Collaborating Across Units to Support Digital Scholarship

In this session, participants shared strategies and best practices for collaborating across units to support digital scholarship. The leaders briefly described two recent examples of successful collaborations at Middlebury College, instituting Omeka support & running a Liberal Arts Data Bootcamp, before opening up for broader discussions and brainstorming

Graph-Sparse LDA: A Topic Model with Structured Sparsity

Originally designed to model text, topic modeling has become a powerful tool for uncovering latent structure in domains including medicine, finance, and vision. The goals for the model vary depending on the application: in some cases, the discovered topics may be used for prediction or some other downstream task. In other cases, the content of the topic itself may be of intrinsic scientific interest. Unfortunately, even using modern sparse techniques, the discovered topics are often difficult to interpret due to the high dimensionality of the underlying space. To improve topic interpretability, we introduce Graph-Sparse LDA, a hierarchical topic model that leverages knowledge of relationships between words (e.g., as encoded by an ontology). In our model, topics are summarized by a few latent concept-words from the underlying graph that explain the observed words. Graph-Sparse LDA recovers sparse, interpretable summaries on two real-world biomedical datasets while matching state-of-the-art prediction performance

Control of Turbulent Flow Over an Articulating Turret for Reduction of Adverse Aero-Optic Effects

Turbulent flows such as wakes and shear layers are highly detrimental to the intensity of any collimated light beams that pass through these regions. The work presented in this thesis utilized suction flow control to help mitigate the adverse affects of the wake and shear layer over a flat aperture on the hemisphere of a three dimensional turret. The hemisphere of the turret was capable of dynamically articulating in two degrees of freedom: pitch and azimuthal rotation. The experiments were performed in the Syracuse University wind tunnel at a Mach number of 0.1, giving a Reynolds number of 500,000. Steady suction at various amounts were initially implemented for both static and dynamic pitching cases. Abatement of the wake above the aperture of the turret was seen for open loop suction actuation in both cases, demonstrating that for our conditions the suction system has enough control authority to reduce the turbulence levels. Building upon this success, a simple proportional closed loop controller was constructed to improve the efficiency of the actuation system by reducing the amount of suction required to achieve the same level of turbulence abatement as with the open loop control. The overall objective of the controller was to drive the velocity fluctuations over the aperture of the turret to zero. The next set of experiments fixed the pitch angle and dynamically rotated the hemisphere in the azimuthal direction. Like the pitch tests, steady suction actuation applied over the top of the turret was able to diminish the size of the wake. A multiple-input-multiple output closed loop controller was then employed with the objective of reducing the velocity fluctuations over the aperture of the turret. By dividing the actuation into two separate zones, the MIMO controller was able to more efficiently decrease the turbulent levels over the aperture when compared to the open loop case. Additional suction control tests were performed over a stationary turret in the Air Force Research Laboratory wind tunnel at Wright-Patterson Air Force Base. Direct measurements of the aero-optic effects were taken via a Malley probe at a fixed pitch angle with and without suction control at a Mach number 0.3, and a corresponding Reynolds number of 2,000,000. Reduction of the aero-optic effects in this test demonstrated that suction control is a practical control input to reduce the near field wavefront abberations due to the turbulent flow over the aperture

Factors Which Decrease the Search Time of an Aircraft Crash

The purpose of this study is to determine what procedures a general aviation aircrew can perform during the course of flight to minimize the search time required to locate the aircraft\u27s crash site in the event of aerial disaster. This study will also serve to quantify the extent each procedure can reduce the overall search time. Findings from this study can then be used to educate pilots to practice these crash-conscious procedures and improve post-crash aircrew survivability

THREE ESSAYS ON REMOTE WORK AND REGIONAL DEVELOPMENT

This dissertation is comprised of three papers that collectively explore the relationship between remote work, or people that work from anywhere, and regional economic development. The first paper measures remote occupational employment in the United States with Census microdata and a shift-share model to decompose the share of occupational growth attributed to remote work. Findings indicate remote work has grown significantly since 2000, with the most pronounced growth in high skill jobs. The second paper uses a mixed-methods design to understand the role of remote work in migration decisions. It concludes that remote work arrangements enable access to employment opportunities that are unavailable locally and supports certain migration. The third paper uses a cross-sectional design and spatial econometrics to investigate the influence of amenities on the concentration of remote workers across a sample of US counties. The findings indicate that amenities, especially recreational and cultural, play a powerful role in explaining variations of remote worker concentrations across counties and that amenities play different roles in the hierarchy of county sizes. The dissertation concludes with a discussion of the implications for place and offers avenues for future inquiry

