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    Mt. Pleasant Church, Conewago Township

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    About two miles south of McSherrystown and a similar distance southwest of Hanover, in Conewago Township, lies the small village of Mt. Pleasant. The community developed at and near the intersection of State Route 194, commonly called the Hanover-Littlestown Pike, and Legislative Route 01005, known in days past as the road from McSherrystown to Gitt\u27s Mill and its segment south of the intersection called in recent times Narrow Drive. In the eastern quadrant of the intersection, a church was built in 1878; nearby and adjacent to the crossroads sat a public school, which had been built sometime before 1858. The school was known by two names, Mt. Pleasant and Schwartz\u27s, and the village itself was also called by some people Schwartz\u27s or Schwartz\u27s Schoolhouse. Further, like the church, the school had religious significance to residents of the vicinity. [excerpt

    March into Oblivion: A Footnote

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    In the above-titled work in 2006, this writer briefly discussed the possibility that President George Washington traversed present Adams County in October 1794, during his return from Bedford to Philadelphia, a belief long and widely held locally. No credible assertion of the President\u27s presence here in 1794 was possible at that time. Recently however, a forgotten narrative was rediscovered ; its author, Jacob Eyster, gives some substance to the previous mere speculation. After extensive research, this writer was graciously requested to produce a sequel to his prior speculative writing. [excerpt

    Linguistics and LIS: A Research Agenda

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    Linguistics and Library and Information Science (LIS) are both interdisciplinary fields that draws from areas such as languages, psychology, sociology, cognitive science, computer science, anthropology, education, and management. The theories and methods of linguistic research can have significant explanatory power for LIS. This article presents a research agenda for LIS that proposes the use of linguistic analysis methods, including discourse analysis, typology, and genre theory

    March into Oblivion

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    The Whiskey Rebellion often is assigned, even by historians, to an obscurity which belies its significance. Its importance was major not only to the people most affected by its cause and those most intimately involved in the playing out of the events, but also to the young federal government, which had to demonstrate its authority yet not trample its own citizens. The situation held a very real potential for tearing apart the fragile nation. President George Washington felt strongly enough about it to involve himself personally in the beginnings of the military action. In the last few years of the century, rapid improvement in economics, safety, and foreign relations, surely spurred in part by the government\u27s reactions to the insurrection, underscored the importance to the nation as a whole. [excerpt

    Scanning Ultrafast Electron Microscopy: A Novel Technique to Probe Photocarrier Dynamics with High Spatial and Temporal Resolutions

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    The dynamics of photo-excited charge carriers, particularly their transport and interactions with defects and interfaces, play an essential role in determining the performance of a wide range of solar and optoelectronic devices. A thorough understanding of these processes requires tracking the motion of photocarriers in both space and time simultaneously with extremely high resolutions, which poses a significant challenge for previously developed techniques, mostly based on ultrafast optical spectroscopy. Scanning ultrafast electron microscopy (SUEM) is a recently developed photon-pump-electron-probe technique that combines the spatial resolution of scanning electron microscopes (SEM) and the temporal resolution of femtosecond ultrafast lasers. Despite many recent excellent reviews for the ultrafast electron microscopy, we dedicate this article specifically to SUEM, where we review the working principle and contrast mechanisms of SUEM in the secondary-electron-detection mode from a users' perspective and discuss the applications of SUEM to directly image photocarrier dynamics in various materials. Furthermore, we propose future theoretical and experimental directions for better understanding and fully utilizing the SUEM measurements to obtain detailed information about the dynamics of photocarriers. To conclude, we envision the potential of expanding SUEM into a versatile platform for probing photophysical processes beyond photocarrier dynamics.Comment: 23 pages, 6 figure

    Multivariate type G Mat\'ern stochastic partial differential equation random fields

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    For many applications with multivariate data, random field models capturing departures from Gaussianity within realisations are appropriate. For this reason, we formulate a new class of multivariate non-Gaussian models based on systems of stochastic partial differential equations with additive type G noise whose marginal covariance functions are of Mat\'ern type. We consider four increasingly flexible constructions of the noise, where the first two are similar to existing copula-based models. In contrast to these, the latter two constructions can model non-Gaussian spatial data without replicates. Computationally efficient methods for likelihood-based parameter estimation and probabilistic prediction are proposed, and the flexibility of the suggested models is illustrated by numerical examples and two statistical applications

    Quantifying the uncertainty of contour maps

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    Contour maps are widely used to display estimates of spatial fields. Instead of showing the estimated field, a contour map only shows a fixed number of contour lines for different levels. However, despite the ubiquitous use of these maps, the uncertainty associated with them has been given a surprisingly small amount of attention. We derive measures of the statistical uncertainty, or quality, of contour maps, and use these to decide an appropriate number of contour lines, that relates to the uncertainty in the estimated spatial field. For practical use in geostatistics and medical imaging, computational methods are constructed, that can be applied to Gaussian Markov random fields, and in particular be used in combination with integrated nested Laplace approximations for latent Gaussian models. The methods are demonstrated on simulated data and an application to temperature estimation is presented
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