E Pluribus Unum: An Evaluation of Student Engagement and Learning in the College Marching Band

Thesis advisor: Karen ArnoldStudent engagement has been associated with a range of desirable outcomes in the undergraduate experience (Astin, 1993, Pascarella & Terenzini, 2005) and music participation has been shown to facilitate important personal and social development among its participants (Hallam, 2010). Despite this, no study has been conducted to evaluate the potential benefits of participation in one of the largest and most visible student organizations on campus: the college marching band. The purpose of this quantitative evaluation was to determine whether marching band students express distinctive patterns of engagement within their respective communities as compared with their non-band peers. Items and scales from the National Survey of Student Engagement (NSSE) were administered to marching band members (n=1,882) at 20 participating universities with National Collegiate Athletic Association (NCAA) Division-I football programs. Data were compared with a sample of general undergraduate (non-band) responses (n=6,095) from the same institutions provided by the NSSE Institute. Findings suggested that band students are more engaged with diverse peers along racial, ethnic, political, ideological, and religious lines (p<.01; Cohen’s d=0.26) and they are more reflective in their learning as evident in their willingness to imagine another’s perspective and reevaluate their own views (p<.01; Cohen’s d=0.19). Compared with non-band peers, marching band members indicated greater personal social responsibility on an array of vectors (p<.01; Cohen’s d=0.36) including: developing a personal code of values and ethics, understanding people of other racial and ethnic backgrounds, understanding themselves, learning effectively on their own, voting in local or national elections, contributing to the welfare of their community, and solving complex real-world problems. After controlling for a range of pre-college and co-existing variables, marching band membership remained the strongest predictor of these desirable outcomes (β=0.172, p<.01).Thesis (PhD) — Boston College, 2016.Submitted to: Boston College. Lynch School of Education.Discipline: Educational Leadership and Higher Education

A Northern Survey of Gamma-Ray Blazar Candidates

In preparation for GLAST, we have compiled a sample of blazar candidates to increase the pool of well studied AGN from which GLAST counterparts will be drawn. Sources were selected with our Figure of Merit (FoM) ranking; thus, they have radio and X-ray properties very similar to the EGRET blazars. Spectroscopic confirmation of these candidates is in progress, and more than 70% of these objects have been identified as flat spectrum radio quasars and BL Lac objects. We present ~250 new optical blazar identifications based on McDonald Observatory spectroscopy, 224 with redshifts. Of these, 167 are in our FoM-selected set. To motivate the Gamma-ray nature of these objects, we analyzed the current release of the EGRET data for possible point sources at their radio positions. We develop two distinct methods to combine multiple EGRET observations of a sky position into a single detection significance. We report a detection of the signal of the set of blazar candidates in the EGRET data at the > 3 sigma level by both techniques. We predict that the majority of these blazar candidates will be found by GLAST due to its increased sensitivity, duty cycle and resolving power.Comment: ApJ Accepted (to appear 10 June 2005

Training to enhance psychiatrist communication with patients with psychosis (TEMPO): cluster randomised controlled trial

Background A better therapeutic relationship predicts better outcomes. However, there is no trial-based evidence on how to improve therapeutic relationships in psychosis. Aims To test the effectiveness of communication training for psychiatrists on improving shared understanding and the therapeutic relationship (trial registration: ISRCTN94846422). Method In a cluster randomised controlled trial in the UK, 21 psychiatrists were randomised. Ninety-seven (51% of those approached) out-patients with schizophrenia/schizoaffective disorder were recruited, and 64 (66% of the sample recruited at baseline) were followed up after 5 months. The intervention group received four group and one individualised session. The primary outcome, rated blind, was psychiatrist effort in establishing shared understanding (self-repair). Secondary outcome was the therapeutic relationship. Results Psychiatrists receiving the intervention used 44% more self-repair than the control group (adjusted difference in means 6.4, 95% CI 1.46–11.33, P<0.011, a large effect) adjusting for baseline self-repair. Psychiatrists rated the therapeutic relationship more positively (adjusted difference in means 0.20, 95% CI 0.03–0.37, P = 0.022, a medium effect), as did patients (adjusted difference in means 0.21, 95% CI 0.01–0.41, P = 0.043, a medium effect). Conclusions Shared understanding can be successfully targeted in training and improves relationships in treating psychosis

