A control theoretic paradigm for cell signaling networks : a simple complexity for a sensitive robustness

The fields of molecular biology and cell biology are being flooded with complex genomic and proteomic datasets of large dimensions. We now recognize that each molecule in the cell and tissue can no longer be viewed as an isolated entity. Instead, each molecule must be considered as one member of an interacting network. Consequently, there is an urgent need for mathematical models to understand the behavior of cell signaling networks in health and in disease.

Reversible and semi-blind relational database watermarking

Database watermarking has received significant research attention in the current decade. Although, almost all watermarking models have been either irreversible (the original relation cannot be restored from the watermarked relation) and/or non-blind (requiring original relation to detect the watermark in watermarked relation). This model has several disadvantages over reversible and blind watermarking (requiring only watermarked relation and secret key from which the watermark is detected and original relation is restored) including inability to identify rightful owner in case of successful secondary watermarking, inability to revert the relation to original data set (required in high precision industries) and requirement to store unmarked relation at a secure secondary storage. To overcome these problems, we propose a watermarking scheme that is reversible as well as blind. We utilize difference expansion on integers to achieve reversibility. The major advantages provided by our scheme are reversibility to high quality original data set, rightful owner identification, resistance against secondary watermarking attacks, and no need to store original database at a secure secondary storage.

Complexity Development Theory and enterprise development at the bottom of the pyramid

In 2001 45% (2.7 billion) of the world’s population of approximately 6.1 billion lived in ‘moderate poverty’ on less than US $ 2 per person per day (World Population Summary, 2012). In the last 60 years there have been many theories attempting to explain development, why some countries have the fastest growth in history, while others stagnate and so far no way has been found to explain the differences. Traditional views imply that development is the aggregation of successes from multiple individual business enterprises, but this ignores the interactions between and among institutions, organisations and individuals in the economy, which can often have unpredictable effects. Complexity Development Theory proposes that by viewing development as an emergent property of society, we can help create better development programs at the organisational, institutional and national levels. This paper asks how the principals of CAS can be used to develop CDT principals used to develop and operate development programs at the bottom of the pyramid in developing economies. To investigate this research question we conduct a literature review to define and describe CDT and create propositions for testing. We illustrate these propositions using a case study of an Asset Based Community Development (ABCD) Program for existing and nascent entrepreneurs in the Democratic Republic of the Congo (DRC). We found evidence that all the principals of CDT were related to the characteristics of CAS. If this is the case, development programs will be able to select which CAS needed to test these propositions.

Managing knowledge for asset management : shifting from process to relational frames

The purpose of this paper is to review existing knowledge management (KM) practices within the field of asset management, identify gaps, and propose a new approach to managing knowledge for asset management. Existing approaches to KM in the field of asset management are incomplete with the focus primarily on the application of data and information systems, for example the use of an asset register. It is contended these approaches provide access to explicit knowledge and overlook the importance of tacit knowledge acquisition, sharing and application. In doing so, current KM approaches within asset management tend to neglect the significance of relational factors; whereas studies in the knowledge management field have showed that relational modes such as social capital is imperative for ef-fective KM outcomes. In this paper, we argue that incorporating a relational ap-proach to KM is more likely to contribute to the exchange of ideas and the devel-opment of creative responses necessary to improve decision-making in asset management. This conceptual paper uses extant literature to explain knowledge management antecedents and explore its outcomes in the context of asset man-agement. KM is a component in the new Integrated Strategic Asset Management (ISAM) framework developed in conjunction with asset management industry as-sociations (AAMCoG, 2012) that improves asset management performance. In this paper we use Nahapiet and Ghoshal’s (1998) model to explain antecedents of relational approach to knowledge management. Further, we develop an argument that relational knowledge management is likely to contribute to the improvement of the ISAM framework components, such as Organisational Strategic Manage-ment, Service Planning and Delivery. The main contribution of the paper is a novel and robust approach to managing knowledge that leads to the improvement of asset management outcomes.

Reduced complexity on-line estimation of hidden Markov model parameters

In this paper we propose and study low complexity algorithms for on-line estimation of hidden Markov model (HMM) parameters. The estimates approach the true model parameters as the measurement noise approaches zero, but otherwise give improved estimates, albeit with bias. On a nite data set in the high noise case, the bias may not be signi cantly more severe than for a higher complexity asymptotically optimal scheme. Our algorithms require O(N3) calculations per time instant, where N is the number of states. Previous algorithms based on earlier hidden Markov model signal processing methods, including the expectation-maximumisation (EM) algorithm require O(N4) calculations per time instant.

The effect of work-integrated learning in highlighting the complexity of work : a pilot study of work self-efficacy

This pilot study aims to examine the effect of work-integrated learning (WIL) on work self-efficacy (WSE) for undergraduate students from the Queensland University of Technology. A WSE instrument was used to examine the seven subscales of WSE. These were; learning, problem solving, pressure, role expectations, team work, sensitivity and work politics. The results of this pilot study revealed that, overall the WSE scores were highest when the students’ did not participate in the WIL unit (comparison group) in comparison to the WIL group. The current paper suggests that WSE scores were changed as a result of WIL participation. These findings open a new path for future studies allowing them to explore the relationship between WIL and the specific subscales of WSE.

