Spatial variation of particle number concentration in school microscale environment

There is significant toxicological evidence of the effects of ultrafine particles (<100nm) on human health (WHO 2005). Studies show that the number concentration of particles has been associated with adverse human health effects (Englert 2004). This work is part of a major study called ‘Ultrafine Particles form Traffic Emissions and Children’s Health’ (UPTECH), which seeks to determine the effect of the exposure to traffic related ultrafine particles on children’s health in schools (http://www.ilaqh.qut.edu.au/Misc/UPT ECH%20Home.htm). Quantification of spatial variation of particle number concentration (PNC) in a microscale environment and identification of the main affecting parameters and their contribution levels are the main aims of this analysis.

Targeting aurora kinases : a novel approach to curb the growth and chemoresistance of androgen refractory prostate cancer

Aurora Kinase (AK) based therapy targeting AK-A & B is effective against some cancers. We have explored its potential against previously unreported incurable, metastatic androgen depletion independent Prostate Cancer (ADIPC). We used androgen sensitive (AS) and ADI lines derived from Transgenic Adenocarcinoma of the Mouse Prostate (TRAMP) mice. The relevance of this model was unequivocally established through focussed array, quantitative PCR and western blotting studies; significantly greater alteration of genes (fold change and number) representing major cancer pathways was shown in ADI cells compared to AS lines. A marked enhancement of in vivo growth of the ADI subline showing the greatest degree of gene modulations [TRAMP C1 (TC1)-T5: TC1-T5] reflected this. In contrast to the parental AS TC1 line, TC1-T5 cells grew with 100% incidence in the prostate, as lung pseudometastases and migrated to the bone and other soft tissues. The potential involvement of AKs in this transition was indicated by the significant upregulation of AK-A/B and their downstream regulators, survivin and phosphorylated-histone H3 in TC1-T5 cells compared to TC1 cells. This led to enhanced sensitivity of TC1-T5 cells to the pan-AK inhibitor, VX680 and to significant reduction in in vivo tumour growth rates when AK-A and/or B were downregulated in TC1-T5 cells. This cell growth inhibition was markedly enhanced when both AKs were downregulated and also led to substantially greater sensitivity of these cells to docetaxel, the only chemotherapeutic with activity against ADI PC. Finally, use of VX680 with docetaxel led to impressive synergies suggesting promise for treating clinical ADI metastatic PC.

Marginal reversible jump Markov chain Monte Carlo with application to motor unit number estimation

Motor unit number estimation (MUNE) is a method which aims to provide a quantitative indicator of progression of diseases that lead to loss of motor units, such as motor neurone disease. However the development of a reliable, repeatable and fast real-time MUNE method has proved elusive hitherto. Ridall et al. (2007) implement a reversible jump Markov chain Monte Carlo (RJMCMC) algorithm to produce a posterior distribution for the number of motor units using a Bayesian hierarchical model that takes into account biological information about motor unit activation. However we find that the approach can be unreliable for some datasets since it can suffer from poor cross-dimensional mixing. Here we focus on improved inference by marginalising over latent variables to create the likelihood. In particular we explore how this can improve the RJMCMC mixing and investigate alternative approaches that utilise the likelihood (e.g. DIC (Spiegelhalter et al., 2002)). For this model the marginalisation is over latent variables which, for a larger number of motor units, is an intractable summation over all combinations of a set of latent binary variables whose joint sample space increases exponentially with the number of motor units. We provide a tractable and accurate approximation for this quantity and also investigate simulation approaches incorporated into RJMCMC using results of Andrieu and Roberts (2009).

