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Full-Text Articles in Physical Sciences and Mathematics
A Study Of Indoor Carbon Dioxide Levels And Sick Leave Among Office Workers, Theodore A. Myatt, John W. Staudenmayer, Kate Adams, Michael Walters, Stephen N. Rudnick, Donald K. Milton
A Study Of Indoor Carbon Dioxide Levels And Sick Leave Among Office Workers, Theodore A. Myatt, John W. Staudenmayer, Kate Adams, Michael Walters, Stephen N. Rudnick, Donald K. Milton
John W Staudenmayer
Background A previous observational study detected a strong positive relationship between sick leave absences and carbon dioxide (CO2) concentrations in office buildings in the Boston area. The authors speculated that the observed association was due to a causal effect associated with low dilution ventilation, perhaps increased airborne transmission of respiratory infections. This study was undertaken to explore this association. Methods We conducted an intervention study of indoor CO2 levels and sick leave among hourly office workers employed by a large corporation. Outdoor air supply rates were adjusted periodically to increase the range of CO2 concentrations. We recorded indoor CO2 concentrations …
On Thickness And Packing Density For Knots And Links, Robert Kusner
On Thickness And Packing Density For Knots And Links, Robert Kusner
Robert Kusner
We describe some problems, observations, and conjectures concerning density of the hexagonal packing of unit disks in R2.thickness and packing density of knots and links in S3 and R3. We prove the thickness of a nontrivial knot or link in S3 is no more than 4 , the thickness of a Hopf link. We also give arguments and evidence supporting the conjecture that the packing density of thick links in R3 or S3 is generally less than √12 , the density of the hexagonal packing of unit disks in R2.
Statistical Issues In The Clustering Of Gene Expression Data, Darlene R. Goldstein, Debashis Ghosh, Erin M. Conlon
Statistical Issues In The Clustering Of Gene Expression Data, Darlene R. Goldstein, Debashis Ghosh, Erin M. Conlon
Erin M. Conlon
This paper illustrates some of the problems which can occur in any data set when clustering samples of gene expression profiles. These include a possible high degree of dependence of results on choice of clustering algorithm, further dependence of results on the choices of genes and samples to be included in the clustering (for example, whether or not to include control samples), and difficulty in assessing the validity of the grouping. We also demonstrate the use of Cox regression as a tool to identify genes influencing survival.