Food Habits of Deer in the Black Hills

This study was conducted in two parts for Master of Science theses by the senior authors of Parts I and II. The study in the Northem Black Hills (Part I) was completed in 1968. Principal and preferred foods were determined for the winter and summer and a pasture study was conducted to measure production and utilization of foods in a typical aspen stand during the summer months. The study in the Southern Black Hills (Part II) was made in 1968 and 1969. Objectives were to determine the principal plants used by mule and white-tailed deer in fall, winter and summer. The utility of the point-analysis technique for measuring rumen contents was evaluated and the technique was applied to rumen contents examined. The studies were supported by the South Dakota Department of Game, Fish and Parks under Federal Aid Project W-75-R through the South Dakota Cooperative Wildlife Research Unit (South Dakota State University, the Bureau of Sport Fisheries and Wildlife, the South Dakota Department of Game, Fish and Parks and the Wildlife Management Institute, cooperating). Special acknowledgement is extended to the personnel of the Wildlife Habitat Project, Rocky Mountain Forest and Range Experiment Station Rapid City, for their assistance in both studies. Dr. Donald Dietz, Project Leader, and Harold E. Messner, Range Technician, were particularly helpful in the development of techniques for analysis of rumen content and the equipment used for the point-analysis method described in Part II. The assistance of William Hepworth, Director of Technical Research, Wyoming Game and Fish Department, in securing the two deer used in the pasture study described in Part I is gratefully acknowledged

Wavelet multiscale analysis for hedge funds: scaling and strategies

The wide acceptance of Hedge Funds by Institutional Investors and Pension Funds has led to an explosive growth in assets under management. These investors are drawn to Hedge Funds due to the seemingly low correlation with traditional investments and the attractive returns. The correlations and market risk (the Beta in the Capital Asset Pricing Model) of Hedge Funds are generally calculated using monthly returns data, which may produce misleading results as Hedge Funds often hold illiquid exchange-traded securities or difficult to price over-the- counter securities. In this paper, the Maximum Overlap Discrete Wavelet Transform (MODWT) is applied to measure the scaling properties of Hedge Fund correlation and market risk with respect to the S&P 500. It is found that the level of correlation and market risk varies greatly according to the strategy studied and the time scale examined. Finally, the effects of scaling properties on the risk profile of a portfolio made up of Hedge Funds is studied using correlation matrices calculated over different time horizons

Study of statistical correlations in intraday and daily financial return time series

The aim of this article is to briefly review and make new studies of correlations and co-movements of stocks, so as to understand the "seasonalities" and market evolution. Using the intraday data of the CAC40, we begin by reasserting the findings of Allez and Bouchaud [New J. Phys. 13, 025010 (2011)]: the average correlation between stocks increases throughout the day. We then use multidimensional scaling (MDS) in generating maps and visualizing the dynamic evolution of the stock market during the day. We do not find any marked difference in the structure of the market during a day. Another aim is to use daily data for MDS studies, and visualize or detect specific sectors in a market and periods of crisis. We suggest that this type of visualization may be used in identifying potential pairs of stocks for "pairs trade".Comment: 22 pages, 11 figures, Springer-Verlag format. To appear in the conference proceedings of Econophys-Kolkata VI: "Econophysics of systemic risk and network dynamics", Eds. F. Abergel, B.K. Chakrabarti, A. Chakraborti and A. Ghosh, to be published by Springer-Verlag (Italia), Milan (2012

Seronegative Herpes simplex Associated Esophagogastric Ulcer after Liver Transplantation

