Hysterectomy is one of the most common gynecological operations done worldwide. Early diagnosis of the psychosexual effects of a hysterectomy and the fast application of appropriate treatment can prevent further worsening and persistence of symptoms, especially with respect to higher levels of anxiety, depression, lower self-esteem, and sexual impact after a hysterectomy. The aim of this study was to assess the psychological and sexual problems of women with hysterectomy. A descriptive study was carried out from March 1, 2023 to May 25, 2023 to determine the level of psychosexual problems experienced by women after hysterectomy. A purposive (non-probability) sample of 120 women who visited the outpatient clinic at Baghdad Teaching H

Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al

This study investigates the implementation of Taguchi design in the estimation of minimum corrosion rate of mild-steel in cooling tower that uses saline solution of different concentration. The experiments were set on the basis of Taguchi’s L16 orthogonal array. The runs were carried out under different condition such as inlet concentration of saline solution, temperature, and flowrate. The Signal-to- Noise ratio and ANOVA analysis were used to define the impact of cooling tower working conditions on the corrosion rate. A regression had been modelled and optimized to identify the optimum level for the working parameters that had been founded to be 13%NaCl, 35ᴼC, and 1 l/min. Also a confirmation run to establish the p

Rate of penetration plays a vital role in field development process because the drilling operation is expensive and include the cost of equipment and materials used during the penetration of rock and efforts of the crew in order to complete the well without major problems. It’s important to finish the well as soon as possible to reduce the expenditures. So, knowing the rate of penetration in the area that is going to be drilled will help in speculation of the cost and that will lead to optimize drilling outgoings. In this research, an intelligent model was built using artificial intelligence to achieve this goal.  The model was built using adaptive neuro fuzzy inference system to predict the rate of penetration in

Background: Cyclophosphamide (Cpd), a common immunosuppressive and chemotherapeutic drug, can cause hepatotoxicity by inducing inflammation and oxidative stress. Dapagliflozin (Dapa) and other sodium-glucose cotransporter-2 inhibitors (SGLT2i) have anti-inflammatory and antioxidant properties, and Silymarin is a natural compound extracted from the seeds of the milk thistle plant (Silybum marianum). It is best known for its antioxidant, anti-inflammatory, and hepatoprotective effects.Objective: By measuring oxidative stress, inflammation, and liver regeneration parameters, with an emphasis on the Nrf2/HO-1 pathway and hepatocyte nuclear factors (HNF4α and HNF6), Dapa's hepatoprotective effects in comparison to Sil on Cpd-induced liv