Despite the importance of sustainable development and its dimensions in developing performance and supporting competitive advantage in economic units, there is a gap and lack of coordination between Combined Assurance providers (management, internal audit, external audit) to report on sustainable development, and the research aims to propose a model for the Combined Assurance report to achieve development sustainable development in the Iraqi economic units, especially the Baghdad Municipality, enables assurance providers to coordinate efforts that lead to the achievement of Combined Assurance, The research found the proposed model for the Combined Assurance report in achieving sustainable development in the Iraqi economic units, especially the Baghdad Municipality, which leads to improving the assurance processes among the assurance providers about economic, environmental and social risks and getting rid of duplication that hinders the achievement of goals and finding practical ways to preserve resources and improvement to achieve sustainable development, The research presented a number of recommendations, represented by the need to implement the joint assurance in the Iraqi economic units, especially the Baghdad Municipality, because it gives a comprehensive view to the senior management of the potential risks related to economic, environmental and social activities, as well as the need to adopt the proposed model for the Combined Assurance report in achieving sustainable development in economic units. Iraqi.
In this paper harmful phytoplankton and herbivorous zooplankton model with Hollimg type IV functional response is proposed and analyzed. The local stability analysis of the system is carried out. The global dynamics of the system is investigated with the help of the Lyapunov function. Finally, the analytical obtained results are supported with numerical simulation.
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The study using Nonparametric methods for roubust to estimate a location and scatter it is depending minimum covariance determinant of multivariate regression model , due to the presence of outliear values and increase the sample size and presence of more than after the model regression multivariate therefore be difficult to find a median location .
It has been the use of genetic algorithm Fast – MCD – Nested Extension and compared with neural Network Back Propagation of multilayer in terms of accuracy of the results and speed in finding median location ,while the best sample to be determined by relying on less distance (Mahalanobis distance)has the stu
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Pseudomonas aeruginosa gram-negative, bacilli and facultative aerobic, P. aeruginosa cause cystic fibrosis patients, wounds, burns, and immunodeficienct patients, that have many virulence factors such as pyocyanin , cytotoxic ,biofilm formation and motility, Eighty-eight isolates belonging to P. aeruginosa were collected including the 66 clinical isolates obtained from different hospitals in Baghdad and were from different sources and 22 environmental isolates from previous studies of soil near oil fields. Microscopical and cultural characteristics were studied and diagnosed using biochemical tests, VITEC device, their ability to adhere to non-living (Polystyrene), living cell line (A549) and cytotoxicity of bacterial filtrate
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Background: Bloody diarrhea plays a major role in
morbidity and mortality especially in developing
countries, it is usually a sign of invasive enteric
infection, there is a thought that amoebic dysentery is
more common than bacillary dysentery in Iraq, and
from 1989 to 1997 amoebic dysentery increase from
20000to 550000 patients.
Objectives: This study aims to:
1. Outline the incidence of various infectious causes of
bloody diarrhea in Erbil district.
2. Assess the effect of multiple factors like age, sex,
source of water supply, etc... On the incidence of
amebic and bacillary dysentery.
3. To provide baseline data for making strategic plan to
reduce the diarrhoeal mortality and morbidity.
Met
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The COVID-19 pandemic has profoundly affected the healthcare sector and the productivity of medical staff and doctors. This study employs machine learning to analyze the post-COVID-19 impact on the productivity of medical staff and doctors across various specialties. A cross-sectional study was conducted on 960 participants from different specialties between June 1, 2022, and April 5, 2023. The study collected demographic data, including age, gender, and socioeconomic status, as well as information on participants' sleeping habits and any COVID-19 complications they experienced. The findings indicate a significant decline in the productivity of medical staff and doctors, with an average reduction of 23% during the post-COVID-19 period. T
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