Wealth Poverty at Social Intersections: Differential Access and Accumulation

The Intersection of several axes of inequality characterize the nature of differential access to assets and debts and varying ability to accumulate wealth at quantifiably discernable “social locations.” In the United States, there exists sizeable gaps in wealth accumulation between single-headed male and female households, as well as between households of different racial/ethnic groups, but the application of Patricia Hill Collins’s Matrix of Domination to the economic analysis of inequality nuances measurable disparities by the intersection of race and gender. In a two-stage methodology using data from the 2010 and 2013 Survey of Consumer Finances (SCF), this thesis aims to first, assess multiplicative and simultaneous gendered and racialized differences in wealth accumulation employing the concept of wealth poverty. Six-month wealth poverty lines were constructed based on a transformation of the Census Bureau’s income poverty thresholds. Multivariate models are used to estimate the likelihood of placement in three categories of wealth poverty: Dis-Accumulation, Mal-Accumulation, and Sufficient Accumulation. Second, the likelihoods of access to assets and debts categorized by the Levy Institute Measure of Economic Well-being (LIMEW) are estimated using Logistic regressions. The findings of this thesis suggest that while all households are more likely to be wealth poor than white male single-headed households, black and Hispanic female-headed households are those most likely to experience the greatest depths of wealth poverty, with debt burdens that typically outweigh their asset holdings. Additive models do not properly assess the premiums and penalties associated with respective racial/ethnic and gendered positioning in relation to white male headed households. Additionally, both multiple jeopardy and racially marginalized households are less likely than white male single-headed households to have wealth escalating assets, such as home equity, real estate and business related assets, and stocks, bonds, and other financial assets, but black female-headed households are interestingly more likely to save for retirement than white male single-households. Black and Hispanic-headed female households- per multiple jeopardy- are most likely to have non-productive debt such as credit card debt in relation to white male-headed households. Hispanic-headed households of either gender are far less likely to have productive debt such as housing debt and the least likely to have received an inheritance compared to white male-headed households

The Journey from Nonexerciser to Exerciser: A Grounded Theory Study

The physiological and psychological health benefits of regular physical exercise are well-documented; however, drop-out rates from both supervised and unsupervised exercise remain high. Many potential influences on exercise behavior have been studied, but with largely inconsistent results, making it difficult to identify key targets for intervention. The purpose of this study was to explore the process through which nonexercisers become exercisers, and the contextual factors which affect movement through this process, in order to enable nurses to more successfully assist clients to incorporate exercise into their lifestyles. The exercise experiences of 22 individuals who had successfully made the transition from nonexerciser to exerciser at some point in their adult lives were explored using grounded theory methodology. Study findings indicated that the process through which these nonexercisers became exercisers centered around the development of an exerciser identity . Prompted by some critical experience to engage in self-appraisal, participants became committed to the idea of changing themselves, by means of exercise. Through the process of experimenting with, evaluating, and confirming the rewards of exercise participation, participants experienced a positive identity change, which made exercise involvement self-reinforcing. Exercising now seemed normal to these individuals--a part of who they were. The context and conditions surrounding exercise participation were found to be important influences on pre-existing identity, the quality of the exercise experience, and changes in exercise identity over time, but did not prevent nor guarantee successful movement through the process of developing an exerciser identity . These findings suggest the need for a significant shift in the focus of exercise research and intervention from behavior to identity. Exercise must be conceived of not just as an activity that people engage in, but as something that becomes a part of who people are, which can change over time. Future research efforts should continue to pursue the link between identity and exercise behavior, using dynamic, context-oriented methods

The Effective Lagrangian for Bulk Fermions in Models with Extra Dimensions

We compute the dimension 6 effective Lagrangian arising from the tree level integration of an arbitrary number of bulk fermions in models with warped extra dimensions. The coefficients of the effective operators are written in terms of simple integrals of the metric and are valid for arbitrary warp factors, with or without an infrared brane, and for a general Higgs profile. All relevant tree level fermion effects in electroweak and flavor observables can be computed using this effective Lagrangian.Comment: 22 pages. V2: typos corrected, matches published versio

Complexity without chaos: Plasticity within random recurrent networks generates robust timing and motor control

