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Assuming a simple Norton type of creep law (ε˙="B·σn, where ˙ε is the secondary creep rate, B the creep constant and σ is the applied stress), we present two procedures based on creep finite element stress and strain analysis which enable the results from bending creep data to be translated into the corresponding Norton law creep parameters.
Output tattoos, on the other hand, allow data to be translated into visual designs.
It is anticipated that proper understanding of and progress in application of predictive approaches for PK and PK-PD data to be translated from animals and humans will lead to an improved predictive value.
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We show how to develop such an ontology and use it to mediate translation through a real scenario where water resources data have to be translated to a standard data transfer format.
All timeseries data need to be translated to the standard data representation format STML.
However, these new data have to be translated into well-designed clinical intervention studies.
To determine the design criteria, the physical data has to be translated into physical variables (amplitudes, pressures, frequencies, etc).
It requires creativity and flexibility, because hard scientific data need to be translated into product claims that truly matter to consumers.
The XML data need to be translated into web pages to be readable by users.
"In health care, there's this gigantic world of unstructured data that needs to be translated into useable information," says Paul Nemirovsky, who co-founded dMetrics with Ariadna Quattoni.
"In health care, there's this gigantic world of unstructured data that needs to be translated into useable information," says Paul Nemirovsky PhD '06, who co-founded dMetrics with Ariadna Quattoni PhD '09.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com