The clay-size fraction of CI chondrites Alais and Orgueil : an AEM study

CI chondrites are used pervasively in the meteorite literature as a cosmochemical reference point for bulk compositions[1], isotope analyses[2] and, within certain models of meteorite evolution, as an important component of an alteration sequence within the carbonaceous chondrite subset[3]. More recently, the chemical variablity of CI chondrite matrices (which comprise >80% of the meteorite), has been cited in discussions about the "chondritic" nature of spectroscopic data from P/comet Halley missions[4] and of chemical data from related materials such as interplanetary dust particles[5]. Most CI chondrites have been studied as bulk samples(e.g. major and trace element abundances)and considerable effort has also been focussed on accessory phases such as magnetites, olivine, sulphates and carbonates [6-8]. A number of early studies showed that the primary constituents of CI matrices are layer silicates and the most definitive structural study on powdered samples identified two minerals: montmorillonite and serpentine[9]. In many cases, as with the study by Bass[9],the relative scarcity of most CI chondrites restricts such bulk analyses to the Orgueil meteorite. The electron microprobe/SEM has been used on petrographic sections to more precisely define the "bulk" composition of at least four CI matrices[3], and as recently summarised by McSween[3], these data define a compositional trend quite different to that obtained for CM chondrite matrices. These "defocussed-beam" microprobe analyses average major element compositions over matrix regions ~lOOµm in diameter and provide only an approximation to silicate mineral composition(s) because their grain sizes are much less than the diameter of the beam. In order to (a) more precisely define the major element compositions of individual mineral grains within CI matrices, and (b)complement previous TEM studies [11,12], we have undertaken an analytical electron microscopy (AEM) study of Alais and Orgueil matrices.

Adaptive sizing of populations and number of islands in distributed genetic algorithms

Deciding the appropriate population size and number of is- lands for distributed island-model genetic algorithms is often critical to the algorithm’s success. This paper outlines a method that automatically searches for good combinations of island population sizes and the number of islands. The method is based on a race between competing parameter sets, and collaborative seeding of new parameter sets. This method is applicable to any problem, and makes distributed genetic algorithms easier to use by reducing the number of user-set parameters. The experimental results show that the proposed method robustly and reliably finds population and islands settings that are comparable to those found with traditional trial-and-error approaches.

Towards Bayesian experimental design for nonlinear models that require a large number of sampling times

The use of Bayesian methodologies for solving optimal experimental design problems has increased. Many of these methods have been found to be computationally intensive for design problems that require a large number of design points. A simulation-based approach that can be used to solve optimal design problems in which one is interested in finding a large number of (near) optimal design points for a small number of design variables is presented. The approach involves the use of lower dimensional parameterisations that consist of a few design variables, which generate multiple design points. Using this approach, one simply has to search over a few design variables, rather than searching over a large number of optimal design points, thus providing substantial computational savings. The methodologies are demonstrated on four applications, including the selection of sampling times for pharmacokinetic and heat transfer studies, and involve nonlinear models. Several Bayesian design criteria are also compared and contrasted, as well as several different lower dimensional parameterisation schemes for generating the many design points.

Mechanical properties of graphene : effects of layer number, temperature and isotope

Herein the mechanical properties of graphene, including Young’s modulus, fracture stress and fracture strain have been investigated by molecular dynamics simulations. The simulation results show that the mechanical properties of graphene are sensitive to the temperature changes but insensitive to the layer numbers in the multilayer graphene. Increasing temperature exerts adverse and significant effects on the mechanical properties of graphene. However, the adverse effect produced by the increasing layer number is marginal. On the other hand, isotope substitutions in graphene play a negligible role in modifying the mechanical properties of graphene.

Efficient solution of multiple cracks in great number using eigen COD boundary integral equations with iteration procedure

A newly developed computational approach is proposed in the paper for the analysis of multiple crack problems based on the eigen crack opening displacement (COD) boundary integral equations. The eigen COD particularly refers to a crack in an infinite domain under fictitious traction acting on the crack surface. With the concept of eigen COD, the multiple cracks in great number can be solved by using the conventional displacement discontinuity boundary integral equations in an iterative fashion with a small size of system matrix to determine all the unknown CODs step by step. To deal with the interactions among cracks for multiple crack problems, all cracks in the problem are divided into two groups, namely the adjacent group and the far-field group, according to the distance to the current crack in consideration. The adjacent group contains cracks with relatively small distances but strong effects to the current crack, while the others, the cracks of far-field group are composed of those with relatively large distances. Correspondingly, the eigen COD of the current crack is computed in two parts. The first part is computed by using the fictitious tractions of adjacent cracks via the local Eshelby matrix derived from the traction boundary integral equations in discretized form, while the second part is computed by using those of far-field cracks so that the high computational efficiency can be achieved in the proposed approach. The numerical results of the proposed approach are compared not only with those using the dual boundary integral equations (D-BIE) and the BIE with numerical Green's functions (NGF) but also with those of the analytical solutions in literature. The effectiveness and the efficiency of the proposed approach is verified. Numerical examples are provided for the stress intensity factors of cracks, up to several thousands in number, in both the finite and infinite plates.

