Emergent innovation through the co-evolution of informal and formal media economies

Well-established distinctions between amateur and professional are blurring as the impact of social media, changes in cultural consumption, and crises in copyright industries’ business models are felt across society and economy. I call this the increasingly rapid co-evolution of the formal market and informal household sectors and analyse it through the concept of ‘social network markets’ – individual choices are made on the basis of other’s choices and such networked preferencing is enhanced by the growing ubiquity of social media platforms. This may allow us better to understand sources of disruption and innovation in audiovisual production and distribution in wealthy Western markets which are as significant as those posed by informal practices outside the West. I examine what is happening around the monetization and professionalization of online video (YouTube, for example) and the socialization of professional production strategies (transmedia, for example) as innovation from the margins.

The evolution of QUT’s Student Success Program : 20,000 students later

“The Student Success Program (SSP) is a monitoring and early intervention program in operation at QUT designed to identify and support those students deemed to be at risk of disengaging for their learning and their institution” (Nelson, Quinn, Marrington & Clarke, 2011, p. 83). This report reflects on the development of the program since its inception in 2007. In acknowledging similar initiatives within the sector that monitor student learning engagement, the Nuts & Bolts session allows for identification and discussion of the critical success factors for these intervention and support programs.

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.

Differential expression and distribution of syndecan-1 and -2 in periodontal wound healing of the rat

Cell-surface proteoglycans participate in several biological functions including interactions with adhesion molecules, growth factors and a variety of other effector molecules. Accordingly, these molecules play a central role in various aspects of cell–cell and cell–matrix interactions. To investigate the expression and distribution of the cell surface proteoglycans, syndecan-1 and -2, during periodontal wound healing, immunohistochemical analyses were carried out using monoclonal antibodies against syndecan-1, or -2 core proteins. Both syndecan-1 and -2 were expressed and distributed differentially at various stages of early inflammatory cell infiltration, granulation tissue formation, and tissue remodeling in periodontal wound healing. Expression of syndecan-1 was noted in inflammatory cells within and around the fibrin clots during the earliest stages of inflammatory cell infiltration. During granulation tissue formation it was noted in fibroblast-like cells and newly formed blood vessels. Syndecan-1 was not seen in newly formed bone or cementum matrix at any of the time periods studied. Syndecan-1 expression was generally less during the late stages of wound healing but was markedly expressed in cells that were close to the repairing junctional epithelium. In contrast, syndecan-2 expression and distribution was not evident at the early stages of inflammatory cell infiltration. During the formation of granulation tissue and subsequent tissue remodeling, syndecan-2 was expressed extracellularly in the newly formed fibrils which were oriented toward the root surface. Syndecan-2 was found to be significantly expressed on cells that were close to the root surface and within the matrix of repaired cementum covering root dentin as well as at the alveolar bone edge. These findings indicate that syndecan-1 and -2 may have distinctive functions during wound healing of the periodontium. The appearance of syndecan-1 may involve both cell–cell and cell–matrix interactions, while syndecan-2 showed a predilection to associate with cell–matrix interactions during hard tissue formation.

Adaptive evolution of color vision as seen through the eyes of butterflies

Butterflies and primates are interesting for comparative color vision studies, because both have evolved middle- (M) and long-wavelength- (L) sensitive photopigments with overlapping absorbance spectrum maxima (lambda(max) values). Although positive selection is important for the maintenance of spectral variation within the primate pigments, it remains an open question whether it contributes similarly to the diversification of butterfly pigments. To examine this issue, we performed epimicrospectrophotometry on the eyes of five Limenitis butterfly species and found a 31-nm range of variation in the lambda(max) values of the L-sensitive photopigments (514-545 nm). We cloned partial Limenitis L opsin gene sequences and found a significant excess of replacement substitutions relative to polymorphisms among species. Mapping of these L photopigment lambda(max) values onto a phylogeny revealed two instances within Lepidoptera of convergently evolved L photopigment lineages whose lambda(max) values were blue-shifted. A codon-based maximum-likelihood analysis indicated that, associated with the two blue spectral shifts, four amino acid sites (Ile17Met, Ala64Ser, Asn70Ser, and Ser137Ala) have evolved substitutions in parallel and exhibit significant d(N)/d(S) >1. Homology modeling of the full-length Limenitis arthemis astyanax L opsin placed all four substitutions within the chromophore-binding pocket. Strikingly, the Ser137Ala substitution is in the same position as a site that in primates is responsible for a 5- to 7-nm blue spectral shift. Our data show that some of the same amino acid sites are under positive selection in the photopigments of both butterflies and primates, spanning an evolutionary distance >500 million years.

