Vision 2020 - A whole life-cycle information management system for built environments

A whole life-cycle information management vision is proposed, the organizational requirements for the realization of the scenario is investigated. Preliminary interviews with construction professionals are reported. Discontinuities at information transfer throughout life-cycle of built environments are resulting from lack of coordination and multiple data collection/storage practices. A more coherent history of these activities can improve the work practices of various teams by augmenting decision making processes and creating organizational learning opportunities. Therefore, there is a need for unifying these fragmented bits of data to create a meaningful, semantically rich and standardized information repository for built environment. The proposed vision utilizes embedded technologies and distributed building information models. Two diverse construction project types (large one-off design, small repetitive design) are investigated for the applicability of the vision. A functional prototype software/hardware system for demonstrating the practical use of this vision is developed and discussed. Plans for case-studies for validating the proposed model at a large PFI hospital and housing association projects are discussed.

In vitro study on gas generation and prebiotic effects of some carbohydrates and their mixtures

This study was carried out to examine the effect or inulin (IN), fructooligosaccharide (FOS), polydextrose (POL) and isomaltooligosaccharides (ISO), alone and in combination, on gas production, gas composition and prebiotic effects. Static batch culture fermentation was performed with faecal samples from three healthy volunteers to study the volume and composition of gas generated and changes in bacterial populations. Four carbohydrates alone or mixed with one another (50:50) were examined. Prebiotic index (PI) was calculated and used to compare the prebiotic effect. The high amount of gas produced by IN was reduced by mixing it with FOS. No reduction in gas generation was observed when POL and ISO mixed with other substrates. It was found that the mixture of IN and FOS was effective in reducing the amount of gas produced while augmenting or maintaining their potential to Support the growth of bifidobacteria in Faecal batch culture as the highest PI was achieved with FOS alone and a mixture of FOS and IN. It was also found that high volume of gas was generated in presence of POL and ISO and they had lower prebiotic effect. The results of this study imply that a Mixture of prebiotics could prove effective in reducing the amount of gas generated by the gut microflora. (c) 2007 Elsevier Ltd. All rights reserved.

Immersive open surgery simulation

Realistic medical simulation has great potential for augmenting or complimenting traditional medical training or surgery planning, and Virtual Reality (VR) is a key enabling technology for delivering this goal. Although, medical simulators are now widely used in medical institutions, the majority of them are still reliant on desktop monitor displays, and many are restricted in their modelling capability to minimally invasive or endoscopic surgery scenarios. Whilst useful, such models lack the realism and interaction of the operating theatre. In this paper, we describe how we are advancing the technology by simulating open surgery procedures in an Immersive Projection Display CAVE environment thereby enabling medical practitioners to interact with their virtual patients in a more realistic manner.

Vertex splitting and connectivity augmentation in hypergraphs

We consider problems of splitting and connectivity augmentation in hypergraphs. In a hypergraph G = (V +s, E), to split two edges su, sv, is to replace them with a single edge uv. We are interested in doing this in such a way as to preserve a defined level of connectivity in V . The splitting technique is often used as a way of adding new edges into a graph or hypergraph, so as to augment the connectivity to some prescribed level. We begin by providing a short history of work done in this area. Then several preliminary results are given in a general form so that they may be used to tackle several problems. We then analyse the hypergraphs G = (V + s, E) for which there is no split preserving the local-edge-connectivity present in V. We provide two structural theorems, one of which implies a slight extension to Mader’s classical splitting theorem. We also provide a characterisation of the hypergraphs for which there is no such “good” split and a splitting result concerned with a specialisation of the local-connectivity function. We then use our splitting results to provide an upper bound on the smallest number of size-two edges we must add to any given hypergraph to ensure that in the resulting hypergraph we have λ(x, y) ≥ r(x, y) for all x, y in V, where r is an integer valued, symmetric requirement function on V*V. This is the so called “local-edge-connectivity augmentation problem” for hypergraphs. We also provide an extension to a Theorem of Szigeti, about augmenting to satisfy a requirement r, but using hyperedges. Next, in a result born of collaborative work with Zoltán Király from Budapest, we show that the local-connectivity augmentation problem is NP-complete for hypergraphs. Lastly we concern ourselves with an augmentation problem that includes a locational constraint. The premise is that we are given a hypergraph H = (V,E) with a bipartition P = {P1, P2} of V and asked to augment it with size-two edges, so that the result is k-edge-connected, and has no new edge contained in some P(i). We consider the splitting technique and describe the obstacles that prevent us forming “good” splits. From this we deduce results about which hypergraphs have a complete Pk-split. This leads to a minimax result on the optimal number of edges required and a polynomial algorithm to provide an optimal augmentation.

View-based modelling of human visual navigation errors

View-based and Cartesian representations provide rival accounts of visual navigation in humans, and here we explore possible models for the view-based case. A visual “homing” experiment was undertaken by human participants in immersive virtual reality. The distributions of end-point errors on the ground plane differed significantly in shape and extent depending on visual landmark configuration and relative goal location. A model based on simple visual cues captures important characteristics of these distributions. Augmenting visual features to include 3D elements such as stereo and motion parallax result in a set of models that describe the data accurately, demonstrating the effectiveness of a view-based approach.

Predicting stock index volatility: can market volume help?

This paper explores a number of statistical models for predicting the daily stock return volatility of an aggregate of all stocks traded on the NYSE. An application of linear and non-linear Granger causality tests highlights evidence of bidirectional causality, although the relationship is stronger from volatility to volume than the other way around. The out-of-sample forecasting performance of various linear, GARCH, EGARCH, GJR and neural network models of volatility are evaluated and compared. The models are also augmented by the addition of a measure of lagged volume to form more general ex-ante forecasting models. The results indicate that augmenting models of volatility with measures of lagged volume leads only to very modest improvements, if any, in forecasting performance.

Computerised therapies for anxiety and depression in children and young people: a systematic review and meta-anaylsis

One quarter of children and young people (CYP) experience anxiety and/or depression before adulthood, but treatment is sometimes unavailable or inadequate. Self-help interventions may have a role in augmenting treatment and this work aimed to systematically review the evidence for computerised anxiety and depression interventions in CYP aged 5–25 years old. Databases were searched for randomised controlled trials and 27 studies were identified. For young people (12–25 years) with risk of diagnosed anxiety disorders or depression, computerised CBT (cCBT) had positive effects for symptoms of anxiety (SMD −0.77, 95% CI −1.45 to −0.09, k = 6, N = 220) and depression (SMD −0.62, 95% CI −1.13 to −0.11, k = 7, N = 279). In a general population study of young people, there were small positive effects for anxiety (SMD −0.15, 95% CI −0.26 to −0.03; N = 1273) and depression (SMD −0.15, 95% CI −0.26 to −0.03; N = 1280). There was uncertainty around the effectiveness of cCBT in children (5–11 years). Evidence for other computerised interventions was sparse and inconclusive. Computerised CBT has potential for treating and preventing anxiety and depression in clinical and general populations of young people. Further program development and research is required to extend its use and establish its benefit in children.

littleBits go LARGE: making electronics more accessible to people with learning disabilities

The “littleBits go LARGE" project extends littleBits electronic modules, an existing product that is aimed at simplifying electronics for a wide range of audiences. In this project we augment the littleBits modules to make them more accessible to people with learning disabilities. We will demonstrate how we have made the modules easier to handle and manipulate physically, and how we are augmenting the design of the modules to make their functions more obvious and understandable.

Targeted activation of toll-like receptors: conjugation of a toll-like receptor 7 agonist to a monoclonal antibody maintains antigen binding and specificity

Therapeutic activation of Toll-like receptors (TLR) has potential for cancer immunotherapy, for augmenting the activity of anti-tumor monoclonal antibodies (mAbs), and for improved vaccine adjuvants. A previous attempt to specifically target TLR agonists to dendritic cells (DC) using mAbs failed because conjugation led to non-specific binding and mAbs lost specificity. We demonstrate here for the first time the successful conjugation of a small molecule TLR7 agonist to an anti-tumour mAb (the anti-hCD 20 rituximab) without compromising antigen specificity. The TLR7 agonist UC-1V150 was conjugated to rituximab using two conjugation methods and yield, molecular substitution ratio, retention of TLR7 activity and specificity of antigen binding were compared. Both conjugation methods produced rituximab-UC-1V150 conjugates with UC-1V150 : rituximab ratio ranging from 1:1 to 3:1 with drug loading quantified by UV spectroscopy and drug substitution ratio verified by MALDI TOF mass spectroscopy. The yield of purified conjugates varied with conjugation method, and dropped as low as 31% using a method previously described for conjugating UC-1V150 to proteins, where a bifunctional crosslinker was firstly reacted with rituximab, and secondly to the TLR7 agonist. We therefore developed a direct conjugation method by producing an amine-reactive UV active version of UC-1V150, termed NHS:UC-1V150. Direct conjugation with NHS:UC-1V150 was quick and simple and gave improved conjugate yields of 65-78%. Rituximab-UC-1V150 conjugates had the expected pro-inflammatory activity in vitro (EC50 28-53 nM) with a significantly increased activity over unconjugated UC-1V150 (EC50 547 nM). Antigen binding and specificity of the rituxuimab-UC-1V150 conjugates was retained, and after incubation with human peripheral blood leukocytes, all conjugates bound strongly only to CD20-expressing B cells whilst no non-specific binding to CD20-negative cells was observed. Selective targeting of Toll-like receptor activation directly within tumors or to DC is now feasible.

Robust multimodal face and fingerprint fusion in the presence of spoofing attacks

Anti-spoofing is attracting growing interest in biometrics, considering the variety of fake materials and new means to attack biometric recognition systems. New unseen materials continuously challenge state-of-the-art spoofing detectors, suggesting for additional systematic approaches to target anti-spoofing. By incorporating liveness scores into the biometric fusion process, recognition accuracy can be enhanced, but traditional sum-rule based fusion algorithms are known to be highly sensitive to single spoofed instances. This paper investigates 1-median filtering as a spoofing-resistant generalised alternative to the sum-rule targeting the problem of partial multibiometric spoofing where m out of n biometric sources to be combined are attacked. Augmenting previous work, this paper investigates the dynamic detection and rejection of livenessrecognition pair outliers for spoofed samples in true multi-modal configuration with its inherent challenge of normalisation. As a further contribution, bootstrap aggregating (bagging) classifiers for fingerprint spoof-detection algorithm is presented. Experiments on the latest face video databases (Idiap Replay- Attack Database and CASIA Face Anti-Spoofing Database), and fingerprint spoofing database (Fingerprint Liveness Detection Competition 2013) illustrate the efficiency of proposed techniques.