575 resultados para Uniform Normal Structure


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Natural convection flow from an isothermal vertical plate with uniform heat source embedded in a stratified medium has been discussed in this paper. The resulting momentum and energy equations of boundary layer approximation are made non-similar by introducing the usual non-similarity transformations. Numerical solutions of these equations are obtained by an implicit finite difference method for a wide range of the stratification parameter, X. The solutions are also obtained for different values of pertinent parameters, namely, the Prandtl number, Pr and the heat generation or absorption parameter, λ and are expressed in terms of the local skin-friction and local heat transfer, which are shown in the graphical form. Effect of heat generation or absorption on the streamlines and isotherms are also shown graphically for different values of λ.

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This paper reports a 2-year longitudinal study on the effectiveness of the Pattern and Structure Mathematical Awareness Program (PASMAP) on students’ mathematical development. The study involved 316 Kindergarten students in 17 classes from four schools in Sydney and Brisbane. The development of the PASA assessment interview and scale are presented. The intervention program provided explicit instruction in mathematical pattern and structure that enhanced the development of students’ spatial structuring, multiplicative reasoning, and emergent generalisations. This paper presents the initial findings of the impact of the PASMAP and illustrates students’ structural development.

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The Pattern and Structure Mathematical Awareness Program(PASMAP) stems from a 2-year longitudinal study on students’ early mathematical development. The paper outlines the interview assessment the Pattern and Structure Assessment(PASA) designed to describe students’ awareness of mathematical pattern and structure across a range of concepts. An overview of students’ performance across items and descriptions of their structural development are described.

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In recent times considerable research attention has been directed to understanding dark networks, especially criminal and terrorist networks. Dark networks are those in which member motivations are self rather than public interested, achievements come at the cost of other individuals, groups or societies and, in addition, their activities are both ‘covert and illegal’ (Raab & Milward, 2003: 415). This ‘darkness’ has implications for the way in which these networks are structured, the strategies adopted and their recruitment methods. Such entities exhibit distinctive operating characteristics including most notably the tension between creating an efficient network structure while retaining the ability to hide from public view while avoiding catastrophic collapse should one member cooperate with authorities (Bouchard 2007). While theoretical emphasis has been on criminal and terrorist networks, recent work has demonstrated that corrupt police networks exhibit some distinctive characteristics. In particular, these entities operate within the shadows of a host organisation - the Police Force and distort the functioning of the ‘Thin Blue Line’ as the interface between the law abiding citizenry and the criminal society. Drawing on data derived from the Queensland Fitzgerald Commission of Enquiry into Police Misconduct and related documents, this paper examines the motivations, structural properties and operational practices of corrupt police networks and compares and contrasts these with other dark networks with ‘bright’ public service networks. The paper confirms the structural differences between dark corrupt police networks and bright networks and suggests. However, structural embeddedness alone is found to be an insufficient theoretical explanation for member involvement in networks and that a set of elements combine to impact decision-making. Although offering important insights into network participation, the paper’s findings are especially pertinent in identifying additional points of intervention for police corruption networks.

