthma by increasing ROS production and inflammatory processes. Thus, we evaluated the level of AngII, the activity of ACE, and the level of malondialdehyde (MDA) as indicators for oxidative stress in 60 asthmatic male patients and 30 non-asthmatic male control. An asthma control test (ACT) was estima

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Objective: The aim of the study to evaluate the nursing care management for diabetes mellitus patient
with total hip replacement after fractured hip.
Methodology: A field study carried out on patients with diabetes mellitus and have total hip
replacement after fractured hip in orthopedic ward at the hospital of surgical specialization (malefemale)during
January 2002 to January 2003.Physical and psychological nursing
assessment
immediately after the surgery was done for the both subjects (control and experimental) and then a
scientific management with daily nursing care were provided to the experimental subject with daily
nursing care to the patient condition by using a scientific and practical methods and leave th

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Asthma is a chronic inflammatory disease of respiratory airways characterized by distinctive history of respiratory symptoms due to variable airflow obstruction which reverses either spontaneously or in response to certain medications. Acetylcholine is a parasympathetic neurotransmitter which plays fundamental roles in the development of persistent asthma. Treatment guidelines recommend using medium doses of inhaled corticosteroids in addition to another controller bronchodilator instead of using high doses inhaled steroid alone for treatment of moderate to severe persistent asthma. The inhaled long acting muscarinic antagonist, tiotropium, was approved recently to control unresponsive asthma to inhaled corticosteroid with or without a long

A program in Visual Basic language was designed to predict the type of radio storm that emitted from Jupiter at specific Local Time (LT) from two different Iraqi locations (Baghdad and Basra), such storms result from the Central Meridian Longitude (CML) of system ??? for Jupiter and phase of Io’s satellite (?Io). Some of these storms are related to position of Io (Io- A,B,C,D) and others are unrelated (non-Io-A,B,C,D) to its position. The input parameters for this program were user specified by determining the observer’s location (longitude), year, month and day. The output program results in form of tables provides the observer with information about the date and the LT of beginning and end of each type of emitted storm. Two Io-storm r