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An alkylphosphinate is an attractive isostere for a carboxylate. The acid is more acidic than a carboxylic acid, is amenable to (^31)P NMR analysis and is subject to easy structural modification by variation of the phosphorus alkyl or aryl substituent. Amino acid complexing agents incorporating carboxymethyl groups are ubiquitous, but the corresponding phosphinic acid analogues have been much less studied. On chelation of a metal ion to a ligand nitrogen and a phosphorus oxygen atom, a new stereogenic centre at phosphorus is created. In polydentate ligands diastereoisomeric complexes may form. A new family of acyclic ligands with phosphinic acid binding groups have been synthesised. The protonation constants have been determined and used for the determination of the stability constants for a range of metal complexes. A complexing agent based on a 9N(_3) macrocyclic skeleton incorporating pendant arm phosphinic acid donors, provides an octahedral site for metal complexation. The structures of seven complexes with a ligand of this type, have been determined by X-ray crystallography. They fall into two groups, those with a C(_3) axis (Cu (II), Co (II), Zn (II) and Ni (II)) and those with an approximate C(_3) axis (Ga (III), Fe (III) and In (III)).

This dissertation examines three important issues in energy markets: price dynamics, information flow, and structural change. We discuss each issue in detail, building empirical time series models, analyzing the results, and interpreting the findings. First, we examine the contemporaneous interdependencies and information flows among crude oil, natural gas, and electricity prices in the United States (US) through the multivariate generalized autoregressive conditional heteroscedasticity (MGARCH) model, Directed Acyclic Graph (DAG) for contemporaneous causal structures and Bernanke factorization for price dynamic processes. Test results show that the DAG from residuals of out-of-sample-forecast is consistent with the DAG from residuals of within-sample-fit. The result supports innovation accounting analysis based on DAGs using residuals of out-of-sample-forecast. Second, we look at the effects of the federal fund rate and/or WTI crude oil price shock on US macroeconomic and financial indicators by using a Factor Augmented Vector Autoregression (FAVAR) model and a graphical model without any deductive assumption. The results show that, in contemporaneous time, the federal fund rate shock is exogenous as the identifying assumption in the Vector Autoregression (VAR) framework of the monetary shock transmission mechanism, whereas the WTI crude oil price return is not exogenous. Third, we examine price dynamics and contemporaneous causality among the price returns of WTI crude oil, gasoline, corn, and the S&P 500. We look for structural break points and then build an econometric model to find the consistent sub-periods having stable parameters in a given VAR framework and to explain recent movements and interdependency among returns. We found strong evidence of two structural breaks and contemporaneous causal relationships among the residuals, but also significant differences between contemporaneous causal structures for each sub-period.

Many researchers would be interested in one question: If a change of X is made, will Y be influenced in response? However, while a lot of statistical methods are developed to analyze association between variables, how to find a causal relationship among variables is relatively neglected. The PC algorithm, developed on the basis of Pearl, Sprites, Glymour, and Scheines‟s studies, is used to find the causal pattern of the real-world observed data. However, PC in Tetrad produces a class of directed acyclic graphs (DAGs) that are statistically equivalent under a normal distribution, and therefore such a distributional assumption causes a series of unidentifiable DAGs because of the same joint probability. In 2006 Shimizu, Hoyer, Hyvärinen, and Kerminen developed the Linear Independent Non-Gaussian Model (LiNGAM) to do a causal search based on the independently non-Gaussian distributed disturbances by applying higher-order moment structures. The research objective of this dissertation is to examine whether the LiNGAM is helpful relative to the PC algorithm, to detect the causal relation of non-normal data. The LiNGAM algorithm is implemented by first doing independent component analysis (ICA) estimation and then discovering the correct ordering of variables. Thus, the procedures of ICA estimation and the process of finding the correct causal orderings in LiNGAM are illustrated. Next, we do a causal search on the retail-level scanner data to investigate the pricing interaction between the manufacturer and the retailer by applying these two algorithms. While PC generates the set of indistinguishable DAGs, LiNGAM gives more exact causal patterns. This work demonstrates the algorithm based on the non-normal distribution assumption makes causal associations clearer. In Chapter IV, we apply a classical structural demand model to investigate the consumer purchase behavior in the carbonated soft drink market. Unfortunately, when further restrictions are imposed, we cannot get reasonable results as most researchers require. LiNGAM is applied to prove the existence of endogeneity for the brand‟s retail price and verify that the brand‟s wholesale price is not a proper instrument for its retail price. Therefore, consistent estimates cannot be derived as the theories suggest. These results imply that economic theory is not always found in restriction applied to observational data.

