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.

Grain size distributions of Magneli phases and metallic titanium in chondritic porous interplanetary dust particles

A mineralogical survey of chondritic interplanetary dust particles (IDPs)showed that these micrometeorites differ significantly in form and texture from components of carbonaceous chondrites and contain some mineral assemblages which do not occur in any meteorite class1. Models of chondritic IDP mineral evolution generally ignore the typical (ultra-) fine grain size of consituent minerals which range between 0.002-0.1µm in size2. The chondritic porous (CP) subset of chondritic IDPs is probably debris from short period comets although evidence for a cometary origin is still circumstantial3. If CP IDPs represent dust from regions of the Solar System in which comet accretion occurred, it can be argued that pervasive mineralogical evolution of IDP dust has been arrested due to cryogenic storage in comet nuclei. Thus, preservation in CP IDPs of "unusual meteorite minerals", such as oxides of tin, bismuth and titanium4, should not be dismissed casually. These minerals may contain specific information about processes that occurred in regions of the solar nebula, and early Solar System, which spawned the IDP parent bodies such as comets and C, P and D asteroids6. It is not fully appreciated that the apparent disparity between the mineralogy of CP IDPs and carbonaceous chondrite matrix may also be caused by the choice of electron-beam techniques with different analytical resolution. For example, Mg-Si-Fe distributions of Cl matrix obtained by "defocussed beam" microprobe analyses are displaced towards lower Fe-values when using analytical electron microscope (AEM)data which resolve individual mineral grains of various layer silicates and magnetite in the same matrix6,7. In general, "unusual meteorite minerals" in chondritic IDPs, such as metallic titanium, Tin01-n(Magneli phases) and anatase8 add to the mineral data base of fine-grained Solar System materials and provide constraints on processes that occurred in the early Solar System.

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.

Simulation of phosphine flow in vertical grain storage : a preliminary numerical study

To fumigate grain stored in a silo, phosphine gas is distributed by a combination of diffusion and fan-forced advection. This initial study of the problem mainly focuses on the advection, numerically modelled as fluid flow in a porous medium. We find satisfactory agreement between the flow predictions of two Computational Fluid Dynamics packages, Comsol and Fluent. The flow predictions demonstrate that the highest velocity (>0.1 m/s) occurs less than 0.2m from the inlet and reduces drastically over one metre of silo height, with the flow elsewhere less than 0.002 m/s or 1% of the velocity injection. The flow predictions are examined to identify silo regions where phosphine dosage levels are likely to be too low for effective grain fumigation.

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.

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.

Co-constructing decimal number knowledge

This mathematics education research provides significant insights for the teaching of decimals to children. It is well known that decimals is one of the most difficult topics to learn and teach. Annette’s research is unique in that it focuses not only on the cognitive, but also on the affective and conative aspects of learning and teaching of decimals. The study is innovative as it includes the students as co-constructors and co-researchers. The findings open new ways of thinking for educators about how students cognitively process decimal knowledge, as well as how students might develop a sense of self as a learner, teacher and researcher in mathematics.

The influence of temperature and introduction point on the detection of Rhyzopertha dominica in stored grain

The presence of insect pests in grain storages throughout the supply chain is a significant problem for farmers, grain handlers, and distributors world-wide. Insect monitoring and sampling programmes are used in the stored grains industry for the detection and estimation of pest populations. At the low pest densities dictated by economic and commercial requirements, the accuracy of both detection and abundance estimates can be influenced by variations in the spatial structure of pest populations over short distances. Geostatistical analysis of Rhyzopertha dominica populations in 2 and 3 dimensions showed that insect numbers were positively correlated over short (0.5 cm) distances, and negatively correlated over longer (.10 cm) distances. At 35 C, insects were located significantly further from the grain surface than at 25 and 30 C. Dispersion metrics showed statistically significant aggregation in all cases. The observed heterogeneous spatial distribution of R. dominica may also be influenced by factors such as the site of initial infestation and disturbance during handling. To account for these additional factors, I significantly extended a simulation model that incorporates both pest growth and movement through a typical stored-grain supply chain. By incorporating the effects of abundance, initial infestation site, grain handling, and treatment on pest spatial distribution, I developed a supply chain model incorporating estimates of pest spatial distribution. This was used to examine several scenarios representative of grain movement through a supply chain, and determine the influence of infestation location and grain disturbance on the sampling intensity required to detect pest infestations at various infestation rates. This study has investigated the effects of temperature, infestation point, and grain handling on the spatial distribution and detection of R. dominica. The proportion of grain infested was found to be dependent upon abundance, initial pest location, and grain handling. Simulation modelling indicated that accounting for these factors when developing sampling strategies for stored grain has the potential to significantly reduce sampling costs while simultaneously improving detection rate, resulting in reduced storage and pest management cost while improving grain quality.

