Desert truffle is considered as a type of Syrian wild fungi that spreads heavily, and it occupies important rank in folk medicine, where its aqueous extract is used for the treatment of some eye and skin illnesses, and people prefer the use of black truffle. This work interested in studying of the most available species; Terfezia claveryi (black) and Tirmania pinoyi (white). The extracts of the two species of truffle were prepared by maceration with water, methanol, and ethanol 70%. Their total phenolic contents (TPC) and total flavonoid contents (TFC) were analyzed using Folin-ciocalteu and Aluminum chloride methods respectively, and their antioxidant activities was tested using 2,2-diphenyl-1-picrylhydrazyl (DPPH) and Ferric Reducing Antioxidant Power (FRAP) methods, after microscopic examination and detection of phytochemical components. Then, phenolic profile of ethanolic 70% extract of black truffle T.claveryi was studied by using LC-MS/MS. The values of TPC were between 25.3-43.6 mg GAE/g dry extract and TFC were between 2.5-6.8 mg QE/g dry extract. The values of DPPH (IC50) and FRAP were between 5.6-9.0 mg/ml and 90.1-153.4 µmol AAE/g dry extract respectively. There is a great similarity in content and activity of two species, also the aqueous extract is similar to other extracts in content and activity, and this means that the method of extract preparation in traditional medicine is reliable. It has been predicted about 14 phenolic compounds in the extract; as p-Hydroxy benzoic acid, Syringic acid and trans-Cinnamic acid. As a result, both truffle species are a new rich resource of antioxidant compounds which are usable in nutritional, cosmetic, and therapeutic applications.
The insulation system of a machine coil includes several layers made of materials with different characteristics. The effective insulation design of machine coils, especially in the machine end winding, depends upon an accurate model of the stress grading system. This paper proposes a modeling approach to predict the transient overvoltage, electric field, and heat generation in machine coils with a stress grading system, considering the variation of physical properties in the insulation layers. A non-uniform line model is used to divide the coil in different segments based on material properties and lengths: overhang, stress grading and slot. The cascaded connection of chain matrices is used to connect segments for the representation of the
... Show MoreOne of the most important problems that would continuously face the Higher education organizations is how to improve the service level presented by them, and how this can lead to increase demand for services of this organizations.As this issue has exhausted many organizations pushed some of them to withdraw from the market Because of weaknesses in their services. Here lies the importance of this matter to be given more attention in order to maintain the organization competitive position. According to that, The selection of the research title (The Impact of Quality on the Level of the University Service Request) which seeks to measure the impact of service quality on the level of demand, At a time when world&
... Show MoreNon-thermal or cold plasma create many reactive species and charged particles when brought into contact with plant extracts. The major constituents involve reactive oxygen species, reactive nitrogen species and plasma ultra-violets. These species can be used to synthesize biologically important nanoparticles. The current study addressed the effect of the green method-based preparation approach on the volumetric analysis of Zn nanoparticles. Under different operating conditions, the traditional thermal method and the microwave method as well as the plasma generation in dielectric barrier discharge reactor were adopted as a preparation approach in this study. The results generally show that the type of method used plays an important rol
... Show MoreDuring COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
... Show More