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Due to their large surface area, complex chemical composition and high alveolar deposition rate, ultrafine particles (UFPs) (< 0.1 ìm) pose a significant risk to human health and their toxicological effects have been acknowledged by the World Health Organisation. Since people spend most of their time indoors, there is a growing concern about the UFPs present in some indoor environments. Recent studies have shown that office machines, in particular laser printers, are a significant indoor source of UFPs. The majority of printer-generated UFPs are organic carbon and it is unlikely that these particles are emitted directly from the printer or its supplies (such as paper and toner powder). Thus, it was hypothesised that these UFPs are secondary organic aerosols (SOA). Considering the widespread use of printers and human exposure to these particles, understanding the processes involved in particle formation is of critical importance. However, few studies have investigated the nature (e.g. volatility, hygroscopicity, composition, size distribution and mixing state) and formation mechanisms of these particles. In order to address this gap in scientific knowledge, a comprehensive study including state-of-art instrumental methods was conducted to characterise the real-time emissions from modern commercial laser printers, including particles, volatile organic compounds (VOCs) and ozone (O3). The morphology, elemental composition, volatility and hygroscopicity of generated particles were also examined. The large set of experimental results was analysed and interpreted to provide insight into: (1) Emissions profiles of laser printers: The results showed that UFPs dominated the number concentrations of generated particles, with a quasi unimodal size distribution observed for all tests. These particles were volatile, non-hygroscopic and mixed both externally and internally. Particle microanalysis indicated that semi-volatile organic compounds occupied the dominant fraction of these particles, with only trace quantities of particles containing Ca and Fe. Furthermore, almost all laser printers tested in this study emitted measurable concentrations of VOCs and O3. A positive correlation between submicron particles and O3 concentrations, as well as a contrasting negative correlation between submicron particles and total VOC concentrations were observed during printing for all tests. These results proved that UFPs generated from laser printers are mainly SOAs. (2) Sources and precursors of generated particles: In order to identify the possible particle sources, particle formation potentials of both the printer components (e.g. fuser roller and lubricant oil) and supplies (e.g. paper and toner powder) were investigated using furnace tests. The VOCs emitted during the experiments were sampled and identified to provide information about particle precursors. The results suggested that all of the tested materials had the potential to generate particles upon heating. Nine unsaturated VOCs were identified from the emissions produced by paper and toner, which may contribute to the formation of UFPs through oxidation reactions with ozone. (3) Factors influencing the particle emission: The factors influencing particle emissions were also investigated by comparing two popular laser printers, one showing particle emissions three orders of magnitude higher than the other. The effects of toner coverage, printing history, type of paper and toner, and working temperature of the fuser roller on particle number emissions were examined. The results showed that the temperature of the fuser roller was a key factor driving the emission of particles. Based on the results for 30 different types of laser printers, a systematic positive correlation was observed between temperature and particle number emissions for printers that used the same heating technology and had a similar structure and fuser material. It was also found that temperature fluctuations were associated with intense bursts of particles and therefore, they may have impact on the particle emissions. Furthermore, the results indicated that the type of paper and toner powder contributed to particle emissions, while no apparent relationship was observed between toner coverage and levels of submicron particles. (4) Mechanisms of SOA formation, growth and ageing: The overall hypothesis that UFPs are formed by reactions with the VOCs and O3 emitted from laser printers was examined. The results proved this hypothesis and suggested that O3 may also play a role in particle ageing. In addition, knowledge about the mixing state of generated particles was utilised to explore the detailed processes of particle formation for different printing scenarios, including warm-up, normal printing, and printing without toner. The results indicated that polymerisation may have occurred on the surface of the generated particles to produce thermoplastic polymers, which may account for the expandable characteristics of some particles. Furthermore, toner and other particle residues on the idling belt from previous print jobs were a very clear contributing factor in the formation of laser printer-emitted particles. In summary, this study not only improves scientific understanding of the nature of printer-generated particles, but also provides significant insight into the formation and ageing mechanisms of SOAs in the indoor environment. The outcomes will also be beneficial to governments, industry and individuals.

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A new scaling analysis has been performed for the unsteady natural convection boundary layer under a downward facing inclined plate with uniform heat flux. The development of the thermal or viscous boundary layers may be classified into three distinct stages including a start-up stage, a transitional stage and a steady stage, which can be clearly identified in the analytical as well as numerical results. Earlier scaling shows that the existing scaling laws of the boundary layer thickness, velocity and steady state time scale for the natural convection flow on a heated plate of uniform heat flux provide a very poor prediction of the Prandtl number dependency of the flow. However, those scalings performed very well with Rayleigh number and aspect ratio dependency. In this study, a new Prandtl number scaling has been developed using a triple-layer integral approach for Pr > 1. It is seen that in comparison to the direct numerical simulations, the new scaling performs considerably better than the previous scaling.

