Educational Expectations and Attainment

This paper examines the role of educational expectations in the educational attainment process. We utilize data from a variety of datasets to document and analyze the trends in educational expectations between the mid-1970s and the early 2000s. We focus on differences across racial/ethnic and socioeconomic groups and examine how young people update their expectations during high school and beyond. The results indicate that expectations rose for all students with the greatest increases among young women. Expectations have become somewhat less predictive of attainment over the past several decades but expectations remain strong predictors of attainment above and beyond other standard determinants of schooling. Interestingly, the data demonstrate that the majority (about 60 percent) of students update their expectations at least once between eighth grade and eight years post-high school. Updating appears to be based, in part, on the acquisition of new information about academic ability.

The Kernel Interaction Trick: Fast Bayesian Discovery of Pairwise Interactions in High Dimensions

Discovering interaction effects on a response of interest is a fundamental problem faced in biology, medicine, economics, and many other scientific disciplines. In theory, Bayesian methods for discovering pairwise interactions enjoy many benefits such as coherent uncertainty quantification, the ability to incorporate background knowledge, and desirable shrinkage properties. In practice, however, Bayesian methods are often computationally intractable for even moderate-dimensional problems. Our key insight is that many hierarchical models of practical interest admit a particular Gaussian process (GP) representation; the GP allows us to capture the posterior with a vector of O(p) kernel hyper-parameters rather than O(p^2) interactions and main effects. With the implicit representation, we can run Markov chain Monte Carlo (MCMC) over model hyper-parameters in time and memory linear in p per iteration. We focus on sparsity-inducing models and show on datasets with a variety of covariate behaviors that our method: (1) reduces runtime by orders of magnitude over naive applications of MCMC, (2) provides lower Type I and Type II error relative to state-of-the-art LASSO-based approaches, and (3) offers improved computational scaling in high dimensions relative to existing Bayesian and LASSO-based approaches.Comment: Accepted at ICML 2019. 20 pages, 4 figures, 3 table

Dopant-modulated pair interaction in cuprate superconductors

Comparison of recent experimental STM data with single-impurity and many-impurity Bogoliubov-de Gennes calculations strongly suggests that random out-of-plane dopant atoms in cuprates modulate the pair interaction locally. This type of disorder is crucial to understanding the nanoscale electronic structure inhomogeneity observed in BSCCO-2212, and can reproduce observed correlations between the positions of impurity atoms and various aspects of the local density of states such as the gap magnitude and the height of the coherence peaks. Our results imply that each dopant atom modulates the pair interaction on a length scale of order one lattice constant.Comment: 5 pages, 4 figure

Andreev states near short-ranged pairing potential impurities

We study Andreev states near atomic scale modulations in the pairing potential in both $s$- and d-wave superconductors with short coherence lengths. For a moderate reduction of the local gap, the states exist only close to the gap edge. If one allows for local sign changes of the order parameter, however, resonances can occur at energies close to the Fermi level. The local density of states (LDOS) around such pairing potential defects strongly resembles the patterns observed by tunneling measurements around Zn impurities in Bi$_2$Sr$_2$CaCu$_2$O$_{8+x}$ (BSCCO). We discuss how this phase impurity model of the Zn LDOS pattern can be distinguished from other proposals experimentally.Comment: 4 pages, 4 figure

Performance of UK wastewater treatment works with respect to trace contaminants

This is the post-print version of the final paper published in Science of Total Environment. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2013 Elsevier B.V.This study examined the performance of 16 wastewater treatment works to provide an overview of trace substance removal in relation to meeting the objectives of the Water Framework Directive (WFD). Collection and analysis of over 2400 samples including sewage influent, process samples at different stages in the treatment process and final effluent has provided data on the performance of current wastewater treatment processes and made it possible to evaluate the need for improved effluent quality. Results for 55 substances, including metals, industrial chemicals and pharmaceuticals are reported. Data for sanitary parameters are also provided. A wide range of removal efficiencies was observed. Removal was not clearly related to the generic process type, indicating that other operational factors tend to be important. Nonetheless, removals for many substances of current concern were high. Despite this, current proposals for stringent water quality standards mean that further improvements in effluent quality are likely to be required

A blinded determination of H0H_0 from low-redshift Type Ia supernovae, calibrated by Cepheid variables

Presently a ${>}3\sigma$ tension exists between values of the Hubble constant $H_0$ derived from analysis of fluctuations in the Cosmic Microwave Background by Planck, and local measurements of the expansion using calibrators of type Ia supernovae (SNe Ia). We perform a blinded reanalysis of Riess et al. 2011 to measure $H_0$ from low-redshift SNe Ia, calibrated by Cepheid variables and geometric distances including to NGC 4258. This paper is a demonstration of techniques to be applied to the Riess et at. 2016 data. Our end-to-end analysis starts from available CfA3 and LOSS photometry, providing an independent validation of Riess et al. 2011. We obscure the value of $H_0$ throughout our analysis and the first stage of the referee process, because calibration of SNe Ia requires a series of often subtle choices, and the potential for results to be affected by human bias is significant. Our analysis departs from that of Riess et al. 2011 by incorporating the covariance matrix method adopted in SNLS and JLA to quantify SN Ia systematics, and by including a simultaneous fit of all SN Ia and Cepheid data. We find $H_0 = 72.5 \pm 3.1$ (stat) $\pm 0.77$ (sys) km s$^{-1}$ Mpc$^{-1}$ with a three-galaxy (NGC 4258+LMC+MW) anchor. The relative uncertainties are 4.3% statistical, 1.1% systematic, and 4.4% total, larger than in Riess et al. 2011 (3.3% total) and the Efstathiou 2014 reanalysis (3.4% total). Our error budget for $H_0$ is dominated by statistical errors due to the small size of the supernova sample, whilst the systematic contribution is dominated by variation in the Cepheid fits, and for the SNe Ia, uncertainties in the host galaxy mass dependence and Malmquist bias.Comment: 38 pages, 13 figures, 13 tables; accepted for publication in MNRA