Sea level rise (SLR) due to climate change is affecting the coastline, causing shoreline changes, the degradation of mangrove forests, and the destruction of coastal resources. This is the cause of a huge amount of mangrove degradation in many parts of the Ganges–Brahmaputra–Meghna delta. A total of 90% of people have been forced to migrate from the island due to extreme weather conditions. In this study, remote sensing (RS) and geographic information system (GIS) techniques were used for LULC change and shoreline shift analyses of Ghoramara Island. LULC classification was carried out using thirty years of Landsat datasets with intervals of ten years (1990 and 2000) and intervals of five years (2005, 2010, 2015, and 2020). The classific

Methotrexate (MTX) is one of the most effective medications to treat rheumatoid arthritis (RA).Aserum of 60 Iraqi male patients suffering from RA as (G1) was newly diagnosis and the same patient in G1 after taking MTX as G2 and 40 Iraqi male healthy control as G3. Nesfatin-1 (Nf-1) is belong to the adipokine family withpleiotropic effect. Nf-1 has been found in different tissues, including stomach, pancreas, bone cells, cartilage and heart. Retinol binding protein (RBP4) was known as transpoter of retinol from its storage sites in the liver to the extrahepatic tissues. Moreover, RBP4 acts as adipokine and contributes in the pathophsyology of prototypic inflammatory disease, rheumatoid arthritis (RA). The results showed a significant increas

Background: Celiac disease is an autoimmune chronic disease that affects the human’s intestine and subsequently reflects its effect on the entire body health by retardation the absorption and immune mediated complications cause the involvement of oral health. The present study intended to evaluate the impact of the histopathological disease activity upon dental enamel defects and dental caries.

Subjects and methods: Forty celiac-diseased patients aged 7-11 years were collected from 3 different teaching hospitals in Baghdad classified by means of the histopathological activity of the intestinal disease according to modified Marsh-Ros

Hypothesis Nanofluid flooding has been identified as a promising method for enhanced oil recovery (EOR) and improved Carbon geo-sequestration (CGS). However, it is unclear how nanoparticles (NPs) influence the CO2-brine interfacial tension (γ), which is a key parameter in pore-to reservoirs-scale fluid dynamics, and consequently project success. The effects of pressure, temperature, salinity, and NPs concentration on CO2-silica (hydrophilic or hydrophobic) nanofluid γ was thus systematically investigated to understand the influence of nanofluid flooding on CO2 geo-storage. Experiments Pendant drop method was used to measure CO2/nanofluid γ at carbon storage conditions using high pressure-high temperature optical cell. Findings CO2/nano

Foreign direct investment (FDI) is one of the most practical types of foreign investment. FDI contributes to job creation, foreign exchange earnings and national income escalation, improving semi-skill and skilled labor. Based on our knowledge, this paper is the first study attempting to investigate the effect of political stability on the FDI in Turkey using an econometric approach. Achieving this objective, a co-integration analysis was conducted between the FDI and its determinants in the short-run and long-run including “macroeconomic indicators” and “Political Stability (PS)” in Turkey. Using annual data from 1974 to 2017 via Auto-Regressive Distributed Lag (ARDL) model. The results confirm the positive correlation betwe

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial