Echocardiography is a widely used imaging technique to examine various cardiac functions, especially to detect the left ventricular wall motion abnormality. Unfortunately the quality of echocardiograph images and complexities of underlying motion captured, makes it difficult for an in-experienced physicians/ radiologist to describe the motion abnormalities in a crisp way, leading to possible errors in diagnosis. In this study, we present a method to analyze left ventricular wall motion, by using optical flow to estimate velocities of the left ventricular wall segments and find relation between these segments motion. The proposed method will be able to present real clinical help to verify the left ventricular wall motion diagnosis.

In this paper the use of a circular array antenna with adaptive system in conjunction with modified Linearly Constrained Minimum Variance Beam forming (LCMVB) algorithm is proposed to meet the requirement of Angle of Arrival (AOA) estimation in 2-D as well as the Signal to Noise Ratio (SNR) of estimated sources (Three Dimensional 3-D estimation), rather than interference cancelation as it is used for. The proposed system was simulated, tested and compared with the modified Multiple Signal Classification (MUSIC) technique for 2-D estimation. The results show the system has exhibited astonishing results for simultaneously estimating 3-D parameters with accuracy approximately equivalent to the MUSIC technique (for estimating elevation and a

<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

BACKGROUND: Burkholderia cepacia adhesion and biofilm formation onto abiotic surfaces is an important feature of clinically relevant isolates. The in vitro biofilm formation of B. cepacia onto coated indwelling urinary catheters (IDCs) with moxifloxacin has not been previously investigated. OBJECTIVES: To examine the ability of B. cepacia to form biofilms on IDCs and the effect of coating IDCs with moxifloxacin on biofilm formation by B. cepacia in vitro. MATERIAL AND METHODS: The adhesion of B. cepacia to coated and uncoated IDCs with moxifloxacin was evaluated. Pieces of IDCs were coated with moxifloxacin (adsorption method). The spectrophotometric method was used to check moxifloxacin leaching into tubes. Coated and uncoated tubes were i

Alpha-tocopherol acetate is one of the most important vitamin E derivatives,that were used  as antioxidants. Adsorbents like kaolin, magnesium carbonate, and microcrystalline cellulose were used successfully to incorporate oily alpha-tocopherol acetate into an acceptable powder dosage form. The results revealed that microcrystalline cellulose as an adsorbents gave the best results with 50% loading capacity at time, 8 minutes before and after incubation period (3 months at 30C°), while kaolin and magnesium carbonate have been shown a significant difference before and after incubation. Addition of 1% w/w magnesium carbonate to the kaolin enhanced the loading capacity by decreasing the time of adsorption from 20 to 6 minutes and 47

   The main focus of this research is to examine the Travelling Salesman Problem (TSP) and the methods used to solve this problem where this problem is considered as one of the combinatorial optimization problems which met wide publicity and attention from the researches for to it's simple formulation and important applications and engagement to the rest of combinatorial problems , which is based on finding the optimal path through known number of cities where the salesman visits each city only once before returning to the city of departure n this research , the benefits  of( FMOLP)   algorithm is employed as one of the best methods to solve the (TSP) problem and the application of the algorithm in conjun