‘Spotty Dick’ : a research experiment to test design suitability for the use of jewelled spot matrix patterns for UV aware men’s swimwear

The great male Aussie cossie is growing spots. The ‘dick’ tog, as it is colloquially referred to, is linked to Australia’s national identify with overtly masculine bronzed Aussie bodies clothed in this iconic apparel. Yet the reality is our hunger for worshiping the sun and the addiction to a beach lifestyle is tempered by the pragmatic need for neck-to-knee, or more apt head-to-toe, swimwear. Spotty Dick is an irreverent play on male swimwear – it experiments with alternate modes to sheath the body with Lyrca in order to protect it from searing UV’s and at the same time light-heartedly fools around with texture and pattern; to be specific, black Scharovsky crystals, jewelled in spot patterns - jewelled clothing is not characteristically aligned to menswear and even less so to the great Aussie cossie. The crystals form a matrix of spots that attempt to provoke a sense of mischievousness aligned to the Aussie beach larrikin. Ironically, spot patterns are in itself a form of a parody, as prolonged sun exposure ages the skin and sun spots can occur if appropriate sun protection is not used. ‘Spotty Dick’ – a research experiment to test design suitability for the use of jewelled spot matrix patterns for UV aware men’s swimwear. The creative work was paraded at 56 shows, over a 2 week period, and an estimated 50,000 people viewed the work.

Modeling ion channel dynamics through reflected stochastic differential equations

Ion channels are membrane proteins that open and close at random and play a vital role in the electrical dynamics of excitable cells. The stochastic nature of the conformational changes these proteins undergo can be significant, however current stochastic modeling methodologies limit the ability to study such systems. Discrete-state Markov chain models are seen as the "gold standard," but are computationally intensive, restricting investigation of stochastic effects to the single-cell level. Continuous stochastic methods that use stochastic differential equations (SDEs) to model the system are more efficient but can lead to simulations that have no biological meaning. In this paper we show that modeling the behavior of ion channel dynamics by a reflected SDE ensures biologically realistic simulations, and we argue that this model follows from the continuous approximation of the discrete-state Markov chain model. Open channel and action potential statistics from simulations of ion channel dynamics using the reflected SDE are compared with those of a discrete-state Markov chain method. Results show that the reflected SDE simulations are in good agreement with the discrete-state approach. The reflected SDE model therefore provides a computationally efficient method to simulate ion channel dynamics while preserving the distributional properties of the discrete-state Markov chain model and also ensuring biologically realistic solutions. This framework could easily be extended to other biochemical reaction networks. © 2012 American Physical Society.

Low rank Runge-Kutta methods, symplecticity and stochastic Hamiltonian problems with additive noise

In this paper we extend the ideas of Brugnano, Iavernaro and Trigiante in their development of HBVM($s,r$) methods to construct symplectic Runge-Kutta methods for all values of $s$ and $r$ with $s\geq r$. However, these methods do not see the dramatic performance improvement that HBVMs can attain. Nevertheless, in the case of additive stochastic Hamiltonian problems an extension of these ideas, which requires the simulation of an independent Wiener process at each stage of a Runge-Kutta method, leads to methods that have very favourable properties. These ideas are illustrated by some simple numerical tests for the modified midpoint rule.

Simple rules to contain an invasive species with a complex life cycle and high dispersal capacity

Designing practical rules for controlling invasive species is a challenging task for managers, particularly when species are long-lived, have complex life cycles and high dispersal capacities. Previous findings derived from plant matrix population analyses suggest that effective control of long-lived invaders may be achieved by focusing on killing adult plants. However, the cost-effectiveness of managing different life stages has not been evaluated. We illustrate the benefits of integrating matrix population models with decision theory to undertake this evaluation, using empirical data from the largest infestation of mesquite (Leguminosae: Prosopis spp) within Australia. We include in our model the mesquite life cycle, different dispersal rates and control actions that target individuals at different life stages with varying costs, depending on the intensity of control effort. We then use stochastic dynamic programming to derive cost-effective control strategies that minimize the cost of controlling the core infestation locally below a density threshold and the future cost of control arising from infestation of adjacent areas via seed dispersal. Through sensitivity analysis, we show that four robust management rules guide the allocation of resources between mesquite life stages for this infestation: (i) When there is no seed dispersal, no action is required until density of adults exceeds the control threshold and then only control of adults is needed; (ii) when there is seed dispersal, control strategy is dependent on knowledge of the density of adults and large juveniles (LJ) and broad categories of dispersal rates only; (iii) if density of adults is higher than density of LJ, controlling adults is most cost-effective; (iv) alternatively, if density of LJ is equal or higher than density of adults, management efforts should be spread between adults, large and to a lesser extent small juveniles, but never saplings. Synthesis and applications.In this study, we show that simple rules can be found for managing invasive plants with complex life cycles and high dispersal rates when population models are combined with decision theory. In the case of our mesquite population, focussing effort on controlling adults is not always the most cost-effective way to meet our management objective.