The Economic Contribution of Casco Bay

EXECUTIVE SUMMARY Casco Bay is an ecological and environmental treasure to the people who live and work there, to the visitors it attracts, and to the diverse wildlife and living resources that make the Bay and watershed their home. However, the Bay also makes significant economic contributions in the form of jobs, provision of natural resources, and the provision of services. The natural amenities provided by Casco Bay also play a very important role in attracting and retaining high-skilled workers to the region that support a growing innovation-based regional economy. The Casco Bay Watershed Region is home to one-quarter of Maine’s population and one-third of the total jobs in the state, despite containing just 4.4 percent of the state’s land mass. It follows that the health of the regional economy is highly dependent upon the health of Casco Bay and its resources, providing a strong case for protecting and caring for Casco Bay and the watershed. Yet, policy makers, business leaders, and the public do not have a strong sense of the scale and ways in which the Bay contributes economic value or how this may change over time. This study addresses these gaps and sets out to achieve three objectives: To provide estimates of the current economic market value that Casco Bay contributes to the regional and state economy; To understand the potential economic implications of changes to the ecological health of the Bay, specifically as a result of the impacts anticipated from climate change; and To establish a framework for continued monitoring and tracking of the health of the ocean economy.

Can’t See the Wood for the Trees: The Returns to Farm Forestry in Ireland

working paperThe period 2007-2009 witnessed considerable variability in the price of outputs such as milk and cereals and this was compounded by a high degree of volatility in the price of inputs such as fertilizer, animal feed and energy. Previously, Irish farms have used the returns to off-farm employment as well as agricultural support payments such as the Single Farm Payment (SFP) and the Rural Environmental Protection Scheme (REPS) to protect their living standards against low and uncertain agricultural market returns. However, the downturn in the Irish economy has led to a reduction in the availability of off-farm employment and also the discontinuation of REPS. This may lead to an increase in afforestation on Irish farms, as forestry offers greater certainty through the provision of an annual premium in addition to the SFP. However, the decision to afforest represents a significant long-term investment decision that should not be entered into without careful economic consideration. The aim of this paper is to use the Discounted Cash Flow (DCF) analysis method to calculate the returns to forestry under alternative opportunity costs associated with conventional agricultural activities being superseded. The returns to forestry are calculated using the Forestry Investment Value Estimator (FIVE). These returns were then incorporated in the DCF model along with the returns to five conventional agricultural enterprises, which would potentially be superseded by forestry. This approach allows for the calculation of the Net Present Value (NPV) of three forestry scenarios

Remote Worker Trends pre and post-COVID-19

Although remote work has been a growing phenomenon since before COVID-19, the pandemic has accelerated this changes exponentially pushing half of the US workforce to work remotely overnight. CBER is examining these trends the potential implications for economic, community, and workforce development in Maine. As this work builds, work products will be provided below

Preliminary Forecast Presentation to the Governor\u27s Economic Recovery Committee - October 13, 2020

Regional forecasts provide state and local leaders and businesses with short-term expectations of the trajectory of recovery. Forecasts incorporate national economic outlooks prepared by the University of Michigan\u27s Research Seminary in Quantitative Economics (RSQE), the US Congressional Budget Office (CBO) Outlooks, and from other vendors such as Moody\u27s Analytics. State level outlooks draw from the Maine Consensus Economic Forecast Committees (CEFC), state specific research and data, and other assumptions. Regional forecasts are prepared using a seven region 80 sector economic model developed by Regional Economic Modeling Inc. (REMI) and are provided for the state and regions that closely coincide with the economic development districts (EDDs). These include Northern Maine (Aroostook-Washington), Eastern Maine, Kennebec Valley, Midcoast, Androscoggin Valley, Greater Portland, and Southern Maine