A unified framework for measuring preferences for schools and neighborhoods

This paper develops a framework for estimating household preferences for school and neighborhood attributes in the presence of sorting. It embeds a boundary discontinuity design in a heterogeneous residential choice model, addressing the endogeneity of school and neighborhood characteristics. The model is estimated using restricted-access Census data from a large metropolitan area, yielding a number of new results. First, households are willing to pay less than 1 percent more in house prices - substantially lower than previous estimates - when the average performance of the local school increases by 5 percent. Second, much of the apparent willingness to pay for more educated and wealthier neighbors is explained by the correlation of these sociodemographic measures with unobserved neighborhood quality. Third, neighborhood race is not capitalized directly into housing prices; instead, the negative correlation of neighborhood percent black and housing prices is due entirely to the fact that blacks live in unobservably lower-quality neighborhoods. Finally, there is considerable heterogeneity in preferences for schools and neighbors, with households preferring to self-segregate on the basis of both race and education. © 2007 by The University of Chicago. All rights reserved.

CPAG: software for leveraging pleiotropy in GWAS to reveal similarity between human traits links plasma fatty acids and intestinal inflammation.

Meta-analyses of genome-wide association studies (GWAS) have demonstrated that the same genetic variants can be associated with multiple diseases and other complex traits. We present software called CPAG (Cross-Phenotype Analysis of GWAS) to look for similarities between 700 traits, build trees with informative clusters, and highlight underlying pathways. Clusters are consistent with pre-defined groups and literature-based validation but also reveal novel connections. We report similarity between plasma palmitoleic acid and Crohn's disease and find that specific fatty acids exacerbate enterocolitis in zebrafish. CPAG will become increasingly powerful as more genetic variants are uncovered, leading to a deeper understanding of complex traits. CPAG is freely available at www.sourceforge.net/projects/CPAG/.

All my children: The roles of semantic category and phonetic similarity in the misnaming of familiar individuals.

Despite knowing a familiar individual (such as a daughter) well, anecdotal evidence suggests that naming errors can occur among very familiar individuals. Here, we investigate the conditions surrounding these types of errors, or misnamings, in which a person (the misnamer) incorrectly calls a familiar individual (the misnamed) by someone else's name (the named). Across 5 studies including over 1,700 participants, we investigated the prevalence of the phenomenon of misnaming, identified factors underlying why it may occur, and tested potential mechanisms. We included undergraduates and MTurk workers and asked questions of both the misnamed and the misnamer. We find that familiar individuals are often misnamed with the name of another member of the same semantic category; family members are misnamed with another family member's name and friends are misnamed with another friend's name. Phonetic similarity between names also leads to misnamings; however, the size of this effect was smaller than that of the semantic category effect. Overall, the misnaming of familiar individuals is driven by the relationship between the misnamer, misnamed, and named; phonetic similarity between the incorrect name used by the misnamer and the correct name also plays a role in misnaming.

Applying CBR to measure similarity of software design structures

This paper examines different ways for measuring similarity between software design models for the purpose of software reuse. Current approaches to this problem are discussed and a set of suitable similarity metrics are proposed and evaluated. Work on the optimisation of weights to increase the competence of a CBR system is presented. A graph matching algorithm and associated metrics capturing the structural similarity between UML class diagrams is presented and demonstrated through an example case.

A critical examination of node-similarity based graph matching algorithms

In this paper, we shall critically examine a special class of graph matching algorithms that follow the approach of node-similarity measurement. A high-level algorithm framework, namely node-similarity graph matching framework (NSGM framework), is proposed, from which, many existing graph matching algorithms can be subsumed, including the eigen-decomposition method of Umeyama, the polynomial-transformation method of Almohamad, the hubs and authorities method of Kleinberg, and the kronecker product successive projection methods of Wyk, etc. In addition, improved algorithms can be developed from the NSGM framework with respects to the corresponding results in graph theory. As the observation, it is pointed out that, in general, any algorithm which can be subsumed from NSGM framework fails to work well for graphs with non-trivial auto-isomorphism structure.