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Natural convection in a triangular enclosure subject to non-uniformly cooling at the inclined surfaces and uniformly heating at the base is investigated numerically. The numerical simulations of the unsteady flows over a range of Rayleigh numbers and aspect ratios are carried out using Finite Volume Method. Since the upper surface is cooled and the bottom surface is heated, the air flow in the enclosure is potentially unstable to Rayleigh Benard instability. It is revealed that the transient flow development in the enclosure can be classified into three distinct stages; an early stage, a transitional stage and a steady stage. It is also found that the flow inside the enclosure strongly depends on the governing parameters, Rayleigh number and aspect ratio. The asymmetric behaviour of the flow about the geometric centre line is discussed in detailed. The heat transfer through the roof and the ceiling as a form of Nusselt number is also reported in this study.

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This chapter argues that evolutionary economics should be founded upon complex systems theory rather than neo-Darwinian analogies concerning natural selection, which focus on supply side considerations and competition amongst firms and technologies. It suggests that conceptions such as production and consumption functions should be replaced by network representations, in which the preferences or, more correctly, the aspirations of consumers are fundamental and, as such, the primary drivers of economic growth. Technological innovation is viewed as a process that is intermediate between these aspirational networks, and the organizational networks in which goods and services are produced. Consumer knowledge becomes at least as important as producer knowledge in determining how economic value is generated. It becomes clear that the stability afforded by connective systems of rules is essential for economic flexibility to exist, but that too many rules result in inert and structurally unstable states. In contrast, too few rules result in a more stable state, but at a low level of ordered complexity. Economic evolution from this perspective is explored using random and scale free network representations of complex systems.

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The formation of hypertrophic scars is a frequent outcome of wound repair and often requires further therapy with treatments such as silicone gel sheets (SGS; Perkins et al., 1983). Although widely used, knowledge regarding SGS and their mechanism of action on hypertrophic scars is limited. Furthermore, SGS require consistent application for at least twelve hours a day for up to twelve consecutive months, beginning as soon as wound reepithelialisation has occurred. Preliminary research at QUT has shown that some species of silicone present in SGS have the ability to permeate into collagen gel skin mimetics upon exposure. An analogue of these species, GP226, was found to decrease both collagen synthesis and the total amount of collagen present following exposure to cultures of cells derived from hypertrophic scars. This silicone of interest was a crude mixture of silicone species, which resolved into five fractions of different molecular weight. These five fractions were found to have differing effects on collagen synthesis and cell viability following exposure to fibroblasts derived from hypertrophic scars (HSF), keloid scars (KF) and normal skin (nHSF and nKF). The research performed herein continues to further assess the potential of GP226 and its fractions for scar remediation by determining in more detail its effects on HSF, KF, nHSF, nKF and human keratinocytes (HK) in terms of cell viability and proliferation at various time points. Through these studies it was revealed that Fraction IV was the most active fraction as it induced a reduction in cell viability and proliferation most similar to that observed with GP226. Cells undergoing apoptosis were also detected in HSF cultures exposed to GP226 and Fraction IV using the Tunel assay (Roche). These investigations were difficult to pursue further as the fractionation process used for GP226 was labour-intensive and time inefficient. Therefore a number of silicones with similar structure to Fraction IV were synthesised and screened for their effect following application to HSF and nHSF. PDMS7-g-PEG7, a silicone-PEG copolymer of low molecular weight and low hydrophilic-lipophilic balance factor, was found to be the most effective at reducing cell proliferation and inducing apoptosis in cultures of HSF, nHSF and HK. Further studies investigated gene expression through microarray and superarray techniques and demonstrated that many genes are differentially expressed in HSF following treatment with GP226, Fraction IV and PDMS7-g-PEG7. In brief, it was demonstrated that genes for TGFβ1 and TNF are not differentially regulated while genes for AIFM2, IL8, NSMAF, SMAD7, TRAF3 and IGF2R show increased expression (>1.8 fold change) following treatment with PDMS7-g-PEG7. In addition, genes for αSMA, TRAF2, COL1A1 and COL3A1 have decreased expression (>-1.8 fold change) following treatment with GP226, Fraction IV and PDMS7-g-PEG7. The data obtained suggest that many different pathways related to apoptosis and collagen synthesis are affected in HSF following exposure to PDMS7-g-PEG7. The significance is that silicone-PEG copolymers, such as GP226, Fraction IV and PDMS7-g-PEG7, could potentially be a non-invasive substitute to apoptosis-inducing chemical agents that are currently used as scar treatments. It is anticipated that these findings will ultimately contribute to the development of a novel scar therapy with faster action and improved outcomes for patients suffering from hypertrophic scars.

