The pandemic of coronavirus disease 2019 (COVID-19), first reported in China, in December 2019 and since then the digestive tract involvement of  COVID-19 has been progressively described. In this review, I summed recent studies, which have addressed the pathophysiology of COVID-19-induced gastrointestinal symptoms, their prevalence, and bowel pathological and radiological findings of infected patients. The effects of gut microbiota on SARS-CoV-2 and the challenges of nutritional therapy of the infected patients are depicted.  Moreover, I provide a concise summary of the recommendations on the management of inflammatory bowel disease, colorectal cancer, and performing endoscopy in the COVID era. Finally, the COVID pancreatic re

This paper presents a modified training method for Recurrent Neural Networks. This method depends on the Non linear Auto Regressive (NARX) model with Modified Wavelet Function as activation function (MSLOG) in the hidden layer. The modified model is known as Modified Recurrent Neural (MRN). It is used for identification Forward dynamics of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot. This model is also used in the design of Direct Inverse Control (DIC). This method is compared with Recurrent Neural Networks that used Sigmoid activation function (RS) in the hidden layer and Recurrent Neural Networks with Wavelet activation function (RW). Simulation results shows that the MRN model is bett

Tax fraud is following different methods of tax evasion (bypassing the laws, instructions and regulations related to tax) by not showing the real taxable income by using laws, instructions and regulations improperly, and because of the weak basic role of forensic accounting in detecting and reducing tax fraud, the problem has become more influential on the state general tax income. The main objective of the research is to identify forensic accounting and the extent to how it can be applied in the General Tax Authority to assist forensic authorities in issuing judgments in fraud cases. To achieve the objectives of the research, the descriptive analytical approach was used to reach the topic of the research, and a questionnaire (co

A Forensic Accounting is represent science that deals with the application of knowledge in the areas of accounting, finance, tax and audit for the analysis, investigation, inquiry, inspection and testing issues in the civil law and criminal law in an attempt to reach the truth through which enable the Forensic Accountant to provide his Expert opinion , forensic accounting plays a major role by providing a range of important services in the field of investigation for fraud and litigation support, As one of the most important legal and accounting functions is to investigate allegations of alleged by the related parties, especially those allegations related to the existence of fraud, since the goal of judicial accountant will depend

Celery and coriander are vastly applied in modern medicine and traditionally because various medicinal and nutritional benefits depend on their medicinal characteristics. The study aimed to detect, isolate and compare extracts contents of phenolic acids (caffeic and p-coumaric acids) in ethyl acetate fraction of fresh and dry aerial parts of coriander (Coriandrum sativum L.) and celery (Apium graveolens L.) of the Apiaceae family. The extraction of these constituents was carried out by maceration method using 70% ethanol and fractionation was done by using petroleum ether, and ethyl acetate. The existence of caffeic and p-coumaric acids in aerial part extracts of two plants was identified by thin-layer chromatography (TLC) and high-

Keys for 22 species representing 10 genera of Thripidae were provided collection of
samples carried out during 1999-2001 in different localities in the middle of Iraq. Of them
four species are described as new to science, Frankliniella megacephala sp. nov; Retithrips
bagdadensis sp. nov; Chirothrips imperatus sp. nov; Taeniothrips tigridis sp. nov; Another
fourteen species are recorded for the first time in Iraq; Thrips meridionalis (Pri.);
Microcephalothrips abdominils (Crawford Scolothrips sexmaculatus (Pergande),);Scolothrips
pallidus (Beach); Scritothrips mangiferae Pri.; Frankliniella tritici Bagnall; Frankliniella
schultzie Trybom; Frankliniella unicolor Morgan; Retithrips aegypticus Marchal; Retithrips
java

Data hiding is the process of encoding extra information in an image by making small modification to its pixels. To be practical, the hidden data must be perceptually invisible yet robust to common signal processing operations. This paper introduces a scheme for hiding a signature image that could be as much as 25% of the host image data and hence could be used both in digital watermarking as well as image/data hiding. The proposed algorithm uses orthogonal discrete wavelet transforms with two zero moments and with improved time localization called discrete slantlet transform for both host and signature image. A scaling factor ? in frequency domain control the quality of the watermarked images. Experimental results of signature image

In this paper, integrated quantum neural network (QNN), which is a class of feedforward

neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that

   Lithology identification plays a crucial role in reservoir characteristics, as it directly influences petrophysical evaluations and informs decisions on permeable zone detection, hydrocarbon reserve estimation, and production optimization. This paper aims to identify lithology and minerals composition within the Mishrif Formation of the Ratawi Oilfield using well log data from five open hole logs of wells RT-2, RT-4, RT-5, RT-6, and RT-42. At this step, the logging lithology identification tasks often involve constructing a lithology identification model based on the assumption that the log data are interconnected. Lithology and minerals were identified using three empirical methods: Neutron-Density cross plots for lithology id