A completely kinematostatically decoupled XY compliant parallel manipulator through new topology structure

This paper deals with a completely kinematostaticaly decoupled XY compliant parallel manipulator (CPM) composed of exactly-constrained compliant modules. A new 4-PP XY translational parallel mechanism (TPM) with a new topology structure is firstly proposed where each two P (P: prismatic) joints on the base in two non-adjacent legs are rigidly connected. A novel 4-PP XY CPM is then obtained by replacing each traditional P join on the base in the 4-PP XY TPM with a compound basic parallelogram module (CBPM) and replacing each traditional P joint on the motion stage with a basic parallelogram module (BPM). Approximate analytical model is derived with comparison to the FEA (finite element analysis) model and experiment for a case study. The proposed novel XY CPM has a compact configuration with good dynamics, and is able to well constrain the parasitic rotation and the cross-axis coupling of the motion stage. The cross-axis motion of the input stage can be completely eliminated, and the lost motion between the input stage and the motion stage is significantly reduced.

Combining and choosing case base maintenance algorithms

Case-Based Reasoning (CBR) uses past experiences to solve new problems. The quality of the past experiences, which are stored as cases in a case base, is a big factor in the performance of a CBR system. The system's competence may be improved by adding problems to the case base after they have been solved and their solutions verified to be correct. However, from time to time, the case base may have to be refined to reduce redundancy and to get rid of any noisy cases that may have been introduced. Many case base maintenance algorithms have been developed to delete noisy and redundant cases. However, different algorithms work well in different situations and it may be difficult for a knowledge engineer to know which one is the best to use for a particular case base. In this thesis, we investigate ways to combine algorithms to produce better deletion decisions than the decisions made by individual algorithms, and ways to choose which algorithm is best for a given case base at a given time. We analyse five of the most commonly-used maintenance algorithms in detail and show how the different algorithms perform better on different datasets. This motivates us to develop a new approach: maintenance by a committee of experts (MACE). MACE allows us to combine maintenance algorithms to produce a composite algorithm which exploits the merits of each of the algorithms that it contains. By combining different algorithms in different ways we can also define algorithms that have different trade-offs between accuracy and deletion. While MACE allows us to define an infinite number of new composite algorithms, we still face the problem of choosing which algorithm to use. To make this choice, we need to be able to identify properties of a case base that are predictive of which maintenance algorithm is best. We examine a number of measures of dataset complexity for this purpose. These provide a numerical way to describe a case base at a given time. We use the numerical description to develop a meta-case-based classification system. This system uses previous experience about which maintenance algorithm was best to use for other case bases to predict which algorithm to use for a new case base. Finally, we give the knowledge engineer more control over the deletion process by creating incremental versions of the maintenance algorithms. These incremental algorithms suggest one case at a time for deletion rather than a group of cases, which allows the knowledge engineer to decide whether or not each case in turn should be deleted or kept. We also develop incremental versions of the complexity measures, allowing us to create an incremental version of our meta-case-based classification system. Since the case base changes after each deletion, the best algorithm to use may also change. The incremental system allows us to choose which algorithm is the best to use at each point in the deletion process.

The role played by angiotensin (1-7) in the regulation of renal haemodynamics and excretory function in anesthetized rats

Initial studies have demonstrated that intra- renal infusion of Ang (1-7) caused a diuresis and natriuresis that was proportional to the degree of activation of the Renin Angiotensin Aldosterone System (RAAS). This raised the question as why the magnitude of this diuresis and natriuresis was compromised in rats receiving a high sodium diet (suppressed RAAS) and enhanced in low sodium fed rats (activated RAAS)? Could the answer lie with changes in intra-renal AT1 or Mas receptor expression? Interestingly, the observed Ang (1-7) induced increases in sodium and water excretion in rats receiving either a low or normal sodium diet were and blocked in the presence of the AT 1 receptor antagonist (Losartan) in the presence of the, 'Mas' receptor antagonist (A-779). These data suggest that both AT1 and 'Mas' receptors need to be functional in order to fully mediate the renal responses to intra-renal Ang (1-7) infusion. Importantly, further experimentation also revealed that there is a proportional relationship between AT 1 receptor expression in the rat renal cortex and the magnitude of the excretory actions of intra renal Ang (1-7) infusion, which is only partially dependent on the level of 'Mas' receptor expression. These observations suggest that although Ang (1-7) induced increases in sodium and water excretion are mediated by the Mas receptor, the magnitude of these excretory responses appear to be dependent upon the level of AT 1 receptor expression and more specifically Ang II/ AT 1 receptor signalling. Thus in rats receiving a low sodium diet, Ang (1-7) acts via the Mas receptor to inhibit Ang II/ AT 1 receptor signalling. In rats receiving a high sodium diet the down regulated AT 1 receptor expression implies a reduction in Ang II/ AT 1 receptor signalling which renders the counter-regulatory effects of intra-renal Ang (1-7) infusion redundant.