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Proteases regulate a spectrum of diverse physiological processes, and dysregulation of proteolytic activity drives a plethora of pathological conditions. Understanding protease function is essential to appreciating many aspects of normal physiology and progression of disease. Consequently, development of potent and specific inhibitors of proteolytic enzymes is vital to provide tools for the dissection of protease function in biological systems and for the treatment of diseases linked to aberrant proteolytic activity. The studies in this thesis describe the rational design of potent inhibitors of three proteases that are implicated in disease development. Additionally, key features of the interaction of proteases and their cognate inhibitors or substrates are analysed and a series of rational inhibitor design principles are expounded and tested. Rational design of protease inhibitors relies on a comprehensive understanding of protease structure and biochemistry. Analysis of known protease cleavage sites in proteins and peptides is a commonly used source of such information. However, model peptide substrate and protein sequences have widely differing levels of backbone constraint and hence can adopt highly divergent structures when binding to a protease’s active site. This may result in identical sequences in peptides and proteins having different conformations and diverse spatial distribution of amino acid functionalities. Regardless of this, protein and peptide cleavage sites are often regarded as being equivalent. One of the key findings in the following studies is a definitive demonstration of the lack of equivalence between these two classes of substrate and invalidation of the common practice of using the sequences of model peptide substrates to predict cleavage of proteins in vivo. Another important feature for protease substrate recognition is subsite cooperativity. This type of cooperativity is commonly referred to as protease or substrate binding subsite cooperativity and is distinct from allosteric cooperativity, where binding of a molecule distant from the protease active site affects the binding affinity of a substrate. Subsite cooperativity may be intramolecular where neighbouring residues in substrates are interacting, affecting the scissile bond’s susceptibility to protease cleavage. Subsite cooperativity can also be intermolecular where a particular residue’s contribution to binding affinity changes depending on the identity of neighbouring amino acids. Although numerous studies have identified subsite cooperativity effects, these findings are frequently ignored in investigations probing subsite selectivity by screening against diverse combinatorial libraries of peptides (positional scanning synthetic combinatorial library; PS-SCL). This strategy for determining cleavage specificity relies on the averaged rates of hydrolysis for an uncharacterised ensemble of peptide sequences, as opposed to the defined rate of hydrolysis of a known specific substrate. Further, since PS-SCL screens probe the preference of the various protease subsites independently, this method is inherently unable to detect subsite cooperativity. However, mean hydrolysis rates from PS-SCL screens are often interpreted as being comparable to those produced by single peptide cleavages. Before this study no large systematic evaluation had been made to determine the level of correlation between protease selectivity as predicted by screening against a library of combinatorial peptides and cleavage of individual peptides. This subject is specifically explored in the studies described here. In order to establish whether PS-SCL screens could accurately determine the substrate preferences of proteases, a systematic comparison of data from PS-SCLs with libraries containing individually synthesised peptides (sparse matrix library; SML) was carried out. These SML libraries were designed to include all possible sequence combinations of the residues that were suggested to be preferred by a protease using the PS-SCL method. SML screening against the three serine proteases kallikrein 4 (KLK4), kallikrein 14 (KLK14) and plasmin revealed highly preferred peptide substrates that could not have been deduced by PS-SCL screening alone. Comparing protease subsite preference profiles from screens of the two types of peptide libraries showed that the most preferred substrates were not detected by PS SCL screening as a consequence of intermolecular cooperativity being negated by the very nature of PS SCL screening. Sequences that are highly favoured as result of intermolecular cooperativity achieve optimal protease subsite occupancy, and thereby interact with very specific determinants of the protease. Identifying these substrate sequences is important since they may be used to produce potent and selective inhibitors of protolytic enzymes. This study found that highly favoured substrate sequences that relied on intermolecular cooperativity allowed for the production of potent inhibitors of KLK4, KLK14 and plasmin. Peptide aldehydes based on preferred plasmin sequences produced high affinity transition state analogue inhibitors for this protease. The most potent of these maintained specificity over plasma kallikrein (known to have a very similar substrate preference to plasmin). Furthermore, the efficiency of this inhibitor in blocking fibrinolysis in vitro was comparable to aprotinin, which previously saw clinical use to reduce perioperative bleeding. One substrate sequence particularly favoured by KLK4 was substituted into the 14 amino acid, circular sunflower trypsin inhibitor (SFTI). This resulted in a highly potent and selective inhibitor (SFTI-FCQR) which attenuated protease activated receptor signalling by KLK4 in vitro. Moreover, SFTI-FCQR and paclitaxel synergistically reduced growth of ovarian cancer cells in vitro, making this inhibitor a lead compound for further therapeutic development. Similar incorporation of a preferred KLK14 amino acid sequence into the SFTI scaffold produced a potent inhibitor for this protease. However, the conformationally constrained SFTI backbone enforced a different intramolecular cooperativity, which masked a KLK14 specific determinant. As a consequence, the level of selectivity achievable was lower than that found for the KLK4 inhibitor. Standard mechanism inhibitors such as SFTI rely on a stable acyl-enzyme intermediate for high affinity binding. This is achieved by a conformationally constrained canonical binding loop that allows for reformation of the scissile peptide bond after cleavage. Amino acid substitutions within the inhibitor to target a particular protease may compromise structural determinants that support the rigidity of the binding loop and thereby prevent the engineered inhibitor reaching its full potential. An in silico analysis was carried out to examine the potential for further improvements to the potency and selectivity of the SFTI-based KLK4 and KLK14 inhibitors. Molecular dynamics simulations suggested that the substitutions within SFTI required to target KLK4 and KLK14 had compromised the intramolecular hydrogen bond network of the inhibitor and caused a concomitant loss of binding loop stability. Furthermore in silico amino acid substitution revealed a consistent correlation between a higher frequency of formation and the number of internal hydrogen bonds of SFTI-variants and lower inhibition constants. These predictions allowed for the production of second generation inhibitors with enhanced binding affinity toward both targets and highlight the importance of considering intramolecular cooperativity effects when engineering proteins or circular peptides to target proteases. The findings from this study show that although PS-SCLs are a useful tool for high throughput screening of approximate protease preference, later refinement by SML screening is needed to reveal optimal subsite occupancy due to cooperativity in substrate recognition. This investigation has also demonstrated the importance of maintaining structural determinants of backbone constraint and conformation when engineering standard mechanism inhibitors for new targets. Combined these results show that backbone conformation and amino acid cooperativity have more prominent roles than previously appreciated in determining substrate/inhibitor specificity and binding affinity. The three key inhibitors designed during this investigation are now being developed as lead compounds for cancer chemotherapy, control of fibrinolysis and cosmeceutical applications. These compounds form the basis of a portfolio of intellectual property which will be further developed in the coming years.

