No vacancy: explaining the undulation of office building construction projects in Chicago\u27s central business district during the 1970s

The research endeavors to explain the absence of office building construction projects in Chicago’s Central Business District between 1976 and 1979. Fourteen office building construction projects were completed between 1970 and 1975 but none during the period studied. Using a socio-spatial perspective to analyze the impact of political, economical, and cultural redevelopment strategies, this paper finds that despite overwhelming neoliberal policies of the 1970s, unusually elevated vacancy rates and cultural provenance altered the course of redevelopment strategies. Among the findings, this research highlights the importance of culturally significant public symbols, such as historic landmark buildings, as catalysts for regulation that resists aggressive redevelopment strategies and influences urban policy decisions

On Nonregularized Estimation of Psychological Networks.

An important goal for psychological science is developing methods to characterize relationships between variables. Customary approaches use structural equation models to connect latent factors to a number of observed measurements, or test causal hypotheses between observed variables. More recently, regularized partial correlation networks have been proposed as an alternative approach for characterizing relationships among variables through off-diagonal elements in the precision matrix. While the graphical Lasso (glasso) has emerged as the default network estimation method, it was optimized in fields outside of psychology with very different needs, such as high dimensional data where the number of variables (p) exceeds the number of observations (n). In this article, we describe the glasso method in the context of the fields where it was developed, and then we demonstrate that the advantages of regularization diminish in settings where psychological networks are often fitted ( p≪n ). We first show that improved properties of the precision matrix, such as eigenvalue estimation, and predictive accuracy with cross-validation are not always appreciable. We then introduce nonregularized methods based on multiple regression and a nonparametric bootstrap strategy, after which we characterize performance with extensive simulations. Our results demonstrate that the nonregularized methods can be used to reduce the false-positive rate, compared to glasso, and they appear to provide consistent performance across sparsity levels, sample composition (p/n), and partial correlation size. We end by reviewing recent findings in the statistics literature that suggest alternative methods often have superior performance than glasso, as well as suggesting areas for future research in psychology. The nonregularized methods have been implemented in the R package GGMnonreg

The Role of Subsurface Flows in Solar Surface Convection: Modeling the Spectrum of Supergranular and Larger Scale Flows

We model the solar horizontal velocity power spectrum at scales larger than granulation using a two-component approximation to the mass continuity equation. The model takes four times the density scale height as the integral (driving) scale of the vertical motions at each depth. Scales larger than this decay with height from the deeper layers. Those smaller are assumed to follow a Kolomogorov turbulent cascade, with the total power in the vertical convective motions matching that required to transport the solar luminosity in a mixing length formulation. These model components are validated using large scale radiative hydrodynamic simulations. We reach two primary conclusions: 1. The model predicts significantly more power at low wavenumbers than is observed in the solar photospheric horizontal velocity spectrum. 2. Ionization plays a minor role in shaping the observed solar velocity spectrum by reducing convective amplitudes in the regions of partial helium ionization. The excess low wavenumber power is also seen in the fully nonlinear three-dimensional radiative hydrodynamic simulations employing a realistic equation of state. This adds to other recent evidence suggesting that the amplitudes of large scale convective motions in the Sun are significantly lower than expected. Employing the same feature tracking algorithm used with observational data on the simulation output, we show that the observed low wavenumber power can be reproduced in hydrodynamic models if the amplitudes of large scale modes in the deep layers are artificially reduced. Since the large scale modes have reduced amplitudes, modes on the scale of supergranulation and smaller remain important to convective heat flux even in the deep layers, suggesting that small scale convective correlations are maintained through the bulk of the solar convection zone.Comment: 36 pages, 6 figure

Grapevine virus C and grapevine leaf roll associated virus 2 are serologically related and appear to be the same virus

Protein extracted from grapevines infected with GLRaV-2 virus was subjected to electrophoresis, followed by Western blots. A protein band of about 23 kDa was detected in all infected plants. When GVC antibodies were used on blots obtained from the same infected plants, a similar protein band was detected in all infected plants. To address the possibility of the presence of another virus with the same molecular weight, the gene coding for the coat protein of GLRaV-2 was cloned and expressed in E. coli. The expressed protein reacted positively to both GLRaV- 2 and GVC antibodies. Using Immunosorbent Electron Microscopy (ISEM), polyclonal antibodies prepared against either GVC or GLRaV-2 trapped and decorated GLRaV-2 particles. The cDNA from GVC-infected grapevines and Nicotiana benthamiana were cloned and sequenced. All of the clones that were sequenced had the same sequence as GLRaV-2. Based on the data obtained, we concluded that GVC is the same virus as GLRaV-2. Keywords

Comparing Gaussian graphical models with the posterior predictive distribution and Bayesian model selection

