ABSTRACT

                   Ticagrelor is an orally administered antiplatelet medicine, direct-acting P2Y12-receptor antagonist. Ticagrelor binds reversibly and noncompetitively to the P2Y12 receptor at a site distinct from that of the endogenous agonist adenosine diphosphate (ADP). Inhibition of platelet aggregation stimulated by ADP is a commonly used pharmacodynamic parameter for P2Y12-receptor antagonists.

                  Ticagrelor is a crystalline powder with an aqueous solubility of approximately 10?g/mL at room temperature.

In the modern world, wind turbine (WT) has become the largest source of renewable energy. The horizontal-axis wind turbine (HAWT) has higher efficiency than the vertical-axis wind turbine (VAWT). The blade pitch angle (BPA) of WT is controlled to increase output power generation over the rated wind speed. This paper proposes an accurate controller for BPA in a 500-kw HAWT. Three types of controllers have been applied and compared to find the best controller: PID controller (PIDC), fuzzy logic type-2 controller (T2FLC), and hybrid type-2 fuzzy-PID controller (T2FPIDC). This paper has been used Mamdani and Sugeno fuzzy inference systems (FIS) to find the best inference system for WT controllers. Furthermore, genetic algorithm (GA) and particl

Background: Polymer surfaces usually present problems in bonding and finishing due to their low hydrophilicity. The aim of this study is to investigate the effect of plasma treatment with the use of two types of gases (oxygen and argon) on surface roughness, and chemical surface properties of acrylic resin denture base polymer material. Materials and Methods: Three heat cured acrylic resin specimens of (2*8*30 mm) dimensions were prepared for each test carried out in this study. Two tests were conducted, surface roughness test and chemical surface analysis test. Results: Application of plasma treatment increased surface roughness for both oxygen and argon plasma treated acrylic resin specimen groups compared with control untreated group,

Preparation of epoxy/MgO and epoxy/SiO2 nanocomposites is
studding. The nano composites were processed by different nano
fillers concentrations (0, 0.01, 0.02, 0.03, 0.04, 0.05, 0.07 and
0.1 wt%). Epoxy resin and nanocomposites containing different
shape nano fillers of (MgO:SiO2 composites), are shear mixing with
ratio 1:1,with different nano hybrid fillers concentrations (0.025,
0.05, 0.1, 0.15, 0.2 and 0.25 wt%) to preparation of epoxy/(MgOSiO2)
hybrid nanocomposites. Experimental tests results indicate that
the composite materials have significantly higher modulus of
elasticity than the matrix material but the hybrid nanocomposites
have lower modulus of elasticity. The wear rate was decreased in
nanoc

This study is a complementary one to an extended series of research work that aims to produce a thermodynamiclly stable asphalt –sulfur blend. Asphalt was physically modified wiht different percentages of asphaltenes , oxidized asphaltenes and then mixed with sulfur as an attempt to obtaine a stable compatible asphalt-sulfur blend. The homogeneneity of asphalt-asphaltenes[oxidized asphaltenes]-sulfur blends were studied microscopically and the results are prsented as photomicrographs. Generally more stable and compatible asphalt-sulfur blends were obtained by this treatment.

This paper proposes two hybrid feature subset selection approaches based on the combination (union or intersection) of both supervised and unsupervised filter approaches before using a wrapper, aiming to obtain low-dimensional features with high accuracy and interpretability and low time consumption. Experiments with the proposed hybrid approaches have been conducted on seven high-dimensional feature datasets. The classifiers adopted are support vector machine (SVM), linear discriminant analysis (LDA), and K-nearest neighbour (KNN). Experimental results have demonstrated the advantages and usefulness of the proposed methods in feature subset selection in high-dimensional space in terms of the number of selected features and time spe

The concept of the active contour model has been extensively utilized in the segmentation and analysis of images. This technology has been effectively employed in identifying the contours in object recognition, computer graphics and vision, biomedical processing of images that is normal images or medical images such as Magnetic Resonance Images (MRI), X-rays, plus Ultrasound imaging. Three colleagues, Kass, Witkin and Terzopoulos developed this energy, lessening “Active Contour Models” (equally identified as Snake) back in 1987. Being curved in nature, snakes are characterized in an image field and are capable of being set in motion by external and internal forces within image data and the curve itself in that order. The present s