Nature and genesis of clay minerals of the Rustler Formation in the vicinity of the Waste Isolation Pilot Plant in Souteastern New Mexico

Detailed mineralogical studies of the matrix and fracture-fill materials of a large number of samples from the Rustler Formation have been carried out using x-ray diffraction, high-resolution transmission electron microscopy, electron microprobe analysis, x-ray fluorescence, and atomic absorption spectrophotometry. These analyses indicate the presence of four clay minerals: interstratified chlorite/saponite, illite, chlorite, and serpentine. Corrensite (regularly stratified chlorite/saponite) is the dominant clay mineral in samples from the Culebra dolomite and two shale layers of the lower unnamed member of the Rustler Formation. Within other layers of the Rustler Formation, disordered mixed chlorite/saponite is usually the most abundant clay mineral. Studies of the morphology and composition of clay crystallites suggest that the corrensite was formed by the alteration of detrital dioctahedral smectite in magnesium-rich pore fluids during early diagenesis of the Rustler Formation. This study provides initial estimates of the abundance and nature of the clay minerals in the Culebra dolomite in the vicinity of the Waste Isolation Pilot Plant.

Integration of opinion into customer analysis model

As e-commerce is becoming more and more popular, the number of customer reviews that a product receives grows rapidly. In order to enhance customer satisfaction and their shopping experiences, it has become important to analysis customers reviews to extract opinions on the products that they buy. Thus, Opinion Mining is getting more important than before especially in doing analysis and forecasting about customers’ behavior for businesses purpose. The right decision in producing new products or services based on data about customers’ characteristics means profit for organization/company. This paper proposes a new architecture for Opinion Mining, which uses a multidimensional model to integrate customers’ characteristics and their comments about products (or services). The key step to achieve this objective is to transfer comments (opinions) to a fact table that includes several dimensions, such as, customers, products, time and locations. This research presents a comprehensive way to calculate customers’ orientation for all possible products’ attributes.

Graphene nanocomposites

Graphene, one of the allotropes (diamond, carbon nanotube, and fullerene) of carbon, is a monolayer of honeycomb lattice of carbon atoms discovered in 2004. The Nobel Prize in Physics 2010 was awarded to Andre Geim and Konstantin Novoselov for their ground breaking experiments on the twodimensional graphene [1]. Since its discovery, the research communities have shown a lot of interest in this novel material owing to its unique properties. As shown in Figure 1, the number of publications on graphene has dramatically increased in recent years. It has been confirmed that graphene possesses very peculiar electrical properties such as anomalous quantum hall effect, and high electron mobility at room temperature (250000 cm2/Vs). Graphene is also one of the stiffest (modulus ~1 TPa) and strongest (strength ~100 GPa) materials. In addition, it has exceptional thermal conductivity (5000 Wm-1K-1). Based on these exceptional properties, graphene has found its applications in various fields such as field effect devices, sensors, electrodes, solar cells, energy storage devices and nanocomposites. Only adding 1 volume per cent graphene into polymer (e.g. polystyrene), the nanocomposite has a conductivity of ~0.1 Sm-1 [2], sufficient for many electrical applications. Significant improvement in strength, fracture toughness and fatigue strength has also been achieved in these nanocomposites [3-5]. Therefore, graphene-polymer nanocomposites have demonstrated a great potential to serve as next generation functional or structural materials.

Spatial variation of particle number concentration in school microscale environments and its impact on exposure assessment

