Interurban Bus: Time to Raise the Profile

A review of development of interurban bus services in Britain in recent years, including case studies showing the effects of major quality improvements and ridership growth, often filling gaps in the rail network. Policy recommendations

Bromide and other ions in the snow, firn air, and atmospheric boundary layer at Summit during GSHOX

Measurements of gas phase soluble bromide in the boundary layer and in firn air, and Br− in aerosol and snow, were made at Summit, Greenland (72.5° N, 38.4° W, 3200 m a.s.l.) as part of a larger investigation into the influence of Br chemistry on HOx cycling. The soluble bromide measurements confirm that photochemical activation of Br− in the snow causes release of active Br to the overlying air despite trace concentrations of Br− in the snow (means 15 and 8 nmol Br− kg−1 of snow in 2007 and 2008, respectively). Mixing ratios of soluble bromide above the snow were also found to be very small (mean \u3c1 ppt both years, with maxima of 3 and 4 ppt in 2007 and 2008, respectively), but these levels clearly oxidize and deposit long-lived gaseous elemental mercury and may perturb HOx partitioning. Concentrations of Br− in surface snow tended to increase/decrease in parallel with the specific activities of the aerosol-associated radionuclides 7Be and 210Pb. Earlier work has shown that ventilation of the boundary layer causes simultaneous increases in 7Be and 210Pb at Summit, suggesting there is a pool of Br in the free troposphere above Summit in summer time. Speciation and the source of this free tropospheric Br− are not well constrained, but we suggest it may be linked to extensive regions of active Br chemistry in the Arctic basin which are known to cause ozone and mercury depletion events shortly after polar sunrise. If this hypothesis is correct, it implies persistence of the free troposphere Br− for several months after peak Br activation in March/April. Alternatively, there may be a ubiquitous pool of Br− in the free troposphere, sustained by currently unknown sources and processes

General Relativistic Three-Dimensional Multi-Group Neutrino Radiation-Hydrodynamics Simulations of Core-Collapse Supernovae

We report on a set of long-term general-relativistic three-dimensional (3D) multi-group (energy-dependent) neutrino-radiation hydrodynamics simulations of core-collapse supernovae. We employ a full 3D two-moment scheme with the local M1 closure, three neutrino species, and 12 energy groups per species. With this, we follow the post-core-bounce evolution of the core of a nonrotating $27$-$M_\odot$ progenitor in full unconstrained 3D and in octant symmetry for $\gtrsim$$380\,\mathrm{ms}$. We find the development of an asymmetric runaway explosion in our unconstrained simulation. We test the resolution dependence of our results and, in agreement with previous work, find that low resolution artificially aids explosion and leads to an earlier runaway expansion of the shock. At low resolution, the octant and full 3D dynamics are qualitatively very similar, but at high resolution, only the full 3D simulation exhibits the onset of explosion.Comment: Accepted to Ap

Comprehension as social and intellectual practice: Rebuilding curriculum in low socioeconomic and cultural minority schools

This article reframes the concept of comprehension as a social and intellectual practice. It reviews current approaches to reading instruction for linguistically and culturally diverse and low socioeconomic students, noting an emphasis on comprehension as autonomous skills. The Four Resources model (Freebody & Luke, 1990) is used to make the case for the integration of comprehension instruction with an emphasis on student cultural and community knowledge, and substantive intellectual and sociocultural content in elementary school curricula. Illustrations are drawn from research underway on the teaching of literacy in primary schools in low SES communities

Correlation effects in quasi one dimensional electron wires

We explore the role of electron correlation in quasi one dimensional quantum wires as the range of the interaction potential is changed and their thickness is varied by performing exact quantum Monte Carlo simulations at various electronic densities. In the case of unscreened interactions with a long range 1/x tail there is a crossover from a liquid to a quasi Wigner crystal state as the density decreases. When this interaction is screened, quasi long range order is prevented from forming, although a significant correlation with 4 k_F periodicity is still present at low densities. At even lower electron concentration, exchange is suppressed and the spin-dependent interactions become negligible, making the electrons behave like spinless fermions. We show that this behavior is shared by the long range and screened interactions by studying the spin and charge excitations of the system in both cases. Finally, we study the effect of electron correlations in the double quantum wire experiment [Steinberg et al., Phys. Rev. B 77, 113307 (2006)], by introducing an accurate model for the screening in the experiment and explicitly including the finite length of the system in our simulations. We find that decreasing the electron density drives the system from a liquid to a state with quite strong 4 k_F correlations. This crossover takes place around $20 \mu m^{-1}$, the density where the electron localization occurs in the experiment. The charge and spin velocities are also in remarkable agreement with the experimental findings in the proximity of the crossover. We argue that correlation effects play an important role at the onset of the localization transition.Comment: minor improvements, 13 pages, 12 figure

