Literature Through the Looking Glass: How Fan Fiction Can Save English

English departments face a crisis of student disinterest. Scholars are struggling to sell the study of literature as practically useful in an increasingly STEM-dominated world. The literary realm of fan fiction, which can serve as a guiding star, demonstrates how a community of readers and writers can reach for ideals of democracy and creativity that acknowledge the inherent worth of studying literature while also examining how such study can help students thrive in a world threatened by censorship and authoritarianism. This is a prescription for a total shift in philosophy for the academic study of literature. Such study has been dominated by copyrighted single-author works, but fan fiction provides a blueprint for a more collaborative approach that more resembles the storytelling found in ancient human societies. I begin with a comparative history of literature study versus the reading and writing of fan fiction to demonstrate how the two worlds mirror each other. This leads to the guiding question of why one world is dying while the other is thriving. I investigate how the strategies that sustain fan fiction can be translated into the academic world, and I argue for a discipline-spanning course adjustment in terms of atmosphere and methodology based on the idea that fan fiction is the ultimate realization of reader-response criticism. The single-author copyrighted work approach has guided literary study in the past fifty years, but the discipline’s response to the lessons of collaborative fan fiction will decide if such study will survive the next fifty

Astro2020 Science White Paper: Toward Finding Earth 2.0: Masses and Orbits of Small Planets with Extreme Radial Velocity Precision

Having discovered that Earth-sized planets are common, we are now embarking on a journey to determine if Earth-like planets are also common. Finding Earth-like planets is one of the most compelling endeavors of the 21st century - leading us toward finally answering the question: Are we alone? To achieve this forward-looking goal, we must determine the masses of the planets; the sizes of the planets, by themselves, are not sufficient for the determination of the bulk and atmospheric compositions. Masses, coupled with the radii, are crucial constraints on the bulk composition and interior structure of the planets and the composition of their atmospheres, including the search for biosignatures. Precision radial velocity is the most viable technique for providing essential mass and orbit information for spectroscopy of other Earths. The development of high quality precision radial velocity instruments coupled to the building of the large telescope facilities like TMT and GMT or space-based platforms like EarthFinder can enable very high spectral resolution observations with extremely precise radial velocities on minute timescales to allow for the modeling and removal of radial velocity jitter. Over the next decade, the legacy of exoplanet astrophysics can be cemented firmly as part of humankind's quest in finding the next Earth - but only if we can measure the masses and orbits of Earth-sized planets in habitable zone orbits around Sun-like stars.Comment: Science White Paper Submitted to the Astro2020 Decadal Survey (35 co-signers in addition to co-authors

Price-Setting Behavior in a Tourism Sharing Economy Accommodation Market: A Hedonic Price Analysis of AirBnB Hosts in the Caribbean

This study investigated the price-setting behaviour of hosts in the tourism sharing economy in the Caribbean. Generally speaking, we find that site, reputation, convenience, personal and amenities attributes, along with country-level indicators significantly affect prices in the Caribbean. More specifically, most attributes have a positive effect on price-setting. Larger accommodations charge higher prices. Hosts with superior reputations charge higher prices. However, listings with a larger number of ratings are associated with lower prices. This may be an artefact of tourists’ preferences for cheaper sharing accommodations, resulting in a relatively higher volume of reviews for properties at the lower end of the price spectrum. Provision of Convenience options have an overall positive effect on prices, although there is evidence that some options can result in lower prices for tourists. The sole Personal attribute investigated is associated with higher price-setting behaviour. Virtually all amenities examined result in greater prices being charged for the space. Results indicate that geography has significant effects on price-setting behaviour. Listings in countries with greater economic and infrastructural development, greater biodiversity, but weaker exchange rates have higher prices. On the other hand, prices are lower in countries where there is more competition for customers

Price-Setting Behavior in a Tourism Sharing Economy Accommodation Market: A Hedonic Price Analysis of AirBnB Hosts in the Caribbean

This study investigated the price-setting behaviour of hosts in the tourism sharing economy in the Caribbean. Generally speaking, we find that site, reputation, convenience, personal and amenities attributes, along with country-level indicators significantly affect prices in the Caribbean. More specifically, most attributes have a positive effect on price-setting. Larger accommodations charge higher prices. Hosts with superior reputations charge higher prices. However, listings with a larger number of ratings are associated with lower prices. This may be an artefact of tourists’ preferences for cheaper sharing accommodations, resulting in a relatively higher volume of reviews for properties at the lower end of the price spectrum. Provision of Convenience options have an overall positive effect on prices, although there is evidence that some options can result in lower prices for tourists. The sole Personal attribute investigated is associated with higher price-setting behaviour. Virtually all amenities examined result in greater prices being charged for the space. Results indicate that geography has significant effects on price-setting behaviour. Listings in countries with greater economic and infrastructural development, greater biodiversity, but weaker exchange rates have higher prices. On the other hand, prices are lower in countries where there is more competition for customers

