The aim of this paper is to shed the light on the concepts of agency theory by measuring one of the problems that arise from it, which is represented by earnings management (EM) practices. The research problem is demonstrated by the failure of some Iraqi banks and their subsequent placement under the supervision of the Central Bank of Iraq, which was attributed, in part, to the inadequacy of the agency model in protecting stakeholders in shareholding institutions, as well as EM, pushed professional institutions to adopt the corporate governance model as a method to regulate the problem of accounting information asymmetry between the parties to the agency. We are using the Beneish M-score model and the financial analysis equations in the Beneish model for bank data for both the income statement and the financial position to do so. The sample includes 30 Iraqi banks listed on the Iraq Stock Exchange from 2014 to 2017, with the goal of inferring agency problems through EM practices. The results show that there are problems for the agency in the research sample banks throughout the research periods, and the percentages of those problems vary from one year to another. Apart from detecting agency problems, the art of financial ratios that have been used can be useful for auditors in conducting financial analyses, and thus they can be used as tools to detect fraud, given those agency problems resulting from profit manipulation are only aspects of fraud in the financial statements.
There is a global shortage of health care providers needed to address all levels of primary and specialty care. The recent COVID-19 pandemic also highlights the importance and added value of health professionals with specialty training in infectious diseases. In the United States, advanced practice providers (APPs) are being engaged to meet the expanding demand for generalist and specialist patient care. The history and development of advanced practice registered nurses (APRNs) and physician assistants (PAs), are discussed as collaborative healthcare providers to promote better understanding of the ways they can be incorporated into a healthcare system. An example of how APPs are utilized to provide both inpatient and outpatient
... Show MoreWe aimed to examine the potential protective effects of Iraqi
Rats were assigned to four groups, six in each group. Group I: rats were administered a daily oral dose of 1 mL/kg/day of distilled water. Group II: rats were intraperitoneally injected with 70 mg/kg DEN once per week for 10 conse
This research presents a numerical study to simulate the heat transfer by forced convection as a result of fluid flow inside channel’s with one-sided semicircular sections and fully filled with porous media. The study assumes that the fluid were Laminar , Steady , Incompressible and inlet Temperature was less than Isotherm temperature of a Semicircular sections .Finite difference techniques were used to present the governing equations (Momentum, Energy and Continuity). Elliptical Grid is Generated using Poisson’s equations . The Algebraic equations were solved numerically by using (LSOR (.This research studied the effect of changing the channel shapes on fluid flow and heat transfer in two cases ,the first: cha
... Show MoreSemiconductor-based photocatalytic processes are widely applied as ecofriendly technology for degrading organic pollutants. Establishing photocatalytic heterojunctions with Z-type photocarriers transfer pathways is projected to be a superb strategy to enhance photocatalytic behavior. In this paper, novel and stable (0D/2D) heterojunctions of CoS-embedded boron-doped g-C3N4 (CoS/BCN) with a high rate of charges transfer/separation were assembled for degradation of malachite green dye (MG). The CoS/BCN photocatalyst achieves a photodegradation efficiency of 96.9 % within 1 h of LED illumination, which is 2.5 and 1.4-fold enhancement compared with bare g-C3N4 and BCN, respectively. Besides, the results of species-trapping trials exhibited that
... Show MoreIn this study, Titanium Dioxide Nanoparticles were synthesized by an easy and eco-friendly technique (green synthesis) using green tea leaves (Camillia sinensis), Nanoparticles were analyzed using structural and optical analysis, the X-ray pattern showed that Titanium Dioxide NPs had a tetragonal structure with (Face Centered Tetragonal) FCT crystal structure, the UV-visible recorded an absorbance peak near 350 nm and calculated energy band gap was 3.5 eV, all measurements were proved the purity and Nano size of prepared Nanoparticles. Biochemical parameters evaluation also mentioned in this research, these analyzes showed that Titanium Dioxide nanoparticles in particular dose (50 mg/kg) have the ability to reduce blood glucose
... Show MoreA robust and sensitive analytical method is presented for the extraction and determination of six pharmaceuticals in freshwater sediments.
Background: Cyclophosphamide (Cpd), a common immunosuppressive and chemotherapeutic drug, can cause hepatotoxicity by inducing inflammation and oxidative stress. Dapagliflozin (Dapa) and other sodium-glucose cotransporter-2 inhibitors (SGLT2i) have anti-inflammatory and antioxidant properties, and Silymarin is a natural compound extracted from the seeds of the milk thistle plant (Silybum marianum). It is best known for its antioxidant, anti-inflammatory, and hepatoprotective effects.Objective: By measuring oxidative stress, inflammation, and liver regeneration parameters, with an emphasis on the Nrf2/HO-1 pathway and hepatocyte nuclear factors (HNF4α and HNF6), Dapa's hepatoprotective effects in comparison to Sil on Cpd-induced liv
... Show MoreThis study proposes a hybrid predictive maintenance framework that integrates the Kolmogorov-Arnold Network (KAN) with Short-Time Fourier Transform (STFT) for intelligent fault diagnosis in industrial rotating machinery. The method is designed to address challenges posed by non-linear and non-stationary vibration signals under varying operational conditions. Experimental validation using the FALEX multispecimen test bench demonstrated a high classification accuracy of 97.5%, outperforming traditional models such as SVM, Random Forest, and XGBoost. The approach maintained robust performance across dynamic load scenarios and noisy environments, with precision and recall exceeding 95%. Key contributions include a hardware-accelerated K
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