The 1995 NRC Ratings of Doctoral Programs: A Hedonic Model

We describe how one can use multivariate regression models and data collected by the National Research Council as part of its recent ranking of doctoral programs (Research-Doctorate Programs in the United States: Continuity and Change) to analyze how measures of program size, faculty seniority, faculty research productivity, and faculty productivity in producing doctoral degrees influence subjective ratings of doctoral programs in 35 academic fields. Using data for one of the fields, economics, we illustrate how university administrators can use the models to compute the impact of changing the number of faculty positions they allocate to the field on the ranking of their programs. Finally, we illustrate how administrators can decompose the differences between a department\u27s rating and the ratings of a group of higher ranked departments in the field into difference due to faculty size, faculty seniority, faculty research productivity, and faculty productivity in producing doctoral students. This decomposition suggests the types of questions that a department and a university should be addressing if they are serious about wanting to improve the department\u27s ranking

Long-distance Spore Transport: Vertical Sections of Spore Clouds over the Sea

RESP-566

Cellular automaton rules conserving the number of active sites

This paper shows how to determine all the unidimensional two-state cellular automaton rules of a given number of inputs which conserve the number of active sites. These rules have to satisfy a necessary and sufficient condition. If the active sites are viewed as cells occupied by identical particles, these cellular automaton rules represent evolution operators of systems of identical interacting particles whose total number is conserved. Some of these rules, which allow motion in both directions, mimic ensembles of one-dimensional pseudo-random walkers. Numerical evidence indicates that the corresponding stochastic processes might be non-Gaussian.Comment: 14 pages, 5 figure

Improving measurements of SF6 for the study of atmospheric transport and emissions

Sulfur hexafluoride (SF6) is a potent greenhouse gas and useful atmospheric tracer. Measurements of SF6 on global and regional scales are necessary to estimate emissions and to verify or examine the performance of atmospheric transport models. Typical precision for common gas chromatographic methods with electron capture detection (GC-ECD) is 1–2%. We have modified a common GC-ECD method to achieve measurement precision of 0.5% or better. Global mean SF6 measurements were used to examine changes in the growth rate of SF6 and corresponding SF6 emissions. Global emissions and mixing ratios from 2000–2008 are consistent with recently published work. More recent observations show a 10% decline in SF6 emissions in 2008–2009, which seems to coincide with a decrease in world economic output. This decline was short-lived, as the global SF6 growth rate has recently increased to near its 2007–2008 maximum value of 0.30±0.03 pmol mol−1 (ppt) yr−1 (95% C.L.)

A Complexity View of Rainfall

We show that rain events are analogous to a variety of nonequilibrium relaxation processes in Nature such as earthquakes and avalanches. Analysis of high-resolution rain data reveals that power laws describe the number of rain events versus size and number of droughts versus duration. In addition, the accumulated water column displays scale-less fluctuations. These statistical properties are the fingerprints of a self-organized critical process and may serve as a benchmark for models of precipitation and atmospheric processes.Comment: 4 pages, 5 figure

Generalized (m,k)-Zipf law for fractional Brownian motion-like time series with or without effect of an additional linear trend

We have translated fractional Brownian motion (FBM) signals into a text based on two ''letters'', as if the signal fluctuations correspond to a constant stepsize random walk. We have applied the Zipf method to extract the $\zeta '$ exponent relating the word frequency and its rank on a log-log plot. We have studied the variation of the Zipf exponent(s) giving the relationship between the frequency of occurrence of words of length $m<8$ made of such two letters: $\zeta '$ is varying as a power law in terms of $m$. We have also searched how the $\zeta '$ exponent of the Zipf law is influenced by a linear trend and the resulting effect of its slope. We can distinguish finite size effects, and results depending whether the starting FBM is persistent or not, i.e. depending on the FBM Hurst exponent $H$. It seems then numerically proven that the Zipf exponent of a persistent signal is more influenced by the trend than that of an antipersistent signal. It appears that the conjectured law $\zeta ' = |2H-1|$ only holds near $H=0.5$. We have also introduced considerations based on the notion of a {\it time dependent Zipf law} along the signal.Comment: 24 pages, 12 figures; to appear in Int. J. Modern Phys

The effect of caffeine mouth rinse on self-paced cycling performance

The aim of the study was to determine whether caffeine mouth rinse would improve 30 min self-paced cycling trial. Twelve healthy active males (age 20.5±0.7 years, mass 87.4±18.3 kg) volunteered for the study. They attended the laboratory on 3 separate occasions performing a 30 min self-paced cycling trial. On one occasion water was given as a mouth rinse for 5 s (PLA), on another occasion a 6.4% maltodextrin (CHO) solution was given for 5 s and finally a caffeine solution (containing 32 mg of caffeine dissolved in 125 ml water; CAF) was given for 5 s. Distance cycled, heart rate, ratings of perceived exertion, cadence, speed and power output were recorded throughout all trials. Distance cycled during the CAF mouth rinse trial (16.2±2.8 km) was significantly greater compared to PLA trial (14.9±2.6 km). There was no difference between CHO and CAF trials (P=0.89). Cadence, power and velocity were significantly greater during the CAF trial compared to both PLA and CHO (P0.05). Caffeine mouth rinse improves 30 min cycling performance by allowing the participant to increase cadence, power and velocity without a concurrent increase in perceived exertion and heart rate

Anomalous jumping in a double-well potential

Noise induced jumping between meta-stable states in a potential depends on the structure of the noise. For an $\alpha$-stable noise, jumping triggered by single extreme events contributes to the transition probability. This is also called Levy flights and might be of importance in triggering sudden changes in geophysical flow and perhaps even climatic changes. The steady state statistics is also influenced by the noise structure leading to a non-Gibbs distribution for an $\alpha$-stable noise.Comment: 11 pages, 7 figure