<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

Since its start spreed "Severe acute respiratory syndrome coronavirus 2" was discovered in Wuhan, China.that is chargeable COVID-19, a pandemic virus, has end up a widespread fitness hassle everywhere in the global Over 2.1 million people have been affected. We analyze serum concentration of CD4 marker and CD8 marker depend in COVID-19 sufferers, and to make clear a relationship between these variables and disorder Progression and severity For those purpose, (158) sufferers with COVID-19 (showed with the aid of using polymerase chain reaction) and (22) seemingly wholesome human beings have been protected withinside the present day examine and taken into consideration as a manipulate group. All examine population (sufferers and manipulate) h

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

The first known use of the term conspiracy theory dated back to the nineteenth century. It is defined as a theory that explains an event or set of circumstances as the result of a secret plot by usually powerful conspirators. It is commonly used, but by no means limited to, extreme political groups. Since the emergence of COVID-19 as a global pandemic in December 2019, the conspiracy theory was present at all stages of the pandemic.

The first known use of the term conspiracy theory dated back to the nineteenth century. It is defined as a theory that explains an event or set of circumstances as the result of a secret plot by usually powerful conspirators. It is commonly used, but by no means limited to, extreme political groups. Since the emergence of COVID-19 as a global pandemic in December 2019, the conspiracy theory was present at all stages of the pandemic.

Drug consultation is an important part of pharmaceutical care. mobile phone call or text message can serve as an easy, effective, and implementable alternative to improving medication adherence and clinical outcomes by providing the information needed significantly for people with chronic illnesses like diabetes and hypertension particularly during pandemics like COVID-19 pandemic.

In the present study, an attempt has been made to study the change in water quality of the river in terms of turbidity during lockdown associated with COVID-19. Iraq announced the longest-ever lockdown on 25 March 2020 due to COVID-19 pandemic. 

In the absence of ground observations, remote sensing data was adopted, especially during this period. The change in the visible region's spectral reflectance of water in part of the river has been analyzed using the Landsat 8 OLI multispectral remote sensing data at Tigris River, Salah al-Din province (Bayji / near the refinery), Iraq. It was found that the green and red bands are most sensitive and can be used to estimate turbidity. Furthermore, the temporal variation in turbidity was a