FaceTouch: Detecting hand-to-face touch with supervised contrastive learning to assist in tracing infectious diseases.

Through our respiratory system, many viruses and diseases frequently spread and pass from one person to another. Covid-19 served as an example of how crucial it is to track down and cut back on contacts to stop its spread. There is a clear gap in finding automatic methods that can detect hand-to-face contact in complex urban scenes or indoors.

Abnormality detection and intelligent severity assessment of human chest computed tomography scans using deep learning: a case study on SARS-COV-2 assessment.

Different respiratory infections cause abnormal symptoms in lung parenchyma that show in chest computed tomography. Since December 2019, the SARS-COV-2 virus, which is the causative agent of COVID-19, has invaded the world causing high numbers of infections and deaths. The infection with SARS-COV-2 virus shows an abnormality in lung parenchyma that can be effectively detected using Computed Tomography (CT) imaging.

Antimicrobial stewardship solutions with a smart innovative tool.

Background: Antimicrobial consumption has been increasing lately. Hence, effective strategies are required to control antimicrobial use and decrease the development of antimicrobial resistance.

Objective: To evaluate the impact of the use of a mobile app on the implementation of antimicrobial stewardship program (ASP) interventions.

Variational-LSTM autoencoder to forecast the spread of coronavirus across the globe.

Modelling the spread of coronavirus globally while learning trends at global and country levels remains crucial for tackling the pandemic. We introduce a novel variational-LSTM Autoencoder model to predict the spread of coronavirus for each country across the globe. This deep Spatio-temporal model does not only rely on historical data of the virus spread but also includes factors related to urban characteristics represented in locational and demographic data (such as population density, urban population, and fertility rate), an index that represents the governmental measures and response amid toward mitigating the outbreak (includes 13 measures such as: 1) school closing, 2) workplace closing, 3) cancelling public events, 4) close public transport, 5) public information campaigns, 6) restrictions on internal movements, 7) international travel controls, 8) fiscal measures, 9) monetary measures, 10) emergency investment in health care, 11) investment in vaccines, 12) virus testing framework, and 13) contact tracing).

In vitro and in vivo hypolipidemic properties of the aqueous extract of , cultivated in colored flasks under artificial illumination.

Background: is blue-green algae that grows mainly in tropical and subtropical lakes and is commonly used due to its nutritional features including high concentrations of protein, vitamins, mineral salts, carotenoids and antioxidants. This study aimed to investigate the anti-hypercholesterolemic potential of aqueous extract of cultivated in different colored flasks under artificial illumination; in vitro and in the diet induced hypercholesterolemic Swiss albino mice.

Methods: was cultivated in red, blue, green and colorless Erlenmeyer flasks containing Zarrouk's medium under aerobic conditions, with incessant illumination by artificial cool white fluorescent with light intensity of 2500 lux (35 µmol photon m s).

A dataset of housing market and self-attitudes towards housing location choices in Alexandria, Egypt.

A survey, of sample size 224, is designed to include the different related-factors to housing location choice, such as; socioeconomic factors, housing characteristics, travel behavior, current self-selection factors, housing demand and future location preferences. It comprises 16 questions, categorized into three different sections; socioeconomic (5 Questions), current dwelling unit characteristics (7 Questions), and housing demand characteristics (4 Questions). The first part, socioeconomic, covers the basic information about the respondent, such as; age, gender, marital status, employment, and car ownership.