Mapping the distribution of luminous and dark matter in strong lensing galaxies

We present the distribution of luminous and dark matter in a set of strong lensing (early-type) galaxies. By combining two independent techniques - stellar population synthesis and gravitational lensing - we can compare the baryonic and dark matter content in these galaxies within the regions that can be probed using the images of the lensed background source. Two samples were studied, extracted from the CASTLES and SLACS surveys. The former probes a wider range of redshifts and allows us to explore the mass distribution out to ~5Re. The high resolution optical images of the latter (using HST/ACS) are used to show a pixellated map of the ratio between total and baryonic matter. We find dark matter to be absent in the cores of these galaxies, with an increasing contribution at projected radii R>Re. The slopes are roughly compatible with an isothermal slope (better interpreted as an adiabatically contracted NFW profile), but a large scatter in the slope exists among galaxies. There is a trend suggesting most massive galaxies have a higher content of dark matter in the regions probed by this analysis.Comment: 10 pages, 6 figures. To appear in "Dark Galaxies and Lost Baryons", IAU244 conference proceeding

Terpenoid-Induced Feeding Deterrence and Antennal Response of Honey Bees

Multiple interacting stressors negatively affect the survival and productivity of managed honey bee colonies. Pesticides remain a primary concern for beekeepers, as even sublethal exposures can reduce bee immunocompetence, impair navigation, and reduce social communication. Pollinator protection focuses on pesticide application guidelines; however, a more active protection strategy is needed. One possible approach is the use of feeding deterrents that can be delivered as an additive during pesticide application. The goal of this study was to validate a laboratory assay designed to rapidly screen compounds for behavioral changes related to feeding or feeding deterrence. The results of this investigation demonstrated that the synthetic Nasonov pheromone and its terpenoid constituents citral, nerol, and geraniol could alter feeding behavior in a laboratory assay. Additionally, electroantennogram assays revealed that these terpenoids elicited some response in the antennae; however, only a synthetic Nasonov pheromone, citral, and geraniol elicited responses that differed significantly from control and vehicle detections

Spatio-temporal cluster analysis of county-based human West Nile virus incidence in the continental United States

<p>Abstract</p> <p>Background</p> <p>West Nile virus (WNV) is a vector-borne illness that can severely affect human health. After introduction on the East Coast in 1999, the virus quickly spread and became established across the continental United States. However, there have been significant variations in levels of human WNV incidence spatially and temporally. In order to quantify these variations, we used Kulldorff's spatial scan statistic and Anselin's Local Moran's I statistic to uncover spatial clustering of human WNV incidence at the county level in the continental United States from 2002–2008. These two methods were applied with varying analysis thresholds in order to evaluate sensitivity of clusters identified.</p> <p>Results</p> <p>The spatial scan and Local Moran's I statistics revealed several consistent, important clusters or hot-spots with significant year-to-year variation. In 2002, before the pathogen had spread throughout the country, there were significant regional clusters in the upper Midwest and in Louisiana and Mississippi. The largest and most consistent area of clustering throughout the study period was in the Northern Great Plains region including large portions of Nebraska, South Dakota, and North Dakota, and significant sections of Colorado, Wyoming, and Montana. In 2006, a very strong cluster centered in southwest Idaho was prominent. Both the spatial scan statistic and the Local Moran's I statistic were sensitive to the choice of input parameters.</p> <p>Conclusion</p> <p>Significant spatial clustering of human WNV incidence has been demonstrated in the continental United States from 2002–2008. The two techniques were not always consistent in the location and size of clusters identified. Although there was significant inter-annual variation, consistent areas of clustering, with the most persistent and evident being in the Northern Great Plains, were demonstrated. Given the wide variety of mosquito species responsible and the environmental conditions they require, further spatio-temporal clustering analyses on a regional level is warranted.</p

Ecological Niche Modeling of Potential West Nile Virus Vector Mosquito Species in Iowa

Ecological niche modeling (ENM) algorithms, Maximum Entropy Species Distribution Modeling (Maxent) and Genetic Algorithm for Rule-set Prediction (GARP), were used to develop models in Iowa for three species of mosquito — two significant, extant West Nile virus (WNV) vectors (Culex pipiens L and Culex tarsalis Coquillett (Diptera: Culicidae)), and the nuisance mosquito, Aedes vexans Meigen (Diptera: Culicidae), a potential WNV bridge vector. Occurrence data for the three mosquito species from a state-wide arbovirus surveillance program were used in combination with climatic and landscape layers. Maxent successfully created more appropriate niche models with greater accuracy than GARP. The three Maxent species' models were combined and the average values were statistically compared to human WNV incidence at the census block group level. The results showed that the Maxent-modeled species' niches averaged together were a useful indicator of WNV human incidence in the state of Iowa. This simple method for creating probability distribution maps proved useful for understanding WNV dynamics and could be applied to the study of other vector-borne diseases

