The activity of the aqueous extract of Olea europaea was tested at concentrations of 8, 15 or 20 mg/kg of body weight on lipid profile in twenty female local rabbits. These animals were randomly divided into four groups (five animals in each group). Three groups were dosed orally with the concentrations mentioned above, while the last was administered with distilled water and considered as a control group. These animals were orally dosed by aqueous extract using a micropipette for 30 days. The results showed that there was a significant (P<0.05) decrease in cholesterol, triglycerides, low density lipoprotein (LDL-cholesterol), very low density lipoprotein (VLDL-cholesterol) concentrations and atherosclerosis index means for the three trea

Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c

Background A prospective clinical study was
performed to compare the efficacy of the use of lowmolecular-
weight heparin group (enoxparin group)
with control group in the prevention of deep-vein
thrombosis after total knee arthroplasty.
Aim of the study: to assess the prevalence of DVT
after total knee arthroplasty and evaluate the
importance of the use of low molecular weight
heparin in the prevention of this DVT.
Methods Thirty-three patients undergoing total
knee arthroplasty were randomly divided into two
groups. One group consisted of 12 patients who
received no prophylaxis with an anticoagulant (the
control group), other group consisted of 21 patients
who received the low-molecular-weight h

This research dealt with the analysis of murder crime data in Iraq in its temporal and spatial dimensions, then it focused on building a new model with an algorithm that combines the characteristics associated with time and spatial series so that this model can predict more accurately than other models by comparing them with this model, which we called the Combined Regression model (CR), which consists of merging two models, the time series regression model with the spatial regression model, and making them one model that can analyze data in its temporal and spatial dimensions. Several models were used for comparison with the integrated model, namely Multiple Linear Regression (MLR), Decision Tree Regression (DTR), Random Forest Reg

The paper uses the Direct Synthesis (DS) method for tuning the Proportional Integral Derivative (PID) controller for controlling the DC servo motor. Two algorithms are presented for enhancing the performance of the suggested PID controller. These algorithms are Back-Propagation Neural Network and Particle Swarm Optimization (PSO). The performance and characteristics of DC servo motor are explained. The simulation results that obtained by using Matlab program show that the steady state error is eliminated with shorter adjusted time when using these algorithms with PID controller. A comparative between the two algorithms are described in this paper to show their effectiveness, which is found that the PSO algorithm gives be

The question of word–formation motivation is one of the most urgent problems of morphological features of diminutive vocabulary in the languages of different structures, Arabic – Semitic and Russian - Slavic. The relevance of this question lies in the fact that the analysis of morphological elements of word-formation motivation plays an important role not only in identifying formal and semantic connections between different units of the same language, but also has an applied value in the comparative study of different languages. Taking in to account that word-formation motivation is usually considered sequentially in order to identify motivational relationships of this type of vocabulary, we will study motivation in comparative analy

The data preprocessing step is an important step in web usage mining because of the nature of log data, which are heterogeneous, unstructured, and noisy. Given the scalability and efficiency of algorithms in pattern discovery, a preprocessing step must be applied. In this study, the sequential methodologies utilized in the preprocessing of data from web server logs, with an emphasis on sub-phases, such as session identification, user identification, and data cleansing, are comprehensively evaluated and meticulously examined.

Different bremsstrahlung spectra from tungsten anode x-ray tube generated at 30, 40 and 50 kV have been examined theoretically and experimentally for an attempt to find a most suitable spectrum to radiograph a test object of 0.01 cm thickness of Cu and Ag. The high contrast using this suitable spectrum is demonstrated and the possible effects of fluorescent radiation are discussed.

This investigation presents an experimental and analytical study on the behavior of reinforced concrete deep beams before and after repair. The original beams were first loaded under two points load up to failure, then, repaired by epoxy resin and tested again. Three of the test beams contains shear reinforcement and the other two beams have no shear reinforcement. The main variable in these beams was the percentage of longitudinal steel reinforcement (0, 0.707, 1.061, and 1.414%). The main objective of this research is to investigate the possibility of restoring the full load carrying capacity of the reinforced concrete deep beam with and without shear reinforcement by using epoxy resin as the material of repair. All be