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

Background: Dental casts come into direct contact with impression materials and other items that are contaminated by saliva and blood from a patient's mouth, leaving the casts susceptible to cross-contamination. The disinfectant solutions of the impression materials cause various adverse reactions. Therefore, disinfection of dental casts may be effective in preventing cross infection. This study was carried out to evaluate the surface hardness, dimensional accuracy, reproduction of details and surface porosity of type III, type IV and type IV extra hard dental stone after immersion in and spray by using SOLO and Sodium hypochlorite disinfectant solutions. Materials and methods: 240 Stone samples were prepared in rubber rings, A total of 60

Dental casts come into direct contact with impression materials and other items that are contaminated by saliva and blood from a patient's mouth, leaving the casts susceptible to cross-contamination. The disinfectant solutions of the impression materials cause various adverse reactions. Therefore, disinfection of dental casts may be effective in preventing cross infection. This study was carried out to evaluate the surface hardness, dimensional accuracy, reproduction of details and surface porosity of type III, type IV and type IV extra hard dental stone after immersion in and spray by using SOLO and Sodium hypochlorite disinfectant solutions. Materials and methods: 240 Stone samples were prepared in rubber rings, A total of 60 test block w

Background: Dental casts come into direct contact with impression materials and other items that are contaminated by saliva and blood from a patient's mouth, leaving the casts susceptible to cross-contamination. The disinfectant solutions of the impression materials cause various adverse reactions. Therefore, disinfection of dental casts may be effective in preventing cross infection. This study was carried out to evaluate the surface hardness, dimensional accuracy, reproduction of details and surface porosity of type III, type IV and type IV extra hard dental stone after immersion in and spray by using SOLO and Sodium hypochlorite disinfectant solutions. Materials and methods: 240 Stone samples were prepared in rubber rings, A total of 60

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

The purpose of this research is to find the estimator of the average proportion of defectives based on attribute samples. That have been curtailed either with rejection of a lot finding the kth defective or with acceptance on finding the kth non defective.

The MLE (Maximum likelihood estimator) is derived. And also the ASN in Single Curtailed Sampling has been derived and we obtain a simplified Formula All the Notations needed are explained.

This paper describes a newly modified wind turbine ventilator that can achieve highly efficient ventilation. The new modification on the conventional wind turbine ventilator system may be achieved by adding a Savonius wind turbine above the conventional turbine to make it work more efficiently and help spinning faster. Three models of the Savonius wind turbine with 2, 3, and 4 blades' semicircular arcs are proposed to be placed above the conventional turbine of wind ventilator to build a hybrid ventilation turbine. A prototype of room model has been constructed and the hybrid turbine is placed on the head of the room roof. Performance's tests for the hybrid turbine with a different number of blades and different values o

   Fracture pressure gradient prediction is complementary in well design and it is must be considered in selecting the safe mud weight, cement design, and determine the optimal casing seat to minimize the common drilling problems. The exact fracture pressure gradient value obtained from tests on the well while drilling such as leak-off test, formation integrity test, cement squeeze ... etc.; however, to minimize the total cost of drilling, there are several methods could be used to calculate fracture pressure gradient classified into two groups: the first one depend on Poisson’s ratio of the rocks and the second is fully empirical methods. In this research, the methods selected are Huubert and willis, Cesaroni I, Cesaroni II,

In many oil fields only the BHC logs (borehole compensated sonic tool) are available to provide interval transit time (Δtp), the reciprocal of compressional wave velocity VP.

   To calculate the rock elastic or inelastic properties, to detect gas-bearing formations, the shear wave velocity VS is needed. Also VS is useful in fluid identification and matrix mineral identification.

   Because of the lack of wells with shear wave velocity data, so many empirical models have been developed to predict the shear wave velocity from compressional wave velocity. Some are mathematical models others used the multiple regression method and neural network technique.

   In this study a number of em