Taxes, Fringe Benefits and Faculty

The growth of employee benefits in academe has closely paralleled their economy-wide growth. This study estimates a complete system describing the demand for benefits and wages using panel data on nearly 1500 institutions of higher learning. The demand for benefits is quite responsive both to changes in real income and to variations in the tax price of benefits. These conclusions are robust with respect to varying definitions of the sample aid of the tax price. They are not altered by estimates that account for unmeasured individual effects on demand. Simulations using the estimates suggest that the Tax Reform Act of 1986 sharply reduced the demand for benefits. Extrapolating the impact to the entire economy suggests that the annual flow of compensation shifted away from benefits by at least $9 billion.

Synthesis and Hardware Implementation of an Unmanned Aerial Vehicle Automatic Landing System Utilizing Quantitative Feedback Theory

Approach and landing are among the most difficult flight regimes for automatic control of fixed-wing aircraft. Additional challenges are introduced when working with unmanned aerial vehicles, such as modelling uncertainty and limited gust tolerance. This thesis develops linear discrete-time automatic landing controllers using Quantitative Feedback Theory to ensure control robustness and adequate disturbance rejection. Controllers are developed in simulation and evaluated in flight tests of the low cost Easy Star remote-controlled platform. System identification of the larger Pegasus unmanned aerial vehicle is performed to identify dynamic models from flight data. A full set of controllers are subsequently developed and evaluated in simulation for the Pegasus. The extensive simulation and experimental testing with the Easy Star will reduce the time required to implement the Pegasus control laws, and will reduce the associated risk by validating the core experimental software. It is concluded that the control synthesis process using Quantitative Feedback Theory provides robust controllers with generally adequate performance, based on simulation and hardware results. The Quantitative Feedback Theory framework provides a good method for synthesizing the inner-loop controllers and satisfying performance requirements, but in many of the cases considered here it is found to be impractical for the outer loop designs. The primary recommendations of this work are: perform additional verification flights on the Easy Star; repeat Pegasus system identification for a landing configuration before flight testing the control laws; design and implement a rudder control loop on the Pegasus for control of the vehicle after touchdown

THREE ESSAYS ON LOCAL PUBLIC FINANCE

This dissertation seeks to develop the subject of local public finance in a manner consistent with the political economy of local governments. For ease of description, each essay will be discussed briefly. The first essay is titled The Provision of Generalized Local Public Goods Financed by Distortionary Taxation. This essay models the provision of a local public good that is simultaneously utilized as a public consumption good and a public intermediate good. Since the public good can simultaneously enter both utility and production functions, it is considered a generalized public good. This is done to model the provision of infrastructure by sub-federal governments, which is financed with taxes on local residents. A theoretical analysis provides a cost-benefit rule for public good provision by a rent-maximizing local government facing mobile households. Illustrative calculations of the marginal cost of public funds are provided. Calibrated to U.S. data, the role of intergovernmental transfers on the provision of infrastructure by rent-maximizing local governments is analyzed. Theoretical evidence of the higher responsiveness of local governments to matching grants relative to lump-sum grants is provided. The second essay is titled The Impact of Local Households\u27 Housing Tenure on Local Public Debt Levels. This essay investigates the relation between local housing tenure and local public debt. It does this by establishing housing tenure as a theoretical basis for the potential differences in how households view public debt. Homeowners capitalize the burden of local public debt into their home value, while renters do not. A hypothesis is generated that an increase in the renter share of households in a locality leads to higher levels of local public debt, all else equal. Using an instrumental variable approach, the empirical evaluation shows an increase in the proportion of renters leads to higher levels of public debt in a panel data set of U.S. local governments. Specifically, a one percentage point increase in the percent of renters increases unfunded public debt per household by $400, or about 7% of the average local debt level, and 24% of the county with the median debt level. This relationship is robust across multiple specifications. The third essay is titled A Spatial Econometric Analysis of Local Households\u27 Housing Tenure on Local Public Debt Levels: Implications for Federalism. This essay extends the model of the second essay by measuring the spatial spillovers using a spatial autoregressive model with autoregressive disturbances. The existence and magnitude of local government spillovers related to local public debt levels are used to inform policy makers at higher levels of government. The analysis identifies possible geographic segmentation of the municipal bond markets and the role of special district debt as a key component of the spatial distribution of local public debt. Additionally, a positive spatial disturbance is found

Standard environmental testing practices

Manual on procedural requirements for performing certain environmental tests on space flight equipment provides information for test equipment designers, quality control and production engineers. Contents of manual are summarized

