New Releases by Jordan Crawford

Infrastructure compatible hydrocarbon biofuel that is proposed to qualify as renewable transportation fuel under the U.S. Energy Independence and Security Act of 2007 (EISA) and Renewable Fuel Standard (RFS2) is evaluated. The process uses hybrid poplar for feedstock, which undergoes dilute acid pretreatment and enzymatic hydrolysis. Sugars are fermented to acetic acid, which undergoes conversion to ethyl acetate, ethanol, ethylene, and finally a saturated hydrocarbon end product with yields of 330 liters of jet fuel per bone dry tonne feed. A lignin rich stream that is not fermented may either be burned for steam and electricity production, or gasified. During the biofuel production process, hydrogen gas is required in two unit operations and may be obtained by various methods including lignin gasification. Both technical and economic aspects of the biorefinery are analyzed, with a range of hydrogen sources considered. These include steam reforming of natural gas, gasification of lignin, and electrolysis of water using seasonal excess hydroelectric capacity in the U.S. Pacific Northwest. Cash operating costs are estimated to range from 0.67 to 0.89 USD per liter of jet fuel depending on facility capacity. Capacities of 95 to 570 million liters (25 to 150 million gallons) of polymer jet fuel per year are investigated, with capital investments in the range of 304 to 1,150 million USD. The production of alternative, intermediate products to jet fuel is briefly explored.

One important aim of synthetic biology is to develop a self-replicating biological system capable of performing useful tasks. A mathematical model of a synthetic organism would greatly enhance its value by providing a platform in which proposed modifications to the system could be rapidly prototyped and tested. Such a platform would allow the explicit connection of genomic sequence information to physiological predictions. As an initial step toward this aim, a Minimal Cell Model (MCM) has been formulated. The MCM is defined as a model of a hypothetical cell with the minimum number of genes necessary to grow and divide in an optimally supportive culture environment. It is chemically detailed in terms of genes and gene products, as well as physiologically complete in terms of bacterial cell processes like DNA replication and cell division. A mathematical framework originally developed for modeling Escherichia coli has been used to build the platform MCM. To lay the foundation for designing an MCM, sensitivity analysis and event detection methods applicable to the E. coli model are presented. An updated version of the E. coli model that links detailed genomic information about the location of dnaA genes and DnaA binding sites on the chromosome to physiological predictions has been developed. The model suggests that the concentration of DnaA binding boxes on the chromosome is critical to determining cell growth and behavior. This update is the first example of including detailed genomic information in a hybrid bacterial cell model, which was an important step toward the massive inclusion of new genes in the MCM. An MCM with 241 product-coding genes (those which produce protein or stable RNA products) is presented. This set is genomically complete and codes for all the functions that a minimal chemoheterotrophic bacterium would require for sustained growth and division. It is shown for the first time that it is possible to test the hypotheses behind a minimal gene set using a chemically detailed, dynamic, whole-cell modeling approach. It has been demonstrated that it is possible to simulate a whole-cell whose behavior depends on its (i) metabolic rates and chemical state, (ii) genome in terms of expression of various genes, (iii) environment both in terms of direct nutrient starvation and competitive inhibition leading to starvation, and (iv) genomic sequence in terms of the locations of genes on the chromosome. All of these behaviors are exhibited by a single-cell model that makes reasonable assumptions about cellular biochemistry, reaction rates, gene expression, and the effect of discrete physiological events on the cell''s behavior.

This thesis tracks the relationship between voter positions on ideological issues and voter partisanship in presidential elections from 1976 to 2004 using data from the ANES. Based on Stimson''s (1975) work, the electorate was divided into quartiles, representing a continuum of political engagement. On one end are those voters that are not paying attention to politics, that do not organize their beliefs along the abstract liberal-conservative dimension, and that are not highly educated. On the other end are those voters that are paying attention to politics, that organize their beliefs along the liberal-conservative dimension, and that are highly educated. I present evidence demonstrating the most politically engaged twenty-five percent of the population are consistently connecting their partisanship and issue positions at higher rates from 1976 to 2004, representing a trend that does not seem to be stalled by any single election. The least politically engaged twenty-five percent of the electorate are not making any absolute or election specific strides in connecting their partisanship and issue positions. The middle fifty percent of the electorate have fluctuated in connecting their issues positions and their partisanship depending on the election. Only the top twenty-five percent of the electorate have made large strides in organizing their political beliefs since 1976, leaving the rest of the electorate lagging far behind.