Coronavirus disease (Covid-19) has threatened human life, so it has become necessary to study this disease from many aspects. This study aims to identify the nature of the effect of interdependence between these countries and the impact of each other on each other by designating these countries as heads for the proposed graph and measuring the distance between them using the ultrametric spanning tree. In this paper, a network of countries in the Middle East is described using the tools of graph theory.

The liver of marsh harrier grossly appeared as large, bi-lobed organ divided into left and right lobes, which are approximately equal in size and not divided into secondary lobes. Histologically, the liver of marsh harrier was found to contain numerous lobules which are not well defined by the connective tissue of the septa except that surrounded the portal triads. The parenchyma of liver composed of irregular branching cords of hepatocytes organized in double rows alternating with tortures path sinusoids which are lined with flattened endothelial cells and large, irregular outlined kupffer cells. Hepatic cords arranged in a radial pattern around the central vein of the liver lobule while in a subscapsular region they run parallel to the ca

The Iraqi and Iranian pottery has a significant role in the contemporary world pottery space, despite the fact that influences created those formulation, thus the researcher supposes that there is a relation between the potter and his environment within Iraq's environment and Iran's environment, which are similar at times and different at other times. The researcher, hence, found himself in front of a number of questions:
1- How much was the Iraqi potter inspired by the environment compared to the Iranian potter?
2- Has the Iraqi and Iranian pottery been really inspired by the environment items or there were modified metaphors?
The current research aims at (identifying the influential environmental characteristics in the Iraq

This paper demonstrates the design of an algorithm to represent the design stages of fixturing system that serve in increasing the flexibility and automation of fixturing system planning for uniform polyhedral part. This system requires building a manufacturing feature recognition algorithm to present or describe inputs such as (configuration of workpiece) and built database system to represents (production plan and fixturing system exiting) to this algorithm. Also knowledge – base system was building or developed to find the best fixturing analysis (workpiece setup, constraints of workpiece and arrangement the contact on this workpiece) to workpiece.

Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with