Is the housing market blind to religion? A perceived substitutability approach to homophily and social integration

Housing markets are unlikely to be impervious to the preferences and prejudices associated with urban segregation. For example, two neighbourhoods with very different religious attributes are unlikely to be perceived as close substitutes by homebuyers that have a strong preference for neighbours of a particular religion. This paper offers a new framework for the conception and measurement of social integration, defined in terms of perceived homophily. Homophily is the tendency for links to form between similar nodes in a network and we can think of perceived homophily as the tendency for any pair of neighbourhoods to be considered by the housing market to be close substitutes. Textbook economic theory suggests that we should expect the degree of perceived substitutability to affect cross-price elasticities. These can be measured empirically to reveal discontinuities in the network of perceived substitutability of different housing locations. Applying homophily coefficients to substitutability measures allows us to estimate perceived religious homophily between neighbourhoods. The approach can be applied to any city or region that has geocoded house transactions and socio-demographic data. We illustrate the method using data on Glasgow and find strong evidence of religious homophily. This suggests an underlying lack of social integration/cohesion and implies that the Glaswegian housing market is by no means blind to religion

Policy-based management for body-sensor networks

Accepted versio

A Policy System to Support Adaptability and Security on Body Sensors

Published versio

The quantum algebra of superspace

We present the complete set of $N=1$, $D=4$ quantum algebras associated to massive superparticles. We obtain the explicit solution of these algebras realized in terms of unconstrained operators acting on the Hilbert space of superfields. These solutions are expressed using the chiral, anti-chiral and tensorial projectors which define the three irreducible representations of the supersymmetry on the superfields. In each case the space-time variables are non-commuting and their commutators are proportional to the internal angular momentum of the representation. The quantum algebra associated to the chiral or the anti-chiral projector is the one obtained by the quantization of the Casalbuoni-Brink-Schwarz (superspin 0) massive superparticle. We present a new superparticle action for the (superspin 1/2) case and show that their wave functions are the ones associated to the irreducible tensor multiplet.Comment: 20 pages;changes in the nomenclatur

Finger: An Efficient Policy System for Body Sensor Networks

Accepted versio

Stability and Quasinormal Modes of Black holes in Tensor-Vector-Scalar theory: Scalar Field Perturbations

The imminent detection of gravitational waves will trigger precision tests of gravity through observations of quasinormal ringing of black holes. While General Relativity predicts just two polarizations of gravitational waves, the so-called plus and cross polarizations, numerous alternative theories of gravity predict up to six different polarizations which will potentially be observed in current and future generations of gravitational wave detectors. Bekenstein's Tensor-Vector-Scalar (TeVeS) theory and its generalization fall into one such class of theory that predict the full gamut of six polarizations of gravitational waves. In this paper we begin the study of quasinormal modes (QNMs) in TeVeS by studying perturbations of the scalar field in a spherically symmetric background. We show that, at least in the case where superluminal propagation of perturbations is not present, black holes are generically stable to this kind of perturbation. We also make a unique prediction that, as the limit of the various coupling parameters of the theory tend to zero, the QNM spectrum tends to $1/\sqrt{2}$ times the QNM spectrum induced by scalar perturbations of a Schwarzschild black hole in General Relativity due to the intrinsic presence of the background vector field. We further show that the QNM spectrum does not vary significantly from this value for small values of the theory's coupling parameters, however can vary by as much as a few percent for larger, but still physically relevant parameters.Comment: Published in Physical Review

Naive mean field approximation for image restoration

We attempt image restoration in the framework of the Baysian inference. Recently, it has been shown that under a certain criterion the MAP (Maximum A Posterior) estimate, which corresponds to the minimization of energy, can be outperformed by the MPM (Maximizer of the Posterior Marginals) estimate, which is equivalent to a finite-temperature decoding method. Since a lot of computational time is needed for the MPM estimate to calculate the thermal averages, the mean field method, which is a deterministic algorithm, is often utilized to avoid this difficulty. We present a statistical-mechanical analysis of naive mean field approximation in the framework of image restoration. We compare our theoretical results with those of computer simulation, and investigate the potential of naive mean field approximation.Comment: 9 pages, 11 figure

