First Observations of the Magnetic Field Geometry in Pre-stellar Cores

We present the first published maps of magnetic fields in pre-stellar cores, to test theoretical ideas about the way in which the magnetic field geometry affects the star formation process. The observations are JCMT-SCUBA maps of 850 micron thermal emission from dust. Linear polarizations at typically ten or more independent positions in each of three objects, L1544, L183 and L43 were measured, and the geometries of the magnetic fields in the plane of the sky were mapped from the polarization directions. The observed polarizations in all three objects appear smooth and fairly uniform. In L1544 and L183 the mean magnetic fields are at an angle of around 30 degrees to the minor axes of the cores. The L43 B-field appears to have been influenced in its southern half, such that it is parallel to the wall of a cavity produced by a CO outflow from a nearby T Tauri star, whilst in the northern half the field appears less disturbed and has an angle of 44 degrees to the core minor axis. We briefly compare our results with published models of magnetized cloud cores and conclude that no current model can explain these observations simultaneously with previous ISOCAM data.Comment: 13 pages, 3 figs, to appear in ApJ Letter

Melt-growth dynamics in CdTe crystals

We use a new, quantum-mechanics-based bond-order potential (BOP) to reveal melt-growth dynamics and fine-scale defect formation mechanisms in CdTe crystals. Previous molecular dynamics simulations of semiconductors have shown qualitatively incorrect behavior due to the lack of an interatomic potential capable of predicting both crystalline growth and property trends of many transitional structures encountered during the melt $\rightarrow$ crystal transformation. Here we demonstrate successful molecular dynamics simulations of melt-growth in CdTe using a BOP that significantly improves over other potentials on property trends of different phases. Our simulations result in a detailed understanding of defect formation during the melt-growth process. Equally important, we show that the new BOP enables defect formation mechanisms to be studied at a scale level comparable to empirical molecular dynamics simulation methods with a fidelity level approaching quantum-mechanical method

Lifetime predictions for the Solar Maximum Mission (SMM) and San Marco spacecraft

Lifetime prediction techniques developed by the Goddard Space Flight Center (GSFC) Flight Dynamics Division (FDD) are described. These techniques were developed to predict the Solar Maximum Mission (SMM) spacecraft orbit, which is decaying due to atmospheric drag, with reentry predicted to occur before the end of 1989. Lifetime predictions were also performed for the Long Duration Exposure Facility (LDEF), which was deployed on the 1984 SMM repair mission and is scheduled for retrieval on another Space Transportation System (STS) mission later this year. Concepts used in the lifetime predictions were tested on the San Marco spacecraft, which reentered the Earth's atmosphere on December 6, 1988. Ephemerides predicting the orbit evolution of the San Marco spacecraft until reentry were generated over the final 90 days of the mission when the altitude was less than 380 kilometers. The errors in the predicted ephemerides are due to errors in the prediction of atmospheric density variations over the lifetime of the satellite. To model the time dependence of the atmospheric densities, predictions of the solar flux at the 10.7-centimeter wavelength were used in conjunction with Harris-Priester (HP) atmospheric density tables. Orbital state vectors, together with the spacecraft mass and area, are used as input to the Goddard Trajectory Determination System (GTDS). Propagations proceed in monthly segments, with the nominal atmospheric drag model scaled for each month according to the predicted monthly average value of F10.7. Calibration propagations are performed over a period of known orbital decay to obtain the effective ballistic coefficient. Progagations using plus or minus 2 sigma solar flux predictions are also generated to estimate the despersion in expected reentry dates. Definitive orbits are compared with these predictions as time expases. As updated vectors are received, these are also propagated to reentryto continually update the lifetime predictions

Multiple Imputation Using Gaussian Copulas

Missing observations are pervasive throughout empirical research, especially in the social sciences. Despite multiple approaches to dealing adequately with missing data, many scholars still fail to address this vital issue. In this paper, we present a simple-to-use method for generating multiple imputations using a Gaussian copula. The Gaussian copula for multiple imputation (Hoff, 2007) allows scholars to attain estimation results that have good coverage and small bias. The use of copulas to model the dependence among variables will enable researchers to construct valid joint distributions of the data, even without knowledge of the actual underlying marginal distributions. Multiple imputations are then generated by drawing observations from the resulting posterior joint distribution and replacing the missing values. Using simulated and observational data from published social science research, we compare imputation via Gaussian copulas with two other widely used imputation methods: MICE and Amelia II. Our results suggest that the Gaussian copula approach has a slightly smaller bias, higher coverage rates, and narrower confidence intervals compared to the other methods. This is especially true when the variables with missing data are not normally distributed. These results, combined with theoretical guarantees and ease-of-use suggest that the approach examined provides an attractive alternative for applied researchers undertaking multiple imputations

Noise-Induced Building Vibrations Caused by Concorde and Conventional Aircraft Operations at Dulles and Kennedy International Airports