APPLICATIONS OF INTENSE MID-INFRARED LASER-PLASMA INTERACTIONS

Intense laser-plasma interaction, generally characterized by focused laser intensities exceeding ~1 TW/cm2, is a major pillar of plasma physics and nonlinear optics with broad applications, including high energy charged particle and photon sources, the generation and study of high energy density physics conditions, fusion energy sources, remote detection techniques, and self-guided nonlinear propagation. For many important applications, longer wavelength lasers provide favorable scaling for laser-plasma interactions, and in several cases enable entirely new phenomena. In this dissertation we present experimental and computational results for three laser-plasma-based applications using ultrashort mid-infrared (mid-IR or MIR) and long-wave-infrared (LWIR) laser pulses. In the first laser wakefield acceleration (LWFA) experiment at mid-IR wavelengths, we demonstrate acceleration of electron bunches driven by relativistic self-focusing collapse of mid-IR laser pulses in near-critical density gas jet targets, and compare scaling of bunch charge and energy to those from common near-infrared systems. Second, we demonstrate that single-electron-seeded avalanche breakdown driven by picosecond mid-IR lasers is an ultrasensitive technique for measuring extremely low plasma densities in gases. We use this technique in two applications. First, we first demonstrate standoff detection of radioactive materials, with avalanche measurements enabling determination of source location and estimates of the radioactivity level. We then use the technique to measure ionization yield induced by an auxiliary laser in atmospheric pressure range gases over 14 orders of magnitude, a record range achievable with no other technique we are aware of. Finally, we present theory and simulations of nonlinear propagation of high power MIR and LWIR multi-picosecond pulses in air, demonstrating that self-guided propagation at moderate intensity is mediated by an ensemble of discrete avalanche plasmas seeded by aerosols

ESTIMATION-BASED SOLUTIONS TO INCOMPLETE INFORMATION PURSUIT-EVASION GAMES

Differential games are a useful tool both for modeling conflict between autonomous systems and for synthesizing robust control solutions. The traditional study of games has assumed decision agents possess complete information about one another’s strategies and numerical weights. This dissertation relaxes this assumption. Instead, uncertainty in the opponent’s strategy is treated as a symptom of the inevitable gap between modeling assumptions and applications. By combining nonlinear estimation approaches with problem domain knowledge, procedures are developed for acting under uncertainty using established methods that are suitable for applications on embedded systems. The dissertation begins by using nonlinear estimation to account for parametric uncertainty in an opponent’s strategy. A solution is proposed for engagements in which both players use this approach simultaneously. This method is demonstrated on a numerical example of an orbital pursuit-evasion game, and the findings motivate additional developments. First, the solutions of the governing Riccati differential equations are approximated, using automatic differentiation to obtain high-degree Taylor series approximations. Second, constrained estimation is introduced to prevent estimator failures in near-singular engagements. Numerical conditions for nonsingularity are approximated using Chebyshev polynomial basis functions, and applied as constraints to a state estimate. Third and finally, multiple model estimation is suggested as a practical solution for time-critical engagements in which the form of the opponent’s strategy is uncertain. Deceptive opponent strategies are identified as a candidate approach to use against an adaptive player, and a procedure for designing such strategies is proposed. The new developments are demonstrated in a missile interception pursuit-evasion game in which the evader selects from a set of candidate strategies with unknown weights

A Comparison of Electromagnetic Induction Mapping to Measurements of Maximum Effluent Flow Depth for Assessing Flow Paths in Vegetative Treatment Areas

Vegetative treatment systems (VTSs) are one type of control structure that has shown potential to control runoff from open feedlots. To achieve maximum performance, sheet-flow over the width of the vegetative treatment area (VTA) is required. Tools, such as maps of flow paths through the VTA, are needed to aid producers in locating concentrated flow paths and in determining the most effective approach to redistribute flow. Members of the USDA-ARS USMARC laboratory have developed remote sensing techniques using Electromagnetic Induction (EMI) to measure spatial nutrient distribution, and identify possible flow paths, within VTAs. The objective of this study was to determine whether apparent soil electrical conductivity maps can be used to locate concentrated flow paths in the VTA. Effluent flow paths in the VTA were determined by measuring the maximum height of flow at different locations within the VTA. In this study, PVC stakes were coated with a water sensitive paint and located throughout the treatment area during effluent release from solid settling basin to the VTA. The maximum depth of flow at each stake was recorded following a release event from the settling basin. The flow maps generated from the data were compared to ECa maps measuring salt build-up in the soil due to basin discharge. The flow paths identified in the EMI maps were generally in agreement with measured water depths in the VTA. Therefore, techniques that use EMI technology can be used by regulators to monitor VTS performance, by design engineers to improve system performance, and by producers to better manage their systems

Electromagnetic Induction Sensor Data to Identify Areas of Manure Accumulation on a Feedlot Surface

A study was initiated to test the validity of using electromagnetic induction (EMI) survey data, a prediction-based sampling strategy, and ordinary linear regression modeling to predict spatially variable feedlot surface manure accumulation. A 30- by 60-m feedlot pen with a central mound was selected for this study. A Dualem-1S EMI meter (Dualem Inc., Milton, ON, Canada) pulled on 2-m spacing was used to collect feedlot surface apparent electrical conductivity (ECa) data. Meter data were combined with global positioning system coordinates at a rate of fi ve readings per second. Two 20-site sampling approaches were used to determine the validity of using EMI data for prediction-based sampling. Soil samples were analyzed for volatile solids (VS), total N (TN), total P (TP), and Cl−. A stratified random sampling (SRS) approach (n = 20) was used as an independent set to test models estimated from the prediction-based (n = 20) response surface sample design (RSSD). Th e RSSD sampling plan demonstrated better design optimality criteria than the SRS approach. Excellent correlations between the EMI data and the ln(Cl−), TN, TP, and VS soil properties suggest that it can be used to map spatially variable manure accumulations. Each model was capable of explaining \u3e90% of the constituent sample variations. Fitted models were used to estimate average manure accumulation and predict spatial variations. The corresponding prediction maps show a pronounced pen design effect on manure accumulation. This technique enables researchers to develop precision practices to mitigate environmental contamination from beef feedlots