Objective: To identify the role and importance of the clinical pharmacist in the Emergency Department on prevent
or reduced the medication error.
Methodology: We collected the medical file of 3400 patients, 1400 patient's file in (A) hospital, and 1000 patient's
file in each of (B and C) hospital, who admitted to the ED, at primary weekdays between 8 am to 2 pm, and
recorded all the intervention made by clinical pharmacist through an active search in clinical charts, with analysis
of the daily medical prescription. The potential severity of harm of the medication error judged by two reviewers,
a permanent emergency physician, and clinical pharmacist based on the National Coordinating Council (NCC) of
Medication Error

Sea level rise (SLR) due to climate change is affecting the coastline, causing shoreline changes, the degradation of mangrove forests, and the destruction of coastal resources. This is the cause of a huge amount of mangrove degradation in many parts of the Ganges–Brahmaputra–Meghna delta. A total of 90% of people have been forced to migrate from the island due to extreme weather conditions. In this study, remote sensing (RS) and geographic information system (GIS) techniques were used for LULC change and shoreline shift analyses of Ghoramara Island. LULC classification was carried out using thirty years of Landsat datasets with intervals of ten years (1990 and 2000) and intervals of five years (2005, 2010, 2015, and 2020). The classific

The study aims to predict Total Dissolved Solids (TDS) as a water quality indicator parameter at spatial and temporal distribution of the Tigris River, Iraq by using Artificial Neural Network (ANN) model. This study was conducted on this river between Mosul and Amarah in Iraq on five positions stretching along the river for the period from 2001to 2011. In the ANNs model calibration, a computer program of multiple linear regressions is used to obtain a set of coefficient for a linear model. The input parameters of the ANNs model were the discharge of the Tigris River, the year, the month and the distance of the sampling stations from upstream of the river. The sensitivity analysis indicated that the distance and discharge

One of the most popular causes for implant infection is dental plaque bacteria. Previous studies have shown the bactericidal effect of CO2 laser irradiation on bacteria associated with soft tissue surrounding the implant materials. No published studies have examined the effect of irradiation by CO2 laser on Streptococcus oralis and Staphylococcus aureus.The aim of this study was to evaluate the bactericidal effect of CO2 laser on bacteria that are causing dental implant infections. This study was carried out on two isolates of bacterial species out of 25 samples, isolated from patients having soft tissue infections around the dental implant. These two pure isolates including Streptococcus oralis and Staphylococcus aureus were identified

In Incremental sheet metal forming process, one important step is to produce tool path, an
accurate tool path is one of the main challenge of incremental sheet metal forming
process. Various factors should be considered prior to generation of the tool path i.e.
mechanical properties of sheet metal, the holding mechanism, tool speed, feed rate and
tool size. In this work investigation studies have been carried out to find the different tool
path strategies to control the twist effect in the final product manufactured by single point
incremental sheet metal forming (SPIF), an adaptive tool path strategy was proposed and
examined for several Aluminum conical models. The comparison of the proposed tool path with t

Background: Mothers are considered as the key role in effect on child's dental behavior. So it is important to involve her in oral health promotion program to prevent early childhood dental caries from occurring in early age. Objectives: To identify the knowledge, practice and attitude of mothers about the oral health of their children. And to measure the change in oral hygiene of children aged (4-7) years old after one month of interventional program on their mothers. Type of study: Non-randomized interventional.Methods: Non-randomized interventional study for one month in Al Shaab area in Baghdad to 65 mothers who have children aged (4-7) years .A modified administrated questionnaire is given to assess mothers’ knowledge, practice an

Precise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables