995 research outputs found
Doctor of Philosophy
dissertationResearchers have long recognized intimate partner abuse as a social problem, but only recently has it been recognized as a public health problem. However, research to this point has failed to examine whether the health effects of intimate partner violence vary by gender. This dissertation uses data from the National Survey of Families and Households to examine the effects of intimate partner abuse on physical health, depression, fear, stress, social connectedness, and access to resources in intimate partner relationships. All models are stratified by gender in order to examine gender differences in health outcomes. Results indicate that there are gender differences, with a female disadvantage on many outcomes. Implications include inclusion of violence outcomes in future research of IPA, and recognition that "symmetry" definitions should include more than simple rates and ratios of violence reporting. Furthermore, this research indicates a need to expand the study of gender in low-level violence to assess other differences that were not addressed in this study
Looking back: corticothalamic feedback and early visual processing
[Abstract] Although once regarded as a simple sensory relay on the way to the cortex, it is increasingly apparent that the thalamus has a role in the ongoing moment-by-moment processing of sensory input and in cognition. This involves extensive corticofugal feedback connections and the interplay of these with the local thalamic circuitry and the other converging inputs. Here, using the feline visual system as the primary model, some of the latest developments in this field are reviewed and placed in the perspective of an integrated view of system function. Cortical feedback mediated by ionotropic and metabotropic glutamate receptors, and effects mediated by the neuromodulator nitric oxide, all have a role in integrating the thalamic mechanism into the cortical circuit. The essential point is that the perspective of higher-level sensory mechanisms shifts and modulates the thalamic circuitry in ways that optimize abstraction of a meaningful representation of the external world. This review is part of the TINS special issue on The Neural Substrates of Cognition.Ministerio de Ciencia y Tecnología; BFI2002–320
Parametric Trajectory Representations for Behaviour Classification
This paper presents an empirical comparison of strategies for representing motion trajectories with fixed-length vectors. We compare four techniques, which have all previously been adopted in the trajectory classification literature: least-squares cubic spline approximation, the Discrete Fourier Transform, Chebyshev polynomial approximation, and the Haar wavelet transform. We measure the class separability of five different trajectory datasets- ranging from vehicle trajectories to pen trajectories- when described in terms of these representations. Results obtained over a range of dimensionalities indicate that the different representations yield similar levels of class separability, with marginal improvements provided by Chebyshev and Spline representations. For the datasets considered here, each representation appears to yield better results when used in conjunction with a curve parametrisation strategy based on arc-length, rather than time. However, we illustrate a situation- pertinent to surveillance applications- where the converse is true
Engineering CD4+ T Cells to Enhance Cancer Immunity
This review presents key advances in combining T cell receptor (TCR) gene transfer to redirect T-cell specificity with gene engineering in order to enhance cancer-protective immune function. We discuss how emerging insights might be applied to CD4+ T cells. Although much attention has been paid to the role of CD8+ cytotoxic T cells in tumour protection, we provide convincing evidence that CD4+ helper T cells play a critical role in cancer immune responses in animal models and also in patients. We demonstrate that genetic engineering technologies provide exciting opportunities to extend the specificity range of CD4+ T cells from MHC class-II-presented epitopes to include peptides presented by MHC class I molecules. Functional enhancement of tumour immunity can improve the sensitivity of T cells to cancer antigens, promote survival in a hostile tumour microenvironment, boost cancer-protective effector mechanisms and enable the formation of T-cell memory. Engineered cancer-specific CD4+ T cells may contribute to protective immunity by a direct pathway involving cancer cell killing, and by an indirect pathway that boosts the function, persistence and memory formation of CD8+ T cells
Further observations on the role of nitric oxide in the feline lateral geniculate nucleus
[Abstract] We have examined the responses of a population of 77 cells in the dorsal lateral geniculate nucleus (dLGN) of the anaesthetized, paralysed cat. Here the synthetic enzyme for the production of nitric oxide, nitric oxide synthase, is found only in the presynaptic terminals of the cholinergic input from the brainstem. In our hands, iontophoretic application of inhibitors of this enzyme resulted both in significant decreases in visual responses and decreased responses to exogenous application of NMDA, effects which were reversed by coapplication of the natural substrate for nitric oxide synthase, L-arginine, but not the biologically inactive isomer, D-arginine. Nitroprusside and S-nitroso-N-acetylpenicillamine (SNAP), nitric oxide donors, but not L-arginine, were able to increase markedly both spontaneous activity and the responsiveness to NMDA application. Furthermore, SNAP application facilitated visual responses. Responses of cells in animals without retinal, cortical and parabrachial input to the LGN suggest a postsynaptic site of action of nitric oxide. This modulation of the gain of visual signals transmitted to the cortex suggests a completely novel pathway for nitric oxide regulation of function, as yet described only in primary sensory thalamus of the mammalian central nervous system.Ministerio de Educación y Ciencia; PB93-034
Always returning: feedback and sensory processing in visual cortex and thalamus
[Abstract] Feedback projections are an integral part of the mammalian visual system. Although it is tempting to relegate them to a subsidiary role in visual processing, because their supposed latency and lag might appear to be unfavourable for an involvement in fast processing, this is a dangerous simplification. Certainly for the world in motion, feedback from higher motion areas can influence the transfer of ascending input when, or even before, the input arrives. Here, we consider the circuit formed by layer 6 feedback cells in the visual cortex and how this straddles the retinothalamic and thalamocortical transfer of visual input. We discuss its links to feedback from the cortical motion area MT (V5), and suggest that motion perception involves a dynamic interplay between MT, V1 and the thalamus. This review is part of the TINS special issue on The Neural Substrates of Cognition
Incremental semi-supervised learning for anomalous trajectory detection
The acquisition of a scene-specific normal behaviour model underlies many existing
approaches to the problem of automated video surveillance. Since it is unrealistic
to acquire a comprehensive set of labelled behaviours for every surveyed scenario,
modelling normal behaviour typically corresponds to modelling the distribution of a
large collection of unlabelled examples. In general, however, it would be desirable to
be able to filter an unlabelled dataset to remove potentially anomalous examples.
This thesis proposes a simple semi-supervised learning framework that could allow
a human operator to efficiently filter the examples used to construct a normal behaviour
model by providing occasional feedback: Specifically, the classification output
of the model under construction is used to filter the incoming sequence of unlabelled
examples so that human approval is requested before incorporating any example classified
as anomalous, while all other examples are automatically used for training.
A key component of the proposed framework is an incremental one-class learning
algorithm which can be trained on a sequence of normal examples while allowing new
examples to be classified at any stage during training. The proposed algorithm represents
an initial set of training examples with a kernel density estimate, before using
merging operations to incrementally construct a Gaussian mixture model while minimising
an information-theoretic cost function. This algorithm is shown to outperform
an existing state-of-the-art approach without requiring off-line model selection.
Throughout this thesis behaviours are considered in terms of whole motion trajectories:
in order to apply the proposed algorithm, trajectories must be encoded
with fixed length vectors. To determine an appropriate encoding strategy, an empirical
comparison is conducted to determine the relative class-separability afforded
by several different trajectory representations for a range of datasets. The results obtained
suggest that the choice of representation makes a small but consistent difference
to class separability, indicating that cubic B-Spline control points (fitted using
least-squares regression) provide a good choice for use in subsequent experiments.
The proposed semi-supervised learning framework is tested on three different real
trajectory datasets. In all cases the rate of human intervention requests drops steadily,
reaching a usefully low level of 1% in one case. A further experiment indicates that
once a sufficient number of interventions has been provided, a high level of classification
performance can be achieved even if subsequent requests are ignored. The automatic
incorporation of unlabelled data is shown to improve classification performance
in all cases, while a high level of classification performance is maintained even when
unlabelled data containing a high proportion of anomalous examples is presented
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