Structural characterization of water-soluble atmospheric organic matter by ultrahigh-resolution mass spectrometry

Isolated water-soluble analytes extracted from fog water collected during a radiation fog event near Fresno, CA were analyzed using collision induced dissociation and ultrahigh-resolution mass spectrometry. Tandem mass analysis was performed on scan ranges between 100-400 u to characterize the structures of nitrogen and/or sulfur containing species. CHNO, CHOS, and CHNOS compounds were targeted specifically because of the high number of oxygen atoms contained in their molecular formulas. The presence of 22 neutral losses corresponding to fragment ions was evaluated for each of the 1308 precursors. Priority neutral losses represent specific polar functional groups (H2O, CO2, CH3OH, HNO3, SO3, etc., and several combinations of these). Additional neutral losses represent non-specific functional groups (CO, CH2O, C3H8, etc.) Five distinct monoterpene derived organonitrates, organosulfates, and nitroxy-organosulfates were observed in this study, including C10H16O7S, C10H17NO7S, C10H17 NO8S, C10H17NO9S, and C10H17NO10S. Nitrophenols and linear alkyl benzene sulfonates were present in high abundance. Liquid chromatography/mass spectrometery methodology was developed to isolate and quantify nitrophenols based on their fragmentation behavior.

Future value based single assignment program representations and optimizations

An optimizing compiler internal representation fundamentally affects the clarity, efficiency and feasibility of optimization algorithms employed by the compiler. Static Single Assignment (SSA) as a state-of-the-art program representation has great advantages though still can be improved. This dissertation explores the domain of single assignment beyond SSA, and presents two novel program representations: Future Gated Single Assignment (FGSA) and Recursive Future Predicated Form (RFPF). Both FGSA and RFPF embed control flow and data flow information, enabling efficient traversal program information and thus leading to better and simpler optimizations. We introduce future value concept, the designing base of both FGSA and RFPF, which permits a consumer instruction to be encountered before the producer of its source operand(s) in a control flow setting. We show that FGSA is efficiently computable by using a series T1/T2/TR transformation, yielding an expected linear time algorithm for combining together the construction of the pruned single assignment form and live analysis for both reducible and irreducible graphs. As a result, the approach results in an average reduction of 7.7%, with a maximum of 67% in the number of gating functions compared to the pruned SSA form on the SPEC2000 benchmark suite. We present a solid and near optimal framework to perform inverse transformation from single assignment programs. We demonstrate the importance of unrestricted code motion and present RFPF. We develop algorithms which enable instruction movement in acyclic, as well as cyclic regions, and show the ease to perform optimizations such as Partial Redundancy Elimination on RFPF.