Objective(s): to determine the effectiveness of instruction intervention upon multipara women's practices to
control stress incontinence.
Methodology: A quasi-experimental study was carried out from (2nd) April, 2010 to 15th June, 2010. Nonprobability
(purposive sample) of (60) multiparous women was selected from Baghdad Teaching Hospital and AlElwia
Maternity Teaching Hospital in Baghdad city, the sample was divided into two groups (30) women were
considered as a study group, and another (30) were considered as the control group. An instructional intervention
was applied on the study group, while the intervention was not applied on control group. A questionnaire was
resolve as a tool of data collection to suit the p

         Sera samples were collected from 60 children aged 4-60 months, all were clinically and serologically proven cases of visceral leishmaniasis, as well as  from 10 healthy children, all were seronegative with no history of parasitic infection who serve as a control during the study. Serum total protein and albumin were measured and compared between the control and visceral leishmaniasis patients. Serum protein profiles have been investigated using the conventional sodium dodecyl sulphate – polyacrylamide gel electrophoresis (SDS-PAGE).  Serum of control group showed the specific protein pattern with five protein bands, while serum protein profile in visceral leishmaniasis pat

Current numerical research was devoted to investigating the effect of castellated steel beams without and with strengthening. The composite concrete asymmetrical double hot rolled steel channels bolted back to back to obtain a built-up I-shape form are used in this study. The top half part of the steel is smaller than the bottom half part, and the two parts were connected by bolting and welding. The ABAQUS/2019 program employed the same length and conditions of loading for four models: The first model is the reference without castellated and strengthening; the second model was castellated without strengthened; the third model was castellated and strengthened with reactive powder concrete encased in the

As a result of the development and global openness and the possibility of companies providing their services outside their spatial boundaries that were determined by them, and the transformation of the world due to the development of the means of communication into a large global market that accommodates all products from different regions and of the same type and production field, competition resulted between companies, and the race to obtain the largest market share It ensures the largest amount of profits, and it is natural for the advertising promotion by companies for their product to shift from an advertisement for one product to a competitive advertisement that calls on the recipient to leave the competing product and switch to it

In this study, the upgrading of Iraqi heavy crude oil was achieved utilizing the solvent deasphalting approach (SDA) and enhanced solvent deasphalting (e-SDA) by adding Nanosilica (NS). The NS was synthesized from local sand. The XRD result, referred to as the amorphous phase, has a wide peak at 2Θ= (22 - 23º) The inclusion of hydrogen-bonded silanol groups (Si–O–H) and siloxane groups (Si–O–Si) in the FTIR spectra. The SDA process was handled using n-pentane solvent at various solvent to oil ratios (SOR) (4-16/1ml/g), room and reflux temperature, and 0.5 h mixing time. In the e-SDA process, various fractions of the NS (1–7 wt.%) have been utilized with 61 nm particle size and 560.86 m²/g surface area in the presence of 12 m

This research explored the performance of steel fiber concrete-filled stainless-steel tube columns stiffened with embedded carbon steel T-sections with various steel fiber ratios under biaxial bending conditions. A numerical parametric analysis was adopted, using finite element modeling with Abaqus CAE/2021 to evaluate the effects of the fiber ratio (ranging from 0% to 1.5%) on the load-bearing capacity and deflection behavior of columns. In addition, the compressive strength of concrete ranged between 45 and 65 MPa. An increase in the fiber ratio led to a substantial improvement in the ultimate load-bearing capacity (up to 24%), a reduction in deflection (of approximately 49%), and an improvement in column ductility, which were obt

This paper is concerned with the numerical solutions of the vorticity transport equation (VTE) in two-dimensional space with homogenous Dirichlet boundary conditions. Namely, for this problem, the Crank-Nicolson finite difference equation is derived.  In addition, the consistency and stability of the Crank-Nicolson method are studied. Moreover, a numerical experiment is considered to study the convergence of the Crank-Nicolson scheme and to visualize the discrete graphs for the vorticity and stream functions. The analytical result shows that the proposed scheme is consistent, whereas the numerical results show that the solutions are stable with small space-steps and at any time levels.

Micro-perforated panel (MPP) absorber is increasingly gaining popularity as an alternative sound absorber in buildings compared to the well-known synthetic porous materials. A single MPP has a typical feature of a Helmholtz resonator with a high amplitude of absorption but a narrow absorption frequency bandwidth. To improve the bandwidth, a single MPP can be cascaded with another single MPP to form a double-layer MPP. This paper proposes the introduction of inhomogeneous perforation in the double-layer MPP system (DL-iMPP) to enhance the absorption bandwidth of a double-layer MPP. Mathematical models are proposed using the equivalent electrical circuit model and are validated with experiments with good agreement. It is revealed that the DL-

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D