Bromelain's activity and potential as an anti-cancer agent:Current evidence and perspectives

The medicinal qualities of pineapple are recognized in many traditions in South America, China and Southeast Asia. These qualities are attributed to bromelain, a 95%-mixture of proteases. Medicinal qualities of bromelain include anti-inflammatory, anti-thrombotic, fibrinolytic and anti-cancer functions. Existing evidence derived from clinical observations as well as from mouse- and cell-based models suggests that bromelain acts systemically, affecting multiple cellular and molecular targets. In recent years, studies have shown that bromelain has the capacity to modulate key pathways that support malignancy. It is now possible to suggest that the anti-cancer activity of bromelain consists in the direct impact on cancer cells and their micro-environment, as well as in the modulation of immune, inflammatory and haemostatic systems. This review will summarize existing data relevant to bromelain's anti-cancer activity and will suggest mechanisms which account for bromelain's effect, in the light of research involving non-cancer models. The review will also identify specific new research questions that will need to be addressed in order for a full assessment of bromelain-based anti-cancer therapy.

Modelling human performance within manufacturing systems design:from a theoretical towards a practical framework

Computer-based simulation is frequently used to evaluate the capabilities of proposed manufacturing system designs. Unfortunately, the real systems are often found to perform quite differently from simulation predictions and one possible reason for this is an over-simplistic representation of workers' behaviour within current simulation techniques. The accuracy of design predictions could be improved through a modelling tool that integrates with computer-based simulation and incorporates the factors and relationships that determine workers' performance. This paper explores the viability of developing a similar tool based on our previously published theoretical modelling framework. It focuses on evolving this purely theoretical framework towards a practical modelling tool that can actually be used to expand the capabilities of current simulation techniques. Based on an industrial study, the paper investigates how the theoretical framework works in practice, analyses strengths and weaknesses in its formulation, and proposes developments that can contribute towards enabling human performance modelling in a practical way.

The mosaic test:benchmarking colour-based image retrieval systems using image mosaics

Evaluation and benchmarking in content-based image retrieval has always been a somewhat neglected research area, making it difficult to judge the efficacy of many presented approaches. In this paper we investigate the issue of benchmarking for colour-based image retrieval systems, which enable users to retrieve images from a database based on lowlevel colour content alone. We argue that current image retrieval evaluation methods are not suited to benchmarking colour-based image retrieval systems, due in main to not allowing users to reflect upon the suitability of retrieved images within the context of a creative project and their reliance on highly subjective ground-truths. As a solution to these issues, the research presented here introduces the Mosaic Test for evaluating colour-based image retrieval systems, in which test-users are asked to create an image mosaic of a predetermined target image, using the colour-based image retrieval system that is being evaluated. We report on our findings from a user study which suggests that the Mosaic Test overcomes the major drawbacks associated with existing image retrieval evaluation methods, by enabling users to reflect upon image selections and automatically measuring image relevance in a way that correlates with the perception of many human assessors. We therefore propose that the Mosaic Test be adopted as a standardised benchmark for evaluating and comparing colour-based image retrieval systems.

Amino acids as cryoprotectants for liposomal delivery systems

Liposomes provide an efficient delivery system for solubilisation and delivery of both small and macro molecules. However, they suffer from the disadvantage of instability when stored as aqueous dispersions. Cryoprotection of the liposomal systems provides an effective approach to overcome poor stability whilst maintaining formulation characteristics, although, the formulation of a freeze-dried product requires the consideration of not only the selection of an appropriate cryoprotectant, but also needs careful consideration of the processing parameters including pre-freezing conditions, primary and secondary drying protocols along with optimisation of cryoprotectant concentration. This current work investigates the application of amino acids as potential cryoprotectants for the stabilisation of liposomes, and results indicate that amino acids show biphasic nature of stabilisation with 4 mol of cryoprotectant per mole of the lipid exhibiting optimum cryoprotection. The investigations of process parameters showed that the pre-freezing temperatures below the glass transition of the amino acids followed by drying for over 6 h resulted in stable formulations. Studies investigating the efficiency of drug retention showed that the cryoprotection offered by lysine was similar to that shown by trehalose, suggesting that amino acids act as effective stabilisers. ESEM analysis was carried out to monitor morphology of the rehydrated liposomes. © 2007 Elsevier B.V. All rights reserved.

Automatic summary assessment for intelligent tutoring systems

Summary writing is an important part of many English Language Examinations. As grading students' summary writings is a very time-consuming task, computer-assisted assessment will help teachers carry out the grading more effectively. Several techniques such as latent semantic analysis (LSA), n-gram co-occurrence and BLEU have been proposed to support automatic evaluation of summaries. However, their performance is not satisfactory for assessing summary writings. To improve the performance, this paper proposes an ensemble approach that integrates LSA and n-gram co-occurrence. As a result, the proposed ensemble approach is able to achieve high accuracy and improve the performance quite substantially compared with current techniques. A summary assessment system based on the proposed approach has also been developed.

Supporting decision-making for self-adaptive systems:from goal models to dynamic decision networks

Context/Motivation - Different modeling techniques have been used to model requirements and decision-making of self-adaptive systems (SASs). Specifically, goal models have been prolific in supporting decision-making depending on partial and total fulfilment of functional (goals) and non-functional requirements (softgoals). Different goalrealization strategies can have different effects on softgoals which are specified with weighted contribution-links. The final decision about what strategy to use is based, among other reasons, on a utility function that takes into account the weighted sum of the different effects on softgoals. Questions/Problems - One of the main challenges about decisionmaking in self-adaptive systems is to deal with uncertainty during runtime. New techniques are needed to systematically revise the current model when empirical evidence becomes available from the deployment. Principal ideas/results - In this paper we enrich the decision-making supported by goal models by using Dynamic Decision Networks (DDNs). Goal realization strategies and their impact on softgoals have a correspondence with decision alternatives and conditional probabilities and expected utilities in the DDNs respectively. Our novel approach allows the specification of preferences over the softgoals and supports reasoning about partial satisfaction of softgoals using probabilities. We report results of the application of the approach on two different cases. Our early results suggest the decision-making process of SASs can be improved by using DDNs. © 2013 Springer-Verlag.

Mitigating the obsolescence of quality specifications models in service-based systems

Requirements-aware systems address the need to reason about uncertainty at runtime to support adaptation decisions, by representing quality of services (QoS) requirements for service-based systems (SBS) with precise values in run-time queryable model specification. However, current approaches do not support updating of the specification to reflect changes in the service market, like newly available services or improved QoS of existing ones. Thus, even if the specification models reflect design-time acceptable requirements they may become obsolete and miss opportunities for system improvement by self-adaptation. This articles proposes to distinguish "abstract" and "concrete" specification models: the former consists of linguistic variables (e.g. "fast") agreed upon at design time, and the latter consists of precise numeric values (e.g. "2ms") that are dynamically calculated at run-time, thus incorporating up-to-date QoS information. If and when freshly calculated concrete specifications are not satisfied anymore by the current service configuration, an adaptation is triggered. The approach was validated using four simulated SBS that use services from a previously published, real-world dataset; in all cases, the system was able to detect unsatisfied requirements at run-time and trigger suitable adaptations. Ongoing work focuses on policies to determine recalculation of specifications. This approach will allow engineers to build SBS that can be protected against market-caused obsolescence of their requirements specifications. © 2012 IEEE.

Self-explanation in adaptive systems

The behaviour of self adaptive systems can be emergent. The difficulty in predicting the system's behaviour means that there is scope for the system to surprise its customers and its developers. Because its behaviour is emergent, a self-adaptive system needs to garner confidence in its customers and it needs to resolve any surprise on the part of the developer during testing and mainteinance. We believe that these two functions can only be achieved if a self-adaptive system is also capable of self-explanation. We argue a self-adaptive system's behaviour needs to be explained in terms of satisfaction of its requirements. Since self-adaptive system requirements may themselves be emergent, a means needs to be found to explain the current behaviour of the system and the reasons that brought that behaviour about. We propose the use of goal-based models during runtime to offer self-explanation of how a system is meeting its requirements, and why the means of meeting these were chosen. We discuss the results of early experiments in self-explanation, and set out future work. © 2012 C.E.S.A.M.E.S.

EPiCS:engineering proprioception in computing systems

Modern compute systems continue to evolve towards increasingly complex, heterogeneous and distributed architectures. At the same time, functionality and performance are no longer the only aspects when developing applications for such systems, and additional concerns such as flexibility, power efficiency, resource usage, reliability and cost are becoming increasingly important. This does not only raise the question of how to efficiently develop applications for such systems, but also how to cope with dynamic changes in the application behaviour or the system environment. The EPiCS Project aims to address these aspects through exploring self-awareness and self-expression. Self-awareness allows systems and applications to gather and maintain information about their current state and environment, and reason about their behaviour. Self-expression enables systems to adapt their behaviour autonomously to changing conditions. Innovations in EPiCS are based on systematic integration of research in concepts and foundations, customisable hardware/software platforms and operating systems, and self-aware networking and middleware infrastructure. The developed technologies are validated in three application domains: computational finance, distributed smart cameras and interactive mobile media systems. © 2012 IEEE.

An examination of the development of LTL hub-and-spoke freight distribution systems

Over recent years, hub-and-spoke distribution techniques have attracted widespread research attention. Despite there being a growing body of literature in this area there is less focus on the spoke-terminal element of the hub-and-spoke system as being a key component in the overall service received by the end-user. Current literature is highly geared towards discussing bulk optimization of freight units rather than to the more discrete and individualistic profile characteristics of shared-user Less-than-truckload (LTL) freight. In this paper, a literature review is presented to review the role hub-and-spoke systems play in meeting multi-profile customer demands, particularly in developing sectors with more sophisticated needs, such as retail. The paper also looks at the use of simulation technology as a suitable tool for analyzing spoke-terminal operations within developing hub-and spoke systems.

Improving “last mile” delivery performance to retailers in hub and spoke distribution systems

Purpose – The purpose of this paper is to investigate the “last mile” delivery link between a hub and spoke distribution system and its customers. The proportion of retail, as opposed to non-retail (trade) customers using this type of distribution system has been growing in the UK. The paper shows the applicability of simulation to demonstrate changes in overall delivery policy to these customers. Design/methodology/approach – A case-based research method was chosen with the aim to provide an exemplar of practice and test the proposition that simulation can be used as a tool to investigate changes in delivery policy. Findings – The results indicate the potential improvement in delivery performance, specifically in meeting timed delivery performance, that could be made by having separate retail and non-retail delivery runs from the spoke terminal to the customer. Research limitations/implications – The simulation study does not attempt to generate a vehicle routing schedule but demonstrates the effects of a change on delivery performance when comparing delivery policies. Practical implications – Scheduling and spreadsheet software are widely used and provide useful assistance in the design of delivery runs and the allocation of staff to those delivery runs. This paper demonstrates to managers the usefulness of investigating the efficacy of current design rules and presents simulation as a suitable tool for this analysis. Originality/value – A simulation model is used in a novel application to test a change in delivery policy in response to a changing delivery profile of increased retail deliveries.

Cognitive systems associated with the hippocampus of the human brain and their role in behaviour and neurodegenerative disease

Cognitive systems research involves the synthesis of ideas from natural and artificial systems in the analysis, understanding, and design of all intelligent systems. This chapter discusses the cognitive systems associated with the hippocampus (HC) of the human brain and their possible role in behaviour and neurodegenerative disease. The hippocampus (HC) is concerned with the analysis of highly abstract data derived from all sensory systems but its specific role remains controversial. Hence, there have been three major theories concerning its function, viz., the memory theory, the spatial theory, and the behavioral inhibition theory. The memory theory has its origin in the surgical destruction of the HC, which results in severe anterograde and partial retrograde amnesia. The spatial theory has its origin in the observation that neurons in the HC of animals show activity related to their location within the environment. By contrast, the behavioral inhibition theory suggests that the HC acts as a ‘comparator’, i.e., it compares current sensory events with expected or predicted events. If a set of expectations continues to be verified then no alteration of behavior occurs. If, however, a ‘mismatch’ is detected then the HC intervenes by initiating appropriate action by active inhibition of current motor programs and initiation of new data gathering. Understanding the cognitive systems of the hippocampus in humans may aid in the design of intelligent systems involved in spatial mapping, memory, and decision making. In addition, this information may lead to a greater understanding of the course of clinical dementia in the various neurodegenerative diseases in which there is significant damage to the HC.