Hierarchical Bayesian CMB Component Separation with the No-U-Turn Sampler

Key to any cosmic microwave background (CMB) analysis is the separation of the CMB from foreground contaminants. In this paper we present a novel implementation of Bayesian CMB component separation. We sample from the full posterior distribution using the No-U-Turn Sampler (NUTS), a gradient based sampling algorithm. Alongside this, we introduce new foreground modelling approaches. We use the mean-shift algorithm to define regions on the sky, clustering according to naively estimated foreground spectral parameters. Over these regions we adopt a complete pooling model, where we assume constant spectral parameters, and a hierarchical model, where we model individual spectral parameters as being drawn from underlying hyper-distributions. We validate the algorithm against simulations of the LiteBIRD and C-BASS experiments, with an input tensor-to-scalar ratio of $r=5\times 10^{-3}$. Considering multipoles $32\leq\ell\leq 121$, we are able to recover estimates for $r$. With LiteBIRD only observations, and using the complete pooling model, we recover $r=(10\pm 0.6)\times 10^{-3}$. For C-BASS and LiteBIRD observations we find $r=(7.0\pm 0.6)\times 10^{-3}$ using the complete pooling model, and $r=(5.0\pm 0.4)\times 10^{-3}$ using the hierarchical model. By adopting the hierarchical model we are able to eliminate biases in our cosmological parameter estimation, and obtain lower uncertainties due to the smaller Galactic emission mask that can be adopted for power spectrum estimation. Measured by the rate of effective sample generation, NUTS offers performance improvements of $\sim10^3$ over using Metropolis-Hastings to fit the complete pooling model. The efficiency of NUTS allows us to fit the more sophisticated hierarchical foreground model, that would likely be intractable with non-gradient based sampling algorithms.Comment: 19 pages, 9 figure

On the Prediction of Extreme Ecological Events

Ecological studies often focus on average effects of environmental factors, but ecological dynamics may depend as much upon environmental extremes. Ecology would therefore benefit from the ability to predict the frequency and severity of extreme environmental events. Some extreme events (e.g., earthquakes) are simple events: either they happen or they don\u27t, and they are generally difficult to predict. In contrast, extreme ecological events are often compound events, resulting from the chance coincidence of run-of-the-mill factors. Here we present an environmental bootstrap method for resampling short-term environmental data (rolling the environmental dice) to calculate an ensemble of hypothetical time series that embodies how the physical environment could potentially play out differently. We use this ensemble in conjunction with mechanistic models of physiological processes to analyze the biological consequences of environmental extremes. Our resampling method provides details of these consequences that would be difficult to obtain otherwise, and our methodology can be applied to a wide variety of ecological systems. Here, we apply this approach to calculate return times for extreme hydrodynamic and thermal events on intertidal rocky shores. Our results demonstrate that the co-occurrence of normal events can indeed lead to environmental extremes, and that these extremes can cause disturbance. For example, the limpet Lottia gigantea and the mussel Mytilus californianus are co-dominant competitors for space on wave-swept rocky shores, but their response to extreme environmental events differ. Limpet mortality can vary drastically through time. Average yearly maximum body temperature of L. gigantea on horizontal surfaces is low, sufficient to kill fewer than 5% of individuals, but on rare occasions environmental factors align by chance to induce temperatures sufficient to kill \u3e99% of limpets. In contrast, mussels do not exhibit large temporal variation in the physical disturbance caused by breaking waves, and this difference in the pattern of disturbance may have ecological consequences for these competing species. The effect of environmental extremes is under added scrutiny as the frequency of extreme events increases in response to anthropogenically forced climate change. Our method can be used to discriminate between chance events and those caused by long-term shifts in climate