Spectrally compact optical subcarrier multiplexing with 42.6Gbit/s AM-PSK payload and 2.5 Gbit/s NRZ labels

A novel approach to optical subcarrier multiplexing with compact spectrum is demonstrated using a 42.6 Gbit/s AM-PSK payload and 2.5 Gbit/s NRZ label. In this implementation, the payload introduces a 4.8 dB penalty on the label receiver sensitivity, and the label causes <1 dB penalty on the payload receiver sensitivity.

A facial expression for anxiety

Anxiety and fear are often confounded in discussions of human emotions. However, studies of rodent defensive reactions under naturalistic conditions suggest anxiety is functionally distinct from fear. Unambiguous threats, such as predators, elicit flight from rodents (if an escape-route is available), whereas ambiguous threats (e.g., the odor of a predator) elicit risk assessment behavior, which is associated with anxiety as it is preferentially modulated by anti-anxiety drugs. However, without human evidence, it would be premature to assume that rodent-based psychological models are valid for humans. We tested the human validity of the risk assessment explanation for anxiety by presenting 8 volunteers with emotive scenarios and asking them to pose facial expressions. Photographs and videos of these expressions were shown to 40 participants who matched them to the scenarios and labeled each expression. Scenarios describing ambiguous threats were preferentially matched to the facial expression posed in response to the same scenario type. This expression consisted of two plausible environmental-scanning behaviors (eye darts and head swivels) and was labeled as anxiety, not fear. The facial expression elicited by unambiguous threat scenarios was labeled as fear. The emotion labels generated were then presented to another 18 participants who matched them back to photographs of the facial expressions. This back-matching of labels to faces also linked anxiety to the environmental-scanning face rather than fear face. Results therefore suggest that anxiety produces a distinct facial expression and that it has adaptive value in situations that are ambiguously threatening, supporting a functional, risk-assessing explanation for human anxiety.

Training Bayesian networks for image segmentation

We are concerned with the problem of image segmentation in which each pixel is assigned to one of a predefined finite number of classes. In Bayesian image analysis, this requires fusing together local predictions for the class labels with a prior model of segmentations. Markov Random Fields (MRFs) have been used to incorporate some of this prior knowledge, but this not entirely satisfactory as inference in MRFs is NP-hard. The multiscale quadtree model of Bouman and Shapiro (1994) is an attractive alternative, as this is a tree-structured belief network in which inference can be carried out in linear time (Pearl 1988). It is an hierarchical model where the bottom-level nodes are pixels, and higher levels correspond to downsampled versions of the image. The conditional-probability tables (CPTs) in the belief network encode the knowledge of how the levels interact. In this paper we discuss two methods of learning the CPTs given training data, using (a) maximum likelihood and the EM algorithm and (b) emphconditional maximum likelihood (CML). Segmentations obtained using networks trained by CML show a statistically-significant improvement in performance on synthetic images. We also demonstrate the methods on a real-world outdoor-scene segmentation task.

An investigation into children’s inductive reasoning strategies:What drives the development of category induction?

In a series of studies, I investigated the developmental changes in children’s inductive reasoning strategy, methodological manipulations affecting the trajectory, and driving mechanisms behind the development of category induction. I systematically controlled the nature of the stimuli used, and employed a triad paradigm in which perceptual cues were directly pitted against category membership, to explore under which circumstances children used perceptual or category induction. My induction tasks were designed for children aged 3-9 years old using biologically plausible novel items. In Study 1, I tested 264 children. Using a wide age range allowed me to systematically investigate the developmental trajectory of induction. I also created two degrees of perceptual distractor – high and low – and explored whether the degree of perceptual similarity between target and test items altered children’s strategy preference. A further 52 children were tested in Study 2, to examine whether children showing a perceptual-bias were in fact basing their choice on maturation categories. A gradual transition was observed from perceptual to category induction. However, this transition could not be due to the inability to inhibit high perceptual distractors as children of all ages were equally distracted. Children were also not basing their strategy choices on maturation categories. In Study 3, I investigated category structure (featural vs. relational category rules) and domain (natural vs. artefact) on inductive preference. I tested 403 children. Each child was assigned to either the featural or relational condition, and completed both a natural kind and an artefact task. A further 98 children were tested in Study 4, on the effect of using stimuli labels during the tasks. I observed the same gradual transition from perceptual to category induction preference in Studies 3 and 4. This pattern was stable across domains, but children developed a category-bias one year later for relational categories, arguably due to the greater demands on executive function (EF) posed by these stimuli. Children who received labels during the task made significantly more category choices than those who did not receive labels, possibly due to priming effects. Having investigated influences affecting the developmental trajectory, I continued by exploring the driving mechanism behind the development of category induction. In Study 5, I tested 60 children on a battery of EF tasks as well as my induction task. None of the EF tasks were able to predict inductive variance, therefore EF development is unlikely to be the driving factor behind the transition. Finally in Study 6, I divided 252 children into either a comparison group or an intervention group. The intervention group took part in an interactive educational session at Twycross Zoo about animal adaptations. Both groups took part in four induction tasks, two before and two a week after the zoo visits. There was a significant increase in the number of category choices made in the intervention condition after the zoo visit, a result not observed in the comparison condition. This highlights the role of knowledge in supporting the transition from perceptual to category induction. I suggest that EF development may support induction development, but the driving mechanism behind the transition is an accumulation of knowledge, and an appreciation for the importance of category membership.

Spatially clustered associations in health GIS

Overlaying maps using a desktop GIS is often the first step of a multivariate spatial analysis. The potential of this operation has increased considerably as data sources and Web services to manipulate them are becoming widely available via the Internet. Standards from the OGC enable such geospatial mashups to be seamless and user driven, involving discovery of thematic data. The user is naturally inclined to look for spatial clusters and correlation of outcomes. Using classical cluster detection scan methods to identify multivariate associations can be problematic in this context, because of a lack of control on or knowledge about background populations. For public health and epidemiological mapping, this limiting factor can be critical but often the focus is on spatial identification of risk factors associated with health or clinical status. Spatial entropy index HSu for the ScankOO analysis of the hypothetical dataset using a vicinity which is fixed by the number of points without distinction between their labels. (The size of the labels is proportional to the inverse of the index) In this article we point out that this association itself can ensure some control on underlying populations, and develop an exploratory scan statistic framework for multivariate associations. Inference using statistical map methodologies can be used to test the clustered associations. The approach is illustrated with a hypothetical data example and an epidemiological study on community MRSA. Scenarios of potential use for online mashups are introduced but full implementation is left for further research.

The impact of brand owner on consumers' brand perceptions : a development of Heider's Balance Theory

Studies have shown that the brand “owner” is very influential in positioning the brand and when the brand “owner” ceases his or her active role the brand will be perceived differently by the consumers. Balance Theory (HBT), a cognitive psychological theory, studies the triadic relationships between two persons and an entity and predicts that when a person’s original perception of the relationship is disturbed, the person restructures to a new balanced perception. Consequently, this research was undertaken to: conceptualize the brand owner’s impact on consumer’s brand perception; test the applicability of both the static and dynamic predictions of the Heider’s Balance Theory in brand owner-consumer-brand relation (OCB); construct and test a model of brand owner-consumer-brand relation; and examine if personality has an influence on OCB. A discovery-oriented approach was taken to understand the selected market segment, the ready-to-wear and diffusion lines of international designer labels. Chinese Brand Personality Scale, fashion proneness and hedonic and utilitarian shopping scales were developed, and validated. 51 customers were surveyed. Both traditional and extended methods used in the Balance Theory were employed in this study. Responses to liked brand have been used to test and develop the model, while those for disliked brand were used for test and confirmation. A “what if’ experimental approach was employed to test the applicability of dynamic HBT theory in OCB Model. The hypothesized OCB Model has been tested and validated. Consumers have been found to have separate views on the brand and the brand owner; and their responses to contrasting ethical and non-ethical news of the brand owner are different. Personality has been found to have an influence and two personality adapted models have been tested and validated. The actual results go beyond the prediction of the Balance Theory. Dominant triple positive balance mode, dominant negative balance mode, and mode of extreme antipathy have been found. It has been found that not all balanced modes are good for the brand. Contrary to Heider’s findings, simply liking may not necessarily lead to unit relation in the OCB Model.

Individual differences in human-computer interaction

This thesis initially presents an 'assay' of the literature pertaining to individual differences in human-computer interaction. A series of experiments is then reported, designed to investigate the association between a variety of individual characteristics and various computer task and interface factors. Predictor variables included age, computer expertise, and psychometric tests of spatial visualisation, spatial memory, logical reasoning, associative memory, and verbal ability. These were studied in relation to a variety of computer-based tacks, including: (1) word processing and its component elements; (ii) the location of target words within passages of text; (iii) the navigation of networks and menus; (iv) command generation using menus and command line interfaces; (v) the search and selection of icons and text labels; (vi) information retrieval. A measure of self-report workload was also included in several of these experiments. The main experimental findings included: (i) an interaction between spatial ability and the manipulation of semantic but not spatial interface content; (ii) verbal ability being only predictive of certain task components of word processing; (iii) age differences in word processing and information retrieval speed but not accuracy; (iv) evidence of compensatory strategies being employed by older subjects; (v) evidence of performance strategy differences which disadvantaged high spatial subjects in conditions of low spatial information content; (vi) interactive effects of associative memory, expertise and command strategy; (vii) an association between logical reasoning and word processing but not information retrieval; (viii) an interaction between expertise and cognitive demand; and (ix) a stronger association between cognitive ability and novice performance than expert performance.

In vivo and in vitro aspects of imidazoline-2(1/2)sites within the central nervous system

The in vivo and in vitro characteristics of the I2 binding site were probed using the technique of drug discrimination and receptor autoradiography. Data presented in this thesis indicates the I2 ligand 2-BFI generates a cue in drug discrimination. Further studies indicated agmatine, a proposed endogenous imidazoline ligand, and a number of imidazoline and imidazole analogues of 2-BFI substitute significantly for 2-BFI. In addition to specific I2 ligands the administration of NRl's (noradrenaline reuptake inhibitors), the sympathomimetic d-amphetamine, the α1-adrenoceptor agonist methoxamine, but not the β1 agonist dobutamine or the β2 agonist salbutamol, gave rise to significant levels of substitution for the 2-BFI cue. The administration of the α1-adrenoceptor antagonist WB4101, prior to 2- BFI itself significantly reduced levels of 2-BFI appropriate responding. Administration of the reversible MAO-A inhibitors moclobemide and Ro41-1049, but not the reversible MAO-B inhibitors lazabemide and Ro16-6491, gave rise to potent dose dependent levels of substitution for the 2-BFI cue. Further studies indicated the administration of a number of β-carbolines and the structurally related indole alkaloid ibogaine also gave rise to dose dependent significant levels of substitution. Due to the relationship of indole alkaloids to serotonin the 5-HT releaser fenfluramine and a number of SSRI's (selective serotonin reuptake inhibitor) were also administered and these compounds gave rise to significant partial (20-80% responses to the 2-BFI lever) levels of substitution. The autoradiographical studies reported here indicate [3H]2-BFI labels I2 sites within the rat arcuate nucleus, area postrema, pineal gland, interpeduncular nucleus and subfornical organ. Subsequent experiments confirmed that the drug discrimination dosing schedule significantly increases levels of [3H]2-BFI 12 binding within two of these nuclei. However, levels of [3H]2-BFI specific binding were significantly reduced within four of these nuclei after chronic treatment with the irreversible MAO inhibitors deprenyl and tranylcypromine but not pargyline, which only reduced levels significantly in two. Further autoradiographical studies indicated that the distribution of [3H]2-BFI within the C57/B mouse compares favourably to that within the rat. Comparison of these levels of binding to those from transgenic mice who over-express MAO-B indicates two possibly distinct populations of [3H]2-BFI 12 sites exist in mouse brain. The data presented here indicates the 2-BFI cue is associated with the selective activation of α1-adrenoceptors and possibly 5-HT receptors. 2-BFI trained rats recognise reversible MAO-A but not MAO-B inhibitors. However, data within this thesis indicates the autoradiographical distribution of I2 sites bears a closer resemblance to that of MAO-B not MAO-A and further studies using transgenic mice that over-express MAO-B suggests a non-MAO-B I2 site exists in mouse brain.

