The influence of an aortic aneurysm on blood flow waveforms is well established, but how to exploit this link for diagnostic purposes still remains challenging. This work uses a combination of experimental and computational modelling to study how aneurysms of various size affect the waveforms. Experimental studies are carried out on fusiform-type aneurysm models, and a comparison of results with those from a one-dimensional fluid–structure interaction model shows close agreement. Further mathematical analysis of these results allows the definition of several indicators that characterize the impact of an aneurysm on waveforms. These indicators are then further studied in a computational model of a systemic blood flow network. This demonstr

Transforming the common normal distribution through the generated Kummer Beta model to the Kummer Beta Generalized Normal Distribution (KBGND) had been achieved. Then, estimating the distribution parameters and hazard function using the MLE method, and improving these estimations by employing the genetic algorithm. Simulation is used by assuming a number of models and different sample sizes. The main finding was that the common maximum likelihood (MLE) method is the best in estimating the parameters of the Kummer Beta Generalized Normal Distribution (KBGND) compared to the common maximum likelihood according to Mean Squares Error (MSE) and Mean squares Error Integral (IMSE) criteria in estimating the hazard function. While the pr

Focusing on the negative role of default risk on banks, as it is one of the most important risks facing banks, which are difficult to determine accurately, and its reflection on the indicators of profitability of cash flows. The increasing competition between banks led to an increase in the credit facilities granted by banks, and was accompanied by an increase in exposure to the risks of default, which led to an impact on the level of performance of banks in terms of achieving the required return according to the levels of high competition. Therefore, the problem of this study focused on the extent to which the risk indicators of default affect the profitability indicators of the cash flows of the banks research sample in the profit

This study was conducted to determine the Immuno – globulins and complements quantitatively. The result revealed that the concentration of Immunoglobulin M(IgM) was increased significantly in patient group comparing with control group . The concentration of complement protein C4 was increased significantly in patient group comparing with control group.IgG of Candida albicans was detected by using ELISA Technique, the result indicated also that this antibody was found in 628% of the women who infected with Vulvovaginal Candidiasis. The sensitivity and specificity of the test were 63% and 89% respectively.

Based on a finite element analysis using Matlab coding, eigenvalue problem has been formulated and solved for the buckling analysis of non-prismatic columns. Different numbers of elements per column length have been used to assess the rate of convergence for the model. Then the proposed model has been used to determine the critical buckling load factor () for the idealized supported columns based on the comparison of their buckling loads with the corresponding hinge supported columns . Finally in this study the critical buckling factor () under end force (P) increases by about 3.71% with the tapered ratio increment of 10% for different end supported columns and the relationship between normalized critical load and slenderness ratio was g

The behavior and shear strength of full-scale (T-section) reinforced concrete deep beams, designed according to the strut-and-tie approach of ACI Code-19 specifications, with various large web openings were investigated in this paper. A total of 7 deep beam specimens with identical shear span-to-depth ratios have been tested under mid-span concentrated load applied monotonically until beam failure. The main variables studied were the effects of width and depth of the web openings on deep beam performance. Experimental data results were calibrated with the strut-and-tie approach, adopted by ACI 318-19 code for the design of deep beams. The provided strut-and-tie design model in ACI 318-19 code provision was assessed and found to be u

In this paper two ranking functions are employed to treat the fuzzy multiple objective (FMO) programming model, then using two kinds of membership function, the first one is trapezoidal fuzzy (TF) ordinary membership function, the second one is trapezoidal fuzzy weighted membership function. When the objective function is fuzzy, then should transform and shrinkage the fuzzy model to traditional model, finally solving these models to know which one is better

This research came with the aim of showing the impact of governance mechanisms on tax avoidance practices, and in light of this, the financial data of the joint stock companies (industrial, service, agricultural, and hotels) listed in the Iraq Stock Exchange amounting to (35) companies were collected during the period (2009-2020). Through the financial reports published on the market website, multiple linear regression analysis was used as a tool to study the relationship between variables, and (Eviews 12) program was used for analysis and hypothesis testing. To achieve the objectives of the research,(administrative ownership, board size, board independence, women's membership) was adopted as an indicator of the dimensions of governance, an

Ration power plants, to generate power, have become common worldwide. One such one is the steam power plant. In such plants, various moving parts of heavy machines generate a lot of noise. Operators are subjected to high levels of noise. High noise level exposure leads to psychological as well physiological problems; different kinds of ill effects. It results in deteriorated work efficiency, although the exact nature of work performance is still unknown. To predict work efficiency deterioration, neuro-fuzzy tools are being used in research. It has been established that a neuro-fuzzy computing system helps in identification and analysis of fuzzy models. The last decade has seen substantial growth in development of various neuro-fuzzy systems