The Baryon Oscillation Spectroscopic Survey of SDSS-III

The Baryon Oscillation Spectroscopic Survey (BOSS) is designed to measure the scale of baryon acoustic oscillations (BAO) in the clustering of matter over a larger volume than the combined efforts of all previous spectroscopic surveys of large scale structure. BOSS uses 1.5 million luminous galaxies as faint as i=19.9 over 10,000 square degrees to measure BAO to redshifts z<0.7. Observations of neutral hydrogen in the Lyman alpha forest in more than 150,000 quasar spectra (g<22) will constrain BAO over the redshift range 2.15<z<3.5. Early results from BOSS include the first detection of the large-scale three-dimensional clustering of the Lyman alpha forest and a strong detection from the Data Release 9 data set of the BAO in the clustering of massive galaxies at an effective redshift z = 0.57. We project that BOSS will yield measurements of the angular diameter distance D_A to an accuracy of 1.0% at redshifts z=0.3 and z=0.57 and measurements of H(z) to 1.8% and 1.7% at the same redshifts. Forecasts for Lyman alpha forest constraints predict a measurement of an overall dilation factor that scales the highly degenerate D_A(z) and H^{-1}(z) parameters to an accuracy of 1.9% at z~2.5 when the survey is complete. Here, we provide an overview of the selection of spectroscopic targets, planning of observations, and analysis of data and data quality of BOSS.Comment: 49 pages, 16 figures, accepted by A

BRCA2 polymorphic stop codon K3326X and the risk of breast, prostate, and ovarian cancers

Background: The K3326X variant in BRCA2 (BRCA2*c.9976A&gt;T; p.Lys3326*; rs11571833) has been found to be associated with small increased risks of breast cancer. However, it is not clear to what extent linkage disequilibrium with fully pathogenic mutations might account for this association. There is scant information about the effect of K3326X in other hormone-related cancers. Methods: Using weighted logistic regression, we analyzed data from the large iCOGS study including 76 637 cancer case patients and 83 796 control patients to estimate odds ratios (ORw) and 95% confidence intervals (CIs) for K3326X variant carriers in relation to breast, ovarian, and prostate cancer risks, with weights defined as probability of not having a pathogenic BRCA2 variant. Using Cox proportional hazards modeling, we also examined the associations of K3326X with breast and ovarian cancer risks among 7183 BRCA1 variant carriers. All statistical tests were two-sided. Results: The K3326X variant was associated with breast (ORw = 1.28, 95% CI = 1.17 to 1.40, P = 5.9x10- 6) and invasive ovarian cancer (ORw = 1.26, 95% CI = 1.10 to 1.43, P = 3.8x10-3). These associations were stronger for serous ovarian cancer and for estrogen receptor–negative breast cancer (ORw = 1.46, 95% CI = 1.2 to 1.70, P = 3.4x10-5 and ORw = 1.50, 95% CI = 1.28 to 1.76, P = 4.1x10-5, respectively). For BRCA1 mutation carriers, there was a statistically significant inverse association of the K3326X variant with risk of ovarian cancer (HR = 0.43, 95% CI = 0.22 to 0.84, P = .013) but no association with breast cancer. No association with prostate cancer was observed. Conclusions: Our study provides evidence that the K3326X variant is associated with risk of developing breast and ovarian cancers independent of other pathogenic variants in BRCA2. Further studies are needed to determine the biological mechanism of action responsible for these associations

Aboveground biomass density models for NASA's Global Ecosystem Dynamics Investigation (GEDI) lidar mission

NASA's Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI's footprint-level (similar to 25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI's waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available