Spatial analysis of biomineralization associated gene expression from the mantle organ of the pearl oyster Pinctada maxima

Background: Biomineralization is a process encompassing all mineral containing tissues produced within an organism. One of the most dynamic examples of this process is the formation of the mollusk shell, comprising a variety of crystal phases and microstructures. The organic component incorporated within the shell is said to dictate this architecture. However general understanding of how this process is achieved remains ambiguous. The mantle is a conserved organ involved in shell formation throughout molluscs. Specifically the mantle is thought to be responsible for secreting the protein component of the shell. This study employs molecular approaches to determine the spatial expression of genes within the mantle tissue to further the elucidation of the shell biomineralization. Results: A microarray platform was custom generated (PmaxArray 1.0) from the pearl oyster Pinctada maxima. PmaxArray 1.0 consists of 4992 expressed sequence tags (ESTs) originating from mantle tissue. This microarray was used to analyze the spatial expression of ESTs throughout the mantle organ. The mantle was dissected into five discrete regions and analyzed for differential gene expression with PmaxArray 1.0. Over 2000 ESTs were determined to be differentially expressed among the tissue sections, identifying five major expression regions. In situ hybridization validated and further localized the expression for a subset of these ESTs. Comparative sequence similarity analysis of these ESTs revealed a number of the transcripts were novel while others showed significant sequence similarities to previously characterized shell related genes.

Stochastic simulation for spatial modelling of dynamic process in a living cell

One of the fundamental motivations underlying computational cell biology is to gain insight into the complicated dynamical processes taking place, for example, on the plasma membrane or in the cytosol of a cell. These processes are often so complicated that purely temporal mathematical models cannot adequately capture the complex chemical kinetics and transport processes of, for example, proteins or vesicles. On the other hand, spatial models such as Monte Carlo approaches can have very large computational overheads. This chapter gives an overview of the state of the art in the development of stochastic simulation techniques for the spatial modelling of dynamic processes in a living cell.

Dynamic texture reconstruction from sparse codes for unusual event detection in crowded scenes

Unusual event detection in crowded scenes remains challenging because of the diversity of events and noise. In this paper, we present a novel approach for unusual event detection via sparse reconstruction of dynamic textures over an overcomplete basis set, with the dynamic texture described by local binary patterns from three orthogonal planes (LBPTOP). The overcomplete basis set is learnt from the training data where only the normal items observed. In the detection process, given a new observation, we compute the sparse coefficients using the Dantzig Selector algorithm which was proposed in the literature of compressed sensing. Then the reconstruction errors are computed, based on which we detect the abnormal items. Our application can be used to detect both local and global abnormal events. We evaluate our algorithm on UCSD Abnormality Datasets for local anomaly detection, which is shown to outperform current state-of-the-art approaches, and we also get promising results for rapid escape detection using the PETS2009 dataset.

An examination of the predictors of blood donors' intentions to donate during two phases of an avian influenza outbreak

BACKGROUND: Data from prior health scares suggest that an avian influenza outbreak will impact on people’s intention to donate blood; however research exploring this is scarce. Using an augmented theory of planned behavior (TPB), incorporating threat perceptions alongside the rational decision-making components of the TPB, the current study sought to identify predictors of blood donors’ intentions to donate during two phases of an avian influenza outbreak. STUDY DESIGN AND METHODS: Blood donors (N = 172) completed an on-line survey assessing the standard TPB predictors as well as measures of threat perceptions from the health belief model (HBM; i.e., perceived susceptibility and severity). Path analyses examined the utility of the augmented TPB to predict donors’ intentions to donate during a low- and high-risk phase of an avian influenza outbreak. RESULTS: In both phases, the model provided a good fit to the data explaining 69% (low risk) and 72% (high risk) of the variance in intentions. Attitude, subjective norm, and perceived susceptibility significantly predicted donor intentions in both phases. Within the low-risk phase, gender was an additional significant predictor of intention, while in the high-risk phase, perceived behavioral control was significantly related to intentions. CONCLUSION: An augmented TPB model can be used to predict donors’ intentions to donate blood in a low-risk and a high-risk phase of an outbreak of avian influenza. As such, the results provide important insights into donors’ decision-making that can be used by blood agencies to maintain the blood supply in the context of an avian influenza outbreak.

Towards a model of dynamic capabilities in innovation-based competitive strategy : insights from project-oriented service firms

With the growing significance of services in most developed economies, there is an increased interest in the role of service innovation in service firm competitive strategy. Despite growing literature on service innovation, it remains fragmented reflecting the need for a model that captures key antecedents driving the service innovation-based competitive advantage process. Building on extant literature and using thirteen in-depth interviews with CEOs of project-oriented service firms, this paper presents a model of innovation-based competitive advantage. The emergent model suggests that entrepreneurial service firms pursuing innovation carefully select and use dynamic capabilities that enable them to achieve greater innovation and sustained competitive advantage. Our findings indicate that firms purposefully use create, extend and modify processes to build and nurture key dynamic capabilities. The paper presents a set of theoretical propositions to guide future research. Implications for theory and practice are discussed. Finally, directions for future research are outlined.

Preliminary study on bridge health prediction using Dynamic Objective Oriented Bayesian Network (DOOBN)

The availability of bridges is crucial to people’s daily life and national economy. Bridge health prediction plays an important role in bridge management because maintenance optimization is implemented based on prediction results of bridge deterioration. Conventional bridge deterioration models can be categorised into two groups, namely condition states models and structural reliability models. Optimal maintenance strategy should be carried out based on both condition states and structural reliability of a bridge. However, none of existing deterioration models considers both condition states and structural reliability. This study thus proposes a Dynamic Objective Oriented Bayesian Network (DOOBN) based method to overcome the limitations of the existing methods. This methodology has the ability to act upon as a flexible unifying tool, which can integrate a variety of approaches and information for better bridge deterioration prediction. Two demonstrative case studies are conducted to preliminarily justify the feasibility of the methodology

Metaheuristics for minimizing the makespan of the dynamic shop scheduling problem

For the shop scheduling problems such as flow-shop, job-shop, open-shop, mixed-shop, and group-shop, most research focuses on optimizing the makespan under static conditions and does not take into consideration dynamic disturbances such as machine breakdown and new job arrivals. We regard the shop scheduling problem under static conditions as the static shop scheduling problem, while the shop scheduling problem with dynamic disturbances as the dynamic shop scheduling problem. In this paper, we analyze the characteristics of the dynamic shop scheduling problem when machine breakdown and new job arrivals occur, and present a framework to model the dynamic shop scheduling problem as a static group-shop-type scheduling problem. Using the proposed framework, we apply a metaheuristic proposed for solving the static shop scheduling problem to a number of dynamic shop scheduling benchmark problems. The results show that the metaheuristic methodology which has been successfully applied to the static shop scheduling problems can also be applied to solve the dynamic shop scheduling problem efficiently.

Internet-enabled international entrepreneurship : a conceptual exploration of the link between a firm’s resource base, dynamic capabilities and international market performance

It has been suggested that the accumulation of valuable resources and capabilities, such as Internet application, is not enough to support a firm’s sustainable competitive advantage, especially for high technology-mediated firms; which often operate in fast changing dynamic environments. While the idea of ‘Internet-enabled resources and capabilities’ has been recognised by RBV theorists, the notion has largely been ignored in conceptual and empirical studies. Given this finding, a conceptual framework is constructed and research issues are then developed in order to focus attention on the relationship between, the Internet and a firm’s resource base, dynamic capabilities and international market performance. We postulate that successful Internet-enabled market performance arises from those international entrepreneurial-oriented firms which encompass: international vision, international business experience, Internet-international marketing capabilities and international networking capabilities. Recommendations for future theory development are presented, along with the implications for international entrepreneurial managers in Australian small and medium sized firms

Human seat modelling using inverse dynamic musculoskeletal models

In this work a biomechanical model is used for simulation of muscle forces necessary to maintain the posture in a car seat under different support conditions.

Mapping the dynamic of Project Management field : Project Management in action

Focusing on the role within and between organizations of the project management discipline to design and implement strategy, as source of competitive advantage, leads us to question the scientific field behind this discipline. This science should be the basis for the development and use of bodies of knowledge, standards, certification programs, education, and competencies, and beyond this as a source of value for people, organizations, and society. Thus the importance to characterize, define, and understand this field and its underlying strength, basis, and development is paramount. For this purpose we propose to give some insights on the current situation. This will lead us to clarify our epistemological position and demonstrate that both constructivism and positivist approaches are required to seize the full dimension and dynamics of the field.We will referee to sociology of actor-networks and qualitative scientometrics leading to the choice of the co-word analysis method in enabling us to capture the project management field and its dynamics.Results of a study based on the analysis of ABI Inform database will be presented and some future trends and scenarios proposed.