Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry with a matrix of carbon nanotubes for the analysis of low-mass compounds in environmental samples

The use of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) for environmental analysis has been mainly focused on qualitative analysis of high-mass molecules, such as toxins, humic acid, and microorganisms. Herein,we describe a novel MALDI-TOF-MS method with a matrix of oxidized carbon nanotubes for analysis of low-mass compounds in environmental samples. A number of chemicals in the environment were qualitatively analyzed by the present method, and it was found that most of them, especially the highly polar chemicals, were measurable with high sensitivity. With the intrinsic ability to measure high-mass chemicals, this method can compensate for the current shortage of methods for environmental analysis for the measurement of highly polar or high-mass chemicals. For sample analysis, arsenic speciation in Chinese traditional medicines was qualified and diphenylolpropane in water samples was quantified. With the relatively high tolerance of the method to interfering molecules, a simple pretreatment or even no pretreatment could be employed before MS detection. Furthermore, this method can be employed in a high-throughput format.

Typed Abstraction of Complex Network Compositions

The heterogeneity and open nature of network systems make analysis of compositions of components quite challenging, making the design and implementation of robust network services largely inaccessible to the average programmer. We propose the development of a novel type system and practical type spaces which reflect simplified representations of the results and conclusions which can be derived from complex compositional theories in more accessible ways, essentially allowing the system architect or programmer to be exposed only to the inputs and output of compositional analysis without having to be familiar with the ins and outs of its internals. Toward this end we present the TRAFFIC (Typed Representation and Analysis of Flows For Interoperability Checks) framework, a simple flow-composition and typing language with corresponding type system. We then discuss and demonstrate the expressive power of a type space for TRAFFIC derived from the network calculus, allowing us to reason about and infer such properties as data arrival, transit, and loss rates in large composite network applications.

Chemical vapour deposition of complex ferroic oxide thin films

Herein is presented a novel chemical vapour deposition (CVD) route for the fabrication of oxide ferroelectrics. A versatile layer-by-layer growth mode was developed to prepare naturally super-latticed bismuth based materials belonging to the Aurivillius phase family, with which good control over composition and crystal structure was achieved. In chapter 3, the effect of epitaxial strain on one of the very simple oxide materials TiO2 was studied. It has been found that the ultra-thin TiO2 films demonstrate ferroelectric behaviour when grown on NdGaO3 substrates. TiO2 exists in various crystal phases, but none of them show ferroelectric behaviour. The epitaxial strain due to the substrate, changes the crystal structure from tetragonal to orthorhombic which in turn leads to ferroelectric behaviour. In chapter 4, a unique growth method for multiferroic BiFeO3 (BFO) thin films is shown, where a phase pure BFO thin films can be prepared even in the presence of excess bismuth precursor during the growth process. This type of growth is usually called adsorption controlled growth and can be used for growing various bismuth containing compounds, where the volatility of bismuth can create various types of defects. Chapter 5 describes the growth of Bi4Ti3O12 thin films in a layer-by-layer growth mode. In this section, the effect of Bi and Ti precursor flows on the growth of thin films is discussed and it is shown that how change in precursor flows leads to out-ofphase boundary defects during the layer-by-layer growth mode. In chapter 6, the growth of a compound Bi5Ti3FeO15, which is a 1:1 mixture of BiFeO3 and Bi4Ti3O12, is presented. The growth mechanism of Bi5Ti3FeO15 thin films is presented, where the Fe precursor flow was controlled from zero to the insertion of one full BiFeO3 perovskite unit cell into the Bi4Ti3O12 structure in addition, the effect of iron precursor flow on crystalline properties is demonstrated. The methods presented in this thesis can be adopted to grow ferroelectric and multiferroic films for industrial applications.

Evaluating functional network inference using simulations of complex biological systems.

MOTIVATION: Although many network inference algorithms have been presented in the bioinformatics literature, no suitable approach has been formulated for evaluating their effectiveness at recovering models of complex biological systems from limited data. To overcome this limitation, we propose an approach to evaluate network inference algorithms according to their ability to recover a complex functional network from biologically reasonable simulated data. RESULTS: We designed a simulator to generate data representing a complex biological system at multiple levels of organization: behaviour, neural anatomy, brain electrophysiology, and gene expression of songbirds. About 90% of the simulated variables are unregulated by other variables in the system and are included simply as distracters. We sampled the simulated data at intervals as one would sample from a biological system in practice, and then used the sampled data to evaluate the effectiveness of an algorithm we developed for functional network inference. We found that our algorithm is highly effective at recovering the functional network structure of the simulated system-including the irrelevance of unregulated variables-from sampled data alone. To assess the reproducibility of these results, we tested our inference algorithm on 50 separately simulated sets of data and it consistently recovered almost perfectly the complex functional network structure underlying the simulated data. To our knowledge, this is the first approach for evaluating the effectiveness of functional network inference algorithms at recovering models from limited data. Our simulation approach also enables researchers a priori to design experiments and data-collection protocols that are amenable to functional network inference.

Development and application of a high resolution liquid chromatographic method for the analysis of complex pigment distributions

Ternary and binary gradient systems have been developed for the high-performance liquid chromatographic analysis of complex pigment distributions typical of natural samples. Improved chromatographic resolution reveals significantly more pigment components in extracts from a sediment (Priest Pot, Cumbria, UK), a microbial mat (les Salines de la Trinital, South Catalonia, Spain) and a culture (C. phaeobacteroides) including novel bacteriochlorophyll derivatives. The methods developed are directly suited to LC–MS analysis and the automated acquisition of MS/MS data for pigments.

Simple models of complex aggregation: Vesicle formation by soft repulsive spheres with dipolelike interactions

Structural and thermodynamic properties of spherical particles carrying classical spins are investigated by Monte Carlo simulations. The potential energy is the sum of short range, purely repulsive pair contributions, and spin-spin interactions. These last are of the dipole-dipole form, with however, a crucial change of sign. At low density and high temperature the system is a homogeneous fluid of weakly interacting particles and short range spin correlations. With decreasing temperature particles condense into an equilibrium population of free floating vesicles. The comparison with the electrostatic case, giving rise to predominantly one-dimensional aggregates under similar conditions, is discussed. In both cases condensation is a continuous transformation, provided the isotropic part of the interatomic potential is purely repulsive. At low temperature the model allows us to investigate thermal and mechanical properties of membranes. At intermediate temperatures it provides a simple model to investigate equilibrium polymerization in a system giving rise to predominantly two-dimensional aggregates.

Development of complex classical force fields through force matching to ab initio data: Application to a room-temperature ionic liquid

Recent experimental neutron diffraction data and ab initio molecular dynamics simulation of the ionic liquid dimethylimidazolium chloride ([dmim]Cl) have provided a structural description of the system at the molecular level. However, partial radial distribution functions calculated from the latter, when compared to previous classical simulation results, highlight some limitations in the structural description offered by force fieldbased simulations. With the availability of ab initio data it is possible to improve the classical description of [dmim]Cl by using the force matching approach, and the strategy for fitting complex force fields in their original functional form is discussed. A self-consistent optimization method for the generation of classical potentials of general functional form is presented and applied, and a force field that better reproduces the observed first principles forces is obtained. When used in simulation, it predicts structural data which reproduces more faithfully that observed in the ab initio studies. Some possible refinements to the technique, its application, and the general suitability of common potential energy functions used within many ionic liquid force fields are discussed.