Sensitivity of the NMR density matrix to pulse sequence parameters : a simplified analytic approach

We present a formalism for the analysis of sensitivity of nuclear magnetic resonance pulse sequences to variations of pulse sequence parameters, such as radiofrequency pulses, gradient pulses or evolution delays. The formalism enables the calculation of compact, analytic expressions for the derivatives of the density matrix and the observed signal with respect to the parameters varied. The analysis is based on two constructs computed in the course of modified density-matrix simulations: the error interrogation operators and error commutators. The approach presented is consequently named the Error Commutator Formalism (ECF). It is used to evaluate the sensitivity of the density matrix to parameter variation based on the simulations carried out for the ideal parameters, obviating the need for finite-difference calculations of signal errors. The ECF analysis therefore carries a computational cost comparable to a single density-matrix or product-operator simulation. Its application is illustrated using a number of examples from basic NMR spectroscopy. We show that the strength of the ECF is its ability to provide analytic insights into the propagation of errors through pulse sequences and the behaviour of signal errors under phase cycling. Furthermore, the approach is algorithmic and easily amenable to implementation in the form of a programming code. It is envisaged that it could be incorporated into standard NMR product-operator simulation packages.

Differential expression of chemokine and matrix re-modelling genes is associated with contrasting schistosome-induced hepatopathology in murine models

The pathological outcomes of schistosomiasis are largely dependent on the molecular and cellular mechanisms of the host immune response. In this study, we investigated the contribution of variations in host gene expression to the contrasting hepatic pathology observed between two inbred mouse strains following Schistosoma japonicum infection. Whole genome microarray analysis was employed in conjunction with histological and immunohistochemical analysis to define and compare the hepatic gene expression profiles and cellular composition associated with the hepatopathology observed in S. japonicum-infected BALB/c and CBA mice. We show that the transcriptional profiles differ significantly between the two mouse strains with high statistical confidence. We identified specific genes correlating with the more severe pathology associated with CBA mice, as well as genes which may confer the milder degree of pathology associated with BALB/c mice. In BALB/c mice, neutrophil genes exhibited striking increases in expression, which coincided with the significantly greater accumulation of neutrophils at granulomatous regions seen in histological sections of hepatic tissue. In contrast, up-regulated expression of the eosinophil chemokine CCL24 in CBA mice paralleled the cellular influx of eosinophils to the hepatic granulomas. Additionally, there was greater down-regulation of genes involved in metabolic processes in CBA mice, reflecting the more pronounced hepatic damage in these mice. Profibrotic genes showed similar levels of expression in both mouse strains, as did genes associated with Th1 and Th2 responses. However, imbalances in expression of matrix metalloproteinases (e.g. MMP12, MMP13) and tissue inhibitors of metalloproteinases (TIMP1) may contribute to the contrasting pathology observed in the two strains. Overall, these results provide a more complete picture of the molecular and cellular mechanisms which govern the pathological outcome of hepatic schistosomiasis. This improved understanding of the immunopathogenesis in the murine model schistosomiasis provides the basis for a better appreciation of the complexities associated with chronic human schistosomiasis.

Modelling passenger flow at airport terminals : individual agent decision model for stochastic passenger behaviour

Airport system is complex. Passenger dynamics within it appear to be complicate as well. Passenger behaviours outside standard processes are regarded more significant in terms of public hazard and service rate issues. In this paper, we devised an individual agent decision model to simulate stochastic passenger behaviour in airport departure terminal. Bayesian networks are implemented into the decision making model to infer the probabilities that passengers choose to use any in-airport facilities. We aim to understand dynamics of the discretionary activities of passengers.

Stable strong order 1.0 schemes for solving stochastic ordinary differential equations

The Balanced method was introduced as a class of quasi-implicit methods, based upon the Euler-Maruyama scheme, for solving stiff stochastic differential equations. We extend the Balanced method to introduce a class of stable strong order 1. 0 numerical schemes for solving stochastic ordinary differential equations. We derive convergence results for this class of numerical schemes. We illustrate the asymptotic stability of this class of schemes is illustrated and is compared with contemporary schemes of strong order 1. 0. We present some evidence on parametric selection with respect to minimising the error convergence terms. Furthermore we provide a convergence result for general Balanced style schemes of higher orders.

