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. In this paper, we introduce a computer vision framework, called FaceTouch, based on deep learning. It comprises deep sub-models to detect humans and analyse their actions. FaceTouch seeks to detect hand-to-face touches in the wild, such as through video chats, bus footage, or CCTV feeds. Despite partial occlusion of faces, the introduced system learns to detect face touches from the RGB representation of a given scene by utilising the representation of the body gestures such as arm movement. This has been demonstrated to be useful in complex urban scenarios beyond simply identifying hand movement and its closeness to faces. Relying on Supervised Contrastive Learning, the introduced model is trained on our collected dataset, given the absence of other benchmark datasets. The framework shows a strong validation in unseen datasets which opens the door for potential deployment.

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. METHODS: This was a longitudinal study conducted at El-Nile Badrawi Hospital in Cairo, Egypt, on inpatients receiving antimicrobials from January 2018 to December 2019. The study included 2 phases: the preimplementation phase, which included a paper-based ASP developed according to the Centers for Disease Control and Prevention Core Elements of Hospital Antibiotic Stewardship Programs 2014, and the mobile app phase where the MEDIcare Pro mobile app was developed and used in ASP intervention implementation. The study outcomes were antimicrobial consumption and cost, length of hospital and intensive care unit (ICU) stay, 30-day mortality rate and readmission rate, and detection of drug-related problems (DRPs). RESULTS: The mobile app statistically significantly decreased antimicrobial consumption from 75.1 defined daily dose (DDD)/100 bed-days in the preimplementation phase to 64.65 DDD/100 bed-days in the mobile app phase, with a total cost savings of E£1,237,476. There was a significant reduction in the length of ICU stay, with a mean difference of 1.63 days between the 2 phases, but no significance was detected regarding length of hospital stay or readmission rate. There was a statistically significant decrease in mortality rate from 1.17% in the preimplementation phase to 0.83% in the mobile app phase (P = 0.02). The frequency of DRPs detected by pharmacists statistically significantly increased from 0.54/100 bed-days in the preimplementation phase to 3.23/100 bed-days in the mobile app phase. CONCLUSION: The use of a mobile app was found to be effective, applicable, and usable in guiding health professionals on rational antimicrobial use.

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 addition, the introduced method learns to generate a graph to adjust the spatial dependences among different countries while forecasting the spread. We trained two models for short and long-term forecasts. The first one is trained to output one step in future with three previous timestamps of all features across the globe, whereas the second model is trained to output 10 steps in future. Overall, the trained models show high validation for forecasting the spread for each country for short and long-term forecasts, which makes the introduce method a useful tool to assist decision and policymaking for the different corners of the globe.

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

BACKGROUND: Spirulina 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 Spirulina platensis cultivated in different colored flasks under artificial illumination; in vitro and in the diet induced hypercholesterolemic Swiss albino mice. METHODS: Spirulina platensis 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-2 s-1). Chlorophyll a and total carotenoid contents were estimated using colorimetric methods, fatty acids composition was determined by GC-Mass, in vitro and in vivo anti-cholesterol assays were used in assessing the anti-hypercholesterolemia potential of obtained Spirulina cells. RESULTS: The results showed that the highest cell dry weight, chlorophyl a, and carotenoid of S. platensis were observed in colorless flasks and that the lowest values were recorded with the green colored flasks. Also, the hot water extract of S. platensis obtained from colorless flasks at a concentration of 15 mg/mL after 60 min of incubation exhibited the greatest reduction of cholesterol level. Gas chromatography-mass spectrometry analysis of S. platensis methanolic extract showed 15 bioactive compounds were identified and grouped according to their chemical structures. An experimental model of hypercholesterolemic mice had been examined for impact of S. platensis individually and combined with atorvastatin drug. All S. platensis groups resulted in a remarkable decrease in plasma total cholesterol, triglycerides and low density lipoprotein; and increase in high density lipoprotein. CONCLUSION: The present study concluded that the hot aqueous extract of S. platensis developed in colorless flasks is recommended as a natural source for bioactive compounds, with anti-cholesterol and antioxidant potentialities.

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. While the second part, current dwelling unit characteristics, covers different aspect concerning the residential unit typology, financial aspects, and travel behavior of the respondent. It includes the tenure types of the residential unit, estimation of the unit price (in the case of ownership or renting), housing typologies, the main reason for choosing the unit, in case of working, the modes of travel to work, and time to reach it, residential mobility in the last decade, and the ownership of any other residential units. The last part, housing demand characteristics, covers the size of the demand for a residential unit, preference in living in a certain area and the reason to choose it, and the preference of residential unit׳s tenure. This survey is a representative sample for the population in Alexandria, Egypt. The data in this article is represented in: How do people select their residential locations in Egypt? The case of Alexandria; JCIT1757.