Ferritin is a key organizer of protected deregulation, particularly below risky hyperferritinemia, by straight immune-suppressive and pro-inflammatory things. , We conclude that there is a significant association between levels of ferritin and the harshness of COVID-19. In this paper we introduce a semi- parametric method for prediction by making a combination between NN and regression models. So, two methodologies are adopted, Neural Network (NN) and regression model in design the model; the data were collected from مستشفى دار التمريض الخاص for period 11/7/2021- 23/7/2021, we have 100 person, With COVID 12 Female & 38 Male out of 50, while 26 Female & 24 Male non COVID out of 50. The input variables of the NN m

In this paper, an algorithm is suggested to train a single layer feedforward neural network to function as a heteroassociative memory. This algorithm enhances the ability of the memory to recall the stored patterns when partially described noisy inputs patterns are presented. The algorithm relies on adapting the standard delta rule by introducing new terms, first order term and second order term to it. Results show that the heteroassociative neural network trained with this algorithm perfectly recalls the desired stored pattern when 1.6% and 3.2% special partially described noisy inputs patterns are presented.

In this article, we design an optimal neural network based on new LM training algorithm. The traditional algorithm of LM required high memory, storage and computational overhead because of it required the updated of Hessian approximations in each iteration. The suggested design implemented to converts the original problem into a minimization problem using feed forward type to solve non-linear 3D - PDEs. Also, optimal design is obtained by computing the parameters of learning with highly precise. Examples are provided to portray the efficiency and applicability of this technique. Comparisons with other designs are also conducted to demonstrate the accuracy of the proposed design.

study was conducted on a stretch of Tigris river crossing Baghdad city to determine the concentration of some chlorophenols pollutants. Aqueous samples were preliminary enriched about 500 times and the chlorophenols have determined using high performance liquid chromatography HPLC. Limits of detection LOD were (0.007–0.012 mg L-1), relative standard deviations RSD% were 2.4%–5.59% and relative recoveries were 51.06%– 104.07%. The existence of chlorophenols in Tigris river was in the range 0.023–4.596 mg L-1. The developed method suggested in this study can be applied for routine analysis and monitoring of chlorinated phenols in environmental aqueous samples.

ABSTRACT

This research aim to measure the critical success factors for total quality management applications, in order to know the key and important role played by these factors at applying the total quality management through a comparative study conducted in a number of a private colleges.

The research problem posed a set of questions, the most important ones are: Are the colleges (sample of research) aware of the critical success factors at applying the total quality management? What is the availability of the critical success factors at the work of the colleges (sample of research)? 

What are the critical success factors in the work of the researc

The L. Cretaceous succession is the main reservoir rock in the south of Iraq. Although the upper Jurassic Sargelu Formation is the main source rock in this area; however, the organic-rich interval within the studied succession, is contribute in these huge accumulations of petroleum. The pyrolysis parameters of the succession; Sulaiy, yamama, Zubair, and Nahr Umr formations showed that the main kerogen type is type III and II with moderate to good HI, which they refer to gas and/or oil prone especially in Zubair, Nahr Umr, and Sulaiy formations. The quantity parameters indicate potential source intervals in respect to (TOC). The maturity parameters suggest the threshold and peak of petroleum generation, which Tmax values ranged around 430

Objective: to assess the risk factors of coronary artery disease patients.
Methodology: A non-probability (purposive) sample of (100) patients. The study population consisted of
a sample of adults from both genders whose ages were 30 years and more, and was newly diagnosed as
having CAD by coronary angiography in the cardiac catheterization unit of An Nasiriyah heart center.
Results: The result of the study showed that the most common modifiable risk factors were low HDL-C
levels (58%), smoking (53%), hypertension (46%), diabetes mellitus (34%), obesity (30%), high
triglycerides (19%), hypercholesterolemia (17%), and high LDLC (14%). All these factors were positively
and significantly associated with the development

The monitoring of lotic ecosystems is important for environmental health after war crisis. This study aimed to detect the fate of the sixteen polycyclic aromatic hydrocarbon compounds (PAHs) as priority pollutants in the water and sediment of Al-Hussainya River in Karbala Province. The results indicated that the concentrations in water samples ranged from 0.24–58.72 ηg.L^-1 for each of the benzo(a) pyrene and benzo(g, h, i)perylene. The concentrations in sediment samples have been observed to be in a range of 0.36–119.06 μg.g^-1 for naphthalene and benzo(g,h,i)perylene. Benzo(g,h,i)perylene recorded the highest concentrations in each of water and sediment samples as compared with the other compound

     Wasit Governorate is characterized by industrials activities such as groups of asphalts and bricks factories, oil fields and thermal power plant, in addition to the agricultural activity that is widely separated, which leads to pollution of the surface soils with heavy metals. The main objective in this research is to assess heavy metals pollution and understand the distribution in the surface soils in the studied area.  Twenty two surface soils samples were collected from 6 districts and 4 subdistricts within Wasit Governorate during April 2017. The results obtained showed that grain size analyzes are classified as sandy mud (sand 9.5%, silt 50.8 % and clays 39.8%). In the term of geochemic