Maxwell's Equations in a Uniformly Rotating Dielectric Medium and the Wilson-Wilson Experiment

This note offers a conceptually straightforward and efficient way to formulate and solve problems in the electromagnetics of moving media based on a representation of Maxwell's equations in terms of differential forms on spacetime together with junction conditions at moving interfaces. This framework is used to address a number of issues that have been discussed recently in this journal about the theoretical description underlying the interpretation of the Wilson-Wilson experiment.Comment: 16 pages, 2 figure

On the Ground Validation of Online Diagnosis with Twitter and Medical Records

Social media has been considered as a data source for tracking disease. However, most analyses are based on models that prioritize strong correlation with population-level disease rates over determining whether or not specific individual users are actually sick. Taking a different approach, we develop a novel system for social-media based disease detection at the individual level using a sample of professionally diagnosed individuals. Specifically, we develop a system for making an accurate influenza diagnosis based on an individual's publicly available Twitter data. We find that about half (17/35 = 48.57%) of the users in our sample that were sick explicitly discuss their disease on Twitter. By developing a meta classifier that combines text analysis, anomaly detection, and social network analysis, we are able to diagnose an individual with greater than 99% accuracy even if she does not discuss her health.Comment: Presented at of WWW2014. WWW'14 Companion, April 7-11, 2014, Seoul, Kore

On the Ground Validation of Online Diagnosis with Twitter and Medical Records

Social media has been considered as a data source for tracking disease. However, most analyses are based on models that prioritize strong correlation with population-level disease rates over determining whether or not specific individual users are actually sick. Taking a different approach, we develop a novel system for social-media based disease detection at the individual level using a sample of professionally diagnosed individuals. Specifically, we develop a system for making an accurate influenza diagnosis based on an individual's publicly available Twitter data. We find that about half (17/35 = 48.57%) of the users in our sample that were sick explicitly discuss their disease on Twitter. By developing a meta classifier that combines text analysis, anomaly detection, and social network analysis, we are able to diagnose an individual with greater than 99% accuracy even if she does not discuss her health.Comment: Presented at of WWW2014. WWW'14 Companion, April 7-11, 2014, Seoul, Kore

Flora of an unusually diverse old growth forest in the southeastern Adirondacks

A lowland, virgin white pine-hemlock stand and associated old-growth habitats were studied at Pack Forest Preserve, Warren County, NY. An area of 48.1 acres, interrupted only by nature trails, has white pines up to 58 inches in diameter, and supports 355 native plant species-an unexpectedly high number, considering its location in the climatically severe Adirondack Mountains. This minimally disturbed old-growth forest and its associated wetlands are not only diverse, but essentially weed-free, making them ideal for future ecological research, botanical teaching and monitoring activities

Physical Bias of Galaxies From Large-Scale Hydrodynamic Simulations

We analyze a new large-scale ($100h^{-1}$Mpc) numerical hydrodynamic simulation of the popular $\Lambda$CDM cosmological model, including in our treatment dark matter, gas and star-formation, on the basis of standard physical processes. The method, applied with a numerical resolution of $<200h^{-1}$kpc (which is still quite coarse for following individual galaxies, especially in dense regions), attempts to estimate where and when galaxies form. We then compare the smoothed galaxy distribution with the smoothed mass distribution to determine the "bias" defined as $b\equiv (\delta M/M)_{gal}/(\delta M/M)_{total}$ on scales large compared with the code numerical resolution (on the basis of resolution tests given in the appendix of this paper). We find that (holding all variables constant except the quoted one) bias increases with decreasing scale, with increasing galactic age or metallicity and with increasing redshift of observations. At the $8h^{-1}$Mpc fiducial comoving scale bias (for bright regions) is 1.35 at $z=0$ reaching to 3.6 at $z=3$, both numbers being consistent with extant observations. We also find that $(10-20)h^{-1}$Mpc voids in the distribution of luminous objects are as observed (i.e., observed voids are not an argument against CDM-like models) and finally that the younger systems should show a colder Hubble flow than do the early type galaxies (a testable proposition). Surprisingly, little evolution is found in the amplitude of the smoothed galaxy-galaxy correlation function (as a function of {\it comoving} separation). Testing this prediction vs observations will allow a comparison between this work and that of Kauffmann et al which is based on a different physical modelingmethod.Comment: in press, ApJ, 26 latex pages plus 7 fig

The Transition State in a Noisy Environment

Transition State Theory overestimates reaction rates in solution because conventional dividing surfaces between reagents and products are crossed many times by the same reactive trajectory. We describe a recipe for constructing a time-dependent dividing surface free of such recrossings in the presence of noise. The no-recrossing limit of Transition State Theory thus becomes generally available for the description of reactions in a fluctuating environment

Observational evidence for stochastic biasing

We show that the galaxy density in the Las Campanas Redshift Survey (LCRS) cannot be perfectly correlated with the underlying mass distribution since various galaxy subpopulations are not perfectly correlated with each other, even taking shot noise into account. This rules out the hypothesis of simple linear biasing, and suggests that the recently proposed stochastic biasing framework is necessary for modeling actual data.Comment: 4 pages, with 2 figures included. Minor revisions to match accepted ApJL version. Links and color fig at http://www.sns.ias.edu/~max/r_frames.html or from [email protected]