Rainfall interception by Santa Monica's municipal urban forest

Effects of urban forests on rainfall interception and runoff reduction have been conceptualized, but not well quantified. In this study rainfall interception by street and park trees in Santa Monica, California is simulated. A mass and energy balance rainfall interception model is used to simulate rainfall interception processes (e.g., gross precipitation, free throughfall, canopy drip, stemflow, and evaporation). Annual rainfall interception by the 29,299 street and park trees was 193,168 m³ (6.6 m³/tree), or 1.6% of total precipitation. The annual value of avoided stormwater treatment and flood control costs associated with reduced runoff was $110,890 ($3.60/tree). Interception rate varied with tree species and sizes. Rainfall interception ranged from 15.3% (0.8 m³/tree) for a small Jacaranda mimosifolia (3.5 cm diameter at breast height) to 66.5% (20.8 m³/tree) for a mature Tristania conferta (38.1 cm). In a 25-year storm, interception by all street and park trees was 12,139.5 m³ (0.4%), each tree yielding $0.60 (0.4 m³/tree) in avoided flood control costs. Rainfall interception varied seasonally, averaging 14.8% during a 21.7 mm winter storm and 79.5% during a 20.3 mm summer storm for a large, deciduous Platanus acerifolia tree. Effects of differences in temporal precipitation patterns, tree population traits, and pruning practices on interception in Santa Monica, Modesto, and Sacramento, California are described.     

Implementation in generic environments

In this paper, we study implementation in “economic environments”. It is shown that there is a dense subset of the set of preference profiles such that given an arbitrary social choice function, f, and ε>0, there exists another social choice function, f _ε, within ε of f uniformly and implementable in Nash equilibrium on the dense subset.     

A Comparison of Partially Adaptive and Reweighted Least Squares Estimation

The small sample performance of least median of squares, reweighted least squares, least squares, least absolute deviations, and three partially adaptive estimators are compared using Monte Carlo simulations. Two data problems are addressed in the paper: (1) data generated from non-normal error distributions and (2) contaminated data. Breakdown plots are used to investigate the sensitivity of partially adaptive estimators to data contamination relative to RLS. One partially adaptive estimator performs especially well when the errors are skewed, while another partially adaptive estimator and RLS perform particularly well when the errors are extremely leptokur-totic. In comparison with RLS, partially adaptive estimators are only moderately effective in resisting data contamination; however, they outperform least squares and least absolute deviation estimators.     

Membranes, mitochondria and amoebae: shape models

Most real-world shapes and images are characterized by high variability- they are not rigid, like crystals, for example—but they are strongly structured. Therefore, a fundamental task in the understanding and analysis of such image ensembles is the construction of models that incorporate both variability and structure in a mathematically precise way. The global shape models introduced in Grenander's general pattern theory are intended to do this. In this paper, we describe the representation of two-dimensional mitochondria and membranes in electron microscope photographs, and three-dimensional amoebae in optical sectioning microscopy. There are three kinds of variability to all of these patterns, which these representations accommodate. The first is the variability in shape and viewing orientation. For this, the typical structure is represented via linear, circular and spherical templates, with the variability accomodated via the application of transformations applied to the templates. The transformations form groups: scale, rotation and translation. They are locally applied throughout the continuum and of high dimension. The second is the textural variability; the inside and outside of these basic shapes are subject to random variation, as well as sensor noise. For this, statistical sensor models and Markov random field texture models are used to connect the constituent structures of the shapes to the measured data. The third variability type is associated with the fact that each scene is made up of a variable number of shapes; this number is not assumed to be known a priori. Each scene has a variable number of parameters encoding the transformations of the templates appropriate for that scene. For this, a single posterior distribution is defined over the countable union of spaces representing models of varying numbers of shapes. Bayesian inference is performed via computation of the conditional expectation of the parametrically defined shapes under the posterior. These conditional mean estimates are generated using jump-diffusion processes. Results for membranes, mitochondria and amoebae are shown.     