The relevance of bacterial isoprenoid biosynthetic pathways for host-microbe interactions

This thesis was undertaken to investigate the relevance of two bacterial isoprenoid biosynthetic pathways (Mevalonate (MVAL) and 2-C-methyl-D-erythritol 4-phosphate (MEP)) for host-microbe interactions. We determined a significant reduction in microbial diversity in the murine gut microbiota (by next generation sequencing) following oral administration of a common anti-cholesterol drug Rosuvastatin (RSV) that targets mammalian and bacterial HMG-CoA reductase (HMG-R) for inhibition of MVAL formation. In tandem we identified significant hepatic and intestinal off-target alterations to the murine metabolome indicating alterations in inflammation, bile acid profiles and antimicrobial peptide synthesis with implications on community structure of the gastrointestinal microbiota in statin-treated animals. However we found no effect on local Short Chain Fatty Acid biosynthesis (metabolic health marker in our model). We demonstrated direct inhibition of bacterial growth in-vitro by RSV which correlated with reductions in bacterial MVAL formation. However this was only at high doses of RSV. Our observations demonstrate a significant RSV-associated impact on the gut microbiota prompting similar human analysis. Successful deletion of another MVAL pathway enzyme (HMG-CoA synthase (mvaS)) involved in Listeria monocytogenes EGDe isoprenoid biosynthesis determined that the enzyme is non-essential for normal growth and in-vivo pathogenesis of this pathogen. We highlight potential evidence for alternative means of synthesis of the HMG-CoA substrate that could render mvaS activity redundant under our test conditions. Finally, we showed by global gene expression analysis (Massive Analysis of cDNA Ends (MACE RNA-seq) a significant role for the penultimate MEP pathway metabolite (E)-4-hydroxy-3-methyl-2-but-2-enyl pyrophosphate (HMBPP) in significant up regulation of genes of immunity and antigen presentation in THP-1 cells at nanomolar levels. We infected THP-1 cells with wild type or HMBPP under/over-producing L. monoctyogenes EGDe mutants and determined subtle effects of HMBPP upon overall host responses to Listeria infection. Overall our findings provide greater insights regarding bacterial isoprenoid biosynthetic pathways for host-microbe/microbe-host dialogue.

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.

Towards the design of monolithic decoupled XYZ compliant parallel mechanisms for multi-function applications

This paper deals with the monolithic decoupled XYZ compliant parallel mechanisms (CPMs) for multi-function applications, which can be fabricated monolithically without assembly and has the capability of kinetostatic decoupling. At first, the conceptual design of monolithic decoupled XYZ CPMs is presented using identical spatial compliant multi-beam modules based on a decoupled 3-PPPR parallel kinematic mechanism. Three types of applications: motion/positioning stages, force/acceleration sensors and energy harvesting devices are described in principle. The kinetostatic and dynamic modelling is then conducted to capture the displacements of any stage under loads acting at any stage and the natural frequency with the comparisons with FEA results. Finally, performance characteristics analysis for motion stage applications is detailed investigated to show how the change of the geometrical parameter can affect the performance characteristics, which provides initial optimal estimations. Results show that the smaller thickness of beams and larger dimension of cubic stages can improve the performance characteristics excluding natural frequency under allowable conditions. In order to improve the natural frequency characteristic, a stiffness-enhanced monolithic decoupled configuration that is achieved through employing more beams in the spatial modules or reducing the mass of each cubic stage mass can be adopted. In addition, an isotropic variation with different motion range along each axis and same payload in each leg is proposed. The redundant design for monolithic fabrication is introduced in this paper, which can overcome the drawback of monolithic fabrication that the failed compliant beam is difficult to replace, and extend the CPM’s life.

A constraint and position identification (CPI) approach for the synthesis of decoupled spatial translational compliant parallel manipulators

This paper introduces a screw theory based method termed constraint and position identification (CPI) approach to synthesize decoupled spatial translational compliant parallel manipulators (XYZ CPMs) with consideration of actuation isolation. The proposed approach is based on a systematic arrangement of rigid stages and compliant modules in a three-legged XYZ CPM system using the constraint spaces and the position spaces of the compliant modules. The constraint spaces and the position spaces are firstly derived based on the screw theory instead of using the rigid-body mechanism design experience. Additionally, the constraint spaces are classified into different constraint combinations, with typical position spaces depicted via geometric entities. Furthermore, the systematic synthesis process based on the constraint combinations and the geometric entities is demonstrated via several examples. Finally, several novel decoupled XYZ CPMs with monolithic configurations are created and verified by finite elements analysis. The present CPI approach enables experts and beginners to synthesize a variety of decoupled XYZ CPMs with consideration of actuation isolation by selecting an appropriate constraint and an optimal position for each of the compliant modules according to a specific application.