Fractional Stokes-Einstein and Debye-Stokes-Einstein relations in a network forming liquid

We study the breakdown of the Stokes-Einstein (SE) and Debye-Stokes-Einstein (DSE) relations for translational and rotational motion in a prototypical model of a network-forming liquid, the ST2 model of water. We find that the emergence of ``fractional'' SE and DSE relations at low temperature is ubiquitous in this system, with exponents that vary little over a range of distinct physical regimes. We also show that the same fractional SE relation is obeyed by both mobile and immobile dynamical heterogeneities of the liquid

USING ORIENTATION TO CONVEY ALERT QUANTITY

Vast amounts of data are presented to users in digital systems that generally require visualizations to simplify and provide more insights in a small number of pixels. This is crucial for targeting users who do not have the time or inclination to parse a large number of charts and graphs, but who want to understand what is happening with their digital systems. To solve this issue, proposed herein is a technique that relies on using the orientation of colored stripes to add a dimension of information to a large dataset, such as a health bar chart indicating alerts. The proposed technique will assist in conveying aspects of a digital system to some users, while also not getting in the way of other users in the same space who do not know what it means

Evidence for roll vortices associated with a land breeze

Time series measurements from an array of meteorological buoys off the Oregon coast displayed periodicities that suggest the presence of atmospheric roll vortices. The roll vortices were associated with nocturnal land breezes, cool air masses moving slowly seaward through the buoy array under the prevailing longshore wind of marine air. It appears that buoyancy and shear are the mechanisms responsible for the observed rolls

Projecting a High-School Quarterback’s Performance at the Collegiate Level: A Comparison of the Rivals, 247 Sports, and ESPN Recruiting Ratings

We examine recruiting ratings for high-school quarterbacks over the period 2006-2012 from Rivals, 247 Sports, and ESPN.  Using Lee & Preacher’s (2013) test of the difference between two dependent correlations with one variable in common and ordinary least squares regression, we determine that the Rivals ratings have the strongest correlation with quarterback performance over the time-period examined.  The 247 Sports ratings follow closely behind the Rivals ratings; however, the ESPN ratings correlate more weakly with a quarterback’s career performance in college