Sources of drug information among adolescent students

A sample of 1023 eighth and tenth grade students in small to medium-sized central Texas school districts was assessed to determine the amount of information they receive from ten sources about six categories of drugs. The amount of information males reported receiving about each drug category was significantly greater than what females reported, and the amount of information that eighth graders reported receiving about each drug category was significantly greater than what tenth graders reported. Television was the primary source of drug information for all categories of drugs except inhalants, for which friends and television were equally important sources. Parents and printed media (magazines or newspapers) were of secondary importance, followed by friends and teachers. Adolescents were less likely to receive drug-related information from experience, siblings, church, doctors, and police. The reliance on the mass media for drug information in smaller school districts is a pattern which has been previously observed in larger urban districts. This consistency suggests that mass media approaches to drug education are likely to be as effective in rural areas and smaller towns as they are among urban adolescents. Implications for television programming are discussed.     

Housing affordability among elderly female heads of household in nonmetropolitan areas

This study investigates the extent and nature of housing affordability for elderly nonmetropolitan female heads of household using data from the Panel Study of Income Dynamics. The results indicate that over one-third of elderly nonmetropolitan female heads of household experience housing poverty and that those who rent, who have fair to poor health, and who are minorities are particularly vulnerable. Housing affordability, measured by the concept of housing poverty, identifies households struggling to meet basic needs while the conventional 25% of income for housing expenditures ratio identifies a larger population. The findings suggest the need for multifaceted public policies to address the problem of housing poverty. Her research interests include housing affordability, housing and community vitality, and decision making. She received her Ph.D. from Purdue University. Sooyoun Park is in the same department as a Project Assistant on a USDA-funded research project entitled “Housing Affordability in Rural Areas,” which is a joint project between Nebraska and Wisconsin. Her research interests focus on housing management behavior in relation to housing expenditure burden. She received her Ph.D. from the University of Nebraska-Lincoln.     

A theory of policy differentiation in single issue electoral politics

Voter preferences are characterized by a parameter s (say, income) distributed on a set S according to a probability measure F. There is a single issue (say, a tax rate) whose level, b, is to be politically decided. There are two parties, each of which is a perfect agent of some constituency of voters, voters with a given value of s. An equilibrium of the electoral game is a pair of policies, b ₁ and b ₂, proposed by the two parties, such that b _i maximizes the expected utility of the voters whom party i represents, given the policy proposed by the opposition. Under reasonable assumptions, the unique electoral equilibrium consists in both parties proposing the favorite policy of the median voter. What theory can explain why, historically, we observe electoral equilibria where the ‘right’ and ‘left’ parties propose different policies? Uncertainty concerning the distribution of voters is introduced. Let {F(t)} _{t ε T} be a class of probability measures on S; all voters and parties share a common prior that the distribution of t is described by a probability measure H on T. If H has finite support, there is in general no electoral equilibrium. However, if H is continuous, then electoral equilibrium generally exists, and in equilibrium the parties propose different policies. Convergence of equilibrium to median voter politics is proved as uncertainty about the distribution of voter traits becomes small.     

Is the GNP fractionally integrated?

The suitability of autoregressive fractionally integrated moving average (ARFIMA) processes for the modeling of US aggregate output is examined. We consider the two most widely used methods for the estimation of the fractionally differencing parameter and discuss the empirical results obtained by applying these methods to the quarterly post-war real GNP as well as to the quarterly post-war real GNP per capita. Contrary to previous findings, we conclude that evidence for a fractional degree of integration is poor.     

Sampling Returns for Realized Variance Calculations: Tick Time or Transaction Time?

This article introduces a new model for transaction prices in the presence of market microstructure noise in order to study the properties of the price process on two different time scales, namely, transaction time where prices are sampled with every transaction and tick time where prices are sampled with every price change. Both sampling schemes have been used in the literature on realized variance, but a formal investigation into their properties has been lacking. Our empirical and theoretical results indicate that the return dynamics in transaction time are very different from those in tick time and the choice of sampling scheme can therefore have an important impact on the properties of realized variance. For RV we find that tick time sampling is superior to transaction time sampling in terms of mean-squared-error, especially when the level of noise, number of ticks, or the arrival frequency of efficient price moves is low. Importantly, we show that while the microstructure noise may appear close to IID in transaction time, in tick time it is highly dependent. As a result, bias correction procedures that rely on the noise being independent, can fail in tick time and are better implemented in transaction time.