. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a

In this paper, some relations between the flows and the Enveloping Semi-group were studied. It allows to associate some properties on the topological compactification to any pointed flows. These relations enable us to study a number of the properties of the principles of flows corresponding with using algebric properties. Also in this paper proofs to some theorems of these relations are given.

Background : The dermatophytesare taxonomically related fungi causing different skin infections referred to as tineas in man or ringworm in man and animals . Objective:This study was established to investigate theof effect of yellow sap and gel of Aloe vera on skin of the rabbits which infected with T.verrucosum. Methods : Twelveskin biopsy were taken from rabbits for histopathological study to know the the effects of the T.verrucosumand treated with yellow sap and gel. Results : the results of histopathological study of effect of yellow sap and gel of Aloe vera on skin of the rabbits which infected with T.verrucosum showed the concentration of the gel of aloe vera at 75% was more effected to treat the infective area of skin with T.verrucos

MS Elias, RGM AL-helfy, Plant Archives, 2019

The Influence of Some Vitamins and Biochemical Parameters on Iraqi Females’ Patients with Malignant Breast Cancer"

The current study was designed to investigate the effect of Tilletia smut spores on histopathological changes in liver and kidney in mice. Twenty animals were divided into two equal groups, 10 mice each, control group fed on normal diet and the treated groups were fed on a mixture of 50% normal diet with 50% wheat infected with Tilletia for 30 days. Histopathological sections taken from liver and kidney treated with Tilletia revealed several alterations. The changes in liver included, multiple granulomatous lesions, area of coagulation necrosis, vacuolar degeneration in the cytoplasm of hepatocytes, proliferation of hepatocytes with formation of pseudolobull which initiates for procancer. Whereas in the kidney, the changes included

An experimental and numerical study has been carried out to investigate the heat transfer by natural convection in a three dimensional annulus enclosure filled with porous media (silica sand) between two inclined concentric cylinders with (and without) annular fins attached to the inner cylinder under steady state condition; The experiments were carried out for a range of modified Rayleigh number (0.2 ≤Ra*≤ 11) and extended to Ra* =500 for numerical study, annulus inclination angle of (δ = 0˚, 30˚, 60˚ and 90˚). The numerical study was to write the governing equation under an assumptions used Darcy law and Boussinesq’s approximation and then solved numerically using finite difference approximation. It was found that the averag

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