Experimental observations of rapid maize streak virus evolution reveal a strand-specific nucleotide substitution bias

Background. Recent reports have indicated that single-stranded DNA (ssDNA) viruses in the taxonomic families Geminiviridae, Parvoviridae and Anellovirus may be evolving at rates of ∼10-4 substitutions per site per year (subs/site/year). These evolution rates are similar to those of RNA viruses and are surprisingly high given that ssDNA virus replication involves host DNA polymerases with fidelities approximately 10 000 times greater than those of error-prone viral RNA polymerases. Although high ssDNA virus evolution rates were first suggested in evolution experiments involving the geminivirus maize streak virus (MSV), the evolution rate of this virus has never been accurately measured. Also, questions regarding both the mechanistic basis and adaptive value of high geminivirus mutation rates remain unanswered. Results. We determined the short-term evolution rate of MSV using full genome analysis of virus populations initiated from cloned genomes. Three wild type viruses and three defective artificial chimaeric viruses were maintained in planta for up to five years and displayed evolution rates of between 7.4 × 10-4 and 7.9 × 10-4 subs/site/year. Conclusion. These MSV evolution rates are within the ranges observed for other ssDNA viruses and RNA viruses. Although no obvious evidence of positive selection was detected, the uneven distribution of mutations within the defective virus genomes suggests that some of the changes may have been adaptive. We also observed inter-strand nucleotide substitution imbalances that are consistent with a recent proposal that high mutation rates in geminiviruses (and possibly ssDNA viruses in general) may be due to mutagenic processes acting specifically on ssDNA molecules. © 2008 Walt et al; licensee BioMed Central Ltd.

Recombination hotspots and host susceptibility modulate the adaptive value of recombination during maize streak virus evolution

Background Maize streak virus -strain A (MSV-A; Genus Mastrevirus, Family Geminiviridae), the maize-adapted strain of MSV that causes maize streak disease throughout sub-Saharan Africa, probably arose between 100 and 200 years ago via homologous recombination between two MSV strains adapted to wild grasses. MSV recombination experiments and analyses of natural MSV recombination patterns have revealed that this recombination event entailed the exchange of the movement protein - coat protein gene cassette, bounded by the two genomic regions most prone to recombination in mastrevirus genomes; the first surrounding the virion-strand origin of replication, and the second around the interface between the coat protein gene and the short intergenic region. Therefore, aside from the likely adaptive advantages presented by a modular exchange of this cassette, these specific breakpoints may have been largely predetermined by the underlying mechanisms of mastrevirus recombination. To investigate this hypothesis, we constructed artificial, low-fitness, reciprocal chimaeric MSV genomes using alternating genomic segments from two MSV strains; a grass-adapted MSV-B, and a maize-adapted MSV-A. Between them, each pair of reciprocal chimaeric genomes represented all of the genetic material required to reconstruct - via recombination - the highly maize-adapted MSV-A genotype, MSV-MatA. We then co-infected a selection of differentially MSV-resistant maize genotypes with pairs of reciprocal chimaeras to determine the efficiency with which recombination would give rise to high-fitness progeny genomes resembling MSV-MatA. Results Recombinants resembling MSV-MatA invariably arose in all of our experiments. However, the accuracy and efficiency with which the MSV-MatA genotype was recovered across all replicates of each experiment depended on the MSV susceptibility of the maize genotypes used and the precise positions - in relation to known recombination hotspots - of the breakpoints required to re-create MSV-MatA. Although the MSV-sensitive maize genotype gave rise to the greatest variety of recombinants, the measured fitness of each of these recombinants correlated with their similarity to MSV-MatA. Conclusions The mechanistic predispositions of different MSV genomic regions to recombination can strongly influence the accessibility of high-fitness MSV recombinants. The frequency with which the fittest recombinant MSV genomes arise also correlates directly with the escalating selection pressures imposed by increasingly MSV-resistant maize hosts.

Front interactions in a three-component system

The three-component reaction-diffusion system introduced in [C. P. Schenk et al., Phys. Rev. Lett., 78 (1997), pp. 3781–3784] has become a paradigm model in pattern formation. It exhibits a rich variety of dynamics of fronts, pulses, and spots. The front and pulse interactions range in type from weak, in which the localized structures interact only through their exponentially small tails, to strong interactions, in which they annihilate or collide and in which all components are far from equilibrium in the domains between the localized structures. Intermediate to these two extremes sits the semistrong interaction regime, in which the activator component of the front is near equilibrium in the intervals between adjacent fronts but both inhibitor components are far from equilibrium there, and hence their concentration profiles drive the front evolution. In this paper, we focus on dynamically evolving N-front solutions in the semistrong regime. The primary result is use of a renormalization group method to rigorously derive the system of N coupled ODEs that governs the positions of the fronts. The operators associated with the linearization about the N-front solutions have N small eigenvalues, and the N-front solutions may be decomposed into a component in the space spanned by the associated eigenfunctions and a component projected onto the complement of this space. This decomposition is carried out iteratively at a sequence of times. The former projections yield the ODEs for the front positions, while the latter projections are associated with remainders that we show stay small in a suitable norm during each iteration of the renormalization group method. Our results also help extend the application of the renormalization group method from the weak interaction regime for which it was initially developed to the semistrong interaction regime. The second set of results that we present is a detailed analysis of this system of ODEs, providing a classification of the possible front interactions in the cases of $N=1,2,3,4$, as well as how front solutions interact with the stationary pulse solutions studied earlier in [A. Doelman, P. van Heijster, and T. J. Kaper, J. Dynam. Differential Equations, 21 (2009), pp. 73–115; P. van Heijster, A. Doelman, and T. J. Kaper, Phys. D, 237 (2008), pp. 3335–3368]. Moreover, we present some results on the general case of N-front interactions.

