Abstract:
Objective: To self-evaluate the effect of SBAR (Situation, Background, Assessment, and Recommendation) educational program on nurse and midwives practices in maternal health report documentation accuracy.
Methods: A quasi- experimental design was carried with the application of pre- post test for nurses and midwives’ knowledge and practices regarding SBAR communication tool. The study was held in Al-Elwia maternity teaching hospital, Al –Karckh maternity hospital and Al-Yarmouk teaching Hospital. purposive sample as it was convenient with inclusion criteria consisted of (84) nurse and midwives. The questionnaire comprised of demographic data, nurses- midwives practices of SBAR using (5) level Likert scale for assessme

Karbala province regarded one part significant zones in Iraq and considered an economic resource of vegetation such as trees of fruits, sieve and other vegetation. This research aimed to utilize Normalized Difference Vegetation index (NDVI) and Subtracted (NDVI) for investigating the current vegetation cover at last four decay. The Normalized Difference Vegetation Index (NDVI) is the most extensively used satellite index of vegetation health and density. The primary goals of this research are gather a gathering of studied area (Karbala province) satellite images in sequence time for a similar region, these image captured by Landsat (TM 1985, TM 1995, ETM+ 2005 and Landsat 8 OLI (Operational Land Imager) 2015. Preprocessing such gap filli

Composite materials are widely used in the engineered assets as aerospace structures, marine and air navigation owing to their high strength/weight ratios. Detection and identification of damage in the composite structures are considered as an important part of monitoring and repairing of structural systems during the service to avoid instantaneous failure. Effective cost and reliability are essential during the process of detecting. The Lamb wave method is an effective and sensitive technique to tiny damage and can be applied for structural health monitoring using low energy sensors; it can provide good information about the condition of the structure during its operation by analyzing the propagation of the wave in the

This research aims to solve the nonlinear model formulated in a system of differential equations with an initial value problem (IVP) represented in COVID-19 mathematical epidemiology model as an application using new approach: Approximate Shrunken are proposed to solve such model under investigation, which combines classic numerical method and numerical simulation techniques in an effective statistical form which is shrunken estimation formula. Two numerical simulation methods are used firstly to solve this model: Mean Monte Carlo Runge-Kutta and Mean Latin Hypercube Runge-Kutta Methods. Then two approximate simulation methods are proposed to solve the current study. The results of the proposed approximate shrunken methods and the numerical

         The aims of the present study are to evaluate the levels of CA19-9 in sera and tissues' homogenate of breast and thyroid benign patients in order to assess its use as an early diagnostic parameter in differentiation between malignant and benign cases. The study was conducted on 8 patients with breast benign tumor and 8 patients with thyroid benign tumor, by the enzyme linked immunosorbent assay (ELISA) technique. The results of CA19-9 levels in sera were (15 ±1.58 and 10.67 ±2.08)U/ml respectively compared with serum CA19-9 levels of control group which was 7.74 ±4.92 U/ml, the results were found to be highly significantly in breast tumor patients and non significantly in thyroid

The present study aimed to use the magnetic field and nanotechnology in the field of water purification, which slots offering high efficiency to the possibility of removing biological contaminants such as viruses and bacteria rather than the use of chemical and physical transactions such as chlorine and bromine, and ultraviolet light and boiling and sedimentation and distillation, ozone and others that have a direct negative impact on human safety and the environment. Where they were investigating the presence in water samples under study Coli phages using Single agar layer method and then treated samples positive for phages to three types of magnetic field fixed as follows (North Pole - South Pole - Bipolar) and compare the re

      The Matching and Mosaic of the satellite imagery play an essential role in many remote sensing and image processing projects. These techniques must be required in a particular step in the project, such as remotely change detection applications and the study of large regions of interest. The matching and mosaic methods depend on many image parameters such as pixel values in the two or more images, projection system associated with the header files, and spatial resolutions, where many of these methods construct the matching and mosaic manually. In this research, georeference techniques were used to overcome the image matching task in semi automotive method. The decision about the quality of the technique can be considered i

   Predicting permeability is a cornerstone of petroleum reservoir engineering, playing a vital role in optimizing hydrocarbon recovery strategies. This paper explores the application of neural networks to predict permeability in oil reservoirs, underscoring their growing importance in addressing traditional prediction challenges. Conventional techniques often struggle with the complexities of subsurface conditions, making innovative approaches essential. Neural networks, with their ability to uncover complicated patterns within large datasets, emerge as a powerful alternative. The Quanti-Elan model was used in this study to combine several well logs for mineral volumes, porosity and water saturation estimation. This model goes be

Cognitive radios have the potential to greatly improve spectral efficiency in wireless networks. Cognitive radios are considered lower priority or secondary users of spectrum allocated to a primary user. Their fundamental requirement is to avoid interference to potential primary users in their vicinity. Spectrum sensing has been identified as a key enabling functionality to ensure that cognitive radios would not interfere with primary users, by reliably detecting primary user signals. In addition, reliable sensing creates spectrum opportunities for capacity increase of cognitive networks. One of the key challenges in spectrum sensing is the robust detection of primary signals in highly negative signal-to-noise regimes (SNR).In this paper ,