Isocratic high performance liquid chromatography on reversed phase a (150x 4.6 mm I.D), 5 ?m ?-Bondapak RP-8 column (with acidic mobile phase allow the separation of doxcycycline hydrochloride with low detection limit of 0.2 µg/ml detected by UV set at 226 nm. The method was validated for Doxycycline between 0.156- to 5 µg/ml. The concentration of doxycycline was assessed in two single dose randomized crossover studies with intervals of one week between two period. In sera of 20 adults healthy male volunteers with average age of (42 + 10) year, body weight 48-85 kg, body height of (160-185cm) after a single dose of doxycycline hydrochoride 100 mg in form of capsules were orally administrated for both formulations. The blood sa

In this paper, CdS/Si hetrojunction solar cell has been made by
Chemical Bath Deposition (CBD) of CdS thin film on to
monocrystalline silicon substrate. XRD measurements approved that
CdS film is changing the structure of CdS films from mixed
hexagonal and cubic phase to the hexagonal phase with [101]
predominant orientation. I-V characterization of the hetrojunction
shows good rectification, with high spectral responsivity of 0.41
A/W, quantum efficiency 90%,and specific detectivity 2.9*1014
cmHz1/2W -1 .

The effects of shot peening treatment (SPT) were studied at (10,20, and 30) minutes on the rotating bending fatigue behavior and the behavior of the alloy steel DIN 41Cr4 vibrations. The hardness test, tensile test, constant amplitude fatigue tests, and the vibration measurements were performed on samples with and without cracks at room temperature (RT), also, the fracture surface was examined and analyzed by a Scanning Electron Microscope (SEM). The results of the investigations, for example, Stress to Number of cycles to failure (S-N) curves, fatigue strength improvement factor of 5% to 10%, the decreasing percentage of maximum Fast Fourier Transform (FFT) acceleration of the shot-peened condition were compared to untr

<p>Combating the COVID-19 epidemic has emerged as one of the most promising healthcare the world's challenges have ever seen. COVID-19 cases must be accurately and quickly diagnosed to receive proper medical treatment and limit the pandemic. Imaging approaches for chest radiography have been proven in order to be more successful in detecting coronavirus than the (RT-PCR) approach. Transfer knowledge is more suited to categorize patterns in medical pictures since the number of available medical images is limited. This paper illustrates a convolutional neural network (CNN) and recurrent neural network (RNN) hybrid architecture for the diagnosis of COVID-19 from chest X-rays. The deep transfer methods used were VGG19, DenseNet121

       In the pandemic era of COVID19, software engineering and artificial intelligence tools played a major role in monitoring, managing, and predicting the spread of the virus. According to reports released by the World Health Organization, all attempts to prevent any form of infection are highly recommended among people. One side of avoiding infection is requiring people to wear face masks. The problem is that some people do not incline to wear a face mask, and guiding them manually by police is not easy especially in a large or public area to avoid this infection. The purpose of this paper is to construct a software tool called Face Mask Detection (FMD) to detect any face that does not wear a mask in a specific