The main challenge is to protect the environment from future deterioration due to pollution and the lack of natural resources. Therefore, one of the most important things to pay attention to and get rid of its negative impact is solid waste. Solid waste is a double-edged sword according to the way it is dealt with, as neglecting it causes a serious environmental risk from water, air and soil pollution, while dealing with it in the right way makes it an important resource in preserving the environment. Accordingly, the proper management of solid waste and its reuse or recycling is the most important factor. Therefore, attention has been drawn to the use of solid waste in different ways, and the most common way is to use it as an alternative

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

The purpose of the current article lies in determining  the impact of the suggestive  exercises on the development of  the mental capabilities of children. The researchers used the experimental method with a single-group design, which was appropriate for the core of the current article . The study samble  has been specified as children aged 4-6 years in Umm Al-Rabi'een Kindergarten, with a total of 95 children. The study samble  (15 children) was randomly selected.  . After the exercises were completed, the post-tests have been carried out  on the sample  with similar circumstances as that of  pre-tests.  Researchers used statistical methods in the SPSS program. After the results were presented, analyzed, and discussed, The resear

Radiotherapy is the branch of clinical medicine concerned with the application of ionizing radiation in the treatment of disease. And it is used to killing of cancer cells in a tissue using ionizing radiation while keeping the sparing of healthy cells at acceptable level. X-ray beams are used to deposit absorbed dose at depth within a patient at the site of the tumor. The aim of this work is studying the relationship between the depth dose and the field size in water phantom and homogenous actual planning. In our work, the dose distribution at different depths (zero-18 cm) deep at1cm interval treated with field size (10×10 and 20×20) cm2 were studied. Results show that high similarity between water phantom and actual planning for

Radiotherapy is the branch of clinical medicine concerned with the application of ionizing radiation in the treatment of disease. And it is used to killing of cancer cells in a tissue using ionizing radiation while keeping the sparing of healthy cells at acceptable level. X-ray beams are used to deposit absorbed dose at depth within a patient at the site of the tumor. The aim of this work is studying the relationship between the depth dose and the field size in water phantom and homogenous actual planning. In our work, the dose distribution at different depths (zero-18 cm) deep at1cm interval treated with field size (10×10 and 20×20) cm2 were studied.
Results show that high similarity between water phantom and actual planning for th