Today, the most common methods used for medical device sterilisation are by gaseous ethylene oxide and by electron beam or gamma irradiation. With X-ray sterilisation about to enter the market, its material compatibility needs to be assessed at doses typically encountered during a sterilisation...
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The year 2014 solution files are based on model calibration effort based on inputs and data from Year 2014 as described in Khangaonkar et al. 2018). It includes water surface elevation, currents, temperature and salinity at an hourly interval. These netcdf files with 24 hourly records include...
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Software
EyeSea software is available at https://github.com/pnnl/EyeSea
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Predicting phenotypic expression from genomic and environmental information is arguably the greatest challenge in today’s biology. Being able to survey genomic content, e.g., as single-nucleotide polymorphism data, within a diverse population and predict the phenotypes of external traits, represents...
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Soil microorganisms play fundamental roles in cycling of soil carbon, nitrogen, and other nutrients, yet we have a poor understanding of how soil microbiomes are shaped by their nutritional and physical environment. In this study, we investigated the successional dynamics of a soil microbiome during...
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The direct and diffused components of downward shortwave radiation (SW), and photosynthetically active radiation (PAR) at the Earth surface play an essential role in biochemical (e.g. photosynthesis) and physical (e.g. energy balance) processes that control weather and climate conditions, and...
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Publication
Soil respiration (Rs), the flow of CO2 from the soil surface to the atmosphere, is one of the largest carbon fluxes in the terrestrial biosphere. The spatial variability of Rs is both large and poorly understood, limiting our ability to robustly scale it in space. One factor in Rs spatial...
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The high temporal variability of the soil-to-atmosphere CO2 flux (soil respiration, RS) has been studied at hourly to multiannual timescales, but remains less well understood than RS spatial variability. How RS fluxes vary and are auto-correlated at various time lags has practical implications for...
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Clean energy from oceans and rivers is becoming a reality with the development of new technologies like tidal and instream turbines that generate electricity from naturally flowing water. These new technologies are being monitored for effects on fish and other wildlife using underwater video...
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Interactive data plots for proteomics and phosphoproteomics data from tumor (n=83) and normal tissue from high-grade serous ovarian cancer.
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Clinical Proteomic Tumor Analysis Consortium (CPTAC) ovarian cancer proteogenomics project. Characterization of tumors using proteomics and phosphoproteomics to identify signatures of drug resistance and characterize pathways associated with tumor versus normal tissue.
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Datasets
1
Dataset
Both the hourly and daily data are provided in the product. The hourly data are grouped by day in distinct NetCDF files, which are named as “EPIC_SW_PAR_Hourly_yyyymmdd.nc” where “yyyy”, “mm”, and “dd” denote year, month, and day (UTC time). The daily data are grouped by month in distinct NetCDF...
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Dataset
Both the hourly and daily data are provided in the product. The hourly data are grouped by day in distinct NetCDF files, which are named as “EPIC_SW_PAR_Hourly_yyyymmdd.nc” where “yyyy”, “mm”, and “dd” denote year, month, and day (UTC time). The daily data are grouped by month in distinct NetCDF...
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Dataset
Both the hourly and daily data are provided in the product. The hourly data are grouped by day in distinct NetCDF files, which are named as “EPIC_SW_PAR_Hourly_yyyymmdd.nc” where “yyyy”, “mm”, and “dd” denote year, month, and day (UTC time). The daily data are grouped by month in distinct NetCDF...
Category
Dataset
Both the hourly and daily data are provided in the product. The hourly data are grouped by day in distinct NetCDF files, which are named as “EPIC_SW_PAR_Hourly_yyyymmdd.nc” where “yyyy”, “mm”, and “dd” denote year, month, and day (UTC time). The daily data are grouped by month in distinct NetCDF...
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