Gaussian graphical models are commonly used to characterize conditional (in)dependence structures (i.e., partial correlation networks) of psychological constructs. Recently attention has shifted from estimating single networks to those from various subpopulations. The focus is primarily to detect differences or demonstrate replicability. We introduce two novel Bayesian methods for comparing networks that explicitly address these aims. The first is based on the posterior predictive distribution, with a symmetric version of Kullback-Leibler divergence as the discrepancy measure, that tests differences between two (or more) multivariate normal distributions. The second approach makes use of Bayesian model comparison, with the Bayes factor, and allows for gaining evidence for invariant network structures. This overcomes limitations of current approaches in the literature that use classical hypothesis testing, where it is only possible to determine whether groups are significantly different from each other. With simulation we show the posterior predictive method is approximately calibrated under the null hypothesis (alpha = .05) and has more power to detect differences than alternative approaches. We then examine the necessary sample sizes for detecting invariant network structures with Bayesian hypothesis testing, in addition to how this is influenced by the choice of prior distribution. The methods are applied to posttraumatic stress disorder symptoms that were measured in 4 groups. We end by summarizing our major contribution, that is proposing 2 novel methods for comparing Gaussian graphical models (GGMs), which extends beyond the social-behavioral sciences. The methods have been implemented in the R package BGGM. Translational Abstract Gaussian graphical models are becoming popular in the social-behavioral sciences. Recently attention has shifted from estimating single networks to those from various subpopulations (e.g., males vs. females). We introduce Bayesian methodology for comparing networks estimated from any number of groups. The first approach is based on the posterior predictive distribution and it allows for determining whether networks are different from one another. This is ideal for testing the null hypothesis of group equality, say, in the context of testing for network replicability (or lack thereof). The second approach is based on Bayesian hypothesis testing and it allows for gaining evidence for network invariances or equality of partial correlations for any number of groups. This is ideal for focusing on specific aspects of the network such as individual partial correlations. In a series of simulations and illustrative examples we demonstrate the utility of the proposed methodology for comparing Gaussian graphical models. The methods have been implemented in the R package BGGM

Latitudinal variation of the solar photospheric intensity

We have examined images from the Precision Solar Photometric Telescope (PSPT) at the Mauna Loa Solar Observatory (MLSO) in search of latitudinal variation in the solar photospheric intensity. Along with the expected brightening of the solar activity belts, we have found a weak enhancement of the mean continuum intensity at polar latitudes (continuum intensity enhancement $\sim0.1 - 0.2$ corresponding to a brightness temperature enhancement of $\sim2.5{\rm K}$). This appears to be thermal in origin and not due to a polar accumulation of weak magnetic elements, with both the continuum and CaIIK intensity distributions shifted towards higher values with little change in shape from their mid-latitude distributions. Since the enhancement is of low spatial frequency and of very small amplitude it is difficult to separate from systematic instrumental and processing errors. We provide a thorough discussion of these and conclude that the measurement captures real solar latitudinal intensity variations.Comment: 24 pages, 8 figs, accepted in Ap

Realistic Magnetohydrodynamical Simulation of Solar Local Supergranulation

Three-dimensional numerical simulations of solar surface magnetoconvection using realistic model physics are conducted. The thermal structure of convective motions into the upper radiative layers of the photosphere, the main scales of convective cells and the penetration depths of convection are investigated. We take part of the solar photosphere with size of 60x60 Mm in horizontal direction and by depth 20 Mm from level of the visible solar surface. We use a realistic initial model of the Sun and apply equation of state and opacities of stellar matter. The equations of fully compressible radiation magnetohydrodynamics with dynamical viscosity and gravity are solved. We apply: 1) conservative TVD difference scheme for the magnetohydrodynamics, 2) the diffusion approximation for the radiative transfer, 3) dynamical viscosity from subgrid scale modeling. In simulation we take uniform two-dimesional grid in gorizontal plane and nonuniform grid in vertical direction with number of cells 600x600x204. We use 512 processors with distributed memory multiprocessors on supercomputer MVS-100k in the Joint Computational Centre of the Russian Academy of Sciences.Comment: 6 pages, 5 figures, submitted to the proceedings of the GONG 2008 / SOHO XXI conferenc

Green Fluorescent Protein in the sea urchin: new experimental approaches to transcriptional regulatory analysis in embryos and larvae

The use of Green Fluorescent Protein (GFP) as a reporter for expression transgenes opens the way to several new experimental strategies for the study of gene regulation in sea urchin development. A GFP coding sequence was associated with three different previously studied cis-regulatory systems, viz those of the SM50 gene, expressed in skeletogenic mesenchyme, the CyIIa gene, expressed in archenteron, skeletogenic and secondary mesenchyme, and the Endo16 gene, expressed in vegetal plate, archenteron and midgut. We demonstrate that the sensitivity with which expression can be detected is equal to or greater than that of whole-mount in situ hybridization applied to detection of CAT mRNA synthesized under the control of the same cis-regulatory systems. However, in addition to the important feature that it can be visualized nondestructively in living embryos, GFP has other advantages. First, it freely diffuses even within fine cytoplasmic cables, and thus reveals connections between cells, which in sea urchin embryos is particularly useful for observations on regulatory systems that operate in the syncytial skeletogenic mesenchyme. Second, GFP expression can be dramatically visualized in postembryonic larval tissues. This brings postembryonic larval developmental processes for the first time within the easy range of gene transfer analyses. Third, GFP permits identification and segregation of embryos in which the clonal incorporation of injected DNA has occurred in any particular desired region of the embryo. Thus, we show explicitly that, as expected, GFP transgenes are incorporated in the same nuclei together with other transgenes with which they are co-injected