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Recent algorithms for monocular motion capture (MoCap) estimate weak-perspective camera matrices between images using a small subset of approximately-rigid points on the human body (i.e. the torso and hip). A problem with this approach, however, is that these points are often close to coplanar, causing canonical linear factorisation algorithms for rigid structure from motion (SFM) to become extremely sensitive to noise. In this paper, we propose an alternative solution to weak-perspective SFM based on a convex relaxation of graph rigidity. We demonstrate the success of our algorithm on both synthetic and real world data, allowing for much improved solutions to marker less MoCap problems on human bodies. Finally, we propose an approach to solve the two-fold ambiguity over bone direction using a k-nearest neighbour kernel density estimator.

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The need to find an alternative to our current transport situation is widely accepted. In most cities of the world, traffic congestion is commonplace and air pollution is normal. Road fatalities are a regular and almost accepted event. And (in most developed nations) as an indirect consequence of our transport choices, obesity is increasing at an alarming rate. The car is undeniably a major contributor to this situation. Additionally the very structure of our cities has evolved to the point that it can be creditably claimed that the city belongs to the car and not to humans. There are however alternatives. There is a plethora of experimental vehicles in all shapes and configurations. And yet, the car is still king. The question is, how do we pick a winner? What are the aspects of the car that make it so appealing? Are these aspects able to be translated into a more sustainable version? What do we need to incorporate in our designs of new vehicles to make them more appealing to the consumers? In this paper I explore these questions and propose a list of design criteria for more sustainable transport options.