Classifying the fertility of dairy cows using milk mid-infrared spectroscopy

The objective of this study was to investigate the potential of milk mid-infrared (MIR) spectroscopy, MIR-derived traits including milk composition, milk fatty acids, and blood metabolic profiles (fatty acids, \u3b2-hydroxybutyrate, and urea), and other on-farm data for discriminating cows of good versus poor likelihood of conception to first insemination (i.e., pregnant vs. open). A total of 6,488 spectral and milk production records of 2,987 cows from 19 commercial dairy herds across 3 Australian states were used. Seven models, comprising different explanatory variables, were examined. Model 1 included milk production; concentrations of fat, protein, and lactose; somatic cell count; age at calving; days in milk at herd test; and days from calving to insemination. Model 2 included, in addition to the variables in model 1, milk fatty acids and blood metabolic profiles. The MIR spectrum collected before first insemination was added to model 2 to form model 3. Fat, protein, and lactose percentages, milk fatty acids, and blood metabolic profiles were removed from model 3 to create model 4. Model 5 and model 6 comprised model 4 and either fertility genomic estimated breeding value or principal components obtained from a genomic relationship matrix derived using animal genotypes, respectively. In model 7, all previously described sources of information, but not MIR-derived traits, were used. The models were developed using partial least squares discriminant analysis. The performance of each model was evaluated in 2 ways: 10-fold random cross-validation and herd-by-herd external validation. The accuracy measures were sensitivity (i.e., the proportion of pregnant cows that were correctly classified), specificity (i.e., the proportion of open cows that were correctly classified), and area under the curve (AUC) for the receiver operating curve. The results showed that in all models, prediction accuracy obtained through 10-fold random cross-validation was higher than that of herd-by-herd external validation, with the difference in AUC ranging between 0.01 and 0.09. In the herd-by-herd external validation, using basic on-farm information (model 1) was not sufficient to classify good- and poor-fertility cows; the sensitivity, specificity, and AUC were around 0.66. Compared with model 1, adding milk fatty acids and blood metabolic profiles (model 2) increased the sensitivity, specificity, and AUC by 0.01, 0.02, and 0.02 unit, respectively (i.e., 0.65, 0.63, and 0.678). Incorporating MIR spectra into model 2 resulted in sensitivity, specificity, and AUC values of 0.73, 0.63, and 0.72, respectively (model 3). The comparable prediction accuracies observed for models 3 and 4 mean that useful information from MIR-derived traits is already included in the spectra. Adding the fertility genomic estimated breeding value and animal genotypes (model 7) produced the highest prediction accuracy, with sensitivity, specificity, and AUC values of 0.75, 0.66, and 0.75, respectively. However, removing either the fertility estimated breeding value or animal genotype from model 7 resulted in a reduction of the prediction accuracy of only 0.01 and 0.02, respectively. In conclusion, this study indicates that MIR and other on-farm data could be used to classify cows of good and poor likelihood of conception with promising accuracy

Environmental Clustering of New Zealand Dairy Herds

Previous studies have found that milk yield (a proxy for feeding level) and temperature-humidity index (THI) are important factors in explaining genotype x environment (G x E) interactions, indicating differences between the abilities of genotypes to forage or consume concentrates effectively or to cope with thermal stress (Ravagnolo and Misztal, 2000; Zwald et al., 2003). The objective of this study was to quantify and cluster (CL) herd environments within New Zealand (NZ) based on production levels, a summer heat load index (HLI) and geographical location

Non-Commutative Geometry and Measurements of Polarized Two Photon Coincidence Counts

Employing Maxwell's equations as the field theory of the photon, quantum mechanical operators for spin, chirality, helicity, velocity, momentum, energy and position are derived. The photon ``Zitterbewegung'' along helical paths is explored. The resulting non-commutative geometry of photon position and the quantum version of the Pythagorean theorem is discussed. The distance between two photons in a polarized beam of given helicity is shown to have a discrete spectrum. Such a spectrum should become manifest in measurements of two photon coincidence counts. The proposed experiment is briefly described.Comment: Latex, 13 pages, 3 figure