Engineering of extracellular matrix scaffolds via hollow fiber cell culture

Extracellular matrix (ECM) tissue scaffolds are seeing increased use for clinical applications, as they significantly decrease the time course of healing for injured tissues; however, the use of animal-sourced matrix for these scaffolds introduces xenogeneic epitopes into the patient toward which deleterious immune responses are directed, decreasing the effectiveness of the scaffold. ECM scaffolds produced in vitro have potential to minimize the foreign body response, as ECM can be cultured using human cell lines and decellularized to produce an allogeneic scaffold with high biocompatibility. The primary challenge of producing ECM-based therapeutics in vitro is fabricating such material in a manner which approximates the composition and architecture of native matrix while maintaining high yield and ease-of-handling. In previous work, we have demonstrated that sacrificial open-cell foams can be used for the production of ECM scaffolds with properties approximating those of native tissues.1 Herein we demonstrate a novel approach for the production of continuous threads of extracellular matrix by statically culturing ECM-secreting fibroblasts in the lumina of mesoporous hollow fiber membranes (HFMs). This approach exploits the fact that mesoporous HFMs prevent cross-membrane transport of high molecular weight proteins produced by cells in their lumina, while allowing for diffusion of low molecular weight cell medium components. Please click Additional Files below to see the full abstract

Airborne sampling of aerosol particles: Comparison between surface sampling at Christmas Island and P-3 sampling during PEM-Tropics B

Bulk aerosol sampling of soluble ionic compounds from the NASA Wallops Island P-3 aircraft and a tower on Christmas Island during PEM-Tropics B provides an opportunity to assess the magnitude of particle losses in the University of New Hampshire airborne bulk aerosol sampling system. We find that most aerosol-associated ions decrease strongly with height above the sea surface, making direct comparisons between mixing ratios at 30 m on the tower and the lowest flight level of the P-3 (150 m) open to interpretation. Theoretical considerations suggest that vertical gradients of sea-salt aerosol particles should show exponential decreases with height. Observed gradients of Na+ and Mg2+, combining the tower observations with P-3 samples collected below 1 km, are well described by exponential decreases (r values of 0.88 and 0.87, respectively), though the curve fit underestimates average mixing ratios at the surface by 25%. Cascade impactor samples collected on the tower show that \u3e99% of the Na+ and Mg2+mass is on supermicron particles, 65% is in the 1–6 micron range, and just 20% resides on particles with diameters larger than 9 microns. These results indicate that our airborne aerosol sampling probes must be passing particles up to at least 6 microns with high efficiency. We also observed that nss SO42− and NH4+, which are dominantly on accumulation mode particles, tended to decrease between 150 and 1000 m, but they were often considerably higher at the lowest P-3 sampling altitudes than at the tower. This finding is presently not well understood

Modelling scour around submerged objects with TELEMAC3D - GAIA

Hydrodynamic

Contrast response function estimation with nonparametric Bayesian active learning

Multidimensional psychometric functions can typically be estimated nonparametrically for greater accuracy or parametrically for greater efficiency. By recasting the estimation problem from regression to classification, however, powerful machine learning tools can be leveraged to provide an adjustable balance between accuracy and efficiency. Contrast sensitivity functions (CSFs) are behaviorally estimated curves that provide insight into both peripheral and central visual function. Because estimation can be impractically long, current clinical workflows must make compromises such as limited sampling across spatial frequency or strong assumptions on CSF shape. This article describes the development of the machine learning contrast response function (MLCRF) estimator, which quantifies the expected probability of success in performing a contrast detection or discrimination task. A machine learning CSF can then be derived from the MLCRF. Using simulated eyes created from canonical CSF curves and actual human contrast response data, the accuracy and efficiency of the machine learning contrast sensitivity function (MLCSF) was evaluated to determine its potential utility for research and clinical applications. With stimuli selected randomly, the MLCSF estimator converged slowly toward ground truth. With optimal stimulus selection via Bayesian active learning, convergence was nearly an order of magnitude faster, requiring only tens of stimuli to achieve reasonable estimates. Inclusion of an informative prior provided no consistent advantage to the estimator as configured. MLCSF achieved efficiencies on par with quickCSF, a conventional parametric estimator, but with systematically higher accuracy. Because MLCSF design allows accuracy to be traded off against efficiency, it should be explored further to uncover its full potential