Preprocessing Solar Images while Preserving their Latent Structure

Telescopes such as the Atmospheric Imaging Assembly aboard the Solar Dynamics Observatory, a NASA satellite, collect massive streams of high resolution images of the Sun through multiple wavelength filters. Reconstructing pixel-by-pixel thermal properties based on these images can be framed as an ill-posed inverse problem with Poisson noise, but this reconstruction is computationally expensive and there is disagreement among researchers about what regularization or prior assumptions are most appropriate. This article presents an image segmentation framework for preprocessing such images in order to reduce the data volume while preserving as much thermal information as possible for later downstream analyses. The resulting segmented images reflect thermal properties but do not depend on solving the ill-posed inverse problem. This allows users to avoid the Poisson inverse problem altogether or to tackle it on each of $\sim$10 segments rather than on each of $\sim$10$^7$ pixels, reducing computing time by a factor of $\sim$10$^6$. We employ a parametric class of dissimilarities that can be expressed as cosine dissimilarity functions or Hellinger distances between nonlinearly transformed vectors of multi-passband observations in each pixel. We develop a decision theoretic framework for choosing the dissimilarity that minimizes the expected loss that arises when estimating identifiable thermal properties based on segmented images rather than on a pixel-by-pixel basis. We also examine the efficacy of different dissimilarities for recovering clusters in the underlying thermal properties. The expected losses are computed under scientifically motivated prior distributions. Two simulation studies guide our choices of dissimilarity function. We illustrate our method by segmenting images of a coronal hole observed on 26 February 2015

Herd on the Street: Informational Inefficiencies in a Market with Short-Term Speculation

Standard models of informed speculation suggest that traders try to learn information that others do not have. This result implicitly relies on the assumption that speculators have long horizons, i.e, can hold the asset forever. By contrast, we show that if speculators have short horizons, they may herd on the same information, trying to learn what other informed traders also know. There can be multiple herding equilibria, and herding speculators may even choose to study information that is completely unrelated to fundamentals. These equilibria are informationally inefficient.

LDC Debt: Forgiveness, Indexation, and Investment Incentives

We compare different indexation schemes in terms of their ability to facilitate forgiveness and reduce the investment disincentives associated with the large LDC debt overhang. Indexing to an endogenous variable (e.g., a country's output) has a negative moral hazard effect on investment, This problem does not arise when payments are linked to an exogenous variable such as commodity prices. Nonetheless, indexing payments to output may be useful when debtors know more about their willingness to invest than lenders. We also reach new conclusions about the desirability of default penalties under asymmetric information.

Detecting Unspecified Structure in Low-Count Images

Unexpected structure in images of astronomical sources often presents itself upon visual inspection of the image, but such apparent structure may either correspond to true features in the source or be due to noise in the data. This paper presents a method for testing whether inferred structure in an image with Poisson noise represents a significant departure from a baseline (null) model of the image. To infer image structure, we conduct a Bayesian analysis of a full model that uses a multiscale component to allow flexible departures from the posited null model. As a test statistic, we use a tail probability of the posterior distribution under the full model. This choice of test statistic allows us to estimate a computationally efficient upper bound on a p-value that enables us to draw strong conclusions even when there are limited computational resources that can be devoted to simulations under the null model. We demonstrate the statistical performance of our method on simulated images. Applying our method to an X-ray image of the quasar 0730+257, we find significant evidence against the null model of a single point source and uniform background, lending support to the claim of an X-ray jet

Selective Predation by Three Esocids: The Role of Prey Behavior and Morphology

We documented differential vulnerability of fathead minnows Pimephales promelas, gizzard shad Dorosoma cepedianum. and bluegills Lepomis macrochirus to predation by muskellunge Esox masquinongy. northern pike E. lucius. and tiger muskellunge E. masquinongy x E. lucius in a 700-L tank. Individual esocids (150-225 mm in total length) were combined with single species groups (N = 15) of optimal-sized prey (25-30% of predator length for bluegills, 37-43% for fathead minnows, and 30-36% for gizzard shad). Capture ability did not differ among esocids; however, mean captures per strike were higher for fathead minnow (0.67) and gizzard shad (0.78) than for bluegill (0.14). Morphology and antipredatory behavior, unique to each prey species, contributed to this differential vulnerability. In the field, we introduced equal numbers and similar sizes of these esocids into two systems, one with centrarchid prey and one with both centrarchid and gizzard shad prey. As predicted from laboratory work, esocids ate fewer prey and grew more slowly when centrarchids were the only prey than they did when gizzard were available. In a third reservoir, containing bluegills and gizzard shad, esocids strongly preferred gizzard shad over bluegills. To maximize growth and survival, esocids should be stocked in systems with soft-rayed or fusiform prey, such as cyprinids or shad, rather than in centrarchid-dominated systems.This study was supported in part by funds from the Federal Aid in Fish Restoration Act under project F-57-R

The Effects of Compost and Polyacrylamide Hydrogel on the Re-Vegetation of Eroded Southern Aspects in the Western Rangeland

MPG Ranch is a conservation-oriented organization in Montana’s Bitterroot valley. Since 2010, MPG has annually planted between 5,000 and 10,000 shrubs and trees with the goal of restoring native plant communities, beautifying the landscape, and providing habitat and forage for wildlife. Plant survival has been lowest on degraded south facing slopes, likely due to a combination of erosion and high solar radiation, which have left the soil with low nutrient content, soil moisture, and high soil temperatures. To resolve these issues, we partnered with MPG to test whether soil amendments can be used to increase plant establishment on degraded hillslopes. Soil amendments included a polyacrylamide hydrogel (Terra-sorb), compost, and Terra-sorb and compost combined. These amendments were tested on three different native shrub species: Cercocarpus ledifolius (curl leaf mountain mahogany), Juniperus scopulorum (Rocky Mountain juniper), and Purshia tridentata (antelope bitterbrush). We assessed the impact of these three soil amendments on plant growth, plant health/mortality rates, and soil chemical and physical properties. Overall results revealed few consistent patterns. Compost as a treatment resulted in the lowest levels of plant mortality whereas plants in the control plots suffered the highest. Plant growth was more dependent on the species in question rather than the amendment used. Mountain mahogany was the most successful in terms of growth both above and below ground with all living plants growing 0 – 1% throughout the course of the season. Our recommendation to MPG is that they continue to monitor these plants for multiple growing seasons in order to determine if they are more or less effective in the long run than what our experiment showed for short-term results