Herpes simplex infection is characterized by acute or subacute infection, often followed by a chronic carrier state. Consecutive recurrences may flare up if immunocompromise occurs. Herpes simplex associated esophagitis or duodenal ulcer have been reported in immunocompromised patients due to neoplasm, HIV/AIDS or therapeutically induced immune deficiency. Here we report the case of an HSV-DNA seronegative patient who developed grade III dysphagia 13 days after allogeneic liver transplantation. Endoscopy revealed an esophageal-gastric ulcer, and biopsy histopathology showed a distinct fibroplastic and capillary ulcer pattern highly suspicious for viral infection. Immunohistochemistry staining revealed a distinct nuclear positive anti-HSV reaction. Antiviral therapy with acyclovir and high-dose PPI led to a complete revision of clinical symptoms within 48 h. Repeat control endoscopy after 7 days showed complete healing of the former ulcer site at the gastroesophageal junction. Although the incidence of post-transplantation Herpes simplex induced gastroesophageal disease is low, the viral HSV ulcer may be included into a differential diagnosis if dysphagia occurs after transplantation even if HSV-DNA PCR is negative

Deriving utility scores for co-morbid conditions: a test of the multiplicative model for combining individual condition scores

BACKGROUND: The co-morbidity of health conditions is becoming a significant health issue, particularly as populations age, and presents important methodological challenges for population health research. For example, the calculation of summary measures of population health (SMPH) can be compromised if co-morbidity is not taken into account. One popular co-morbidity adjustment used in SMPH computations relies on a straightforward multiplicative combination of the severity weights for the individual conditions involved. While the convenience and simplicity of the multiplicative model are attractive, its appropriateness has yet to be formally tested. The primary objective of the current study was therefore to examine the empirical evidence in support of this approach. METHODS: The present study drew on information on the prevalence of chronic conditions and a utility-based measure of health-related quality of life (HRQoL), namely the Health Utilities Index Mark 3 (HUI3), available from Cycle 1.1 of the Canadian Community Health Survey (CCHS; 2000–01). Average HUI3 scores were computed for both single and co-morbid conditions, and were also purified by statistically removing the loss of functional health due to health problems other than the chronic conditions reported. The co-morbidity rule was specified as a multiplicative combination of the purified average observed HUI3 utility scores for the individual conditions involved, with the addition of a synergy coefficient s for capturing any interaction between the conditions not explained by the product of their utilities. The fit of the model to the purified average observed utilities for the co-morbid conditions was optimized using ordinary least squares regression to estimate s. Replicability of the results was assessed by applying the method to triple co-morbidities from the CCHS cycle 1.1 database, as well as to double and triple co-morbidities from cycle 2.1 of the CCHS (2003–04). RESULTS: Model fit was optimized at s = .99 (i.e., essentially a straightforward multiplicative model). These results were closely replicated with triple co-morbidities reported on CCHS 2000–01, as well as with double and triple co-morbidities reported on CCHS 2003–04. CONCLUSION: The findings support the simple multiplicative model for computing utilities for co-morbid conditions from the utilities for the individual conditions involved. Future work using a wider variety of conditions and data sources could serve to further evaluate and refine the approach

Model Cortical Association Fields Account for the Time Course and Dependence on Target Complexity of Human Contour Perception

Can lateral connectivity in the primary visual cortex account for the time dependence and intrinsic task difficulty of human contour detection? To answer this question, we created a synthetic image set that prevents sole reliance on either low-level visual features or high-level context for the detection of target objects. Rendered images consist of smoothly varying, globally aligned contour fragments (amoebas) distributed among groups of randomly rotated fragments (clutter). The time course and accuracy of amoeba detection by humans was measured using a two-alternative forced choice protocol with self-reported confidence and variable image presentation time (20-200 ms), followed by an image mask optimized so as to interrupt visual processing. Measured psychometric functions were well fit by sigmoidal functions with exponential time constants of 30-91 ms, depending on amoeba complexity. Key aspects of the psychophysical experiments were accounted for by a computational network model, in which simulated responses across retinotopic arrays of orientation-selective elements were modulated by cortical association fields, represented as multiplicative kernels computed from the differences in pairwise edge statistics between target and distractor images. Comparing the experimental and the computational results suggests that each iteration of the lateral interactions takes at least ms of cortical processing time. Our results provide evidence that cortical association fields between orientation selective elements in early visual areas can account for important temporal and task-dependent aspects of the psychometric curves characterizing human contour perception, with the remaining discrepancies postulated to arise from the influence of higher cortical areas