Terpenoid-Induced Feeding Deterrence and Antennal Response of Honey Bees

Multiple interacting stressors negatively affect the survival and productivity of managed honey bee colonies. Pesticides remain a primary concern for beekeepers, as even sublethal exposures can reduce bee immunocompetence, impair navigation, and reduce social communication. Pollinator protection focuses on pesticide application guidelines; however, a more active protection strategy is needed. One possible approach is the use of feeding deterrents that can be delivered as an additive during pesticide application. The goal of this study was to validate a laboratory assay designed to rapidly screen compounds for behavioral changes related to feeding or feeding deterrence. The results of this investigation demonstrated that the synthetic Nasonov pheromone and its terpenoid constituents citral, nerol, and geraniol could alter feeding behavior in a laboratory assay. Additionally, electroantennogram assays revealed that these terpenoids elicited some response in the antennae; however, only a synthetic Nasonov pheromone, citral, and geraniol elicited responses that differed significantly from control and vehicle detections

Extended Near-Infrared Emission from Candidate Protostars in the Taurus-Auriga Molecular Cloud

We describe near-IR imaging data for a sample of 23 class I sources in the Taurus-Auriga dark clouds. Combining our data with previous photometry, we detect brightness variations of 0.1-0.5 mag in many sources. The near-IR morphologies are consistent with mm continuum measurements. Most (60%) of the sample are true protostars; the rest may be objects in transition between class I and class II, T Tauri stars with edge-on disks, or heavily reddened T Tauri stars.Comment: 15 pages, 3 tables, 4 figures; to appear in the June 2002 Astronomical Journa

Angular diameters, fluxes and extinction of compact planetary nebulae: further evidence for steeper extinction towards the Bulge

We present values for angular diameter, flux and extinction for 70 Galactic planetary nebulae observed using narrow band filters. Angular diameters are derived using constant emissivity shell and photoionization line emission models. The mean of the results from these two models are presented as our best estimate. Contour plots of 36 fully resolved objects are included and the low intensity contours often reveal an elliptical structure that is not always apparent from FWHM measurements. Flux densities are determined, and for both H-alpha and O[III] there is little evidence of any systematic differences between observed and catalogued values. Observed H-alpha extinction values are determined using observed H-alpha and catalogued radio fluxes. H-alpha extinction values are also derived from catalogued H-alpha and H-beta flux values by means of an Rv dependent extinction law. Rv is then calculated in terms of observed extinction values and catalogued H-alpha and H-beta flux values. Comparing observed and catalogue extinction values for a subset of Bulge objects, observed values tend to be lower than catalogue values calculated with Rv = 3.1. For the same subset we calculate = 2.0, confirming that toward the Bulge interstellar extinction is steeper than Rv = 3.1. For the inner Galaxy a relation with the higher supernova rate is suggested, and that the low-density warm ionized medium is the site of the anomalous extinction. Lowvalues of extinction are also derived using dust models with a turnover radius of 0.08 microns.Comment: Accepted by MNRAS. 17 pages, 9 figures (including 36 contour plots of PNe), 5 Tables (including 2 large tables of angular diameters, fluxes and extinction

Gravity Spy: Integrating Advanced LIGO Detector Characterization, Machine Learning, and Citizen Science

(abridged for arXiv) With the first direct detection of gravitational waves, the Advanced Laser Interferometer Gravitational-wave Observatory (LIGO) has initiated a new field of astronomy by providing an alternate means of sensing the universe. The extreme sensitivity required to make such detections is achieved through exquisite isolation of all sensitive components of LIGO from non-gravitational-wave disturbances. Nonetheless, LIGO is still susceptible to a variety of instrumental and environmental sources of noise that contaminate the data. Of particular concern are noise features known as glitches, which are transient and non-Gaussian in their nature, and occur at a high enough rate so that accidental coincidence between the two LIGO detectors is non-negligible. In this paper we describe an innovative project that combines crowdsourcing with machine learning to aid in the challenging task of categorizing all of the glitches recorded by the LIGO detectors. Through the Zooniverse platform, we engage and recruit volunteers from the public to categorize images of glitches into pre-identified morphological classes and to discover new classes that appear as the detectors evolve. In addition, machine learning algorithms are used to categorize images after being trained on human-classified examples of the morphological classes. Leveraging the strengths of both classification methods, we create a combined method with the aim of improving the efficiency and accuracy of each individual classifier. The resulting classification and characterization should help LIGO scientists to identify causes of glitches and subsequently eliminate them from the data or the detector entirely, thereby improving the rate and accuracy of gravitational-wave observations. We demonstrate these methods using a small subset of data from LIGO's first observing run.Comment: 27 pages, 8 figures, 1 tabl