Pedigree-free animal models : the relatedness matrix reloaded

Animal models typically require a known genetic pedigree to estimate quantitative genetic parameters. Here we test whether animal models can alternatively be based on estimates of relatedness derived entirely from molecular marker data. Our case study is the morphology of a wild bird population, for which we report estimates of the genetic variance-covariance matrices (G) of six morphological traits using three methods: the traditional animal model; a molecular marker-based approach to estimate heritability based on Ritland's pairwise regression method; and a new approach using a molecular genealogy arranged in a relatedness matrix (R) to replace the pedigree in an animal model. Using the traditional animal model, we found significant genetic variance for all six traits and positive genetic covariance among traits. The pairwise regression method did not return reliable estimates of quantitative genetic parameters in this population, with estimates of genetic variance and covariance typically being very small or negative. In contrast, we found mixed evidence for the use of the pedigree-free animal model. Similar to the pairwise regression method, the pedigree-free approach performed poorly when the full-rank R matrix based on the molecular genealogy was employed. However, performance improved substantially when we reduced the dimensionality of the R matrix in order to maximize the signal to noise ratio. Using reduced-rank R matrices generated estimates of genetic variance that were much closer to those from the traditional model. Nevertheless, this method was less reliable at estimating covariances, which were often estimated to be negative. Taken together, these results suggest that pedigree-free animal models can recover quantitative genetic information, although the signal remains relatively weak. It remains to be determined whether this problem can be overcome by the use of a more powerful battery of molecular markers and improved methods for reconstructing genealogies.

Using advanced traits of passengers to facilitate route-choice decision-making

Research interest in pedestrian behaviour spans the retail industry, emergency services, urban planners and other agencies. Most models to simulate and model pedestrian movement can be distinguished on the basis of geographical scale, from the micro-scale movement of obstacle avoidance, through the meso-scale of individuals planning multi-stop shopping trips, up to the macro-scale of overall flow of masses of people between places. In this paper, route-choice decision-making model is devised for modelling passengers flow in airport terminal. A set of devised advanced traits of passengers is firstly proposed. Advanced traits take into account a passenger’s cognitive preferences and demonstrate underlying motivations of route-choice decisions. Although the activities of passengers are normally regarded as stochastic and sometimes unpredictable, real scenarios of passenger flows are basically feasible to be compared with virtual simulations in terms of tactical route-choice decision-making. Passengers in the model are as intelligent agents who possess a bunch of initial basic traits and are categorized into five distinguish groups in terms of routing preferences. Route choices are consecutively determined by inferring current advanced traits according to the utility matrix.

The unresolved struggles between project managers and functional managers in matrix organizations

Having personal that works in projects but belongs to a functional organization is the way that many companies organized their labor force today. Previous research shows that this implies management contradictions and ambiguities between functional manager and project manager; there are unresolved struggles between these two roles in terms of power, accountability, authority and legitimacy. With this paper we aim to analyze those struggles based on previous research and to generate working hypotheses. We first provide a review of the different matrix organizations focusing on the relation between the functional manager and the project manager. We then review the literature concerning temporary organizations and projects as temporary organizations. We conclude by integrating the findings of these perspectives and by identifying working hypotheses and areas for further research.

The financial services cultural orientation matrix

With saturation within domestic marketplaces and increased growth opportunities overseas, many financial service providers are investing in foreign markets. However, cultural attitudes towards money can present market entry challenges to financial service providers. The industry would therefore benefit from a strategic model that helps to align financial marketing mixes with the cultural dimensions of a foreign market. The Financial Services Cultural Orientation (FSCO) Matrix has therefore been designed, with three cultural dimensions identified which influence preference for financial products; preference for cash, aversion to debt and savings orientation. Based on a combination of these dimensions and their relative strength within a culture, eight different consumer segments for financial products are identified, and marketing strategies for each consumer segment are then proposed. Three cultural clusters from the GLOBE Project House et al. (2002) are used to highlight possible geographic markets for each of these consumer segments. In particular, this paper focuses on GLOBE’s Confucian Asia, Southern Asia and Anglo cultural clusters, as these clusters represent the most well established financial markets in the world and the fastest growing financial markets for the future. The FSCO Matrix provides the financial services industry with an innovative and practical tool for addressing cross-cultural challenges and developing successful marketing strategies for entry into foreign markets.

The rationale for using microscopic units of a donor matrix in cartilage defect repair

The efficacy of existing articular cartilage defect repair strategies are limited. Native cartilage tissue forms via a series of exquisitely orchestrated morphogenic events spanning through gestation into early childhood. However, defect repair must be achieved in a non-ideal microenvironment over an accelerated time-frame compatible with the normal life of an adult patient. Scaffolds formed from decellularized tissues are commonly utilized to enable the rapid and accurate repair of tissues such as skin, bladder and heart valves. The intact extracellular matrix remaining following the decellularization of these relatively low-matrix-density tissues is able to rapidly and accurately guide host cell repopulation. By contrast, the extraordinary density of cartilage matrix limits both the initial decellularization of donor material as well as its subsequent repopulation. Repopulation of donor cartilage matrix is generally limited to the periphery, with repopulation of lacunae deeper within the matrix mass being highly inefficient. Herein, we review the relevant literature and discuss the trend toward the use of decellularized donor cartilage matrix of microscopic dimensions. We show that 2-µm microparticles of donor matrix are rapidly integrate with articular chondrocytes, forming a robust cartilage-like composites with enhanced chondrogenic gene expression. Strategies for the clinical application of donor matrix microparticles in cartilage defect repair are discussed.