It is widely accepted that the complex dynamics characteristic of recurrent neural circuits contributes in a fundamental manner to brain function. Progress has been slow in understanding and exploiting the computational power of recurrent dynamics for two main reasons: nonlinear recurrent networks often exhibit chaotic behavior and most known learning rules do not work in robust fashion in recurrent networks. Here we address both these problems by demonstrating how random recurrent networks (RRN) that initially exhibit chaotic dynamics can be tuned through a supervised learning rule to generate locally stable neural patterns of activity that are both complex and robust to noise. The outcome is a novel neural network regime that exhibits both transiently stable and chaotic trajectories. We further show that the recurrent learning rule dramatically increases the ability of RRNs to generate complex spatiotemporal motor patterns, and accounts for recent experimental data showing a decrease in neural variability in response to stimulus onset

Simple and Realistic Composite Higgs Models in Flat Extra Dimensions

We construct new composite Higgs/gauge-Higgs unification (GHU) models in flat space that overcome all the difficulties found in the past in attempting to construct models of this sort. The key ingredient is the introduction of large boundary kinetic terms for gauge (and fermion) fields. We focus our analysis on the electroweak symmetry breaking pattern and the electroweak precision tests and show how both are compatible with each other. Our models can be seen as effective TeV descriptions of analogue warped models. We point out that, as far as electroweak TeV scale physics is concerned, one can rely on simple and more flexible flat space models rather than considering their unavoidably more complicated warped space counterparts. The generic collider signatures of our models are essentially undistinguishable from those expected from composite Higgs/warped GHU models, namely a light Higgs, colored fermion resonances below the TeV scale and sizable deviations to the Higgs and top coupling.Comment: 30 figures, 9 figures; v2: minor improvements, one reference added, version to appear in JHE

Radiative Electroweak Symmetry Breaking in a Little Higgs Model

We present a new Little Higgs model, motivated by the deconstruction of a five-dimensional gauge-Higgs model. The approximate global symmetry is $SO(5)_0\times SO(5)_1$, breaking to $SO(5)$, with a gauged subgroup of $[SU(2)_{0L}\times U(1)_{0R}]\times O(4)_1$, breaking to $SU(2)_L \times U(1)_Y$. Radiative corrections produce an additional small vacuum misalignment, breaking the electroweak symmetry down to $U(1)_{EM}$. Novel features of this model are: the only un-eaten pseudo-Goldstone boson in the effective theory is the Higgs boson; the model contains a custodial symmetry, which ensures that $\hat{T}=0$ at tree-level; and the potential for the Higgs boson is generated entirely through one-loop radiative corrections. A small negative mass-squared in the Higgs potential is obtained by a cancellation between the contribution of two heavy partners of the top quark, which is readily achieved over much of the parameter space. We can then obtain both a vacuum expectation value of $v=246$ GeV and a light Higgs boson mass, which is strongly correlated with the masses of the two heavy top quark partners. For a scale of the global symmetry breaking of $f=1$ TeV and using a single cutoff for the fermion loops, the Higgs boson mass satisfies 120 GeV $\lesssim M_H\lesssim150$ GeV over much of the range of parameter space. For $f$ raised to 10 TeV, these values increase by about 40 GeV. Effects at the ultraviolet cutoff scale may also raise the predicted values of the Higgs boson mass, but the model still favors $M_H\lesssim 200$ GeV.Comment: 32 pages, 10 figures, JHEP style. Version accepted for publication in JHEP. Includes additional discussion of sensitivity to UV effects and fine-tuning, revised Fig. 9, added appendix and additional references

Exponential Random Graph Modeling for Complex Brain Networks

Exponential random graph models (ERGMs), also known as p* models, have been utilized extensively in the social science literature to study complex networks and how their global structure depends on underlying structural components. However, the literature on their use in biological networks (especially brain networks) has remained sparse. Descriptive models based on a specific feature of the graph (clustering coefficient, degree distribution, etc.) have dominated connectivity research in neuroscience. Corresponding generative models have been developed to reproduce one of these features. However, the complexity inherent in whole-brain network data necessitates the development and use of tools that allow the systematic exploration of several features simultaneously and how they interact to form the global network architecture. ERGMs provide a statistically principled approach to the assessment of how a set of interacting local brain network features gives rise to the global structure. We illustrate the utility of ERGMs for modeling, analyzing, and simulating complex whole-brain networks with network data from normal subjects. We also provide a foundation for the selection of important local features through the implementation and assessment of three selection approaches: a traditional p-value based backward selection approach, an information criterion approach (AIC), and a graphical goodness of fit (GOF) approach. The graphical GOF approach serves as the best method given the scientific interest in being able to capture and reproduce the structure of fitted brain networks