Knowledge management for more sustainable water systems

The management and sharing of complex data, information and knowledge is a fundamental and growing concern in the Water and other Industries for a variety of reasons. For example, risks and uncertainties associated with climate, and other changes require knowledge to prepare for a range of future scenarios and potential extreme events. Formal ways in which knowledge can be established and managed can help deliver efficiencies on acquisition, structuring and filtering to provide only the essential aspects of the knowledge really needed. Ontologies are a key technology for this knowledge management. The construction of ontologies is a considerable overhead on any knowledge management programme. Hence current computer science research is investigating generating ontologies automatically from documents using text mining and natural language techniques. As an example of this, results from application of the Text2Onto tool to stakeholder documents for a project on sustainable water cycle management in new developments are presented. It is concluded that by adopting ontological representations sooner, rather than later in an analytical process, decision makers will be able to make better use of highly knowledgeable systems containing automated services to ensure that sustainability considerations are included.

Advanced techniques for the improvement of optical transmission systems

This thesis presents the experimental investigation into two novel techniques which can be incorporated into current optical systems. These techniques have the capability to improve the performance of transmission and the recovery of the transmitted signal at the receiver. The experimental objectives are described and the results for each technique are presented in two sections: The first experimental section is on work related to Ultra-long Raman Fibre lasers (ULRFLs). The fibre lasers have become an important research topic in recent years due to the significant improvement they give over lumped Raman amplification and their potential use in the development of system with large bandwidths and very low losses. The experiments involved the use of ASK and DPSK modulation types over a distance of 240km and DPSK over a distance of 320km. These results are compared to the current state of-the-art and against other types of ultra-long transmission amplification techniques. The second technique investigated involves asymmetrical, or offset, filtering. This technique is important because it deals with the strong filtering regimes that are a part of optical systems and networks in modern high-speed communications. It allows the improvement of the received signal by offsetting the central frequency of a filter after the output of a Delay Line Interferometer (DLI), which induces significant improvement in BER and/or Qvalues at the receiver and therefore an increase in signal quality. The experimental results are then concluded against the objectives of the experimental work and potential future work discussed.

Marketing performance assessment systems and the business context

Purpose ‐ This study provides empirical evidence for the contextuality of marketing performance assessment (MPA) systems. It aims to introduce a taxonomical classification of MPA profiles based on the relative emphasis placed on different dimensions of marketing performance in different companies and business contexts. Design/methodology/approach ‐ The data used in this study (n=1,157) were collected using a web-based questionnaire, targeted to top managers in Finnish companies. Two multivariate data analysis techniques were used to address the research questions. First, dimensions of marketing performance underlying the current MPA systems were identified through factor analysis. Second, a taxonomy of different profiles of marketing performance measurement was created by clustering respondents based on the relative emphasis placed on the dimensions and characterizing them vis-á-vis contextual factors. Findings ‐ The study identifies nine broad dimensions of marketing performance that underlie the MPA systems in use and five MPA profiles typical of companies of varying sizes in varying industries, market life cycle stages, and competitive positions associated with varying levels of market orientation and business performance. The findings support the previously conceptual notion of contextuality in MPA and provide empirical evidence for the factors that affect MPA systems in practice. Originality/value ‐ The paper presents the first field study of current MPA systems focusing on combinations of metrics in use. The findings of the study provide empirical support for the contextuality of MPA and form a classification of existing contextual systems suitable for benchmarking purposes. Limited evidence for performance differences between MPA profiles is also provided.