Gambling and the use of credit: an individual and household level analysis

We explore the relationship between gambling and other forms of risk-taking behaviour, i.e. exposure to debt and the use of credit, at the individual and household level using representative pooled cross-section data drawn from the UK Expenditure and Food Surveys (EFS), 2001 to 2007. Gambling and the use of credit are shown to be positively correlated at the household level. While both the incidence and amount of gambling vary according to household income, the positive association between gambling and the use of credit is remarkably stable across household income. In addition to our household level analysis, we also explore the prevalence of intra-household gambling, which has attracted relatively limited attention in the existing literature. It is apparent that there is strong intra-household correlation in both gambling activity and in the use of credit, with somewhat stronger relationships in lower income households

Balancing the Tradeoff between Profit and Fairness in Rideshare Platforms During High-Demand Hours

Rideshare platforms, when assigning requests to drivers, tend to maximize profit for the system and/or minimize waiting time for riders. Such platforms can exacerbate biases that drivers may have over certain types of requests. We consider the case of peak hours when the demand for rides is more than the supply of drivers. Drivers are well aware of their advantage during the peak hours and can choose to be selective about which rides to accept. Moreover, if in such a scenario, the assignment of requests to drivers (by the platform) is made only to maximize profit and/or minimize wait time for riders, requests of a certain type (e.g. from a non-popular pickup location, or to a non-popular drop-off location) might never be assigned to a driver. Such a system can be highly unfair to riders. However, increasing fairness might come at a cost of the overall profit made by the rideshare platform. To balance these conflicting goals, we present a flexible, non-adaptive algorithm, \lpalg, that allows the platform designer to control the profit and fairness of the system via parameters $\alpha$ and $\beta$ respectively. We model the matching problem as an online bipartite matching where the set of drivers is offline and requests arrive online. Upon the arrival of a request, we use \lpalg to assign it to a driver (the driver might then choose to accept or reject it) or reject the request. We formalize the measures of profit and fairness in our setting and show that by using \lpalg, the competitive ratios for profit and fairness measures would be no worse than $\alpha/e$ and $\beta/e$ respectively. Extensive experimental results on both real-world and synthetic datasets confirm the validity of our theoretical lower bounds. Additionally, they show that \lpalg under some choice of $(\alpha, \beta)$ can beat two natural heuristics, Greedy and Uniform, on \emph{both} fairness and profit

Calculations of Neutron Reflectivity in the eV Energy Range from Mirrors made of Heavy Nuclei with Neutron-Nucleus Resonances

We evaluate the reflectivity of neutron mirrors composed of certain heavy nuclei which possess strong neutron-nucleus resonances in the eV energy range. We show that the reflectivity of such a mirror for some nuclei can in principle be high enough near energies corresponding to compound neutron-nucleus resonances to be of interest for certain scientific applications in non-destructive evaluation of subsurface material composition and in the theory of neutron optics beyond the kinematic limit.Comment: 18 pages, 5 figures, 1 tabl

Confluent Orthogonal Drawings of Syntax Diagrams

We provide a pipeline for generating syntax diagrams (also called railroad diagrams) from context free grammars. Syntax diagrams are a graphical representation of a context free language, which we formalize abstractly as a set of mutually recursive nondeterministic finite automata and draw by combining elements from the confluent drawing, layered drawing, and smooth orthogonal drawing styles. Within our pipeline we introduce several heuristics that modify the grammar but preserve the language, improving the aesthetics of the final drawing.Comment: GD 201

Investigating Sources of Variability and Error in Simulations of Carbon Dioxide in an Urban Region

