Microcalorimetric studies of the iridium catalyst for hydrazine decomposition reaction

Microcalorimetric studies of H-2, NH3 and O-2 adsorption, as well as the NH3 decomposition activities evaluation were used to characterize the iridium catalysts for hydrazine decomposition with different supports (Al2O3, SiO,) and iridium contents (1.8, 10.8 and 22.1%). The higher H-2 chemisorption amounts on Ir/Al2O3 catalysts than those on the corresponding Ir/SiO2 counterparts revealed that the strong interaction of iridium and Al2O3 led to higher dispersion of iridium on Ir/Al2O3 catalysts than on Ir/SiO2 catalysts. The larger increase in strong H-2 adsorption sites on highly loaded Ir/Al2O3 than the corresponding Ir/SiO2 ones could be attributed to the interaction not only between iridium atoms but also between iridium and Al2O3. The microcalorimetric results for NH3 adsorption showed that no apparent chemisorption of NH3 existed on Ir/SiO2 catalysts while NH3 chemisorption amounts increased on Ir/Al2O3 catalysts with iridium loadings, which arose from the interaction of the catalysts support of Al2O3 With chloride anion. Both highly dispersed iridium active sites and chloride anion on Ir/Al2O3 catalysts could be beneficial to the intermediate NH3 decomposition in N2H4 decomposition. The similar O-2 plots of differential heat versus normalized coverage on Ir/Al2O3 and Ir/SiO2 catalysts could not be due to the metal-support interaction, but to the formation of strong Ir-O bond. (C) 2005 Elsevier B.V. All rights reserved.

Optimisation of immune effector function within the tumour microenvironment

Cancer represents a leading of cause of death in the developed world, inflicting tremendous suffering and plundering billions from health budgets. The traditional treatment approaches of surgery, radiotherapy and chemotherapy have achieved little in terms of cure for this deadly disease. Instead, life is prolonged for many, with dubious quality of life, only for disease to reappear with the inevitable fatal outcome. “Blue sky” thinking is required to tackle this disease and improve outcomes. The realisation and acceptance of the intrinsic role of the immune system in cancer pathogenesis, pathophysiology and treatment represented such a “blue sky” thought. Moreover, the embracement of immunotherapy, the concept of targeting immune cells rather than the tumour cells themselves, represents a paradigm shift in the approach to cancer therapy. The harnessing of immunotherapy demands radical and innovative therapeutic endeavours – endeavours such as gene and cell therapies and RNA interference, which two decades ago existed as mere concepts. This thesis straddles the frontiers of fundamental tumour immunobiology and novel therapeutic discovery, design and delivery. The work undertaken focused on two distinct immune cell populations known to undermine the immune response to cancer – suppressive T cells and macrophages. Novel RNAi mediators were designed, validated and incorporated into clinically relevant gene therapy vectors – involving a traditional lentiviral vector approach, and a novel bacterial vector strategy. Chapter 2 deals with the design of novel RNAi mediators against FOXP3 – a crucial regulator of the immunosuppressive regulatory T cell population. Two mediators were tested and validated. The superior mediator was taken forward as part of work in chapter 3. Chapter 3 deals with transposing the RNA sequence from chapter 2 into a DNA-based construct and subsequent incorporation into a lentiviral-based vector system. The lentiviral vector was shown to mediate gene delivery in vitro and functional RNAi was achieved against FOXP3. Proof of gene delivery was further confirmed in vivo in tumour-bearing animals. Chapter 4 focuses on a different immune cell population – tumour-associated macrophages. Non-invasive bacteria were explored as a specific means of delivering gene therapy to this phagocytic cell type. Proof of delivery was shown in vitro and in vivo. Moreover, in vivo delivery of a gene by this method achieved the desired immune response in terms of cytokine profile. Overall, the data presented here advance exploration within the field of cancer immunotherapy, introduce novel delivery and therapeutic strategies, and demonstrate pre-clinically the potential for such novel anti-cancer therapies.