Measuring similarity of software designs using graph matching for CBR

This paper examines different ways of measuring similarity between software design models for Case Based Reasoning (CBR) to facilitate reuse of software design and code. The paper considers structural and behavioural aspects of similarity between software design models. Similarity metrics for comparing static class structures are defined and discussed. A Graph representation of UML class diagrams and corresponding similarity measures for UML class diagrams are defined. A full search graph matching algorithm for measuring structural similarity diagrams based on the identification of the Maximum Common Sub-graph (MCS) is presented. Finally, a simple evaluation of the approach is presented and discussed.

Diet of auklet chicks in the Aleutian Islands, Alaska: similarity among islands, interspecies overlap, and relationships to ocean climate

Seabirds are effective samplers of the marine environment, and can be used to measure resource partitioning among species and sites via food loads destined for chicks. We examined the composition, overlap, and relationships to changing climate and oceanography of 3,216 food loads from Least, Crested, and Whiskered Auklets (Aethia pusilla, A. cristatella, A. pygmaea) breeding in Alaska during 1994–2006. Meals comprised calanoid copepods (Neocalanus spp.) and euphausiids (Thysanoessa spp.) that reflect secondary marine productivity, with no difference among Buldir, Kiska, and Kasatochi islands across 585 km of the Aleutian Islands. Meals were very similar among species (mean Least–Crested Auklet overlap C = 0.68; Least–Whiskered Auklet overlap C = 0.96) and among sites, indicating limited partitioning of prey resources for auklets feeding chicks. The biomass of copepods and euphausiids in Least and Crested Auklet food loads was related negatively to the summer (June–July–August) North Pacific Gyre Oscillation, while in Whiskered Auklet food loads, this was negatively related to the winter (December–January–February) Pacific Decadal Oscillation, both of which track basin-wide sea-surface temperature (SST) anomalies. We found a significant quadratic relationship between the biomass of calanoid copepods in Least Auklet food loads at all three study sites and summer (June–July) SST, with maximal copepod biomass between 3–6°C (r 2 = 0.71). Outside this temperature range, zooplankton becomes less available to auklets through delayed development. Overall, our results suggest that auklets are able to buffer climate-mediated bottom-up forcing of demographic parameters like productivity, as the composition of chick meals has remained constant over the course of our study.

Analyses of sublittoral macrobenthic community change in a marine nature reserve using similarity profiles (SIMPROF).

Sublittoral macrobenthic communities in the Skomer Marine Nature Reserve (SMNR), Pembrokeshire, Wales, were sampled at 10 stations in 1993, 1996, 1998, 2003, 2007 and 2009 using a Day grab and a 0.5 mm mesh. The time series is analysed using Similarities Profiles (SIMPROF) tests and associated methods. Q-mode analysis using clustering with Type 1 SIMPROF addresses multivariate structure among samples, showing that there is clear structure associated with differences among years. Inverse (r-mode) analysis using Type 2 SIMPROF decisively rejects a hypothesis that species are not associated with each other. Clustering of the variables (species) with Type 3 SIMPROF identifies groups of species which covary coherently through the time-series. The time-series is characterised by a dramatic decline in abundances and diversity between the 1993 and 1996 surveys. By 1998 there had been a shift in community composition from the 1993 situation, with different species dominating. Communities had recovered in terms of abundance and species richness, but different species dominated the community. No single factor could be identified which unequivocally explained the dramatic changes observed in the SMNR. Possible causes were the effects of dispersed oil and dispersants from the Sea Empress oil spill in February 1996 and the cessation of dredge-spoil disposal off St Anne’s Head in 1995, but the most likely cause was severe weather. With many species, and a demonstrable recovery from an impact, communities within the SMNR appear to be diverse and resilient. If attributable to natural storms, the changes observed here indicate that natural variability may be much more important than is generally taken into account in the design of monitoring programmes.