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Vaccines That Can Protect Against Many Coronaviruses Could Prevent Another Pandemic


In 2017, three leading vaccine researchers submitted a grant application with an ambitious goal. At the time, no one had proved a vaccine could stop even a single beta coronavirus—the notorious viral group then known to include the lethal agents of severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS), as well as several causes of the common cold and many bat viruses. But these researchers wanted to develop a vaccine against them all. Grant reviewers at the National Institute of Allergy and Infectious Diseases (NIAID) deemed the plan “outstanding.” But they gave the proposal a low priority score, dooming its bid for funding.

 

https://doi.org/10.1126/science.abi9939

Read the full article at: www.sciencemag.org

The post Vaccines That Can Protect Against Many Coronaviruses Could Prevent Another Pandemic appeared first on Antonios Bouris.


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Boosting fiber optics communications with advanced quantum-enhanced receiver


Fiber optic technology is the holy grail of high-speed, long-distance telecommunications. Still, with the continuing exponential growth of internet traffic, researchers are warning of a capacity crunch.

 

In AVS Quantum Science, researchers from the National Institute of Standards and Technology and the University of Maryland show how quantum-enhanced receivers could play a critical role in addressing this challenge. The scientists developed a method to enhance receivers based on quantum physics properties to dramatically increase network performance while significantly reducing the error bit rate (EBR) and energy consumption.

 

Fiber optic technology relies on receivers to detect optical signals and convert them into electrical signals. The conventional detection process, largely as a result of random light fluctuations, produces ‘shot noise,’ which decreases detection ability and increases EBR. To accommodate this problem, signals must continually be amplified as pulsating light becomes weaker along the optic cable, but there is a limit to maintaining adequate amplification when signals become barely perceptible.

 

Read the full article at: phys.org

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Accelerating Single Cell Genomic Analysis using RAPIDS


The human body is made up of nearly 40 trillion cells, of many different types. Recent advances in experimental biology have made it possible to explore the genetic material of single cells.

 

RAPIDS is a suite of open-source Python libraries that can speed up data science workflows using GPU acceleration. Starting from a single-cell count matrix, RAPIDS libraries can be used to perform data processing, dimensionality reduction, clustering, visualization, and comparison of cell clusters.

 

Several examples are inspired by the Scanpy tutorials and based upon the AnnData format. Currently, examples provide for scRNA-seq and scATAC-seq, and can be scaled up to 1 million cells. The authors also show how to create GPU-powered interactive, in-browser visualizations to explore single-cell datasets.

 

Dataset sizes for single-cell genomics studies are increasing, presently reaching millions of cells. With RAPIDS, it becomes easy to analyze large datasets interactively and in real time, enabling faster scientific discoveries.

 

Github repository is here

Read the full article at: developer.nvidia.com

The post Accelerating Single Cell Genomic Analysis using RAPIDS appeared first on Antonios Bouris.


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