The Black Hole Mass - Stellar Velocity Dispersion Relationship for Quasars in the Sloan Digital Sky Survey Data Release 7

We assess evolution in the black hole mass - stellar velocity dispersion relationship (M-sigma relationship) for quasars in the Sloan Digital Sky Survey Data Release 7 for the redshift range 0.1 < z < 1.2. We estimate the black hole mass using the "photoionization method," with the broad Hbeta or Mg II emission line and the quasar continuum luminosity. For the stellar velocity dispersion, we use the narrow [O III] or [O II] emission line as a surrogate. This study is a follow-up to an earlier study in which we investigated evolution in the M-sigma relationship in quasars from Data Release 3. The greatly increased number of quasars in our new sample has allowed us to break our lower-redshift subsample into black hole mass bins and probe the M-sigma relationship for constant black hole mass. The M-sigma relationship for the highest-mass (log M > 9 solar masses) and lowest-mass (log M < 7.5 solar masses) black holes appears to evolve significantly, however most or all of this apparent evolution can be accounted for by various observational biases due to intrinsic scatter in the relationship and to uncertainties in observed quantities. The M-sigma relationship for black holes in the middle mass range (7.5 < log M < 9 solar masses) shows minimal change with redshift. The overall results suggest a limit of +/- 0.2 dex on any evolution in the M-sigma relationship for quasars out to z ~ 1 compared with the relationship observed in the local universe. Intrinsic scatter may also provide a plausible way to reconcile the wide range of results of several different studies of the black hole - galaxy relationships.Comment: 8 pages, 6 figures, submitted to Ap

Responses of king penguin Aptenodytes patagonicus adults and chicks to two food-related odours

Increasing evidence suggests that penguins are sensitive to dimethyl sulphide (DMS), a scented airborne compound that a variety of marine animals use to find productive areas of the ocean where prey is likely to be found. Here we present data showing that king penguins Aptenodytes patagonicus are also sensitive to DMS. We deployed DMS on a lake near a king penguin colony at Ratmanoff beach in the Kerguelen archipelago. We also presented DMS to ‘sleeping’ adults on the beach. On the lake, penguins responded to the DMS deployments by swimming more, while on the beach, penguins twitched their heads and woke up more for the DMS than for the control presentations. Interestingly, penguins did not respond to cod liver oil deployments on the lake; mirroring at-sea studies of other penguins. Although at-sea studies are needed to confirm that king penguins use DMS as a surface cue that informs them of productivity under the water, this study is an important first step in understanding how these birds locate prey over significant distances

Ablution of the Self

Artwor

Getting Around When You’re Just Getting By: The Travel Behavior and Transportation Expenditures of Low-Income Adults, MTI Report 10-02

How much do people with limited resources pay for cars, public transit, and other means of travel? How does their transportation behavior change during periods of falling employment and rising fuel prices? This research uses in-depth interviews with 73 adults to examine how rising transportation costs impact low-income families. The interviews examine four general areas of interest: travel behavior and transportation spending patterns; the costs and benefits of alternative modes of travel; cost management strategies; and opinions about the effect of changing transportation prices on travel behavior. Key findings include: Most low-income household are concerned about their transportation costs. Low-income individuals actively and strategically manage their household resources in order to survive on very limited means and to respond to changes in income or transportation costs. In making mode-choice decisions, low-income travelers—like higher-income travelers—carefully evaluate the costs of travel (time and out-of-pocket expenses) against the benefits of each of the modes. Some low-income individuals in our sample were willing to endure higher transportation expenditures—such as the costs of auto ownership or congestion tolls—if they believed that they currently benefit or would potentially benefit from these increased expenses. Although low-income households find ways to cover their transportation expenditures, many of these strategies had negative effects on households. The report concludes with recommendations on how to increase transportation affordability, minimize the impact that new transportation taxes or fees have on low-income people, and develop new research and data collection to support the previous two efforts