Junior Recital

List of performers and performances

Reconstructing Bison and Mammoth Migration During the Late Pleistocene and Early Holocene of Central Texas Using Strontium Isotopes

During the Late Pleistocene (LP; past 130,000 years), over two-thirds of large mammal (\u3e45kg) species went extinct globally. While the role of humans is hotly debated, the effect of these extinctions is growing clearer; the extinctions resulted in widespread and lasting faunal community reorganization. However, the impact of these extinctions on dietary and migratory behavior within faunal communities is unknown. Our study examines the impact of the megafaunal extinctions on the dietary and migratory behavior of surviving Bison individuals in Texas using carbon, oxygen, and strontium isotopes. Strontium isotopes are incorporated into mammalian enamel during their tooth development and varies as these organisms travel to areas with new bedrock. To capture movement within an individual in the fossil record, serially sampling a single tooth can reveal the movements of an individual across space. Here, we examine the carbon, oxygen, and strontium isotopes from the enamel of two ubiquitous Pleistocene genera (Bison and Mammuthus) before the megafaunal extinctions. We preferentially sampled sites older than the commonly cited (12 Ka) date for widespread human occupation in North America. We also sampled Bison that survived the megafaunal extinction to compare migratory patterns before and after the extinction. This study thus presents high-resolution, serially sampled stable isotope data on bison (n=10) and mammoths (n=5) collected from five LP sites, dating from 33 to 11 Ka, in central Texas. Preliminary strontium isotope data suggest that Mammuthus has larger home ranges in Texas (\u3e100km) than modern savannah elephants (30–50km). Our data will reveal important information about the effects of megafaunal extinction on migratory patterns through time. Given the small samples sizes of this study, additional research is needed to refine our understanding of the mechanisms causing this spatial and temporal variation and its relevance to other taxa

Analysis of Observed Contamination Through SAGE III's First Year on Orbit

SAGE III is a payload on the International Space Station that conducts measurements of ozone and other atmospheric constituents through the use of a moderate resolution spectrometer with an operating wavelength range of 290 nm to 1550 nm. Because of the optically sensitive nature of the payload, a suite of eight Thermoelectric Quartz Crystal Microbalances (TQCMs) were included to monitor the operating environment. During the rst year of operation, the SAGE III TQCMs were instrumental in detecting several periods of higher contamination and localizing their sources. A clear window made from quartz crystal covers the instrument assembly's aperture. Under nominal operating conditions, this window is only open during science gathering activities. However, if the rates of contamination accumulation are detected to be above the background rate, the window will be kept closed during science gathering to protect the optically sensitive instrument mirror. An analysis of the signal transmissions through the window for the wavelengths of 290 nm to 1550 nm has been conducted to determine any possible degradation of the window and potential in uence on science data collected to date, and established a baseline for future analysis

Carbon Free Boston: Transportation Technical Report

Part of a series of reports that includes: Carbon Free Boston: Summary Report; Carbon Free Boston: Social Equity Report; Carbon Free Boston: Technical Summary; Carbon Free Boston: Buildings Technical Report; Carbon Free Boston: Waste Technical Report; Carbon Free Boston: Energy Technical Report; Carbon Free Boston: Offsets Technical ReportOVERVIEW: Transportation connects Boston’s workers, residents and tourists to their livelihoods, health care, education, recreation, culture, and other aspects of life quality. In cities, transit access is a critical factor determining upward mobility. Yet many urban transportation systems, including Boston’s, underserve some populations along one or more of those dimensions. Boston has the opportunity and means to expand mobility access to all residents, and at the same time reduce GHG emissions from transportation. This requires the transformation of the automobile-centric system that is fueled predominantly by gasoline and diesel fuel. The near elimination of fossil fuels—combined with more transit, walking, and biking—will curtail air pollution and crashes, and dramatically reduce the public health impact of transportation. The City embarks on this transition from a position of strength. Boston is consistently ranked as one of the most walkable and bikeable cities in the nation, and one in three commuters already take public transportation. There are three general strategies to reaching a carbon-neutral transportation system: • Shift trips out of automobiles to transit, biking, and walking;1 • Reduce automobile trips via land use planning that encourages denser development and affordable housing in transit-rich neighborhoods; • Shift most automobiles, trucks, buses, and trains to zero-GHG electricity. Even with Boston’s strong transit foundation, a carbon-neutral transportation system requires a wholesale change in Boston’s transportation culture. Success depends on the intelligent adoption of new technologies, influencing behavior with strong, equitable, and clearly articulated planning and investment, and effective collaboration with state and regional partners.Published versio

Learning low-rank latent mesoscale structures in networks

It is common to use networks to encode the architecture of interactions between entities in complex systems in the physical, biological, social, and information sciences. Moreover, to study the large-scale behavior of complex systems, it is important to study mesoscale structures in networks as building blocks that influence such behavior. In this paper, we present a new approach for describing low-rank mesoscale structure in networks, and we illustrate our approach using several synthetic network models and empirical friendship, collaboration, and protein--protein interaction (PPI) networks. We find that these networks possess a relatively small number of `latent motifs' that together can successfully approximate most subnetworks at a fixed mesoscale. We use an algorithm that we call "network dictionary learning" (NDL), which combines a network sampling method and nonnegative matrix factorization, to learn the latent motifs of a given network. The ability to encode a network using a set of latent motifs has a wide range of applications to network-analysis tasks, such as comparison, denoising, and edge inference. Additionally, using our new network denoising and reconstruction (NDR) algorithm, we demonstrate how to denoise a corrupted network by using only the latent motifs that one learns directly from the corrupted networks.Comment: 55 pages, 14 figures, 1 tabl

A Flexible Broadband Antenna and Transmission Line Network for a Wearable Microwave Breast Cancer Detection System

First, we report on the design, simulation and measurement of a 2-4 GHz conformable antenna optimized for skin contact and implemented on a flexible printed circuit for integration into a wearable device. Second, we experimentally verify the suitability of appropriately long (~10 cm) microstrip traces for the wearable system signal distribution network, which features varying radii of curvature. Consequently, the contribution of the here reported work is two-fold. First, the experimental results obtained both with breast phantoms and on-body measurements, demonstrate a return loss below -10 dB in the desired frequency band. Phantom results also show a through-breast transmission coefficient of above -40 dB at the centre frequency of 3 GHz. Second, and essential for signal integrity in our target application, the results show that the longitudinal curvature of such a microstrip does not increase transmission line losses