In this paper a theoretical attempt is made to determine whether changes in the aorta diameter at different location along the aorta can be detected by brachial artery measurement.  The aorta is divided into six main parts, each part with 4 lumps of 0.018m length. It is assumed that a desired section of the aorta has a radius change of 100,200, 500%. The results show that there is a significant change for part 2 (lumps 5-8) from the other parts. This indicates that the nearest position to the artery gives the significant change in the artery wave pressure while other parts of the aorta have a small effect.

One of the most Interesting natural phenomena is clouds that have a very strong effect on the climate, weather and the earth's energy balance. Also clouds consider the key regulator for the average temperature of the plant. In this research monitoring and studying the cloud cover to know the clouds types and whether they are rainy or not rainy using visible and infrared satellite images. In order to interpret and know the types of the clouds visually without using any techniques, by comparing between the brightness and the shape of clouds in the same area for both the visible and infrared satellite images, where the differences in the contrasts of visible image are the albedo differences, while in the infrared images is the temperature d

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

A robust and sensitive analytical method is presented for the extraction and determination of six pharmaceuticals in freshwater sediments.

Background: The bond strength of root canal sealers to dentin and gutta-percha seems to be an important property for maintaining the stability of root canal filling, which potentially influences both leakage and root strength. The objective of this, in vitro, study was to evaluate the shear bond strength of three different endodontic sealers (Gutta-Flow, AH Plus, Apexit Plus) to dentin, in the presence and absence of the smear layer and gutta percha. Material and Methods: After slicing off the occlusal 2mm of 60 extracted human maxillary premolar teeth, the exposed dentin served as the tested surfaces; the teeth were fixed with cold cure acrylic, and were divided into two groups according to the smear layer presence, group A without smear

Visceral leishmaniasis is a neglected tropical disease on the rise in different regions of Iraq, especially in areas with poor hygiene and among refugee populations. The effectiveness of existing chemotherapy for leishmaniasis is constrained by its high toxicity, cost, and the development of drug resistance. The current research examined various concentrations (ranging from 125 to 1000 μM) of lupeol to evaluate its ability to boost the generation of nitric oxide, which has anti-leishmanial properties, in an ex-vivo macrophage model. Griess assay was used to detect the nitric oxide (NO) production in Leishmania donovani infected U937 cell-line macrophages along 24 and 48 hours post treated. The nitric oxide concentration was signifi

NiO nanoparticle synthesis by chemical method and characterized by XRD with crystal size 11.72
nm and grain size 13 nm from FESEM image also NiO micro used ,two NiO as an additive to evaluate the
possibility of producing photodegradable polymers, the practical application of solid-phase photocatalytic
degradation of polyvinyl chloride (PVC- NiO composite films) was investigated. PVC has a negative impact
on the environment since its polymer degrades slowly, yet it has a wide range of industrial applications and
the amount used shows no evidence of diminishing use. Thus, a synthesis of modified PVC- NiO micro and
nano has been studied with 0, 50, 100, 150, 200, 250, and 300 (hours) as irradiation time a

This study include design and synthesis of 2 derivatives of compounds consisting of mefenamic acid, glycine and organic nitrates (2-nitrooxy ethanol or 1,3-dinitrooxy-2-propanol). Nitric oxide NO has been reported to support many of the same mucosal protection mechanisms as prostaglandins and is sufficient for acute gastroprotection and ulcer healing. So we suppose these 2 compounds would reduce non-steroidal anti-inflammatory drugs NSAIDs gastrointestinal side effect.

Key words: Non-Steroidal anti-inflammatory dr