Robust clustering of multi-type relational data via a heterogeneous manifold ensemble

High-Order Co-Clustering (HOCC) methods have attracted high attention in recent years because of their ability to cluster multiple types of objects simultaneously using all available information. During the clustering process, HOCC methods exploit object co-occurrence information, i.e., inter-type relationships amongst different types of objects as well as object affinity information, i.e., intra-type relationships amongst the same types of objects. However, it is difficult to learn accurate intra-type relationships in the presence of noise and outliers. Existing HOCC methods consider the p nearest neighbours based on Euclidean distance for the intra-type relationships, which leads to incomplete and inaccurate intra-type relationships. In this paper, we propose a novel HOCC method that incorporates multiple subspace learning with a heterogeneous manifold ensemble to learn complete and accurate intra-type relationships. Multiple subspace learning reconstructs the similarity between any pair of objects that belong to the same subspace. The heterogeneous manifold ensemble is created based on two-types of intra-type relationships learnt using p-nearest-neighbour graph and multiple subspaces learning. Moreover, in order to make sure the robustness of clustering process, we introduce a sparse error matrix into matrix decomposition and develop a novel iterative algorithm. Empirical experiments show that the proposed method achieves improved results over the state-of-art HOCC methods for FScore and NMI.

Therapeutic practice with refugee clients: a qualitative study of therapist experience

Background There is limited research on the subjective experience of therapists and their understanding of therapeutic process when working with people from refugee backgrounds. Objective The present study provides a qualitative account of therapists’ conceptions of therapeutic practice and experiences of working therapeutically with refugee clients. Method Participants were 12 mental health workers who had worked therapeutically with people from refugee backgrounds, with an average of 7.6 years (range 1.5-16 years) experience in this field. Participants completed a semi-structured interview and completed a brief quantitative survey. Findings Thematic analysis revealed a number of super-ordinate themes. Four key themes are explored in the current study: principles of therapeutic practice; therapy as a relational experience; the role of context in informing therapeutic work with refugee clients; and the impact of therapeutic work on the therapist. Discussion The results revealed the complexity and demands of working with people from refugee backgrounds. Further, the lack of research evidence for the methods of therapeutic practice described in the current study highlights the distinction between naturalistic therapeutic practice and the current state of the evidence regarding therapeutic interventions for refugee clients. The findings have important implications for training and supporting therapists to work with people who have fled their countries of origin and who have often been exposed to highly traumatic events.

Ongoing Adaptation as a Feature of Complexity : Further Thoughts and Possible Ideas for Pedagogy in Physical Activity

This chapter takes as its central premise the human capacity to adapt to changing environments. It is an idea that is central to complexity theory but receives only modest attention in relation to learning. To do this we will draw from a range of fields and then consider some recent research in motor control that may extend the discussion in ways not yet considered, but that will build on advances already made within pedagogy and motor control synergies. Recent work in motor control indicates that humans have far greater capacity to adapt to the ‘product space’ than was previously thought, mainly through fast heuristics and on-line corrections. These are changes that can be made in real (movement) time and are facilitated by what are referred to as ‘feed-forward’ mechanisms that take advantage of ultra-fast ways of recognizing the likely outcomes of our movements and using this as a source of feedback. We conclude by discussing some possible ideas for pedagogy within the sport and physical activity domains, the implications of which would require a rethink on how motor skill learning opportunities might best be facilitated.

How does the use of a reflective journal enhance students’ critical thinking about complexity?

Introduction to Youth Services is a second year Social Work and Human Services unit. In this unit a reflective writing task was introduced to assess students’ reflections on an ongoing tutorial discussion to which they contributed. The discussion was based on a fictional young person each tutorial group ‘worked with’ across eight weeks of a semester. In developing the process and the criteria for the reflective journal, the ideas raised by the Teaching and Assessing Reflective Learning (TARL) in Higher Education project (see Chap. 2) were utilised, scaffolding the work with resources and submission of a draft. The students were also invited to choose the form of reflective process they used, it could be a written journal but did not need to be. The evidence exemplified that a reflective journal is an effective tool for students to record their developing understanding regarding the concept that issues people experience are complex and compounding. Importantly, it was also a useful vehicle for students to begin to consider the impacts of their own and others’ values and beliefs on their response to the issues raised within the case discussion. The reflective journal also helped participants to consider how this learning contributes to the ongoing development of their professional practice framework.

Complexity and high-end computing in biology and medicine

Biomedical systems involve a large number of entities and intricate interactions between these. Their direct analysis is, therefore, difficult, and it is often necessary to rely on computational models. These models require significant resources and parallel computing solutions. These approaches are particularly suited, given parallel aspects in the nature of biomedical systems. Model hybridisation also permits the integration and simultaneous study of multiple aspects and scales of these systems, thus providing an efficient platform for multidisciplinary research.