Stealth marketing is considered as one of the contemporary issues that researchers have begun to explore as a current understanding. It is the marketing approach used by organizations to promote their products and services to the public in implicit and indirect manner. In this article, the concept of stealth marketing will be discussed throw its advantages and disadvantages. In addition, the different techniques of stealth marketing have been discussed including: viral marketing, celebrity marketing, brand pushers, bait-and-tease marketing, video games marketing, and marketing in music. Furthermore, a new technique of marketing entitled “Marketing through social responsibility” has been added and discussed according to the themes in the

Background: Prolonged use of low-dose estrogen ''20 micrograms or less" Combined oral contraceptive pill (that have estrogen and progesterone steroid hormone) had an effect on bone turnover .Bone mineral density is used in clinical medicine as an indirect indicator of osteoporosis and fracture risk. The aim of the study: The aim of this study was to investigate the effect of low dose oral contraceptive pill on the cortical thickness (in millimeter) and bone mineral density at the mandibular cortex of mental and gonial regions in Hounsfield unit(HU) using spiral computed tomography. Material and method: This prospective study was conducted on computed tomographic image of 100 women aged between (20-40) years .The collected sample includes

Human cytomegalovirus (CMV) is the globally highly prevalent herpesvirus worldwide. CMV infects populations of all ages according to the Center for Disease Control and Prevention (CDC) and World Health Organization (WHO). CMV infections remain the most common viral complication potentially multiple in humans and are a major cause of congenital normality in women, which is why they are critical for diagnosis in several times when it happens during pregnancy. Pregnant women with CMV infection can be in charge of abortion or congenital expandaedby. This study involves the collection a total of (90) samples taken from each aborted and pregnant woman (70 with abortion cases and 20 of pregnant without history of abortion as control subjects) r

Amino acids were analyzed in stomach regions of males & females of Felis catus (Domestic Cat) & Sciurus carolinesis (Eastern Gray Squirrel ), where it was stated that there are (18) amino acids as following : Aspartic acid (Asp), Glutamic acid (Gla), Serine (Ser), Arginine (Arg), Aspargine ( Asn), Cysteine (Cys), Alanine (Ala), Proline (Pro), Glyscine (Gly), Threonine (Thr), Tyrosine (Tyr), Valine (Val), Methionine (Met), Histidine ( His), Isoleucine (ile), Leucine (leu), Phenylalanine (Phe ) and Lysine (lys). Results have shown there are significant differences in concentration of amino acids between different region of stomach between males & females of Felis catus in part and between males & females of Sciurus carolinesis (Eastern Gray S

hemorrhagic fever (VHF), one of which is Filoviridae. The Filoviridae family includes the Ebola virus , is responsible for the current VHF outbreak in West Africa. Viral hemorrhagic fevers (VHFs) occur in various regions around the world, yet traditional diagnostic testing for these diseases has typically been conducted in major reference laboratories located in Europe and the United States. In this review, we explore the current understanding of the mechanisms driving the pathogenesis of viral hemorrhagic fevers (VHFs) and examine the progress in developing preventive and therapeutic strategies for these infections.

After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings