Resilient Architecture: Adaptive Community Living in Coastal Locations

How can architects design for coastal inundation caused by climate change, what are the methods and strategies currently being implemented as a response to coastal inundation, and how can these strategies influence the design approach for a self-sustaining community that can survive and thrive in a low-lying coastal area? Climate change is caused by an expenditure of planet-harming resources being improperly or inefficiently utilized and consumed. This can lead to a rise of global sea level and an increased severity of storm surges. Resilience is defined as the ability to overcome challenges and difficulties. Coastal resilience is the ability for a coastal community to independently withstand shocks caused by hazardous storms and coastal flooding, adapt to future occurrences, and rebuild when necessary. Incorporating resilient and adaptable design elements into architecture could help to create a more sustainable built environment that reacts more efficiently to challenges and difficulties that occur in the natural world. The intent of this thesis is to design a coastal community-living development that serves as a case study for how communities in low-lying areas can be elevated in order to sustain fluctuating coastal conditions. An ideal setting for the implementation of this thesis is Pleasure Beach Park, a low-lying barrier beach located on the coastline of Bridgeport, Connecticut. Through research and analysis of this location, this design responds to and includes essential programmatic elements deemed necessary for a community to exist in the area, as well as vital attributes that collectively form a resilient coastal community

The Neonatal Microbiome and Necrotizing Enterocolitis.

Necrotizing enterocolitis (NEC) is a devastating disorder that affects approximately 10% of premature infants. Its mortality remains high (15-30%), and its cause remains unknown. About 80% of cases occur within 35 days of birth among hospitalized newborns of low birth weight. Probiotics diminish the incidence and severity of NEC, and NEC does not occur antepartum. NEC affects a readily identifiable at-risk group, has a tightly defined interval before its onset, occurs in an organ system that is intimately associated with a microbial population in flux, has a plausible association with the intestinal microbiota, and cohorts at risk have rarely been studied in large numbers, or prospectively. This disorder, therefore, provides a unique opportunity to explore the role of the human enteric microbiome in a devastating disease. Moreover, NEC epidemiology and age-incidence present an ability to enroll and study cohorts that are highly likely to provide valuable pathophysiologic and microbiologic insights.

In this project, we will identify and quantify the microbial components of stool and its products before and at the onset of NEC. In doing so, we will test the overarching hypothesis that NEC is a direct or indirect consequence of the enteric biomass, its products, or both. We will use multicenter cohorts of premature infants at high risk of developing NEC, extend our research on this disease currently sponsored by the Washington University Institute of Clinical and Translational Sciences, and continue our longstanding collaborations with the Genome Center at Washington University and the Washington University Digestive Diseases Research Core Center (Informatics Core). The Aims of this proposal are to (1) conduct a case cohort study in which we compare clinical data and biological specimens from cases and well-matched controls; (2) determine if the kind and density of intestinal biomass, its gene content, and transcriptional activity are associated with, and potential determinants of, NEC; and (3) determine if host risk alleles for intestinal inflammation play a role in the development of NEC. These efforts will be accomplished using subjects from three collaborating neonatal intensive care units (NICUs), focusing on the critical, instructive, and understudied pre-NEC stage of illness, and formulating a data repository that will be a resource for investigators worldwide who wish to focus their efforts on NEC, its precipitants, and its prevention and cure.
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Political Underrepresentation and Domestic Terrorism: The Deficiency of Minority Descriptive Representation as a Causal Factor of Violent Radicalization in Western European Democracies

Electoral systems are vital in controlling the levels of minority descriptive representation in a government because each system contains characteristics that make it easier or more difficult for a member of a minority group to be elected to office. Because of this power, I focus on the role of electoral systems in Western European democracies as a possible, causal factor of domestic terrorism by way of their effect on the level of a country’s minority descriptive representation, and therefore, levels of minority inclusion. To test my hypotheses, I use both quantitative and qualitative data in linear regression models, and a comparative case study of France and Denmark. The results of the data analysis indicate that countries that employ more exclusive electoral systems experience significantly higher rates of domestic terrorism than countries that employ more inclusive electoral systems. The findings of this study present a correlation between the descriptive underrepresentation of minority groups in Western European democracies and the corresponding levels of domestic terrorism experienced by these countries

The complex position of migrant children in European legislation and education

Across Europe, migrant children often have lower educational outcomes than non-migrant children. This is a trajectory that can begin early in the school career and have long-term implications and is due to a host of school and non-school factors. This chapter offers an overview of migrant children’s protection, support and education as well as a synopsis of some of the legislation that impacts young migrants and their integration into schools. To this end, it highlights two contrasting cases (those of Belgium and Poland) in order to better illustrate the fact that even in countries with very different histories of migration, approaches to integration and school systems, there are many common obstacles facing migrant children in schools. Available data on the training of teachers and support workers, migrant children’s access to and placement in schools and the structural space for children’s agency in schools is presented here in order to illustrate the difference between policy and the lived reality of migrant children’s integration into schools. The treatment of children in policy and programming that is summarised here shows the complicated position migrant children occupy in policy, society and education systems

New statistical method identifes cytokines that distinguish stool microbiomes

Regressing an outcome or dependent variable onto a set of input or independent variables allows the analyst to measure associations between the two so that changes in the outcome can be described by and predicted by changes in the inputs. While there are many ways of doing this in classical statistics, where the dependent variable has certain properties (e.g., a scalar, survival time, count), little progress on regression where the dependent variable are microbiome taxa counts has been made that do not impose extremely strict conditions on the data. In this paper, we propose and apply a new regression model combining the Dirichlet-multinomial distribution with recursive partitioning providing a fully non-parametric regression model. This model, called DM-RPart, is applied to cytokine data and microbiome taxa count data and is applicable to any microbiome taxa count/metadata, is automatically fit, and intuitively interpretable. This is a model which can be applied to any microbiome or other compositional data and software (R package HMP) available through the R CRAN website

