This paper introduces an experimental study on the behavior of confined concrete filled aluminum tubular (CFT) column to improve strength design, ductility and durability of concrete composite structures under concentrically loaded in compression to failure. To achieve this: seven column specimens with same concrete diameter 100mm and without steel reinforcement have been examined through experimental testing, which are used to study the effects of the thickness of the aluminum tube encased concrete ( thickness : 0mm, 2mm, 3mm, 4mm and 5mm with same length of column 450mm), length of column (thickness 5mm and length of column 700mm) and durability (thickness 5mm and length of column 450mm) on the structural behavior of &

Problem of water scarcity is becoming common in many parts of the world.  Thus to overcome this problem proper management of water and an efficient irrigation systems are needed.  Irrigation with buried vertical ceramic pipe is known as a very effective in management of irrigation water.  The two- dimensional transient flow of water from a buried vertical ceramic pipe through homogenous porous media is simulated numerically using the software HYDRUS/2D to predict empirical formulas that describe the predicted results accurately.   Different values of pipe lengths and hydraulic conductivity were selected.  In addition, different values of initial volumetric soil water content were assumed in this simulation a

Background BK polyomavirus is one of the common post-transplant viral infections, affecting ∼15% of renal transplantation recipients (RTR), leading to graft loss in more than half of cases. Objectives Study the rate of detection of BK virus (BKV) in RTRs in Pap-stained urine cytology specimens. Methods A single center study, urine samples were collected from 99 RTR patients, with 15 Living Donors (LD) and 15 patients with chronic kidney disease (CKD) were taken as controls. And urine cytology smears were Pap stained for detection of decoy cells (DCs). Results Out of the 99 RTRs, 27 (27.3%) patients were decoy positive, 8 out of these 27 patients had uncommon DCs, and 5 out of these 27 cytology positive patients (18.5%) had biopsy proven B

         The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the proposed LAD-Atan estimator

ABSTRACT: BACKGROUND: The main goal of facelift surgery is to reduce the effect of aging by reposition of face soft tissue in to more youthful orientation. There are many methods for SMAS plication which had different design and vector of pull. AIM OF STUDY: To evaluate the effectiveness and longitivity of 7 shaped SMAS plication in facelift. PATIENT AND METHODS: From January 2020 to march 2021, 10 female patients with age (45-60) years were presented with facial sagging, those patients were subjected to subcutaneous facelift with 7 shaped SMAS plication with fat greft in Al-Shaheed Ghazi Al-Harri Hospital and Baghdad burn medical center at Baghdad medical complex. RESULTS: The average follow up period was 6 to 12 months. The mean operative

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol