Matching relevance features with ontological concepts

In order to comprehend user information needs by concepts, this paper introduces a novel method to match relevance features with ontological concepts. The method first discovers relevance features from user local instances. Then, a concept matching approach is developed for matching these features to accurate concepts in a global knowledge base. This approach is significant for the transition of informative descriptor and conceptional descriptor. The proposed method is elaborately evaluated by comparing against three information gathering baseline models. The experimental results shows the matching approach is successful and achieves a series of remarkable improvements on search effectiveness.

The Human Fertilisation and Embryology Act 2008 : restrictions on the creation of “saviour siblings” and the relevance of the harm principle

This paper provides an overview of the regulatory developments in the UK which impact on the use of in vitro fertilization (IVF) and embryo screening techniques for the creation of “saviour siblings.” Prior to the changes implemented under the Human Fertilisation and Embryology Act 2008, this specific use of IVF was not addressed by the legislative framework and regulated only by way of policy issued by the Human Fertilisation and Embryology Authority (HFEA). Following the implementation of the statutory reforms, a number of restrictive conditions are now imposed on the face of the legislation. This paper considers whether there is any justification for restricting access to IVF and pre-implantation tissue typing for the creation of “saviour siblings.” The analysis is undertaken by examining the normative factors that have guided the development of the UK regulatory approach prior to the 2008 legislative reforms. The approach adopted in relation to the “saviour sibling” issue is compared to more general HFEA policy, which has prioritized the notion of reproductive choice and determined that restrictions on access are only justified on the basis of harm considerations.

Open up the building : architectural relevance of building-users and their participations

As buildings have become more advanced and complex, our ability to understand how they are operated and managed has diminished. Modern technologies have given us systems to look after us but it appears to have taken away our say in how we like our environment to be managed. The aim of this paper is to discuss our research concerning spaces that are sensitive to changing needs and allow building-users to have a certain level of freedom to understand and control their environment. We discuss why, what we call the Active Layer, is needed in modern buildings; how building inhabitants are to interact with it; and the development of interface prototypes to test consequences of having the Active Layer in our environment.

A data mining framework for relevance feature discovery

This thesis is a study for automatic discovery of text features for describing user information needs. It presents an innovative data-mining approach that discovers useful knowledge from both relevance and non-relevance feedback information. The proposed approach can largely reduce noises in discovered patterns and significantly improve the performance of text mining systems. This study provides a promising method for the study of Data Mining and Web Intelligence.

Superactivation of metal electrode surfaces and its relevance to COads oxidation at fuel cell anodes

The inhibiting effect of COads on platinum-based anodes is a major problem in the development of ambient temperature, polyelectrolyte membrane-type fuel cells. One of the unusual features of the response for the oxidative removal of the species in question is that the response observed for this reaction in the positive sweep is highly dependent on the CO admission potential, for example, when the COads is formed in the Hads region it undergoes oxidation at unusually low potentials. Such behaviour is attributed here to hydrogen activation of the platinum surface, with the result that oxide mediators (and COads oxidation) occurs at an earlier stage of the positive sweep. It is also demonstrated, for both platinum and gold in acid solution, that dramatic premonolayer oxidation responses may be observed following suitable preactivation of the electrode surfaces. It is suggested that the defect state of a solid electrode surface is an important variable whose investigation may yield improved fuel cell anode performance.

Characteristics of nontuberculous mycobacteria from a municipal water distribution system and their relevance to human infections

This thesis documented pathogenic species of nontuberculous mycobacteria in the Brisbane water distribution system. When water and shower aerosol strains were compared with human strains of mycobacteria, the study found that the likelihood of acquiring infection from municipal water was specific for four main species. The method for isolation of mycobacteria from water was refined, followed by sampling from 220 sites across Brisbane. A variety of species (incl 15 pathogens) were identified and genotypically compared to human strains. For M. abscessus and M. lentiflavum, water strains clustered with human strains. Pathogenic strains of M. kansasii were found, though non-pathogenic strains dominated. Waterborne strains of M. fortuitum differed to human strains. Extensive home sampling of 20 patients with NTM disease, supported the theory that the risk of acquiring NTM from water or shower aerosols appears species specific for M. avium, M. kansasii, M. lentiflavum and M. abscessus.

A reciprocal collaborative method using relevance feedback and feature importance

In a people-to-people matching systems, filtering is widely applied to find the most suitable matches. The results returned are either too many or only a few when the search is generic or specific respectively. The use of a sophisticated recommendation approach becomes necessary. Traditionally, the object of recommendation is the item which is inanimate. In online dating systems, reciprocal recommendation is required to suggest a partner only when the user and the recommended candidate both are satisfied. In this paper, an innovative reciprocal collaborative method is developed based on the idea of similarity and common neighbors, utilizing the information of relevance feedback and feature importance. Extensive experiments are carried out using data gathered from a real online dating service. Compared to benchmarking methods, our results show the proposed method can achieve noticeable better performance.

But what makes it doctoral? Taking on the traditionalists : interdisciplinary, practice-led doctoral research in the creative industries - a case study in academic politics, research, rigour and relevance

This paper examines a Doctoral journey of interdisciplinary exploration, explication, examination...and exasperation. In choosing to pursue a practice-led doctorate I had determined from the outset that ‘writing 100,000 words that only two people ever read’, was not something which interested me. Hence, the oft-asked question of ‘what kind of doctorate’ I was engaged in, consistently elicited the response, “a useful one”. In order to satisfy my own imperatives of authenticity and usefulness, my doctoral research had to clearly demonstrate relevance to; productively inform; engage with; and add value to: wider professional field(s) of practice; students in the university courses I teach; and the broader community - not just the academic community. Consequently, over the course of my research, the question, ‘But what makes it Doctoral?’ consistently resounded and resonated. Answering that question, to satisfy not only the traditionalists asking it but, perhaps surprisingly, some academic innovators - and more particularly, myself as researcher - revealed academic/political inconsistencies and issues which challenged both the fundamental assumptions and actuality of practice-led research. This paper examines some of those inconsistencies, issues and challenges and provides at least one possible answer to the question: ‘But what makes it Doctoral?’

Enhanced n-gram extraction using relevance feature discovery

Guaranteeing the quality of extracted features that describe relevant knowledge to users or topics is a challenge because of the large number of extracted features. Most popular existing term-based feature selection methods suffer from noisy feature extraction, which is irrelevant to the user needs (noisy). One popular method is to extract phrases or n-grams to describe the relevant knowledge. However, extracted n-grams and phrases usually contain a lot of noise. This paper proposes a method for reducing the noise in n-grams. The method first extracts more specific features (terms) to remove noisy features. The method then uses an extended random set to accurately weight n-grams based on their distribution in the documents and their terms distribution in n-grams. The proposed approach not only reduces the number of extracted n-grams but also improves the performance. The experimental results on Reuters Corpus Volume 1 (RCV1) data collection and TREC topics show that the proposed method significantly outperforms the state-of-art methods underpinned by Okapi BM25, tf*idf and Rocchio.

A topic based document relevance ranking model

Topic modelling has been widely used in the fields of information retrieval, text mining, machine learning, etc. In this paper, we propose a novel model, Pattern Enhanced Topic Model (PETM), which makes improvements to topic modelling by semantically representing topics with discriminative patterns, and also makes innovative contributions to information filtering by utilising the proposed PETM to determine document relevance based on topics distribution and maximum matched patterns proposed in this paper. Extensive experiments are conducted to evaluate the effectiveness of PETM by using the TREC data collection Reuters Corpus Volume 1. The results show that the proposed model significantly outperforms both state-of-the-art term-based models and pattern-based models.

Prognostic and therapeutic relevance of FLIP and procaspase-8 overexpression in non-small cell lung cancer

Non-small cell lung carcinoma remains by far the leading cause of cancer-related deaths worldwide. Overexpression of FLIP, which blocks the extrinsic apoptotic pathway by inhibiting caspase-8 activation, has been identified in various cancers. We investigated FLIP and procaspase-8 expression in NSCLC and the effect of HDAC inhibitors on FLIP expression, activation of caspase-8 and drug resistance in NSCLC and normal lung cell line models. Immunohistochemical analysis of cytoplasmic and nuclear FLIP and procaspase-8 protein expression was carried out using a novel digital pathology approach. Both FLIP and procaspase-8 were found to be significantly overexpressed in tumours, and importantly, high cytoplasmic expression of FLIP significantly correlated with shorter overall survival. Treatment with HDAC inhibitors targeting HDAC1-3 downregulated FLIP expression predominantly via post-transcriptional mechanisms, and this resulted in death receptor- and caspase-8-dependent apoptosis in NSCLC cells, but not normal lung cells. In addition, HDAC inhibitors synergized with TRAIL and cisplatin in NSCLC cells in a FLIP- and caspase-8-dependent manner. Thus, FLIP and procaspase-8 are overexpressed in NSCLC, and high cytoplasmic FLIP expression is indicative of poor prognosis. Targeting high FLIP expression using HDAC1-3 selective inhibitors such as entinostat to exploit high procaspase-8 expression in NSCLC has promising therapeutic potential, particularly when used in combination with TRAIL receptor-targeted agents.

Langerhans cells in the cornea of diabetic patients : relevance to diabetic neuropathy

Purpose The presence of a lymphocytic infiltration in autonomic ganglia and an increased prevalence of autoantibodies and iritis in diabetic patients with autonomic neuropathy suggests a role for autoimmune mechanisms in the development of diabetic and perhaps somatic neuropathy. Corneal Langerhans cells are antigenpresenting cells which can be identified in corneal immunologic conditions using in-vivo confocal microscopy. The aim of this study was to assess the presence and density of Langerhans cells (LCs) in Bowman’s layer of the cornea in diabetic patients with varying degrees of neuropathy compared to healthy control subjects. Method 128 diabetic patients aged 58±1 years with differing severity of neuropathy (NDS – 4.7±0.28) and 26 control subjects aged 53±3 years were examined with in-vivo corneal confocal microscopy to quantify the density of “Langerhans cells” (LCs). Results LCs were observed more often in diabetic patients (73.8%) compared to control subjects (46.1%), P = 0.001. The LC density (number/mm2) was also significantly increased in diabetic patients (17.73±1.45) compared to control subjects (6.94±1.58, P = 0.001). There was a significant correlation between the density of LCs with age (r = 0.162, P = 0.047) and severity of neuropathy assessed by NDS (r =−0.202, P = 0.02). Conclusions In vivo corneal confocal microscopy enables quantification of Langerhans cells in Bowman’s layer of the cornea. There is a relationship between density of LCs and the degree of nerve damage. Corneal confocal microscopy could be a valuable tool to establish the role of immune mediated corneal nerve damage and provide insights into the pathogenesis of diabetic neuropathy.

Back to the roots : mean-variance analysis of relevance estimations

Recently, mean-variance analysis has been proposed as a novel paradigm to model document ranking in Information Retrieval. The main merit of this approach is that it diversifies the ranking of retrieved documents. In its original formulation, the strategy considers both the mean of relevance estimates of retrieved documents and their variance. How- ever, when this strategy has been empirically instantiated, the concepts of mean and variance are discarded in favour of a point-wise estimation of relevance (to replace the mean) and of a parameter to be tuned or, alternatively, a quantity dependent upon the document length (to replace the variance). In this paper we revisit this ranking strategy by going back to its roots: mean and variance. For each retrieved document, we infer a relevance distribution from a series of point-wise relevance estimations provided by a number of different systems. This is used to compute the mean and the variance of document relevance estimates. On the TREC Clueweb collection, we show that this approach improves the retrieval performances. This development could lead to new strategies to address the fusion of relevance estimates provided by different systems.

Fault diagnosis of low speed bearing based on acoustic emission signal and multi-class relevance vector machine

This study presents an acoustic emission (AE) based fault diagnosis for low speed bearing using multi-class relevance vector machine (RVM). A low speed test rig was developed to simulate the various defects with shaft speeds as low as 10 rpm under several loading conditions. The data was acquired using anAEsensor with the test bearing operating at a constant loading (5 kN) andwith a speed range from20 to 80 rpm. This study is aimed at finding a reliable method/tool for low speed machines fault diagnosis based on AE signal. In the present study, component analysis was performed to extract the bearing feature and to reduce the dimensionality of original data feature. The result shows that multi-class RVM offers a promising approach for fault diagnosis of low speed machines.

The relevance of shared experiences : a multi-level study of collective efficacy as a moderator of job control in the stressor-strain relationship

Karasek's Job Demand-Control model proposes that control mitigates the positive effects of work stressors on employee strain. Evidence to date remains mixed and, although a number of individual-level moderators have been examined, the role of broader, contextual, group factors has been largely overlooked. In this study, the extent to which control buffered or exacerbated the effects of demands on strain at the individual level was hypothesized to be influenced by perceptions of collective efficacy at the group level. Data from 544 employees in Australian organizations, nested within 23 workgroups, revealed significant three-way cross-level interactions among demands, control and collective efficacy on anxiety and job satisfaction. When the group perceived high levels of collective efficacy, high control buffered the negative consequences of high demands on anxiety and satisfaction. Conversely, when the group perceived low levels of collective efficacy, high control exacerbated the negative consequences of high demands on anxiety, but not satisfaction. In addition, a stress-exacerbating effect for high demands on anxiety and satisfaction was found when there was a mismatch between collective efficacy and control (i.e. combined high collective efficacy and low control). These results provide support for the notion that the stressor-strain relationship is moderated by both individual- and group-level factors.