Quiescent Galaxies in the 3D-HST Survey: Spectroscopic Confirmation of a Large Number of Galaxies with Relatively Old Stellar Populations at z~2

Quiescent galaxies at z~2 have been identified in large numbers based on rest-frame colors, but only a small number of these galaxies have been spectroscopically confirmed to show that their rest-frame optical spectra show either strong Balmer or metal absorption lines. Here, we median stack the rest-frame optical spectra for 171 photometrically-quiescent galaxies at 1.4 < z < 2.2 from the 3D-HST grism survey. In addition to Hbeta (4861A), we unambiguously identify metal absorption lines in the stacked spectrum, including the G-band (4304A), Mg I (5175A), and Na I (5894A). This finding demonstrates that galaxies with relatively old stellar populations already existed when the universe was ~3 Gyr old, and that rest-frame color selection techniques can efficiently select them. We find an average age of 1.3^0.1_0.3 Gyr when fitting a simple stellar population to the entire stack. We confirm our previous result from medium-band photometry that the stellar age varies with the colors of quiescent galaxies: the reddest 80% of galaxies are dominated by metal lines and have a relatively old mean age of 1.6^0.5_0.4 Gyr, whereas the bluest (and brightest) galaxies have strong Balmer lines and a spectroscopic age of 0.9^0.2_0.1 Gyr. Although the spectrum is dominated by an evolved stellar population, we also find [OIII] and Hbeta emission. Interestingly, this emission is more centrally concentrated than the continuum with L_[OIII] = 1.7 +/- 0.3 x 10^40 erg s^-1, indicating residual central star formation or nuclear activity.Comment: 6 pages, 4 figures, accepted for publication in the Astrophysical Journal Letter

Dynamic Changes in High‐Sensitivity Cardiac Troponin I Are Associated with Dynamic Changes in Sum Absolute QRST Integral on Surface Electrocardiogram in Acute Decompensated Heart Failure

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135259/1/anec12379_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/135259/2/anec12379.pd

Exploring the chemical link between local ellipticals and their high-redshift progenitors

We present Keck/MOSFIRE K-band spectroscopy of the first mass-selected sample of galaxies at $z\sim2.3$. Targets are selected from the 3D-HST Treasury survey. The six detected galaxies have a mean [NII]$\lambda$6584/H$\alpha$ ratio of $0.27\pm0.01$, with a small standard deviation of 0.05. This mean value is similar to that of UV-selected galaxies of the same mass. The mean gas-phase oxygen abundance inferred from the [NII]/H$\alpha$ ratios depends on the calibration method, and ranges from 12+log(O/H)$_{gas}=8.57$ for the {Pettini} & {Pagel} (2004) calibration to 12+log(O/H)$_{gas}= 8.87$ for the {Maiolino} {et~al.} (2008) calibration. Measurements of the stellar oxygen abundance in nearby quiescent galaxies with the same number density indicate 12+log(O/H)$_{stars}= 8.95$, similar to the gas-phase abundances of the $z\sim2.3$ galaxies if the {Maiolino} {et~al.} (2008) calibration is used. This suggests that these high-redshift star forming galaxies may be progenitors of today's massive early-type galaxies. The main uncertainties are the absolute calibration of the gas-phase oxygen abundance and the incompleteness of the $z\sim2.3$ sample: the galaxies with detected H$\alpha$ tend to be larger and have higher star formation rates than the galaxies without detected H$\alpha$, and we may still be missing the most dust-obscured progenitors.Comment: 7 pages, 5 figures. Accepted for publication in ApJ

New statistical method identifies cytokines that distinguish stool microbiomes.

Regressing an outcome or dependent variable onto a set of input or independent variables allows the analyst to measure associations between the two so that changes in the outcome can be described by and predicted by changes in the inputs. While there are many ways of doing this in classical statistics, where the dependent variable has certain properties (e.g., a scalar, survival time, count), little progress on regression where the dependent variable are microbiome taxa counts has been made that do not impose extremely strict conditions on the data. In this paper, we propose and apply a new regression model combining the Dirichlet-multinomial distribution with recursive partitioning providing a fully non-parametric regression model. This model, called DM-RPart, is applied to cytokine data and microbiome taxa count data and is applicable to any microbiome taxa count/metadata, is automatically fit, and intuitively interpretable. This is a model which can be applied to any microbiome or other compositional data and software (R package HMP) available through the R CRAN website

Hypothesis Testing and Power Calculations for Taxonomic-Based Human Microbiome Data

This paper presents new biostatistical methods for the analysis of microbiome data based on a fully parametric approach using all the data. The Dirichlet-multinomial distribution allows the analyst to calculate power and sample sizes for experimental design, perform tests of hypotheses (e.g., compare microbiomes across groups), and to estimate parameters describing microbiome properties. The use of a fully parametric model for these data has the benefit over alternative non-parametric approaches such as bootstrapping and permutation testing, in that this model is able to retain more information contained in the data. This paper details the statistical approaches for several tests of hypothesis and power/sample size calculations, and applies them for illustration to taxonomic abundance distribution and rank abundance distribution data using HMP Jumpstart data on 24 subjects for saliva, subgingival, and supragingival samples. Software for running these analyses is available