It has not yet been established whether the spatial variation of particle number concentration (PNC) within a microscale environment can have an effect on exposure estimation results. In general, the degree of spatial variation within microscale environments remains unclear, since previous studies have only focused on spatial variation within macroscale environments. The aims of this study were to determine the spatial variation of PNC within microscale school environments, in order to assess the importance of the number of monitoring sites on exposure estimation. Furthermore, this paper aims to identify which parameters have the largest influence on spatial variation, as well as the relationship between those parameters and spatial variation. Air quality measurements were conducted for two consecutive weeks at each of the 25 schools across Brisbane, Australia. PNC was measured at three sites within the grounds of each school, along with the measurement of meteorological and several other air quality parameters. Traffic density was recorded for the busiest road adjacent to the school. Spatial variation at each school was quantified using coefficient of variation (CV). The portion of CV associated with instrument uncertainty was found to be 0.3 and therefore, CV was corrected so that only non-instrument uncertainty was analysed in the data. The median corrected CV (CVc) ranged from 0 to 0.35 across the schools, with 12 schools found to exhibit spatial variation. The study determined the number of required monitoring sites at schools with spatial variability and tested the deviation in exposure estimation arising from using only a single site. Nine schools required two measurement sites and three schools required three sites. Overall, the deviation in exposure estimation from using only one monitoring site was as much as one order of magnitude. The study also tested the association of spatial variation with wind speed/direction and traffic density, using partial correlation coefficients to identify sources of variation and non-parametric function estimation to quantify the level of variability. Traffic density and road to school wind direction were found to have a positive effect on CVc, and therefore, also on spatial variation. Wind speed was found to have a decreasing effect on spatial variation when it exceeded a threshold of 1.5 (m/s), while it had no effect below this threshold. Traffic density had a positive effect on spatial variation and its effect increased until it reached a density of 70 vehicles per five minutes, at which point its effect plateaued and did not increase further as a result of increasing traffic density.

Re-framing fashion : from original and copy to adaptation

Partington notes that clothing produced by individual consumers through adaptation of patterns is contextualised as a watered down version of original couture. In its most reductive form, this notion characterises fashion as commercial and exploitative. Descriptors such as appropriation, imitation, copy and so forth have restricted the opportunity to understand fashion as a major global cultural form and institution. Therefore exploring and understanding the concept of adaptation will shift the attention from a superficial assessment of original versus imitation or copy to adaptation as a practice that provides a better framework for the understanding of designers’ and couturiers’ innovative practices and creativity, describing also the active engagement of consumers with fashion at the micro level. Adaptation can also provide a way to understand different historical shifts in the fashion system, from individual creative agency with home dressmaking and re-making to the explosion of the mass market and the consequent abandonment of such practices. Home dressmaking has been replaced by fashion remix of mass produced garments, a practice that thrives in our environment of globalised fast fashion. Thus this chapter suggests the need for a contextual requalification of concepts such as original, copy, imitation and copyright, and argues that these categories have been played against each other, but they are in fact interdependent. Today, big labels and conglomerates try to control knowledge and innovation through copyright, but, fashion escapes copyright because, in fashion, creativity is contextual. The institutionalisation of couture from 1868 served as a way to control knowledge about production processes in fashion; on the other hand, adaptation practices, often subversive, have been fundamental to the democratisation of fashion.

Alteration of the foetal skin's response to Lipopolysaccharide (LPS) following Ureplasma Parvum exposure

Early preterm birth (<32 weeks) is associated with in utero infection and inflammation. We used an ovine model of in utero infection to ask if exposure to Ureaplasma serovar 3 (UP) modulated the response of the fetal skin to LPS.

Urban agriculture : a growing field of research workshop at INTERACT 2013

Growing food presents diverse challenges and opportunities within the urban environment. As cities develop, population density rises, land prices rise, and the opportunity to use land for traditional farming and gardening diminishes. Counter to this trend there are a growing number of both community gardens, city farms, guerrilla gardening, rooftop and vertical gardens, pot plants, windowsill herbs, and other balcony or backyard gardens cropping up in different cities, all with a purpose to produce food. This workshop brings to-gether practitioners and researchers in the field of urban agriculture and Hu-man-Computer Interaction to explore and opportunities for technology design to support the different forms of growing practice and foster local food production in cities. This 1-day workshop will serve as an active forum for researchers and practi-tioners across various fields including, but not limited to, agriculture and gar-dening, education, urban planning, human-computer interaction, and communi-ty engagement. This workshop has three distinct points of focus: i) Individual and small-scale gardening and food production, and how to connect like minded people who are involved in these practices to share their knowledge ii) Com-munities involved in urban agriculture, either through community gardens, city farms, or grassroots movements, often dependant on volunteer participation, providing the challenge of managing limited resources iii) Environmental and sociocultural sustainability through urban agriculture. The participants will have an opportunity to present their own work. This will be followed by a visit to a nearby city farm, which will provide a local context for a group design exercise. Finally the workshop will conclude with panel dis-cussions to review opportunities for further research and collaborations beyond the conference. For more information, please visit the workshop website, at http://www.urbaninformatics.net/resources/interact2013cfp/