Respiratory management in severe acute respiratory syndrome coronavirus 2 infection.

The severe acute respiratory syndrome coronavirus 2 pandemic is to date affecting more than a million of patients and is challenging healthcare professionals around the world. Coronavirus disease 2019 may present with a wide range of clinical spectrum and severity, including severe interstitial pneumonia with high prevalence of hypoxic respiratory failure requiring intensive care admission. There has been increasing sharing experience regarding the patient's clinical features over the last weeks which has underlined the need for general guidance on treatment strategies. We summarise the evidence existing in the literature of oxygen and positive pressure treatments in patients at different stages of respiratory failure and over the course of the disease, including environment and ethical issues related to the ongoing coronavirus disease 2019 infection

CARBOTRAF: A decision Support system for reducing pollutant emissions by adaptive traffic management

Traffic congestion with frequent “stop & go” situations causes substantial pollutant emissions. Black carbon (BC) is a good indicator of combustion-related air pollution and results in negative health effects. Both BC and CO2 emissions are also known to contribute significantly to global warming. Current traffic control systems are designed to improve traffic flow and reduce congestion. The CARBOTRAF system combines real-time monitoring of traffic and air pollution with simulation models for emission and local air quality prediction in order to deliver on-line recommendations for alternative adaptive traffic management. The aim of introducing a CARBOTRAF system is to reduce BC and CO2 emissions and improve air quality by optimizing the traffic flows. The system is implemented and evaluated in two pilot cities, Graz and Glasgow. Model simulations link traffic states to emission and air quality levels. A chain of models combines micro-scale traffic simulations, traffic volumes, emission models and air quality simulations. This process is completed for several ITS scenarios and a range of traffic boundary conditions. The real-time DSS system uses all these model simulations to select optimal traffic and air quality scenarios. Traffic and BC concentrations are simultaneously monitored. In this paper the effects of ITS measures on air quality are analysed with a focus on BC

Air quality impact of a decision support system for reducing pollutant emissions: CARBOTRAF

Traffic congestion with frequent “stop & go” situations causes substantial pollutant emissions. Black carbon (BC) is a good indicator of combustion-related air pollution and results in negative health effects. Both BC and CO2 emissions are also known to contribute significantly to global warming. Current traffic control systems are designed to improve traffic flow and reduce congestion. The CARBOTRAF system combines real-time monitoring of traffic and air pollution with simulation models for emission and local air quality prediction in order to deliver on-line recommendations for alternative adaptive traffic management. The aim of introducing a CARBOTRAF system is to reduce BC and CO2 emissions and improve air quality by optimizing the traffic flows. The system is implemented and evaluated in two pilot cities, Graz and Glasgow. Model simulations link traffic states to emission and air quality levels. A chain of models combines micro-scale traffic simulations, traffic volumes, emission models and air quality simulations. This process is completed for several ITS scenarios and a range of traffic boundary conditions. The real-time DSS system uses these off-line model simulations to select optimal traffic and air quality scenarios. Traffic and BC concentrations are simultaneously monitored. In this paper the effects of ITS measures on air quality are analysed with a focus on BC

Reducing environmental impact by adaptive traffic control and management for urban road networks

This paper investigates the effectiveness of traffic signal control and variable message sign (VMS) as environmental traffic management tool. The focus is on black carbon and CO2, which are among the highest contributors to climate change. The modelling tool chain adopted to support this study includes traffic microsimulation, emission modelling and dispersion modelling. A number of scenarios have been simulated with different levels of demand and VMS compliance rates. The results demonstrate the potential of these interventions in reducing black carbon and CO2 emissions and improving air quality, as well as reducing traffic congestion and travel delays

Non-A Hepatitis B Virus Genotypes in Antenatal Clinics, United Kingdom

Serostatus for viral e antigen is no longer accurate for inferring potential infectivity of pregnant virus carriers