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The InSAR Scientific Computing Environment (ISCE) provides both a modular, flexible, and extensible framework for building software components and applications that work together seamlessly as well as a toolbox for processing InSAR data into higher level geodetic image products from a diverse array of radar satellites and aircraft. ISCE easily scales to serve as the SAR processing engine at the core of the NASA JPL Advanced Rapid Imaging and Analysis (ARIA) Center for Natural Hazards as well as a software toolbox for individual scientists working with SAR data. ISCE is planned as the foundational element in processing NISAR data, enabling a new class of analyses that take greater advantage of the long time and large spatial scales of these data. ISCE in ARIA is also a SAR Foundry for development of new processing components and workflows to meet the needs of both large processing centers and individual users. The ISCE framework contains object-oriented Python components layered to construct Python InSAR components that manage legacy Fortran/C InSAR programs. The Python user interface enables both command-line deployment of workflows as well as an interactive "sand box" (the Python interpreter) where scientists can "play" with the data. Recent developments in ISCE include the addition of components to ingest Sentinel-1A SAR data (both stripmap and TOPS-mode) and a new workflow for processing the TOPS-mode data. New components are being developed to exploit polarimetric-SAR data to provide the ecosystem and land-cover/land-use change communities with rigorous and efficient tools to perform multi-temporal, polarimetric and tomographic analyses in order to generate calibrated, geocoded and mosaicked Level-2 and Level-3 products (e.g., maps of above-ground biomass or forest disturbance). ISCE has been downloaded by over 200 users by a license for WinSAR members through the Unavco.org website. Others may apply directly to JPL for a license at download.jpl.nasa.gov.
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Severe acute respiratory syndrome (SARS) is a dangerous infection with pandemic potential. It emerged in 2002 and its aetiological agent, the SARS Coronavirus (SARS-CoV), crossed the species barrier to infect humans, showing high morbidity and mortality rates. No vaccines are currently licensed for SARS-CoV and important efforts have been performed during the first outbreak to develop diagnostic tools. Here we demonstrate the transient expression in Nicotiana benthamiana of two important antigenic determinants of the SARS-CoV, the nucleocapsid protein (N) and the membrane protein (M) using a virus-derived vector or agro-infiltration, respectively. For the M protein, this is the first description of production in plants, while for plant-derived N protein we demonstrate that it is recognized by sera of patients from the SARS outbreak in Hong Kong in 2003. The availability of recombinant N and M proteins from plants opens the way to further evaluation of their potential utility for the development of diagnostic and protection/therapy tools to be quickly manufactured, at low cost and with minimal risk, to face potential new highly infectious SARS-CoV outbreaks.