Quantifying the roles of cell motility and cell proliferation in a circular barrier assay

Moving fronts of cells are essential features of embryonic development, wound repair and cancer metastasis. This paper describes a set of experiments to investigate the roles of random motility and proliferation in driving the spread of an initially confined cell population. The experiments include an analysis of cell spreading when proliferation was inhibited. Our data have been analysed using two mathematical models: a lattice-based discrete model and a related continuum partial differential equation model. We obtain independent estimates of the random motility parameter, D, and the intrinsic proliferation rate, λ, and we confirm that these estimates lead to accurate modelling predictions of the position of the leading edge of the moving front as well as the evolution of the cell density profiles. Previous work suggests that systems with a high λ/D ratio will be characterized by steep fronts, whereas systems with a low λ/D ratio will lead to shallow diffuse fronts and this is confirmed in the present study. Our results provide evidence that continuum models, based on the Fisher–Kolmogorov equation, are a reliable platform upon which we can interpret and predict such experimental observations.

Cometary evolution : Clues from chondritic interplanetary dust particles

Cometary and interplanetary dust particles (IDP) are compared, and the mineralogical evolution of comet nuclei is discussed. Chondritic IDP have properties consistent with properties expected for cometary dust. The complex and varied mineralogy of these particles may indicate mineral alteration processes that occur in comet nuclei. Depending on the thermal budget of a comet, the upper few meters of nucleus material may maintain temperatures within regimes of hydrocryogenic (200 to 237K) and low-temperature aqueous (274 to 400K) alteration. Thus, layer silicates, carbonates, and sulfates may be important components of cometary dust and, correspondingly are common constituents of chondritic IDPs. Alteration of comet starting materials may be a common occurrence, and depends on the specific physical and chemical properties of each individual comet.

Adaptive stepsize based on control theory for stochastic differential equations

The numerical solution of stochastic differential equations (SDEs) has been focused recently on the development of numerical methods with good stability and order properties. These numerical implementations have been made with fixed stepsize, but there are many situations when a fixed stepsize is not appropriate. In the numerical solution of ordinary differential equations, much work has been carried out on developing robust implementation techniques using variable stepsize. It has been necessary, in the deterministic case, to consider the "best" choice for an initial stepsize, as well as developing effective strategies for stepsize control-the same, of course, must be carried out in the stochastic case. In this paper, proportional integral (PI) control is applied to a variable stepsize implementation of an embedded pair of stochastic Runge-Kutta methods used to obtain numerical solutions of nonstiff SDEs. For stiff SDEs, the embedded pair of the balanced Milstein and balanced implicit method is implemented in variable stepsize mode using a predictive controller for the stepsize change. The extension of these stepsize controllers from a digital filter theory point of view via PI with derivative (PID) control will also be implemented. The implementations show the improvement in efficiency that can be attained when using these control theory approaches compared with the regular stepsize change strategy.

Numerical simulation of stochastic ordinary differential equations in biomathematical modelling

In this work we discuss the effects of white and coloured noise perturbations on the parameters of a mathematical model of bacteriophage infection introduced by Beretta and Kuang in [Math. Biosc. 149 (1998) 57]. We numerically simulate the strong solutions of the resulting systems of stochastic ordinary differential equations (SDEs), with respect to the global error, by means of numerical methods of both Euler-Taylor expansion and stochastic Runge-Kutta type.

Numerical methods for strong solutions of stochastic differential equations : an overview

This paper gives a review of recent progress in the design of numerical methods for computing the trajectories (sample paths) of solutions to stochastic differential equations. We give a brief survey of the area focusing on a number of application areas where approximations to strong solutions are important, with a particular focus on computational biology applications, and give the necessary analytical tools for understanding some of the important concepts associated with stochastic processes. We present the stochastic Taylor series expansion as the fundamental mechanism for constructing effective numerical methods, give general results that relate local and global order of convergence and mention the Magnus expansion as a mechanism for designing methods that preserve the underlying structure of the problem. We also present various classes of explicit and implicit methods for strong solutions, based on the underlying structure of the problem. Finally, we discuss implementation issues relating to maintaining the Brownian path, efficient simulation of stochastic integrals and variable-step-size implementations based on various types of control.