On Estimating Marginal Tax Rates and Tax Progressivities for U.S. States

This research presents a simple procedure for improving state-specific estimates of marginal tax rates (MTR’s). Most research employing MTR’s follows a procedure developed by Koester and Kormendi (K&K, 1987). Unfortunately, the time-invariant nature of the K&K estimates precludes their use as explanatory variables in panel data studies. Furthermore, their estimates are not based on statutory tax parameters. In contrast, our procedure produces timevarying estimates of MTR’s that are directly related to observed changes in statutory tax parameters. Using comprehensive data on state tax policy parameters, our procedure produces state-specific MTR’s estimates for all 50 states over the years 1977-2004. We compare our refined MTR’s to alternative estimates and evaluate implications for estimating tax progressivity for US states.State tax revenues; Marginal tax rates; Tax burden; Tax progressivity; Economic growth.

Computer Analysis and Description of Pottery Sherd Patterns

This thesis describes an automated system for the analysis and description of patterns composed of straight line elements. It represents the second stage in the development of a system intended to aid archaeologists in tracing the evolution of decorative patterns found on pottery sherds. The samples provided by the Anthropology Department for this project are pottery rims excavated from sites at Penitas, Nayarit, Mexico. The input data are digitized pictures of photographs of the samples. The first phase of the system is image processing. A set of low level operators is employed to obtain as final output a pictorial and vector description of all line segments in the pattern. The second phase constructs a series of descriptions of the pattern, in which the successive steps reflect increasing levels of complexity in the interrelationships of the pattern elements. It first finds parallel and connected relationships between pairs of lines. The pairs are examined to obtain groups of equally-spaced parallel lines, and groups of lines connected at mutual endpoints, The groups are analyzed to yield the independent patterns which compose the picture, and the patterns are named in their left-to-right order

Proximal Factors Predicting Student Performance in a Self-Paced College Psychology Course

This study examined the effectiveness of using selected self-report measures assessing motivational orientation, learning strategies, procrastination, and perceptions of daily hassles to facilitate the prediction of student engagement in a self-paced introductory psychology course. Research has shown these factors to be associated with academic success, and of concern to instructors and students alike. Surveys that economically and effectively assess these factors would be invaluable for the instructor attempting to predict student engagement and determining possible interventions to promote academic success. Four surveys purporting to measure the constructs were chosen. A demographic survey was also administered

Using Alexa for flashcard-based learning

Despite increasing awareness of Alexa’s potential as an educational tool, there remains a limited scope for Alexa skills to accommodate the features required for effective language learning. This paper describes an investigation into implementing ‘spaced-repetition’, a non-trivial feature of flashcard-based learning, through the development of an Alexa skill called ‘Japanese Flashcards’. Here we show that existing Alexa development features such as skill persistence allow for the effective implementation of spaced-repetition and suggest a heuristic adaptation of the spaced-repetition model that is appropriate for use with voice assistants (VAs). We also highlight areas of the Alexa development process that limit the facilitation of language learning, namely the lack of multilingual speech recognition, and offer solutions to these current limitations. Overall, the investigation shows that Alexa can successfully facilitate simple L2-L1 flashcard-based language learning and highlights the potential for Alexa to be used as a sophisticated and effective language learning tool

Environmental factors influencing the spread of the highly pathogenic avian influenza H5N1 virus in wild birds in Europe

A large number of occurrences of the highly pathogenic avian influenza (HPAI) H5N1 virus in wild birds were reported in Europe. The relationship between the occurrence pattern and environmental factors has, however, not yet been explored. This research uses logistic regression to quantify the relationships between anthropogenic or physical environmental factors and HPAI H5N1 occurrences. Our results indicate that HPAI H5N1 occurrences are highly correlated with the following: the increased normalized difference vegetation index (NDVI) in December; intermediate NDVI in March; lower elevations; increased minimum temperatures in January; and reduced precipitation in January. A predictive risk map of HPAI H5N1 occurrences in wild birds in Europe was generated on the basis of five key environmental factors. Independent validation of the risk map showed the predictive model to be of high accuracy (79%). The analysis suggests that HPAI H5N1 occurrences in wild birds are strongly influenced by the availability of food resources and are facilitated by increased temperatures and reduced precipitation. We therefore deduced that HPAI H5N1 occurrences in wild birds in Europe are probably caused by contact with other wild birds and not by contact with domestic poultry. These findings are important considerations for the global surveillance of HPAI H5N1 occurrences in wild birds

The preparation of laboratory specimens as an aid to the diagnosis of animal diseases

Many problems in connection with animal diseases require for their solution the application of methods which can only be undertaken in properly equipped laboratories. This ordinarily involves the collection, packing, and shipping of samples of specimens. The manner in which this is done is a most important factor and to a very large extent is responsible either for the success or for the failure of the undertaking. The discussion of the subject to which the following pages are devoted is taken in hand in the hope that it may provide guidance to the veterinarians and others who may have occasion to require the assistance of a laboratory in the solution of disease problems

A Field test of the Wind Erosion Prediction System

Field data need to be collected to test wind erosion models under a broad range of climate, soil, and management conditions. The objective of this study was to test the USDA- ARS Wind Erosion Prediction System (WEPS) for a field with winter wheat plants in a modest amount of flat residue. A 600 m by 415 m field was selected near Burlington, CO, USA. Big Spring Number Eight (BSNE) samplers were used to measure wind blown sediment flux and automated devices (Sensits) for continuous detection of saltation. A weather station recorded relevant meteorological data. Detailed measurements of the field surface were taken on three dates. The experiment was conducted from 25 November, 2000 through 12 April, 2001. One dust storm occurred during this experimental period, with a net field sediment loss of 0.06 kg/m2. Spatial variability of sediment discharge was high and could be explained by spatial differences in field conditions. WEPS overestimated the protective power of small wheat plants. It needs a provision to account for standing biomass that is not uniformly spaced, such as wheat plants in the field. Wind erosion (and WEPS) is very sensitive to soil surface water content, which is difficult to measure. Albedo is a good indicator of soil wetness right at the soil surface, but additional research is needed to use albedo for quantifying soil surface water content