Coastal and Inland Aquatic Data Products for the Hyperspectral Infrared Imager (HyspIRI)

The HyspIRI Aquatic Studies Group (HASG) has developed a conceptual list of data products for the HyspIRI mission to support aquatic remote sensing of coastal and inland waters. These data products were based on mission capabilities, characteristics, and expected performance. The topic of coastal and inland water remote sensing is very broad. Thus, this report focuses on aquatic data products to keep the scope of this document manageable. The HyspIRI mission requirements already include the global production of surface reflectance and temperature. Atmospheric correction and surface temperature algorithms, which are critical to aquatic remote sensing, are covered in other mission documents. Hence, these algorithms and their products were not evaluated in this report. In addition, terrestrial products (e.g., land use land cover, dune vegetation, and beach replenishment) were not considered. It is recognized that coastal studies are inherently interdisciplinary across aquatic and terrestrial disciplines. However, products supporting the latter are expected to already be evaluated by other components of the mission. The coastal and inland water data products that were identified by the HASG, covered six major environmental and ecological areas for scientific research and applications: wetlands, shoreline processes, the water surface, the water column, bathymetry and benthic cover types. Accordingly, each candidate product was evaluated for feasibility based on the HyspIRI mission characteristics and whether it was unique and relevant to the HyspIRI science objectives

Identifying and tracking evolving water masses in optically complex aquatic environments

Earth's climate is intimately associated with biogeochemical processes of the sea. Biological Oceanography explores mechanisms controlling carbon uptake by phytoplankton, carbon transfer through biogeochemical processes, and energy flow through ecosystems. Satellite Oceanography affords a synoptic view of the sea surface and reveals underlying physical, chemical, and biological processes. Since the advent of ocean color satellites in 1978, ocean color algorithms evolved from quantifying phytoplankton biomass to addressing more complex bio-optical and oceanographic problems: characterizing inherent optical properties of the water column, estimating primary productivity, and detecting water masses. Locating a water mass, tracking its changes, and discriminating its constituents using bio-optical algorithms are the three objectives of this dissertation. The first objective identifies the location of the Columbia River Plume (CRP) by using light absorption by chromophoric dissolved organic matter (a CDOM) as an optical proxy for salinity. It relates in situ measurements of (a CDOM to salinity using linear regression analysis, then computes "synthetic" salinity using MODIS-Aqua satellite imagery. The algorithm is robust at predicting salinity of the CRP on the Oregon and Washington shelf. The second objective identifies sub-mesoscale features within the CRP and tracks their changes in space and time. It employs k-means clustering and discriminant function analysis to identify water types from bio-optical and environmental input variables using in situ and MODIS-Aqua satellite observations. The algorithm is robust at identifying features in satellite and mooring data, consistent with measured and modeled water masses in previous work. The third objective involves development of an optical model (PHYDOTax) that discriminates phytoplankton taxa contained within an algal bloom. A hyperspectral ocean color signature-library for known phytoplankton (dinoflagellates, diatoms, haptophytes, cryptophytes, chlorophytes, cyanophytes, and phycocyanin-containing eukaryotes) was developed and then PHDYOTax decomposed ocean color spectra for culture mixtures and field samples into constituent taxa. PHYDOTax is robust at discriminating phytoplankton taxa and is one of the first algorithms to distinguish dinoflagellates from diatoms in ocean color data. These algorithms are new tools for the oceanographic community to constrain the location of carbon uptake and transfer through space and time in the CRP, and to partition energy flow through different phytoplankton-taxon dominated ecosystems

An appraisal of respiratory system compliance in mechanically ventilated covid-19 patients

BackgroundHeterogeneous respiratory system static compliance (CRS) values and levels of hypoxemia in patients with novel coronavirus disease (COVID-19) requiring mechanical ventilation have been reported in previous small-case series or studies conducted at a national level.MethodsWe designed a retrospective observational cohort study with rapid data gathering from the international COVID-19 Critical Care Consortium study to comprehensively describe CRS—calculated as: tidal volume/[airway plateau pressure-positive end-expiratory pressure (PEEP)]—and its association with ventilatory management and outcomes of COVID-19 patients on mechanical ventilation (MV), admitted to intensive care units (ICU) worldwide.ResultsWe studied 745 patients from 22 countries, who required admission to the ICU and MV from January 14 to December 31, 2020, and presented at least one value of CRS within the first seven days of MV. Median (IQR) age was 62 (52–71), patients were predominantly males (68%) and from Europe/North and South America (88%). CRS, within 48 h from endotracheal intubation, was available in 649 patients and was neither associated with the duration from onset of symptoms to commencement of MV (p = 0.417) nor with PaO2/FiO2 (p = 0.100). Females presented lower CRS than males (95% CI of CRS difference between females-males: − 11.8 to − 7.4 mL/cmH2O p RS was marginal (p = 0.139). Ventilatory management varied across CRS range, resulting in a significant association between CRS and driving pressure (estimated decrease − 0.31 cmH2O/L per mL/cmH20 of CRS, 95% CI − 0.48 to − 0.14, p RS (+ 10 mL/cm H2O) was only associated with being discharge from the ICU within 28 days (HR 1.14, 95% CI 1.02–1.28, p = 0.018).ConclusionsThis multicentre report provides a comprehensive account of CRS in COVID-19 patients on MV. CRS measured within 48 h from commencement of MV has marginal predictive value for 28-day mortality, but was associated with being discharged from ICU within the same period. Trial documentation: Available at https://www.covid-critical.com/study.Trial registration: ACTRN12620000421932

Risk of COVID-19 after natural infection or vaccinationResearch in context

Summary: Background: While vaccines have established utility against COVID-19, phase 3 efficacy studies have generally not comprehensively evaluated protection provided by previous infection or hybrid immunity (previous infection plus vaccination). Individual patient data from US government-supported harmonized vaccine trials provide an unprecedented sample population to address this issue. We characterized the protective efficacy of previous SARS-CoV-2 infection and hybrid immunity against COVID-19 early in the pandemic over three-to six-month follow-up and compared with vaccine-associated protection. Methods: In this post-hoc cross-protocol analysis of the Moderna, AstraZeneca, Janssen, and Novavax COVID-19 vaccine clinical trials, we allocated participants into four groups based on previous-infection status at enrolment and treatment: no previous infection/placebo; previous infection/placebo; no previous infection/vaccine; and previous infection/vaccine. The main outcome was RT-PCR-confirmed COVID-19 >7–15 days (per original protocols) after final study injection. We calculated crude and adjusted efficacy measures. Findings: Previous infection/placebo participants had a 92% decreased risk of future COVID-19 compared to no previous infection/placebo participants (overall hazard ratio [HR] ratio: 0.08; 95% CI: 0.05–0.13). Among single-dose Janssen participants, hybrid immunity conferred greater protection than vaccine alone (HR: 0.03; 95% CI: 0.01–0.10). Too few infections were observed to draw statistical inferences comparing hybrid immunity to vaccine alone for other trials. Vaccination, previous infection, and hybrid immunity all provided near-complete protection against severe disease. Interpretation: Previous infection, any hybrid immunity, and two-dose vaccination all provided substantial protection against symptomatic and severe COVID-19 through the early Delta period. Thus, as a surrogate for natural infection, vaccination remains the safest approach to protection. Funding: National Institutes of Health