Housing Price Dynamics Within a Metropolitan Area

This paper analyzes the pattern of cross-sectional house price appreciation in the Boston metropolitan area from 1982 to 1994. The empirical results are consistent with many of the predictions of a standard urban model in which towns have a fixed set of locational attributes and amenities. In particular, the evidence suggests that house prices in towns with a large share of residents working in the manufacturing sector in 1980 grew less quickly in the ensuing years when aggregate manufacturing employment fell. As baby boomers moved into middle age, house values appreciated faster in towns with a larger initial percentage of middle-aged residents. Housing values rose more slowly in towns that allowed additional construction, and values rose faster in towns closer to Boston. Finally, as fewer families had children who attended public schools statewide, the price premium associated with housing in towns with good schools fell. All of these findings support the view that town amenities and public services are not easily replicated or quickly adaptable to shifts in demand, even within a metropolitan area.

The biosynthesis of cyanobacterial sunscreen scytonemin in intertidal microbial mat communities

We have examined the biosynthesis and accumulation of cyanobacterial sunscreening pigment scytonemin within intertidal microbial mat communities using a combination of chemical, molecular, and phylogenetic approaches. Both laminated (layered) and nonlaminated mats contained scytonemin, with morphologically distinct mats having different cyanobacterial community compositions. Within laminated microbial mats, regions with and without scytonemin had different dominant oxygenic phototrophs, with scytonemin-producing areas consisting primarily of Lyngbya aestuarii and scytonemin-deficient areas dominated by a eukaryotic alga. The nonlaminated mat was populated by a diverse group of cyanobacteria and did not contain algae. The amplification and phylogenetic assignment of scytonemin biosynthetic gene scyC from laminated mat samples confirmed that the dominant cyanobacterium in these areas, L. aestuarii, is likely responsible for sunscreen production. This study is the first to utilize an understanding of the molecular basis of scytonemin assembly to explore its synthesis and function within natural microbial communities.Chemistry and Chemical Biolog

"I See You Face to Face": The Poet-Reader Relationship in Walt Whitman's "Crossing Brooklyn Ferry"

Thesis advisor: Robert KernIn this paper, I argue that Walt Whitman alters his poetic program from his first to second edition of Leaves of Grass. By intensifying the emphasis on individuality and personality, Whitman overcomes the limitations of his vastness by allowing for intimate contact with a future reader. I continue to argue that the poem "Crossing Brooklyn Ferry" exemplifies the emphasis on individuality and personal union. Instead of assuming a relationship with his reader, Whitman sets for himself the goal of making this relationship possible.Thesis (BA) — Boston College, 2004.Submitted to: Boston College. College of Arts and Sciences.Discipline: English.Discipline: College Honors Program

Land Surface Modeling and Evaporative Stress Products for Increased Situational Awareness

No abstract availabl

Exploring the Use of Machine Learning to Develop a Predictive Model for Future Fire Seasons

No abstract availabl

Contour Error Map Algorithm

The contour error map (CEM) algorithm and the software that implements the algorithm are means of quantifying correlations between sets of time-varying data that are binarized and registered on spatial grids. The present version of the software is intended for use in evaluating numerical weather forecasts against observational sea-breeze data. In cases in which observational data come from off-grid stations, it is necessary to preprocess the observational data to transform them into gridded data. First, the wind direction is gridded and binarized so that D(i,j;n) is the input to CEM based on forecast data and d(i,j;n) is the input to CEM based on gridded observational data. Here, i and j are spatial indices representing 1.25-km intervals along the west-to-east and south-to-north directions, respectively; and n is a time index representing 5-minute intervals. A binary value of D or d = 0 corresponds to an offshore wind, whereas a value of D or d = 1 corresponds to an onshore wind. CEM includes two notable subalgorithms: One identifies and verifies sea-breeze boundaries; the other, which can be invoked optionally, performs an image-erosion function for the purpose of attempting to eliminate river-breeze contributions in the wind fields

Using Deep Learning to Predict Yearly Wildfire Potential from Antecedent Land Surface and Meteorological Data

No abstract availabl

Understanding Changes in Modeled Land Surface Characteristics Prior to Lightning-Initiated Holdover Fire Breakout

Lightning initiated wildfires are only 16% of the total number of wildfires within the United States, but account for 56% of the acreage burned. One of the challenges with lightning-initiated wildfires is their ability to "holdover" which means smolder for up to 2+ weeks before breaking out into a full fledged fire. This work helps characterize the percentage of holdover events due to lightning, and helps quantify changes in the land surface characteristics to help understand trends in soil moisture and vegetation stress that potentially contribute to the fire breaking out into a full wildfire

River Flood Prediction Using a Long Short-Term Memory Recurrent Neural Network

No abstract availabl