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With the growing number of XML documents on theWeb it becomes essential to effectively organise these XML documents in order to retrieve useful information from them. A possible solution is to apply clustering on the XML documents to discover knowledge that promotes effective data management, information retrieval and query processing. However, many issues arise in discovering knowledge from these types of semi-structured documents due to their heterogeneity and structural irregularity. Most of the existing research on clustering techniques focuses only on one feature of the XML documents, this being either their structure or their content due to scalability and complexity problems. The knowledge gained in the form of clusters based on the structure or the content is not suitable for reallife datasets. It therefore becomes essential to include both the structure and content of XML documents in order to improve the accuracy and meaning of the clustering solution. However, the inclusion of both these kinds of information in the clustering process results in a huge overhead for the underlying clustering algorithm because of the high dimensionality of the data. The overall objective of this thesis is to address these issues by: (1) proposing methods to utilise frequent pattern mining techniques to reduce the dimension; (2) developing models to effectively combine the structure and content of XML documents; and (3) utilising the proposed models in clustering. This research first determines the structural similarity in the form of frequent subtrees and then uses these frequent subtrees to represent the constrained content of the XML documents in order to determine the content similarity. A clustering framework with two types of models, implicit and explicit, is developed. The implicit model uses a Vector Space Model (VSM) to combine the structure and the content information. The explicit model uses a higher order model, namely a 3- order Tensor Space Model (TSM), to explicitly combine the structure and the content information. This thesis also proposes a novel incremental technique to decompose largesized tensor models to utilise the decomposed solution for clustering the XML documents. The proposed framework and its components were extensively evaluated on several real-life datasets exhibiting extreme characteristics to understand the usefulness of the proposed framework in real-life situations. Additionally, this research evaluates the outcome of the clustering process on the collection selection problem in the information retrieval on the Wikipedia dataset. The experimental results demonstrate that the proposed frequent pattern mining and clustering methods outperform the related state-of-the-art approaches. In particular, the proposed framework of utilising frequent structures for constraining the content shows an improvement in accuracy over content-only and structure-only clustering results. The scalability evaluation experiments conducted on large scaled datasets clearly show the strengths of the proposed methods over state-of-the-art methods. In particular, this thesis work contributes to effectively combining the structure and the content of XML documents for clustering, in order to improve the accuracy of the clustering solution. In addition, it also contributes by addressing the research gaps in frequent pattern mining to generate efficient and concise frequent subtrees with various node relationships that could be used in clustering.

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Twin studies offer the opportunity to determine the relative contribution of genes versus environment in traits of interest. Here, we investigate the extent to which variance in brain structure is reduced in monozygous twins with identical genetic make-up. We investigate whether using twins as compared to a control population reduces variability in a number of common magnetic resonance (MR) structural measures, and we investigate the location of areas under major genetic influences. This is fundamental to understanding the benefit of using twins in studies where structure is the phenotype of interest. Twenty-three pairs of healthy MZ twins were compared to matched control pairs. Volume, T2 and diffusion MR imaging were performed as well as spectroscopy (MRS). Images were compared using (i) global measures of standard deviation and effect size, (ii) voxel-based analysis of similarity and (iii) intra-pair correlation. Global measures indicated a consistent increase in structural similarity in twins. The voxel-based and correlation analyses indicated a widespread pattern of increased similarity in twin pairs, particularly in frontal and temporal regions. The areas of increased similarity were most widespread for the diffusion trace and least widespread for T2. MRS showed consistent reduction in metabolite variation that was significant in the temporal lobe N-acetylaspartate (NAA). This study has shown the distribution and magnitude of reduced variability in brain volume, diffusion, T2 and metabolites in twins. The data suggest that evaluation of twins discordant for disease is indeed a valid way to attribute genetic or environmental influences to observed abnormalities in patients since evidence is provided for the underlying assumption of decreased variability in twins.