The first part of this work was to synthesise partially fluorinated reactive compounds and then to study their reactivity towards nucleophiles and electrophiles. These reactive compounds were obtained in a two step process from both cyclopentane and adamantane and in a three step process for cyclopentanol. The first step was the free radical addition of the cycloalkanes, cycloalcohol to hexafluoropropene via thermal and/or radiochemical alkylations. For the cyclic alkane derivatives, the second step was a stereospecific dehydrofluorination of the fluorocarbon chain, whereas for the cyclic alcohol, a dehydration and then dehydrofluorination were performed to give the conjugated diene. Finally, the fluoroalkene reactivity was studied via nucleophilic and electrophilic addition reactions. The second part of my work was to study the free radical addition of tertiary amines to hexafluoropropene, an example is illustrated below.

Many parallel programming languages allow programmers to describe parallelism by using constructs such as fork/join. When executed, such programs can be modeled as directed graphs, with nodes representing a computation and edges representing the sequence and dependency. However, because it does not coerce regularity in the computation, the general model is not amenable to efficient execution of the resulting program. Therefore, a more restrictive model called Series-Parallel DAG (Directed Acyclic Graph) has been proposed and adopted by several major parallel languages. As reported by the Cilk developers, many parallel computations can be easily expressed in the series-parallel model, and there are provably efficient scheduling algorithms for the SP DAGs. Nevertheless, it remains open how much inherent parallelism will be lost when conforming to the model, because expressing a computation in the series-parallel model may also induce performance losses. We will show that any general DAG can be converted into an SP DAG without violating the original precedence relations; moreover, the conversion can be carried out in essentially linear time and space, and the resulting DAG exhibits little loss in the parallelism. Since the resulting SP DAG can then be executed with high efficiency, it implies that the languages based on SP DAGs are not as restrictive as they were thought to be. / Singapore-MIT Alliance (SMA)

Given a graph G = (V, E), two players, Alice and Bob, alternate their turns to choose uncolored edges to be colored. Whenever an uncolored edge is chosen, it is colored by the least positive integer so that no monochromatic cycle is created. Alice¡¦s goal is to minimize the total number of colors used in the game, while Bob¡¦s goal is to maximize it. The game Grundy arboricity of G is the number of colors used in the game when both players use optimal strategies. This thesis discusses the game Grundy arboricity of graphs. It is proved that if a graph G has arboricity k, then the game Grundy arboricity of G is at most 3k − 1. If a graph G has an acyclic orientation D with maximum out-degree at most k, then the game Grundy arboricity of G is at most 3k − 2.

We present a methodology for exploiting shared-memory parallelism within matrix computations by expressing linear algebra algorithms as directed acyclic graphs. Our solution involves a separation of concerns that completely hides the exploitation of parallelism from the code that implements the linear algebra algorithms. This approach to the problem is fundamentally different since we also address the issue of programmability instead of strictly focusing on parallelization. Using the separation of concerns, we present a framework for analyzing and developing scheduling algorithms and heuristics for this problem domain. As such, we develop a theory and practice of scheduling concepts for matrix computations in this dissertation. / text

Thesis (M. Sc.)--University of Canterbury, 2006. / Typescript (photocopy). Includes bibliographical references (p. 77-79). Also available via the World Wide Web.

Thesis (M.S.)--Ohio University, November, 2006. / Title from PDF t.p. Includes bibliographical references.