This paper aims at studying the illocutionary speech acts: direct and indirect to show the most dominant ones in a presidential speech delivered by the USA president. The speech is about the most critical health issue in the world, COVID-19 outbreak.  A descriptive qualitative study was conducted by observing the first speech delivered by president Trump concerning coronavirus outbreak and surveying the illocutionary acts: directive, declarative, commissive, expressive, and representative. Searle's (1985) classification of illocutionary speech acts is adopted in the analysis.

     What are the main types of the illocutionary speech acts performed by Trump in his speech?; Why does

Trigeminal Neuralgia (TN) is one of the most commonly painful cranial neuralgia characterized by paroxysmal attacks as short lasting facial pain along the trigeminal nerve branches. The aim of the present study is to innovate a biochemical relationship between (melatonin, GALNT12 and Zn) and TN and also to examine the biochemical action of tegretol (carbamazepine) as a treatment on the above biochemical parameters. Blood samples were collected from fifty four (54) trigeminal neuralgia patients diagnosed by magnetic radiation image (MRI). Patients were classified into four groups: G3 (40- 70) years composed of (12) diagnosed male (without treatment), G4 (48- 75) years composed of (12) diagnosed female (without treatment), G5 (34- 76)

Infection of the gastric mucosa with Helicobacter pylori is strongly associated with chronic gastritis, peptic ulcer and gastric cancer. Helicobacter pylori virulence factors include a variety of proteins that are involved in its pathogenesis, such as VacA and CagA. Another group of virulence factors is clearly important for colonization of H.pylori in the gastric mucosa. These include urease, motility factors (flagellin), and Superoxide dismutase (SOD). Because of this organism's microaerophilic nature and the increased levels of reactive oxygen in the infected host, we expect that other factors involved in the response to oxidative stress are likely to be required for virulence. Superoxide dismutase is a near

Liposome-mediated transfection of cancer cells provide a valuable experimental technique to study cellular gene expression and may also be adapted for gene therapy studies. However, the widely recognized advantage of liposome-mediated transfection is high efficiency. Therefore, this study were performed to optimize transfection techniques in human larynx carcinoma cell line Hep-2 using the commercial synthetic lipid TransFast™ Reagent and monitoring the expression efficiency by using the pSV-?-galactosidase Control Vector which encoded ?-galactosidase, maximum transfection efficiency were achieved with TransFast™ Reagent used at the Charge ratios of 2:1 and 0.5 µg DNA/ml, this is indicate that TransFast™ Reagent can be used as an eff

This study aims to assess the accuracy of digital elevation model (DEM) created with utilization of handheld Global Positioning System (GPS) and comparing with Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM), version 2. It is known that the quality of the DEM is affected by both of accuracy of elevation at each pixel (absolute accuracy) and accuracy of presented morphology (relative accuracy). The University of Baghdad, Al Jadriya campus was selected as a study area to create and analysis the resulting DEM. Additionally, Geographic Information System (GIS) was used to visualize, analyses and interpolate GPS track points (elevation data) of the study area. In this

Some of the main challenges in developing an effective network-based intrusion detection system (IDS) include analyzing large network traffic volumes and realizing the decision boundaries between normal and abnormal behaviors. Deploying feature selection together with efficient classifiers in the detection system can overcome these problems.  Feature selection finds the most relevant features, thus reduces the dimensionality and complexity to analyze the network traffic.  Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance.  In this study, two different sets of select