Outdoor and indoor noise levels resulting from aircraft flyovers and certain nonaircraft events were recorded, as were the associated vibration levels in the walls, windows, and floors at building test sites. In addition, limited subjective tests were conducted to examine the human detection and annoyance thresholds for building vibration and rattle caused by aircraft noise. Representative peak levels of aircraft noise-induced building vibrations are reported and comparisons are made with structural damage criteria and with vibration levels induced by common domestic events. In addition, results of a pilot study are reported which indicate the human detection threshold for noise-induced floor vibrations

Concorde noise-induced building vibrations John F. Kennedy International Airport

The outdoor and indoor noise levels resulting from aircraft flyovers and certain nonaircraft events were recorded at six home sites along with the associated vibration levels in the walls, windows, and floors of these test homes. Limited subjective tests conducted to examine the human detection and annoyance thresholds for building vibration and rattle caused by aircraft noise showed that both vibration and rattle were detected subjectively in several houses for some operations of both the Concorde and subsonic aircraft. Preliminary results indicate that the relationship between window vibration and aircraft noise is: (1) linear, with vibration levels being accurately predicted from OASPL levels measured near the window; (2) consistent from flyover to flyover for a given aircraft type under approach conditions; (3) no different for Concorde than for other conventional jet transports (in the case of window vibrations induced under approach power conditions); and (4) relatively high levels of window vibration measured during Concorde operations are due more to higher OASPL levels than to unique Concorde source characteristics

Concorde noise-induced building vibrations: John F. Kennedy International Airport

Outdoor and indoor noise levels resulting from aircraft flyovers and certain nonaircraft events were recorded at eight homesites and a school along with the associated vibration levels in the walls, windows, and floors at these test sites. Limited subjective tests were conducted to examine the human detection and annoyance thresholds for building vibration and rattle caused by aircraft noise. Both vibration and rattle were detected subjectively in several houses for some operations of both the Concorde and subsonic aircraft. Seated subjects more readily detected floor vibrations than wall or window vibrations. Aircraft noise generally caused more window vibrations than common nonaircraft events such as walking and closing doors. Nonaircraft events and aircraft flyovers resulted in comparable wall vibration levels, while floor vibrations were generally greater for nonaircraft events than for aircraft flyovers. The relationship between structural vibration and aircraft noise is linear, with vibration levels being accurately predicted from overall sound pressure levels (OASPL) measured near the structure. Relatively high levels of structural vibration measured during Concorde operations are due more to higher OASPL levels than to unique Concorde-source characteristics

Levels of genetic polymorphism: marker loci versus quantitative traits

Species are the units used to measure ecological diversity and alleles are the units of genetic diversity. Genetic variation within and among species has been documented most extensively using allozyme electrophoresis. This reveals wide differences in genetic variability within, and genetic distances among, species, demonstrating that species are not equivalent units of diversity. The extent to which the pattern observed for allozymes can be used to infer patterns of genetic variation in quantitative traits depends on the forces generating and maintaining variability. Allozyme variation is probably not strictly neutral but, nevertheless, heterozygosity is expected to be influenced by population size and genetic distance will be affected by time since divergence. The same is true for quantitative traits influenced by many genes and under weak stabilizing selection. However, the limited data available suggest that allozyme variability is a poor predictor of genetic variation in quantitative traits within populations. It is a better predictor of general phenotypic divergence and of postzygotic isolation between populations or species, but is only weakly correlated with prezygotic isolation. Studies of grasshopper and planthopper mating signal variation and assortative mating illustrate how these characters evolve independently of general genetic and morphological variation. The role of such traits in prezygotic isolation, and hence speciation, means that they will contribute significantly to the diversity of levels of genetic variation within and among species

A biophysical model of prokaryotic diversity in geothermal hot springs

Recent field investigations of photosynthetic bacteria living in geothermal hot spring environments have revealed surprisingly complex ecosystems, with an unexpected level of genetic diversity. One case of particular interest involves the distribution along hot spring thermal gradients of genetically distinct bacterial strains that differ in their preferred temperatures for reproduction and photosynthesis. In such systems, a single variable, temperature, defines the relevant environmental variation. In spite of this, each region along the thermal gradient exhibits multiple strains of photosynthetic bacteria adapted to several distinct thermal optima, rather than the expected single thermal strain adapted to the local environmental temperature. Here we analyze microbiology data from several ecological studies to show that the thermal distribution field data exhibit several universal features independent of location and specific bacterial strain. These include the distribution of optimal temperatures of different thermal strains and the functional dependence of the net population density on temperature. Further, we present a simple population dynamics model of these systems that is highly constrained by biophysical data and by physical features of the environment. This model can explain in detail the observed diversity of different strains of the photosynthetic bacteria. It also reproduces the observed thermal population distributions, as well as certain features of population dynamics observed in laboratory studies of the same organisms