The use  analysis  value chain such  information in the provision as financial  so information quality meet and satisfy the needs of users such information , particularly investors and lenders   as the identification needs   financial information and the knowledge as their behavior influenced by that information can be based on the accounting profession to focus on improving their function in order to achieve its goal that satisfying their needs and rationalize their decisions . In accounting thought discovered fertile ground for users preferences as one of the entrances   theorising positive which is based on the need to include knowledge on accounting hypothesis that explain the

Introduction: Although it is discouraged, community pharmacy customers can obtain oral corticosteroids (OCSs) without prescriptions from some community pharmacies in Iraq. Medication abuse is defined as the use of medication for non-medical reasons. Objectives: The study aimed to determine demographics, beliefs, and perceptions associated with the abuse of oral corticosteroids for non-illness reasons among community pharmacy customers. Methods: This cross-sectional study was conducted in fall 2018 in four provinces in Iraq. Customers of 19 community pharmacies asking for OCSs for themselves without a prescription were administered a paper survey. This study used the Theory of Reasoned Action (TRA) to measure the relation

The main purpose of this investigation is to evaluate the concentrations of six essential metals (Na⁺, Mg²⁺, K⁺, Ca²⁺, Fe²⁺ and Zn²⁺) in saffron and a farm soil using the neutron activation analysis (NAA) as a nuclear spectrometry method. The stratified random sampling method was used here. The NAA results showed the well uptake of Mg²⁺, K⁺, Ca²⁺, Fe²⁺, and Zn²⁺ in saffron, which is lower than the toxicity range. Based on the contamination factor and geoaccumulation index, soil contamination levels were determined uncontaminated by Zn, moderately contaminated by Na⁺ and Fe²⁺, and strongly contamin

Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l

The monthly time series of the Total Suspended Solids (TSS) concentrations in Euphrates River at Nasria was analyzed as a time series. The data used for the analysis was the monthly series during (1977-2000).

The series was tested for nonhomogenity and found to be nonhomogeneous. A significant positive jump was observed after 1988. This nonhomogenity was removed using a method suggested by Yevichevich (7). The homogeneous series was then normalized using Box and Cox (2) transformation. The periodic component of the series was fitted using harmonic analyses, and removed from the series to obtain the dependent stochastic component. This component was then modeled using first order autoregressive model (Markovian chain). The above a

Reseach target the most important topic, is Activity and ProfitabilityIndictors Analysis for
Nationality and Iraqi Insurance Company, In order to stand on them ability to cover its risks
and explore the efficiency asset and its avialible resources using to determine them abilities to
profit generation from its insurance activity. The analysis was focus to examine their profit
and activity power, and test the significant differences aming them performance. Test 2
hypothese that is related and result it sign that the 2 company no has significant differences at
profitability and activity level. The research depend on coneclusion, recommended two
company to work at efficiency with cost element of insurance activity in or

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

  In this study, light elements for 13C , 16O for  (α,n) and (n,α) reactions as well as α-particle energy  from 2.7 MeV  to 3.08 MeV are used as far as the data of reaction cross sections are available. The more recent cross sections data of (α,n) and (n,α) reactions are reproduced in fine steps 0.02 MeV for  16O (n,α) 13C  in the specified energy range, as well as cross section (α,n)  values were derived from the published data of (n,α) as a function of α-energy in the same fine energy steps by using the principle inverse reactions. This calculation involves only the ground state of  13C , 16O  in the reactions 13C (α,n) 16O  and  16O (n,α) 13C.

Abstract:

Since the railway transport sector is very important in many countries of the world, we have tried through this research to study the production function of this sector and to indicate the level of productivity under which it operates.

It was found through the estimation and analysis of the production function Kub - Duglas that the railway transport sector in Iraq suffers from a decline in the level of productivity, which was reflected in the deterioration of the level of services provided for the transport of passengers and goods. This led to the loss of the sector of importance in supporting the national economy and the reluctance of most passengers an