How a second wave of COVID-19 infections may evolve across Europe over the next few months, using data on infection rates and travel within and between European countries, is modelled in a Scientific Reports paper. The findings suggest that a second wave in Europe will occur between July 2020 and January 2021 and that the precise timing of peaks in infection rates for each country could be controlled via social distancing, control of local hotspots and border control measures.
Using the largest development dataset yet (n=3841), and a systematic machine learning framework, Mount Sinai researchers developed a COVID-19 mortality prediction model that showed high accuracy (AUC=0·91) when applied to test datasets of retrospective (n=961) and prospective (n=249) patients. This model was based on three clinical features: patient's age, minimum oxygen saturation over the course of their medical encounter, and type of patient encounter (inpatient vs outpatient and telehealth visits).
In a paper publishing on Tuesday in the SIAM Journal of Applied Mathematics, Daozhou Gao of Shanghai Normal University investigated the way in which human dispersal affects disease control and total extent of an infection's spread.
The COVID-19 pandemic has caused "kinks" in the movement of goods and services around the globe, but how important a role do multinational companies play in local economies and supply chains?
Researchers at the University of Helsinki have developed a technique in which a computer models visual perception by monitoring human brain signals. In a way, it is as if the computer tries to imagine what a human is thinking about. As a result of this imagining, the computer is able to produce entirely new information, such as fictional images that were never before seen. The technique is based on a novel brain-computer interface.
The turbulence code GENE (Gyrokinetic Electromagnetic Numerical Experiment), developed at Max Planck Institute for Plasma Physics (IPP) at Garching, Germany, has proven to be very useful for the theoretical description of turbulence in the plasma of tokamak-type fusion devices. Extended for the more complex geometry of stellarator-type devices, computer simulations with GENE now indicate a new method to reduce plasma turbulence in stellarator plasmas. This could significantly increase the efficiency of a future fusion power plant.
In the 2019 Boeing 737 Max crash, the recovered black box from the aftermath hinted that a failed pressure sensor may have caused the ill-fated aircraft to nose dive. This incident and others have fueled a larger debate on sensor selection, number and placement to prevent the reoccurrence of such tragedies. Texas A&M University researchers have now developed a comprehensive mathematical framework that can help engineers make informed decisions about which sensors to use.
Artificial intelligence (AI) experts at the University of Massachusetts Amherst and the Baylor College of Medicine report that they have successfully addressed what they call a "major, long-standing obstacle to increasing AI capabilities" by drawing inspiration from a human brain memory mechanism known as "replay."
Cornell University systems engineers examined data from a busy New York state food bank and, using a new algorithm, found ways to better allocate food and elevate nutrition in the process.
ETH researchers have used a computer model to test a new hypothesis about the formation of the Alps while simulating seismic activity in Switzerland. This will help improve current earthquake risk models.