Purpose: To contribute to the development of an appropriate program for the management of medical waste based on clear-cut principles in order to reach the overall goal of improving the public health and environment of the population in our country.

Design / Approach / Introduction: The research is based on the analytical descriptive approach as a method of study in the field of data collection using a check list and analysis of the data through the use of some statistical treatments.

 Results: The need is to establish a medical waste management in hospitals and follow international standards in all stages of waste management from sorting, collection, transportation and treat

This study aims to suggest an alternative to the use of quality agricultural soil in the brick industry (Iraq). The Late Miocene claystone bed in the Injana Formation in central Iraq was targeted through the study of 18 exposed sections that were sampled by using the trench sampling method. The claystones are characterized by quartz (36.4%) followed by calcite (32.8%), quartz (36.4%) feldspar (2.6%), gypsum (1.3%) and dolomite (0.7%), kaolinite (10.5%), illite (7.7%), chlorite (6.7%), palygorskite (6.0%) and montmorillonite (0.7%). New thermal mineral phases were formed at 950°C, including diopside (62.9%), quartz (18.4%), wollastonite (8.28%), akermanite (7.6%), Anorthite (6.25%), Nosean (4.9%), gehlenite (3.75%) and Lazurite (3.1

The objective of this study is to verify the overall performance and evaluate the wastewater quality of the wastewater treatment plant at the Abu Ghraib Dairy Factory and compare the results with the Iraqi Quality Standards (IQS) for effluent disposal and with the national determinants of treated water use. Agricultural irrigation wastewater, which included daily assessment records of the main parameters affecting wastewater [five-day biochemical oxygen demand (BOD5), chemical oxygen demand (COD), total dissolved solids (T.D.S), total suspended solids (TSS), phosphate (PO4), nitrate (NO3), hydrogen ion concentration (pH)] obtained from the quality control department of Abu Ghraib dairy plant registered from January 2017 to December 2020. Th

Introduction: COVID-19 vaccine have been indicated to successfully decrease the hazard for symptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection furthermore associated hospitalisations. Objective: To study the immune response among different types of SARS-CoV-2 vaccines. Methods: This study includes 100 vaccinated individuals (43 Sinopharm, 30 AstraZeneca and 27 Pfizer) with one or two doses from different health centres in Baghdad. During the period from April 2021 to the end of May 2021, SARS-CoV-2 IgG and SARS-CoV-2 IgM levels were detected using AFIAS-6 device depending on FIA (Fluorescence Immunoassay) technique. Results: 93% of the cases were positive for IgG levels, and negative in 7% case

In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi

In this paper, a least squares group finite element method for solving coupled Burgers' problem in   2-D is presented. A fully discrete formulation of least squares finite element method is analyzed, the backward-Euler scheme for the time variable is considered, the discretization with respect to space variable is applied as biquadratic quadrangular elements with nine nodes for each element. The continuity, ellipticity, stability condition and error estimate of least squares group finite element method are proved.  The theoretical results  show that the error estimate of this method is . The numerical results are compared with the exact solution and other available literature when the convection-dominated case to illustrate the effic