Synthesis, crystallography and biological activity of myo-inositol phosphates

The antioxidant property of myo-inositol hexakisphosphate is important in the prevention of hydroxyl radical formation which may allow it to act as a 'safe' carrier of iron within the cell. Here, the hypothesis that the recently discovered natural product, myo-inositol 1,2,3-trisphosphate represents the simplest structure to mimic phytate's antioxidant activity has been tested. The first synthesis of myo-inositol 1,2,3-trisphosphate has been completed, along with its X-ray structure determination and that of key synthetic intermediates. Iron binding studies of myo-inositol 1,2,3-trisphosphate demonstrated that phosphate groups with the equatorial-axial-equatorial conformation are required for complete inhibition of hydroxyl radical formation. myo-Inositol monophosphatase is a key enzyme in recycling myo-inositol from its monophosphates in the brain and its inhibition is implicated in lithium's antimanic properties. Current synthetic strategies require inositol compounds to be protected (often with more than one group), resolved, phosphorylated and deprotected to produce the desired optically active myo-inositol phosphates. Here, the synthesis of myo-inositol 3-phosphate has been achieved in only 4 steps from myo-inositol. The stereoselective addition of the chiral phosphorylating agent (2R,4S,5R)-2-chloro-3,4-dimethyl-5-phenyl-1,3,2-oxazaphospholidin-2-one to a protected inositol intermediate allowed separation of diastereoisomers and easy deprotection to myo-inositol 3-phosphate. This strategy also allows the possible introduction of labels of oxygen and sulphur to give a thiophosphate of known stereochemistry at phosphorus which would be useful for the analysis of the stereochemical course of phosphate hydrolysis catalysed by inositol monophosphatase.

Individual differences in the sensory perception of fats

Excessive consumption of dietary fat is acknowledged to be a widespread problem linked to a range of medical conditions. Despite this, little is known about the specific sensory appeal held by fats and no previous published research exists concerning human perception of non-textural taste qualities in fats. This research aimed to address whether a taste component can be found in sensory perception of pure fats. It also examined whether individual differences existed in human taste responses to fat, using both aggregated data analysis methods and multidimensional scaling. Results indicated that individuals were able to detect both the primary taste qualities of sweet, salty, sour and bitter in pure processed oils and reliably ascribe their own individually-generated taste labels, suggested that a taste component may be present in human responses to fat. Individual variation appeared to exist, both in the perception of given taste qualities and in perceived intensity and preferences. A number of factors were examined in relation to such individual differences in taste perception, including age, gender, genetic sensitivity to 6-n-propylthiouracil, body mass, dietary preferences and intake, dieting behaviours and restraint. Results revealed that, to varying extents, gender, age, sensitivity to 6-n-propylthiouracil, dietary preferences, habitual dietary intake and restraint all appeared to be related to individual variation in taste responses to fat. However, in general, these differences appeared to exist in the form of differing preferences and levels of intensity with which taste qualities detected in fat were perceived, as opposed to the perception of specific taste qualities being associated with given traits or states. Equally, each of these factors appeared to exert only a limited influence upon variation in sensory responses and thus the potential for using taste responses to fats as a marker for issues such as over-consumption, obesity or eating disorder is at present limited.

The application of artificial neural networks to the interpretation and classification of freshwater benthic invertebrate communities

This thesis presents a thorough and principled investigation into the application of artificial neural networks to the biological monitoring of freshwater. It contains original ideas on the classification and interpretation of benthic macroinvertebrates, and aims to demonstrate their superiority over the biotic systems currently used in the UK to report river water quality. The conceptual basis of a new biological classification system is described, and a full review and analysis of a number of river data sets is presented. The biological classification is compared to the common biotic systems using data from the Upper Trent catchment. This data contained 292 expertly classified invertebrate samples identified to mixed taxonomic levels. The neural network experimental work concentrates on the classification of the invertebrate samples into biological class, where only a subset of the sample is used to form the classification. Other experimentation is conducted into the identification of novel input samples, the classification of samples from different biotopes and the use of prior information in the neural network models. The biological classification is shown to provide an intuitive interpretation of a graphical representation, generated without reference to the class labels, of the Upper Trent data. The selection of key indicator taxa is considered using three different approaches; one novel, one from information theory and one from classical statistical methods. Good indicators of quality class based on these analyses are found to be in good agreement with those chosen by a domain expert. The change in information associated with different levels of identification and enumeration of taxa is quantified. The feasibility of using neural network classifiers and predictors to develop numeric criteria for the biological assessment of sediment contamination in the Great Lakes is also investigated.