Greenhouse gas (GHG) emissions estimation methods that use atmospheric trace gas observations, including inverse modeling techniques, perform better when carbon dioxide (CO2) fluxes are more accurately transported and dispersed in the atmosphere by a numerical model. In urban areas, transport and dispersion is particularly difficult to simulate using current mesoscale meteorological models due, in part, to added complexity from surface heterogeneity and fine spatial/temporal scales. It is generally assumed that the errors in GHG estimation methods in urban areas are dominated by errors in transport and dispersion. Other significant errors include, but are not limited to, those from assumed emissions magnitude and spatial distribution. To assess the predictability of simulated trace gas mole fractions in urban observing systems using a numerical weather prediction model, we employ an Eulerian model that combines traditional meteorological variables with multiple passive tracers of atmospheric CO2 from anthropogenic inventories and a biospheric model. The predictability of the Eulerian model is assessed by comparing simulated atmospheric CO2 mole fractions to observations from four in situ tower sites (three urban and one rural) in the Washington DC/Baltimore, MD area for February 2016. Four different gridded fossil fuel emissions inventories along with a biospheric flux model are used to create an ensemble of simulated atmospheric CO2 observations within the model. These ensembles help to evaluate whether the modeled observations are impacted more by the underlying emissions or transport. The spread of modeled observations using the four emission fields indicates the model's ability to distinguish between the different inventories under various meteorological conditions. Overall, the Eulerian model performs well; simulated and observed average CO2 mole fractions agree within 1% when averaged at the three urban sites across the month. However, there can be differences greater than 10% at any given hour, which are attributed to complex meteorological conditions rather than differences in the inventories themselves. On average, the mean absolute error of the simulated compared to actual observations is generally twice as large as the standard deviation of the modeled mole fractions across the four emission inventories. This result supports the assumption, in urban domains, that the predicted mole fraction error relative to observations is dominated by errors in model meteorology rather than errors in the underlying fluxes in winter months. As such, minimizing errors associated with atmospheric transport and dispersion may help improve the performance of GHG estimation models more so than improving flux priors in the winter months. We also find that the errors associated with atmospheric transport in urban domains are not restricted to certain times of day. This suggests that atmospheric inversions should use CO2 observations that have been filtered using meteorological observations rather than assuming that meteorological modeling is most accurate at certain times of day (such as using only mid-afternoon observations)

NOTES: WOODPECKER FORAGE AVAILABILITY IN HABI- TAT DISTURBANCES OF THE BLACK HILLS

Habitat disturbance events are critical to ecological systems in which some bird species have become specialized. The vegetation community, reduced competition, ability to avoid predators, nest-site characteristics, and forage opportunities within a disturbed ecosystem are all aspects that make it desirable for selection by particular species (Svärdson 1949, Cody 1981, Martin 1998). Specifically, avian species rely on the forest conditions created by fire, insects, and disease (Brawn et al. 2001, Hunter et al. 2001, Devictor et al. 2008). In the Black Hills National Forest (BHNF) of South Dakota,two major types of natural disturbances include wildfires and mountain pine beetle (Dendroctonus ponderosae; MPB) infestations. Dead trees (snags) created by these disturbances attract a suite of insects and wildlife species. Bark beetles (Family: Curculionidae, Scolytinae) and wood borer beetles (Families: Buprestidae and Cerambycidae) are of particular importance to black-backed woodpeckers (Picoides arcticus; BBWO) because they feed almost exclusively on the larvae of these insects (Beal 1911, Murphy and Lehnhausen 1998, Hutto 2006, Bonnot et al. 2008, Bonnot et al. 2009). Black-backed woodpeckers are of key interest to resource management agencies due to their habitat specialization needs and the management activities like wildfire salvage logging and pre-thinning that occur in these disturbance areas (Hutto 1995, 2006). These management activities potentially reduce nest site and food availability for BBWOs and, as a result, they were recently petitioned for protection under the Endangered Species Act (Hanson et al. 2012). Following a fire event or insect infestation, the relative probability of using trees affected by the disturbance increases over surrounding healthy trees (Rota 2013). As a result, we were interested in understanding the food that is available to the woodpeckers following these forest disturbances

Vulnerability analysis of satellite-based synchronized smart grids monitoring systems

The large-scale deployment of wide-area monitoring systems could play a strategic role in supporting the evolution of traditional power systems toward smarter and self-healing grids. The correct operation of these synchronized monitoring systems requires a common and accurate timing reference usually provided by a satellite-based global positioning system. Although these satellites signals provide timing accuracy that easily exceeds the needs of the power industry, they are extremely vulnerable to radio frequency interference. Consequently, a comprehensive analysis aimed at identifying their potential vulnerabilities is of paramount importance for correct and safe wide-area monitoring system operation. Armed with such a vision, this article presents and discusses the results of an experimental analysis aimed at characterizing the vulnerability of global positioning system based wide-area monitoring systems to external interferences. The article outlines the potential strategies that could be adopted to protect global positioning system receivers from external cyber-attacks and proposes decentralized defense strategies based on self-organizing sensor networks aimed at assuring correct time synchronization in the presence of external attacks