With the increasing demands to use remote sensing approaches, such as aerial photography, satellite imagery, and LiDAR in archaeological applications, there is still a limited number of studies assessing the differences between remote sensing methods in extracting new archaeological finds. Therefore, this work aims to critically compare two types of fine-scale remotely sensed data: LiDAR and an Unmanned Aerial Vehicle (UAV) derived Structure from Motion (SfM) photogrammetry. To achieve this, aerial imagery and airborne LiDAR datasets of Chun Castle were acquired, processed, analyzed, and interpreted. Chun Castle is one of the most remarkable ancient sites in Cornwall County (Southwest England) that had not been surveyed and explored

          A histological study showed the wall of the stomach in Pica pica and Herpestes javanicus consists of four layers: mucosa, submucosa, muscularis externa and serosa. Also, the present study showed many  differences in the histological structures of the stomach for each in both types. The stomach of P. pica consists of two portions: the proventiculus and gizzard, while the stomach of H. javanicus consists of three portions: cardiac, fundic and pyloric regions. The mucosa layer formed short gastric folds, named plicae. In the proventiculus of P. pica, sulcus is found between each two plicae, but the folds called gastric p

          A histological study showed the wall of the stomach in Pica pica and Herpestes javanicus consists of four layers: mucosa, submucosa, muscularis externa and serosa. Also, the present study showed many  differences in the histological structures of the stomach for each in both types. The stomach of P. pica consists of two portions: the proventiculus and gizzard, while the stomach of H. javanicus consists of three portions: cardiac, fundic and pyloric regions. The mucosa layer formed short gastric folds, named plicae. In the proventiculus of P. pica, sulcus is found between each two plicae, but the folds called gastric pits in the gizzard, which are full with koilin. Lamina properia in both types contained gastric g

The levels of circulating angiogenic and anti-angiogenic factors, namely vascular endothelial growth factor–A (VEGF-A) and soluble vascular endothelial growth factor receptor-1 (sVEGFR-1), have been linked to the development of renal dysfunction due to the proliferation of microvasculature within the kidneys of type 2 diabetic (T2DM) patients. The study aims to scrutinize serum levels of VEGF and sVEGFR-1 in a sample of Iraqi diabetic nephropathy patients to support their reliability as markers for the prediction of nephropathy in type 2 diabetes mellitus patients as well as to assess the ACE inhibitor’s effect on the levels of these two markers. Method: The ninety participants of this case-control study were split into three gr

Big developments in technology have led to upset the balance of ideas, given of its own post new properties for products not provided by traditional technology, especially economic units operating within the industrial sector, and therefore it is important to develop the Iraqi industrial sector and interest to do its vital role in light Of progress technological.The research aims to Find the use of advanced manufacturing technologies that lead to customized production and quality appropriate whether they are low quality and low cost or low cost and suitable quality or high quality and high cost to win customer satisfaction.While the important conclusions is that the application of advanced manufacturing technology is not limited to techn

The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system