Under the influence? The construction of foetal alcohol syndrome in UK newspapers

Today, alongside many other proscriptions, women are expected to abstain or at least limit their alcohol consumption during pregnancy. This advice is reinforced through warning labels on bottles and cans of alcoholic drinks. In most (but not all) official policies, this is linked to a risk of Foetal Alcohol Syndrome (FAS) or one of its associated conditions. However, given that there is little medical evidence that low levels of alcohol consumption have an adverse impact on the foetus, we need to examine broader societal ideas to explain why this has now become a policy concern. This paper presents a quantitative and qualitative assessment of analysis of the media in this context. By analysing the frames over time, this paper will trace the emergence of concerns about alcohol consumption during pregnancy. It will argue that contemporary concerns about FAS are framed around a number of pre-existing discourses including alcohol consumption as a social problem, heightened concerns about children at risk and shifts in ideas about the responsibility of motherhood including during the pre-conception and pregnancy periods. Whilst the newspapers regularly carried critiques of the abstinence position now advocated, these challenges focused did little to refute current parenting cultures.

FASTtrack applied pharmaceutical practice

This revision guide takes the student pharmacist or pharmacy technician through the main stages involved in pharmaceutical dispensing. It gives bullet points of basic information on applied pharmacy practice followed by questions and answers. This reference text accompanies the compulsory dispensing courses found in all undergraduate MPharm programmes and equivalent technical training courses. Changes for the new edition include: * Information on revisions to the community pharmacy contract. * Additional content on new advanced community pharmacy services. * Revised worked examples and student questions. * Updated prescription labelling information, including the use of new cautionary and warning labels. * Updated references and bibliography.

Learning task specific distributed paragraph representations using a 2-tier convolutional neural network

We introduce a type of 2-tier convolutional neural network model for learning distributed paragraph representations for a special task (e.g. paragraph or short document level sentiment analysis and text topic categorization). We decompose the paragraph semantics into 3 cascaded constitutes: word representation, sentence composition and document composition. Specifically, we learn distributed word representations by a continuous bag-of-words model from a large unstructured text corpus. Then, using these word representations as pre-trained vectors, distributed task specific sentence representations are learned from a sentence level corpus with task-specific labels by the first tier of our model. Using these sentence representations as distributed paragraph representation vectors, distributed paragraph representations are learned from a paragraph-level corpus by the second tier of our model. It is evaluated on DBpedia ontology classification dataset and Amazon review dataset. Empirical results show the effectiveness of our proposed learning model for generating distributed paragraph representations.

Self-training from labeled features for sentiment analysis

Sentiment analysis concerns about automatically identifying sentiment or opinion expressed in a given piece of text. Most prior work either use prior lexical knowledge defined as sentiment polarity of words or view the task as a text classification problem and rely on labeled corpora to train a sentiment classifier. While lexicon-based approaches do not adapt well to different domains, corpus-based approaches require expensive manual annotation effort. In this paper, we propose a novel framework where an initial classifier is learned by incorporating prior information extracted from an existing sentiment lexicon with preferences on expectations of sentiment labels of those lexicon words being expressed using generalized expectation criteria. Documents classified with high confidence are then used as pseudo-labeled examples for automatical domain-specific feature acquisition. The word-class distributions of such self-learned features are estimated from the pseudo-labeled examples and are used to train another classifier by constraining the model's predictions on unlabeled instances. Experiments on both the movie-review data and the multi-domain sentiment dataset show that our approach attains comparable or better performance than existing weakly-supervised sentiment classification methods despite using no labeled documents.