Artefactual structure from least squares multidimensional scaling

We consider the problem of illusory or artefactual structure from the visualisation of high-dimensional structureless data. In particular we examine the role of the distance metric in the use of topographic mappings based on the statistical field of multidimensional scaling. We show that the use of a squared Euclidean metric (i.e. the SSTRESs measure) gives rise to an annular structure when the input data is drawn from a high-dimensional isotropic distribution, and we provide a theoretical justification for this observation.

MILVA:An interactive tool for the exploration of multidimensional microarray data

Clustering techniques such as k-means and hierarchical clustering are commonly used to analyze DNA microarray derived gene expression data. However, the interactions between processes underlying the cell activity suggest that the complexity of the microarray data structure may not be fully represented with discrete clustering methods.

Peer mentoring in higher education:a multidimensional approach to conceptualising the role of peer mentoring programmes in enhancing the first year undergraduate experience

Across the literature researchers agree that the concept of mentoring results in positive outcomes for both mentors and mentees alike (Enrich et al, 2004). From a pedagogical perspective, student focused mentoring activities in Higher Education are generally perceived to comprise dyadic or triadic relationships that encapsulate a diverse range of learning strategies and/or support mechanisms. Whilst there exists a significant amount of literature regarding the wider value of Peer Mentoring in Higher Education, there remains a notable gap in knowledge about the value of such programmes in enhancing the first year undergraduate experience and thus promoting a smooth transition to University. Using the emergent study findings of a large international project, a multidimensional conceptual framework bringing together the theoretical, conceptual and contextual determinants of Peer Mentoring is proposed. This framework makes a distinctive contribution to current pedagogical theory and practice – particularly in relation to the first year experience.

Symbolic use of export information:a multidimensional conceptualisation, its' effect on performance and key antecedents

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

Quantifying the complexity of chaos in multibasin multidimensional dynamics of molecular systems

The simulated classical dynamics of a small molecule exhibiting self-organizing behavior via a fast transition between two states is analyzed by calculation of the statistical complexity of the system. It is shown that the complexity of molecular descriptors such as atom coordinates and dihedral angles have different values before and after the transition. This provides a new tool to identify metastable states during molecular self-organization. The highly concerted collective motion of the molecule is revealed. Low-dimensional subspaces dynamics is found sensitive to the processes in the whole, high-dimensional phase space of the system. © 2004 Wiley Periodicals, Inc.

Bridging the gap between stylistic and cognitive approaches to authorship analysis using systemic functional linguistics and multidimensional analysis

In the present state of the art of authorship attribution there seems to be an opposition between two approaches: cognitive and stylistic methodologies. It is proposed in this article that these two approaches are complementary and that the apparent gap between them can be bridged using Systemic Functional Linguistics (SFL) and in particular some of its theoretical constructions, such as codal variation. This article deals with the theoretical explanation of why such a theory would solve the debate between the two approaches and shows how these two views of authorship attribution are indeed complementary. Although the article is fundamentally theoretical, two example experimental trials are reported to show how this theory can be developed into a workable methodology of doing authorship attribution. In Trial 1, a SFL analysis was carried out on a small dataset consisting of three 300-word texts collected from three different authors whose socio-demographic background matched across a number of parameters. This trial led to some conclusions about developing a methodology based on SFL and suggested the development of another trial, which might hint at a more accurate and useful methodology. In Trial 2, Biber's (1988) multidimensional framework is employed, and a final methodology of authorship analysis based on this kind of analysis is proposed for future research. © 2013, EQUINOX PUBLISHING.

Developing multidimensional metrics for evaluating paediatric neurodevelopmental disorders

Healthy brain functioning depends on efficient communication of information between brain regions, forming complex networks. By quantifying synchronisation between brain regions, a functionally connected brain network can be articulated. In neurodevelopmental disorders, where diagnosis is based on measures of behaviour and tasks, a measure of the underlying biological mechanisms holds promise as a potential clinical tool. Graph theory provides a tool for investigating the neural correlates of neuropsychiatric disorders, where there is disruption of efficient communication within and between brain networks. This research aimed to use recent conceptualisation of graph theory, along with measures of behaviour and cognitive functioning, to increase understanding of the neurobiological risk factors of atypical development. Using magnetoencephalography to investigate frequency-specific temporal dynamics at rest, the research aimed to identify potential biological markers derived from sensor-level whole-brain functional connectivity. Whilst graph theory has proved valuable for insight into network efficiency, its application is hampered by two limitations. First, its measures have hardly been validated in MEG studies, and second, graph measures have been shown to depend on methodological assumptions that restrict direct network comparisons. The first experimental study (Chapter 3) addressed the first limitation by examining the reproducibility of graph-based functional connectivity and network parameters in healthy adult volunteers. Subsequent chapters addressed the second limitation through adapted minimum spanning tree (a network analysis approach that allows for unbiased group comparisons) along with graph network tools that had been shown in Chapter 3 to be highly reproducible. Network topologies were modelled in healthy development (Chapter 4), and atypical neurodevelopment (Chapters 5 and 6). The results provided support to the proposition that measures of network organisation, derived from sensor-space MEG data, offer insights helping to unravel the biological basis of typical brain maturation and neurodevelopmental conditions, with the possibility of future clinical utility.

Intelligent outcome measures in liaison psychiatry:essential even if not desirable. Commentary on... a multidimensional Framework for Routine Outcome Measurement in Liaison Psychiatry (FROM-LP)

Service development is guided by outcome measures that inform service commissioners and providers. Those in liaison psychiatry should be encouraged to develop a positive approach that integrates the collection of outcome measures into everyday clinical practice. The Framework for Routine Outcome Measurement in Liaison Psychiatry (FROM-LP) is a very useful tool to measure service quality and clinical effectiveness, using a combination of clinician-rated and patient-rated outcome measures and patient-rated experience measures. However, it does not include measures of cost-effectiveness or training activities. The FROM-LP is a significant step towards developing nationally unified outcome measures.