Gingival crevicular fluid (GCF) may reflect the events associated with orthodontic tooth movement. Attempts have been conducted to identify biomarkers reflecting optimum orthodontic force, unwanted sequallea (i.e. root resorption) and accelerated tooth movement. The aim of the present study is to find out a standardized GCF collection, storage and total protein extraction method from apparently healthy gingival sites with orthodontics that is compatible with further high-throughput proteomics. Eighteen patients who required extractions of both maxillary first premolars were recruited in this study. These teeth were randomly assigned to either heavy (225g) or light force (25g), and their site specific GCF was collected at baseline and aft

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Oil from Brassca campestris (local variety) was extracted with hexane using Soxhlet. The extracted oil was characterized and its antimicrobial activity was determined as well. The content of extracted oil was 40% with 0.5% of volatile oil .Oil was immiscible with polar solvent such as ethanol, acetone and water, while it was easily miscible with chloroform due to its hydrophobicity. The result of organoleptic tests revealed that the oil is clear yellow in color and odorless with acceptable taste. The oil was stable at 4 -25 C? for a month. Refractive index (RI) of oil was 1.4723 with density of 0.914, [both at 4-25 C?]. Boiling point 386 C?. Infra red spectroscopy (IR) indicated the presence of different chemical groups (C=C

In the image processing’s field and computer vision it’s important to represent the image by its information. Image information comes from the image’s features that extracted from it using feature detection/extraction techniques and features description. Features in computer vision define informative data. For human eye its perfect to extract information from raw image, but computer cannot recognize image information. This is why various feature extraction techniques have been presented and progressed rapidly. This paper presents a general overview of the feature extraction categories for image.

The study aims to identify the role of Nizwa University in disseminating the concept of knowledge economy among students from the point of view of the faculty members. The researchers used the descriptive approach, as well as used a questionnaire consisting of (20) items distributed into (4) fields. It was administered to a sample of (93) Faculty members. The results of the study showed that the role of the Nizwa University in spreading the concept of knowledge economy among students from the point of view of the faculty members was of a moderate degree. The education and training field came first with the highest average, while the scientific research and innovation field came in the last level. There were no statistically significant d

The current study included details of the anatomical characteristics of vegetative parts including the root, stem, leaf in cultivated Iraq for the species Brassciaaleraceacabbage, where the study dealt with the stomatal index and the rate of both the length and width of the stomatal complex and the thickness of the periderm, the tissue, cortex, vascular cylinder and pith. The parts were taken and measured after the plant was treated with brassinolide and the treated species with brassinolide and non-treated were measured and the study showed that there was a clear variation in the properties above.

Education around the world has been negatively affected by the new coronavirus disease (COVID-19) pandemic. Many institutions had to transition to distance learning in compliance with the enforced safety measures. Distance learning might work well for settings with stable internet connections, professional technical teams, and basic implementation of technology in education. In contrast, distance learning faces serious challenges in less fortunate settings with inferior infrastructure. This report aims to shed light on the immediate action steps taken at a leading pharmacy school in Iraq to accommodate for the enforced changes in pharmacy education. The University of Baghdad College of Pharmacy went from less than minimal technology impl