Neonatal EEG classification using atomic decomposition

The electroencephalogram (EEG) is an important noninvasive tool used in the neonatal intensive care unit (NICU) for the neurologic evaluation of the sick newborn infant. It provides an excellent assessment of at-risk newborns and formulates a prognosis for long-term neurologic outcome.The automated analysis of neonatal EEG data in the NICU can provide valuable information to the clinician facilitating medical intervention. The aim of this thesis is to develop a system for automatic classification of neonatal EEG which can be mainly divided into two parts: (1) classification of neonatal EEG seizure from nonseizure, and (2) classifying neonatal background EEG into several grades based on the severity of the injury using atomic decomposition. Atomic decomposition techniques use redundant time-frequency dictionaries for sparse signal representations or approximations. The first novel contribution of this thesis is the development of a novel time-frequency dictionary coherent with the neonatal EEG seizure states. This dictionary was able to track the time-varying nature of the EEG signal. It was shown that by using atomic decomposition and the proposed novel dictionary, the neonatal EEG transition from nonseizure to seizure states could be detected efficiently. The second novel contribution of this thesis is the development of a neonatal seizure detection algorithm using several time-frequency features from the proposed novel dictionary. It was shown that the time-frequency features obtained from the atoms in the novel dictionary improved the seizure detection accuracy when compared to that obtained from the raw EEG signal. With the assistance of a supervised multiclass SVM classifier and several timefrequency features, several methods to automatically grade EEG were explored. In summary, the novel techniques proposed in this thesis contribute to the application of advanced signal processing techniques for automatic assessment of neonatal EEG recordings.

The Effect of Wood Burial and Submersion on Decomposition: Implications for Reducing Carbon Emissions

Gemstone Team Carbon Sinks

A domain decomposition algorithm for viscous/inviscid coupling

In fluid mechanics, it is well accepted that the Euler equation is one of the reduced forms of the Navier-Stokes equation by truncating the viscous effect. There are other truncation techniques currently being used in order to truncate the Navier-Stokes equation to a reduced form. This paper describes one such technique, suitable for adaptive domain decomposition methods for the solution of viscous flow problems. The physical domain of a viscous flow problem is partitioned into viscous and inviscid subdomains without overlapping regions, and the technique is embedded into a finite volume method. Some numerical results are provided for a flat plate and the NACA0012 aerofoil. Issues related to distributed computing are discussed.

A defect equation approach for the coupling of subdomains in domain decomposition methods

A defect equation for the coupling of nonlinear subproblems defined in nonoverlapped subdomains arise in domain decomposition methods is presented. Numerical solutions of defect equations by means of quasi-Newton methods are considered.

Domain decomposition using a 2-level correction scheme

The PHYSICA software was developed to enable multiphysics modelling allowing for interaction between Computational Fluid Dynamics (CFD) and Computational Solid Mechanics (CSM) and Computational Aeroacoustics (CAA). PHYSICA uses the finite volume method with 3-D unstructured meshes to enable the modelling of complex geometries. Many engineering applications involve significant computational time which needs to be reduced by means of a faster solution method or parallel and high performance algorithms. It is well known that multigrid methods serve as a fast iterative scheme for linear and nonlinear diffusion problems. This papers attempts to address two major issues of this iterative solver, including parallelisation of multigrid methods and their applications to time dependent multiscale problems.

Feller transition functions, Resolvent Decomposition Theorems, and their application in unstable denumerable Markov processes

This paper surveys the recent progresses made in the field of unstable denumerable Markov processes. Emphases are laid upon methodology and applications. The important tools of Feller transition functions and Resolvent Decomposition Theorems are highlighted. Their applications particularly in unstable denumerable Markov processes with a single instantaneous state and Markov branching processes are illustrated.

A domain decomposition algorithm for inverse welding problems

A mathematical model and a numerical scheme for the inverse determination of heat sources generated by means of a welding process is presented in this paper. The accuracy of the heat source retrieval is discussed.

Domain decomposition methods for welding problems

This paper, a 2-D non-linear electric arc-welding problem is considered. It is assumed that the moving arc generates an unknown quantity of energy which makes the problem an inverse problem with an unknown source. Robust algorithms to solve such problems e#ciently, and in certain circumstances in real-time, are of great technological and industrial interest. There are other types of inverse problems which involve inverse determination of heat conductivity or material properties [CDJ63][TE98], inverse problems in material cutting [ILPP98], and retrieval of parameters containing discontinuities [IK90]. As in the metal cutting problem, the temperature of a very hot surface is required and it relies on the use of thermocouples. Here, the solution scheme requires temperature measurements lied in the neighbourhood of the weld line in order to retrieve the unknown heat source. The size of this neighbourhood is not considered in this paper, but rather a domain decomposition concept is presented and an examination of the accuracy of the retrieved source are presented. This paper is organised as follows. The inverse problem is formulated and a method for the source retrieval is presented in the second section. The source retrieval method is based on an extension of the 1-D source retrieval method as proposed in [ILP].

Electronic packaging and reduction in modelling time using domain decomposition

The domain decomposition method is directed to electronic packaging simulation in this article. The objective is to address the entire simulation process chain, to alleviate user interactions where they are heavy to mechanization by component approach to streamline the model simulation process.