In order to achieve overall balance in the economy to be achieved in different markets and at one time (market commodity, monetary and labor market and the balance of payments and public budget), did not provide yet a model from which to determine the overall balance in the economy and the difficulty of finding the inter-relationship between all these markets and put them applied in the form of allowing the identification of balance in all markets at once.

One of the best models that have dealt with this subject is a model
(LM-BP-IS), who teaches balance in the commodity market and money market and balance of payments and the importance of this issue This research tries to shed light on the reality

Polycystic ovary syndrome (PCOS) is the most endocrine problem in women of regenerative age. PCOS women typically belong to an age and sex group which is at higher risk for severe coronavirus disease (COVID-19). COVID-19 targets cells through angiotensin-converting enzyme 2 (ACE2) receptor presents on cells in veins, lungs, heart, digestion tracts, and kidneys. Renin-Angiotensin System (RAS) over activity has likewise been described in metabolic disorders; type 2 diabetes mellitus (T2DM), and conditions shared by women with polycystic ovary condition. The point of this study is to know the job of renin and ACE2 in PCOS and coronavirus and its relationship with hormones and other metabolic parameters related. The study groups consist of 1

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 offers a systemic review of the deep learning methods to detect violence on campus, which is a critical issue in intelligent surveillance to improve the student safety and prompt cut off of violent accidents. The review reviews studies published 2018-2025, concentrating on model structure to detect fights, bullying, vandalism, and aggressive behavior on problematic campuses due to occlusion and light variations and complicated human interactions. The research design includes a comparative study of different deep learning networks, such as CNNs, RNNs, 3D CNNs, attention-based networks, transformers, graph neural networks, neuro-fuzzy, and multimodal systems and federated learning methods. The paper also assesses benchmark

The main idea that led me to write such research paper within the framework of Germanic linguistics is that I have not found any topic dealing with the term correlate in the German language, except in several articles in linguistic journals as well as one topic in a book describing the use of such a linguistic phenomenon in the language system. The research initially deals with the definition of the correlate at the level of the German language system. Correlate is unity describes specific relation of two sentences and identifies denoted constructs. Correlate is called a placeholder at the syntactic level because it does not occupy its original topological fields in the syntactic structure. The correlate (es) or the prepositiona

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

The Machine learning methods, which are one of the most important branches of promising artificial intelligence, have great importance in all sciences such as engineering, medical, and also recently involved widely in statistical sciences and its various branches, including analysis of survival, as it can be considered a new branch used to estimate the survival and was parallel with parametric, nonparametric and semi-parametric methods that are widely used to estimate survival in statistical research. In this paper, the estimate of survival based on medical images of patients with breast cancer who receive their treatment in Iraqi hospitals was discussed. Three algorithms for feature extraction were explained: The first principal compone

Background: COVID-19 has caused a considerable number of hospital admissions in China since December 2019. Many COVID-19 patients experience signs of acute respiratory distress syndrome, and some are even in danger of dying. Objective: to measure the serum levels of D-dimer, Neutrophil-Lymphocyte count ratio (NLR), and neopterin in patients hospitalized with severe COVID-19 in Baghdad, Iraq. And to determine the cut-off values (critical values) of these markers for the distinction between the severe patients diagnosed with COVID‐19 and the controls. Materials and methods: In this case-control study, we collect blood from 89 subjects, 45 were severe patients hospitalized in many Baghdad medical centers who were diagnosed with COVID

These days, it is crucial to discern between different types of human behavior, and artificial intelligence techniques play a big part in that.  The characteristics of the feedforward artificial neural network (FANN) algorithm and the genetic algorithm have been combined to create an important working mechanism that aids in this field. The proposed system can be used for essential tasks in life, such as analysis, automation, control, recognition, and other tasks. Crossover and mutation are the two primary mechanisms used by the genetic algorithm in the proposed system to replace the back propagation process in ANN. While the feedforward artificial neural network technique is focused on input processing, this should be based on the proce