Increased ventral striatal volume in college-aged binge drinkers

BACKGROUND Binge drinking is a serious public health issue associated with cognitive, physiological, and anatomical differences from healthy individuals. No studies, however, have reported subcortical grey matter differences in this population. To address this, we compared the grey matter volumes of college-age binge drinkers and healthy controls, focusing on the ventral striatum, hippocampus and amygdala. METHOD T1-weighted images of 19 binge drinkers and 19 healthy volunteers were analyzed using voxel-based morphometry. Structural data were also covaried with Alcohol Use Disorders Identification Test (AUDIT) scores. Cluster-extent threshold and small volume corrections were both used to analyze imaging data. RESULTS Binge drinkers had significantly larger ventral striatal grey matter volumes compared to controls. There were no between group differences in hippocampal or amygdalar volume. Ventral striatal, amygdalar, and hippocampal volumes were also negatively related to AUDIT scores across groups. CONCLUSIONS Our findings stand in contrast to the lower ventral striatal volume previously observed in more severe forms of alcohol use disorders, suggesting that college-age binge drinkers may represent a distinct population from those groups. These findings may instead represent early sequelae, compensatory effects of repeated binge and withdrawal, or an endophenotypic risk factor

Modifiers of short-term effects of ozone on mortality in eastern Massachusetts - A case-crossover analysis at individual level

<p>Abstract</p> <p>Background</p> <p>Substantial epidemiological studies demonstrate associations between exposure to ambient ozone and mortality. A few studies simply examine the modification of this ozone effect by individual characteristics and socioeconomic status, but socioeconomic status was usually coded at the city level.</p> <p>Methods</p> <p>This study used a case-crossover design to examine whether impacts of ozone on mortality were modified by socioeconomic status coded at the tract or characteristics at an individual level in eastern Massachusetts, US for a period May-September, 1995-2002, with a total of 157,197 non-accident deaths aging 35 years or older. We used moving averages of maximal 8-hour concentrations of ozone monitored at 8 stationary stations as personal exposure.</p> <p>Results</p> <p>A 10 ppb increase in the four-day moving average of maximal 8-hour ozone was associated with 1.68% (95% confidence interval (CI): 0.51%, 2.87%), 1.96% (95% CI: -1.83%, 5.90%), 8.28% (95% CI: 0.66%, 16.48%), 0.44% (95% CI: -1.45%, 2.37%), -0.83% (95% CI: -2.94%, 1.32%), -1.09% (95% CI: -4.27%, 2.19%) and 6.5% (95% CI: 1.74%, 11.49%) changes in all natural deaths, respiratory disorders, diabetes, cardiovascular diseases, heart diseases, acute myocardial infarction and stroke, respectively. We did not find any evidence that the associations were significantly modified by socioeconomic status or individual characteristics although small differences of estimates across subpopulations were demonstrated.</p> <p>Conclusions</p> <p>Exposure to ozone was associated with specific cause mortality in Eastern Massachusetts during May-September, 1995-2002. There was no evidence that effects of ozone on mortality were significantly modified by socioeconomic status and individual characteristics.</p

Heavy-light decay topologies as a new strategy to discover a heavy gluon

We study the collider phenomenology of the lightest Kaluza-Klein excitation of the gluon, G*, in theories with a warped extra dimension. We do so by means of a two-site effective lagrangian which includes only the lowest-lying spin-1 and spin-1/2 resonances. We point out the importance of the decays of G* to one SM plus one heavy fermion, that were overlooked in the previous literature. It turns out that, when kinematically allowed, such heavy-light decays are powerful channels for discovering the G*. In particular, we present a parton-level Montecarlo analysis of the final state Wtb that follows from the decay of G* to one SM top or bottom quark plus its heavy partner. We find that at \sqrt{s} = 7 TeV and with 10 fb^{-1} of integrated luminosity, the LHC can discover a KK gluon with mass in the range M_{G*} = (1.8 - 2.2) TeV if its coupling to a pair of light quarks is g_{G*qqbar} = (0.2-0.5) g_3. The same process is also competitive for the discovery of the top and bottom partners as well. We find, for example, that the LHC at \sqrt{s} = 7 TeV can discover a 1 TeV KK bottom quark with an integrated luminosity of (5.3 - 0.61) fb^{-1} for g_{G*qqbar} = (0.2-0.5) g_3.Comment: 36 pages, 13 figures. v2: a few typos corrected, comments added, version published in JHE