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As volume is more closely related to surface area (Winkler et al., 2010; in our data the LIs for volume and surface were also significantly correlated; r13 = 0.89, P = 0.000011), the outcomes may indeed be driven primarily by surface asymmetries.
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These maps graphically depict the accumulated susceptibility data in the LIS for all bacteria identified in samples from ICU patients during the previous year and from the patients who have undergone antibiograms.
The same indicator, in this case the ratio of physicians to nursing and midwifery personnel (indicator of skills mix), was measured for different countries through two different types of data sources: household-based labour force survey data (as compiled through the LIS project, see [ 30]) versus the routinely reported data.
The method is based on (1) summation and unfolding of multidimensional predicted classification scores, which results in a Linear Image Signature (LIS) and (2) multivariate LIS data analysis (LIS-MVA).
In addition, neither systemic nor pulmonary levels of suPAR (on admission and their maximal values) were associated with the extent of burn injury or the extent of pulmonary injury, as neither of them correlated with the percentage of TBSA burned, the LIS, or the OI (data not shown).
Using synoptic reports, consistent data elements with minimized typographical and transcription errors can be generated and placed in the LIS relational database, enabling quicker access to desired information and improved communication for appropriate cancer management.
The LIS is calculated by using the worst physical data recorded during the 24 hours of that day and the number of quadrants (0 4) on the chest radiograph showing alveolar consolidations.
Although several different data types may have been available in many countries, only selected surveys were retained by the LIS project based in part on comparability of information on income sources or other labour market indicators.
Many national statistical agencies participating in the LIS project mapped their occupational classifications to ISCO-88 for data dissemination.
(The LIS project had compiled surveys for nine other countries that were not used here because the occupational data did not enable differentiation of the health workforce).
I joined the Lis lab in April 2018.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com