Carbon dioxide geo-sequestration (CGS) into sediments in the form of (gas) hydrates is one proposed method for reducing anthropogenic carbon dioxide emissions to the atmosphere and, thus reducing global warming and climate change. However, there is a serious lack of understanding of how such CO2 hydrate forms and exists in sediments. We thus imaged CO2 hydrate distribution in sandstone, and investigated the hydrate morphology and cluster characteristics via x-ray micro-computed tomography in 3D in-situ. A substantial amount of gas hydrate (∼17% saturation) was observed, and the stochastically distributed hydrate clusters followed power-law relations with respect to their size distributions and surface area-volume relationships. The layer-

Objective: The study the association of procalcitonin (PCT) and c-reactive protein (CRP) levels in COVID-19 patients and it's role as a guide in progress and management of those patients. Methodology: This cross-sectional study analyzed 200 CIOVID-19 patients in a single privet center in Baghdad, Iraq from January 1, 2021 to January 1, 2022. Demographic data like age, sex, and clinical symptoms were recorded. High sensitivity CRP and PCT in the serum were measured via dry fluorescence immunoassay (Lansionbio-China). Results: Out of 200 patients, 50 had moderate Covid and 150 had severe disease. Mean serum PCT levels was 0.039±0.05 ng/mL in the moderate group (range 0.011-0.067) and 0.43±0.21 ng/mL in the severe group (range 0.21

Background: since December 2019, China and in particularly Wuhan, faced an unprecedented an outbreak challenge of coronavirus disease 2019, caused by the severe acute respiratory syndrome coronavirus 2. Clinical characteristics of Iraqi patients with COVID-19 and risk factors for mortality needed to be shared with the health care providers to improve the overall disease experience. Methods: prospective, single-center study recruited patients with confirmed SARS-CoV-2 infection who were admitted to Al-Shifaa Isolation Center / Baghdad Medical City between the mid of March and the end of April 2020 until had been discharged or had died. Demographic data, information on clinical signs, symptoms, at presentation, treatment, have been collected

Purpose: The current research attempts to diagnosis the reflection level of Information Technology (IT) Capabilities (Architectural, infrastructure, human resources, relationships resources, and dynamic capabilities) at Baghdad soft drinks Company/Al- Zafaraniya to achieving the competitive superiority represented by indicators (Cost, quality, flexibility, delivery and innovation). Recognizing the importance of the subjects studied, and because of the importance of the expected results of the field under consideration.

Design/Methodology/Approach: The experimental method has been used, the questionnaire used to collect th

This paper tries to understand the poetic reference in the images of woman, she-camel, horse and their manifestations in Tarafah-ibnulAbd's poetry. There has got my attention the fact that these three images have their own distinct taste which is characterised by a clear rhythm, let alone the  lively nature that is filled with liveliness and activity to be in harmony with the poet's youth. For these three images represented the best manifestations of his psychological and artistic poetics. The paper adopts an artistic analysis to arrive at the psychological aspects of these experiences-the woman, the she-camel, and the horse- and to understand the functions of their images and symbolic reference.

With the continuous progress of image retrieval technology, the speed of searching for the required image from a large amount of image data has become an important issue. Convolutional neural networks (CNNs) have been used in image retrieval. However, many image retrieval systems based on CNNs have poor ability to express image features. Content-based Image Retrieval (CBIR) is a method of finding desired images from image databases. However, CBIR suffers from lower accuracy in retrieving images from large-scale image databases. In this paper, the proposed system is an improvement of the convolutional neural network for greater accuracy and a machine learning tool that can be used for automatic image retrieval. It includes two phases

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

Due to the huge variety of 5G services, Network slicing is promising mechanism for dividing the physical network resources in to multiple logical network slices according to the requirements of each user. Highly accurate and fast traffic classification algorithm is required to ensure better Quality of Service (QoS) and effective network slicing. Fine-grained resource allocation can be realized by Software Defined Networking (SDN) with centralized controlling of network resources. However, the relevant research activities have concentrated on the deep learning systems which consume enormous computation and storage requirements of SDN controller that results in limitations of speed and accuracy of traffic classification mechanism. To fill thi