Image of landsate-7 taken by thematic mapper was used and classified using supervised method. Results of supervised classification indicated presence of nine land cover classes. Salt-soils class shows the highest reflectance value while water bodies' class shows the lowest values. Also the results indicated that soil properties show different effects on reflectance. There was a high significant positive relation of carbonate, gypsum, electric conductivity and silt content, while there was a week positive relation with sand and negative relation with organic matter, water content, bulk density and cataion exchange capacity.
The Catharanthus roseus plant was extracted and converted to nanoparticles in this work. The Soxhlet method extracted alkaloid compounds from the plant Catharanthus roseus and converted them to the nanoscale. Chitosan polymer was used as a linking material and converted to Chitosan nanoparticles using Sodium TriPolyPhosphate (STPP). The extracted alkaloids were linked with Chitosan nanoparticles CSNPs by maleic anhydride to get the final product (CSNPs- Linker- alkaloids). The synthesized (CSNPs- Linker- alkaloids) was characterized using SEM spectroscopy UV–Vis., Zeta Potential, and HPLC High-Performance Liquid Chromatography. Scanning electron microscope (SEM) analysis shows that the Chitosan nanoparticles (CSNPs) have small dim
... Show MoreCommunication of the human brain with the surroundings became reality by using Brain- Computer Interface (BCI) based mechanism. Electroencephalography (EEG) being the non-invasive method has become popular for interaction with the brain. Traditionally, the devices were used for clinical applications to detect various brain diseases but with the advancement in technologies, companies like Emotiv, NeuoSky are coming up with low cost, easily portable EEG based consumer graded devices that can be used in various application domains like gaming, education etc as these devices are comfortable to wear also. This paper reviews the fields where the EEG has shown its impact and the way it has p
Background: Denture cleansing was an important step that could prevent the spread of infection and improve a patient's health, the durability of the dentures, and the overall quality of life; therefore, it was necessary to choose a suitable cleanser that, in addition to being effective, did not have an unfavorable effect on the qualities of the denture base resin itself when used for an extended period. For this purpose, this study aimed to evaluate the effect of tea tree oil (TTO) on Candida albicans adhesion and the surface roughness property of poly(methyl methacrylate) denture material after immersion in TTO. Methods: A total of 55 heat-cured acrylic resin specimens were used for C. albicans adherence and surface roughness tests. The
... Show MoreBackground: Although bleaching is typically considered a safe procedure, various investigations have found minor negative effects and changes in mineral composition. The aim was to Evaluate and compare the efficacy of using Nanohydroxyapatite serum on surface microhardness of enamel surface before and after bleaching with chemically cured Boost bleaching. Material and methods: ten sound human permanent upper and lower premolar teeth were used and their roots were removed 2 mm apically to the cementoenamel junction, the crowns were sectioned mesiodistally into two halves buccal and lingual/palatal, the buccal surface was further subdivided into two halves. The samples were embeded in an acrylic resin, resulting in 30 specimens divide
... Show MoreImmune-mediated hepatitis is a severe impendence to human health, and no effective treatment is currently available. Therefore, new, safe, low-cost therapies are desperately required. Berbamine (BE), a natural substance obtained primarily from
This c
Data scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for