Detecting Anomalies in Graphs with Numeric Labels

This paper presents Yagada, an algorithm to search labelled graphs for anomalies using both structural data and numeric attributes. Yagada is explained using several security-related examples and validated with experiments on a physical Access Control database. Quantitative analysis shows that in the upper range of anomaly thresholds, Yagada detects twice as many anomalies as the best-performing numeric discretization algorithm. Qualitative evaluation shows that the detected anomalies are meaningful, representing a com- bination of structural irregularities and numerical outliers.

CHARACTERIZATION OF THE CYSTEINE PROTEINASES OF THE COMMON LIVER FLUKE FASCIOLA-HEPATICA USING NOVEL, ACTIVE-SITE-DIRECTED AFFINITY LABELS

The excreted/secreted proteinases of adult and juvenile Fasciola hepatica maintained in vitro were found to hydrolyse the fluorogenic substrates Cbz-Phe-Arg- and Cbz-Arg-Arg-NHMec. This activity was demonstrated to have a classical cysteine proteinase inhibitor profile, with turn-over of both substrates being blocked by pre-incubation with E64 and peptidyl diazomethanes. The Cbz-Arg-Arg-NHMec hydrolysing activity of the mature fluke exhibited an alkaline stability not characteristic of its mammalian lysosomal counterparts. Further, the biotinylated affinity reagents biotin-Phe-Ala CHN2 and biotin-Phe-Cys(SBzyl)-CHN2 were used to label and characterize these cysteine proteinases in terms of apparent molecular weight and subsite specificity. Adult fluke media were found to contain four species of molecular weights 66, 58, 50 and 25-26 kDa; juvenile media contained three species of molecular weights 66, 54 and 25-26 kDa. The major 25-26 kDa cysteine proteinase common to both stages was shown to have a subsite specificity similar to that of mammalian cathepsin B.

Food Labels, Autonomy and the Right (Not) to Know

Food labelling has been overlooked in the emerging body of literature concerning the normative dimensions of food and drink policies. In this paper, I argue that arguments normally advanced in bioethics and medical ethics regarding the “right to know” and the “right not to know” can provide useful normative guidelines for critically assessing existing and proposed food labelling regimes. More specifically, I claim that food labelling ought to respect the legitimate interests and the autonomy of both consumers who seek knowledge about their food in order to make informed dietary choices and consumers who prefer to remain ignorant about the contents and effects of their food in order to avoid the emotional and psychological harm, or more simply the loss of enjoyment, which may result from receiving that information.

Finding the Most Descriptive Substructures in Graphs with Discrete and Numeric Labels

Many graph datasets are labelled with discrete and numeric attributes. Most frequent substructure discovery algorithms ignore numeric attributes; in this paper we show how they can be used to improve search performance and discrimination. Our thesis is that the most descriptive substructures are those which are normative both in terms of their structure and in terms of their numeric values. We explore the relationship between graph structure and the distribution of attribute values and propose an outlier-detection step, which is used as a constraint during substructure discovery. By pruning anomalous vertices and edges, more weight is given to the most descriptive substructures. Our method is applicable to multi-dimensional numeric attributes; we outline how it can be extended for high-dimensional data. We support our findings with experiments on transaction graphs and single large graphs from the domains of physical building security and digital forensics, measuring the effect on runtime, memory requirements and coverage of discovered patterns, relative to the unconstrained approach.

Smart, Reusable labels for assessing self-cleaning films

Novel, reversible (reusable) photocatalyst activity indicator labels, which undergo a rapid colour change when in contact with a photocatalytic film via the photoreduction of methylene blue contained within the label’s adhesive, are explored as a method for assessing the activity of self-cleaning glass in situ and the laboratory, using digital photography.

Assembly intermediates in polyketide biosynthesis; enantioselective syntheses of beta-hydroxycarbonyl compounds

A versatile approach for the enantioselective synthesis of functionalised beta-hydroxy N-acetylcysteamine thiol esters has been developed which allows the facile incorporation of isotopic labels. It has been shown that a remarkable reversal of selectivity occurs in the titanium mediated aldol reaction of the acyloxazolidone intermediate using either (S)- or (R)-tert-butyldimethylsilyloxybutanal. The aldol products are valuable intermediates in the synthesis of 4-hydroxy-6-substituted gamma-lactones.

The Combination of Multiple Classifiers Using an Evidential Reasoning Approach

In many domains when we have several competing classifiers available we want to synthesize them or some of them to get a more accurate classifier by a combination function. In this paper we propose a ‘class-indifferent’ method for combining classifier decisions represented by evidential structures called triplet and quartet, using Dempster's rule of combination. This method is unique in that it distinguishes important elements from the trivial ones in representing classifier decisions, makes use of more information than others in calculating the support for class labels and provides a practical way to apply the theoretically appealing Dempster–Shafer theory of evidence to the problem of ensemble learning. We present a formalism for modelling classifier decisions as triplet mass functions and we establish a range of formulae for combining these mass functions in order to arrive at a consensus decision. In addition we carry out a comparative study with the alternatives of simplet and dichotomous structure and also compare two combination methods, Dempster's rule and majority voting, over the UCI benchmark data, to demonstrate the advantage our approach offers. (A continuation of the work in this area that was published in IEEE Trans on KDE, and conferences)

Constructing probabilistic ATMS using extended incidence calculus

This paper discusses the relations between extended incidence calculus and assumption-based truth maintenance systems (ATMSs). We first prove that managing labels for statements (nodes) in an ATMS is equivalent to producing incidence sets of these statements in extended incidence calculus. We then demonstrate that the justification set for a node is functionally equivalent to the implication relation set for the same node in extended incidence calculus. As a consequence, extended incidence calculus can provide justifications for an ATMS, because implication relation sets are discovered by the system automatically. We also show that extended incidence calculus provides a theoretical basis for constructing a probabilistic ATMS by associating proper probability distributions on assumptions. In this way, we can not only produce labels for all nodes in the system, but also calculate the probability of any of such nodes in it. The nogood environments can also be obtained automatically. Therefore, extended incidence calculus and the ATMS are equivalent in carrying out inferences at both the symbolic level and the numerical level. This extends a result due to Laskey and Lehner.

"To be accepted as normal": Public understanding and misconceptions concerning survivors of brain injury.

PRIMARY OBJECTIVE: To determine the views held by the general public in Northern Ireland towards survivors of brain injury. RESEARCH DESIGN: Qualitative semi-structured interviews. METHODS AND PROCEDURES: Interviews were conducted with 16 members of the general public. Ten questions addressed issues such as the role of survivors of brain injury in society, the challenges they face and the characteristics ascribed to them. MAIN OUTCOMES AND RESULTS: When asked to describe someone with a brain injury participants typically used negative labels and identified the most common problems as relating to physical, cognitive, emotional and social functioning. There was a general failure to recognize that brain injury was a 'hidden' disability, with most participants expecting some outward manifestation. Relatively few previous studies have employed a qualitative approach to explore how the public perceives survivors of brain injury. CONCLUSION: Members of the public have an increasing awareness of the challenges faced by survivors of brain injury. However, in spite of this, perceptions of aggressiveness, dependency and unhappiness were still evident, suggesting potential problems in reintegrating survivors of brain injury with their communities.