The federal photovoltaics commercialization program

The dissertation presents a political and economic history of the federal government's program to commercialize photovoltaic energy for terrestrial use. Chapter 1 is a detailed history of the program. Chapter 2 is a brief review of the Congressional roll call voting literature. Chapter 3 develops PV benefit measures at the state and Congressional district level necessary for an econometric analysis of PV roll call voting. Chapter 4 presents the econometric analysis.

Because PV power was considerably more expensive than conventional power, the program was designed to make PV a significant power source in the long term, emphasizing research and development, although sizeable amounts have been spent for procurement (direct government purchases and indirectly through tax credits). The decentralized R and D program pursued alternative approaches in parallel, with subsequent funding dependent on earlier progress. Funding rose rapidly in the 1970s before shrinking in the 1980s. Tax credits were introduced in 1978, with the last of the credits due to expire this year.

Major issues in the program have been the appropriate magnitude of demonstrations and government procurement, whether decentralized, residential use or centralized utility generation would first be economic, the role of storage in PV, and the role of PV in a utility's generation mix.

Roll call voting on solar energy (all votes analyzed occurred from 1975-1980) was influenced in a cross-sectional sense by all the influences predicted: party and ideology, local economic benefits of the technology, local PV federal spending and manufacturing, and appropriations committee membership. The cross-sectional results for ideology are consistent with the strongly ideological character of solar energy politics and the timing of funding increases and decreases discussed in Chapter 1. Local PV spending and manufacturing was less significant than ideology or the economic benefits of the technology. Because time series analysis of the votes was not possible, it is not possible to test the role of economic benefits to the nation as a whole.

Protein structure refinement algorithms

Protein structure prediction has remained a major challenge in structural biology for more than half a century. Accelerated and cost efficient sequencing technologies have allowed researchers to sequence new organisms and discover new protein sequences. Novel protein structure prediction technologies will allow researchers to study the structure of proteins and to determine their roles in the underlying biology processes and develop novel therapeutics.

Difficulty of the problem stems from two folds: (a) describing the energy landscape that corresponds to the protein structure, commonly referred to as force field problem; and (b) sampling of the energy landscape, trying to find the lowest energy configuration that is hypothesized to be the native state of the structure in solution. The two problems are interweaved and they have to be solved simultaneously. This thesis is composed of three major contributions. In the first chapter we describe a novel high-resolution protein structure refinement algorithm called GRID. In the second chapter we present REMCGRID, an algorithm for generation of low energy decoy sets. In the third chapter, we present a machine learning approach to ranking decoys by incorporating coarse-grain features of protein structures.

I. The crystal structure of a new dimer of triphenylfluorocyclobutadiene. II. A low temperature refinement of the cyanuric triazide structure

I. THE CRYSTAL STRUCTURE OF A NEW DIMER OF TRIPHENYLFLUOROCYCLOBUTADIENE

The crystal structure of thermal isomer of the “head-to-head” dimer of triphenylfluorocyclobutadiene was determined by the direct method. The Σ₂ relationship involving the low angle reflections with the largest E’s were found and solved for the signs by the symbolic method of Zachariasen. The structure was seen in the electron density map and the E-map, and was refined antisotropically by the method of least squares. The residual R was 0.065.

The structure is a gem-difluorohexaphenyldihydropentalene. All of the phenyl groups are planar as it is the cyclopentadiene ring of the dihydropentalene skeleton. Overcrowding at the position of the flourines causes some deviations from the normal bond angles in the cyclopentene ring.

The list of observed and calculated structure factors on pages 32-34 will not be legible on the microfilm. Photographic copies may be obtained from the California Institute of Technology.

II. A LOW TEMPERATURE REFINEMENT OF THE CYANURIC TRIAZIDE STRUCTURE

The structure of cyanuric triazide was refined anisotropically by the method of least squares. Three-dimensional intensity data, which has been collected photographically with MoK_α radiation at -110˚C, were used in the refinement. The residual R was reduced to 0.081.

The structure is completely planar, and there is no significant bond alternation in the cyanuric ring. The packing of the molecules causes the azide groups to deviate from linearity by 8 degrees.

Probability in Quantum Mechanics: The Everett Interpretation and the Decision-Theoretic Program

The Everett interpretation of quantum mechanics is an increasingly popular alternative to the traditional Copenhagen interpretation, but there are a few major issues that prevent the widespread adoption. One of these issues is the origin of probabilities in the Everett interpretation, which this thesis will attempt to survey. The most successful resolution of the probability problem thus far is the decision-theoretic program, which attempts to frame probabilities as outcomes of rational decision making. This marks a departure from orthodox interpretations of probabilities in the physical sciences, where probabilities are thought to be objective, stemming from symmetry considerations. This thesis will attempt to offer evaluations on the decision-theoretic program.