Sampling stored-product insect pests : a comparison of four statistical sampling models for probability of pest detection

Background: Developing sampling strategies to target biological pests such as insects in stored grain is inherently difficult owing to species biology and behavioural characteristics. The design of robust sampling programmes should be based on an underlying statistical distribution that is sufficiently flexible to capture variations in the spatial distribution of the target species. Results: Comparisons are made of the accuracy of four probability-of-detection sampling models - the negative binomial model,1 the Poisson model,1 the double logarithmic model2 and the compound model3 - for detection of insects over a broad range of insect densities. Although the double log and negative binomial models performed well under specific conditions, it is shown that, of the four models examined, the compound model performed the best over a broad range of insect spatial distributions and densities. In particular, this model predicted well the number of samples required when insect density was high and clumped within experimental storages. Conclusions: This paper reinforces the need for effective sampling programs designed to detect insects over a broad range of spatial distributions. The compound model is robust over a broad range of insect densities and leads to substantial improvement in detection probabilities within highly variable systems such as grain storage.

Resequencing and fine-mapping of the chromosome 12q13-14 locus associated with multiple sclerosis refines the number of implicated genes

Multiple sclerosis (MS) is a common chronic inflammatory disease of the central nervous system. Susceptibility to the disease is affected by both environmental and genetic factors. Genetic factors include haplotypes in the histocompatibility complex (MHC) and over 50 non-MHC loci reported by genome-wide association studies. Amongst these, we previously reported polymorphisms in chromosome 12q13-14 with a protective effect in individuals of European descent. This locus spans 288 kb and contains 17 genes, including several candidate genes which have potentially significant pathogenic and therapeutic implications. In this study, we aimed to fine-map this locus. We have implemented a two-phase study: a variant discovery phase where we have used next-generation sequencing and two target-enrichment strategies [long-range polymerase chain reaction (PCR) and Nimblegen's solution phase hybridization capture] in pools of 25 samples; and a genotyping phase where we genotyped 712 variants in 3577 healthy controls and 3269 MS patients. This study confirmed the association (rs2069502, P = 9.9 × 10−11, OR = 0.787) and narrowed down the locus of association to an 86.5 kb region. Although the study was unable to pinpoint the key-associated variant, we have identified a 42 (genotyped and imputed) single-nucleotide polymorphism haplotype block likely to harbour the causal variant. No evidence of association at previously reported low-frequency variants in CYP27B1 was observed. As part of the study we compared variant discovery performance using two target-enrichment strategies. We concluded that our pools enriched with Nimblegen's solution phase hybridization capture had better sensitivity to detect true variants than the pools enriched with long-range PCR, whilst specificity was better in the long-range PCR-enriched pools compared with solution phase hybridization capture enriched pools; this result has important implications for the design of future fine-mapping studies.

Numerical characterization of the mechanical properties of metal nanowires

Nanowires (NWs) have attracted appealing and broad application owing to their remarkable mechanical, optical, electrical, thermal and other properties. To unlock the revolutionary characteristics of NWs, a considerable body of experimental and theoretical work has been conducted. However, due to the extremely small dimensions of NWs, the application and manipulation of the in situ experiments involve inherent complexities and huge challenges. For the same reason, the presence of defects appears as one of the most dominant factors in determining their properties. Hence, based on the experiments' deficiency and the necessity of investigating different defects' influence, the numerical simulation or modelling becomes increasingly important in the area of characterizing the properties of NWs. It has been noted that, despite the number of numerical studies of NWs, significant work still lies ahead in terms of problem formulation, interpretation of results, identification and delineation of deformation mechanisms, and constitutive characterization of behaviour. Therefore, the primary aim of this study was to characterize both perfect and defected metal NWs. Large-scale molecular dynamics (MD) simulations were utilized to assess the mechanical properties and deformation mechanisms of different NWs under diverse loading conditions including tension, compression, bending, vibration and torsion. The target samples include different FCC metal NWs (e.g., Cu, Ag, Au NWs), which were either in a perfect crystal structure or constructed with different defects (e.g. pre-existing surface/internal defects, grain/twin boundaries). It has been found from the tensile deformation that Young's modulus was insensitive to different styles of pre-existing defects, whereas the yield strength showed considerable reduction. The deformation mechanisms were found to be greatly influenced by the presence of defects, i.e., different defects acted in the role of dislocation sources, and many affluent deformation mechanisms had been triggered. Similar conclusions were also obtained from the compressive deformation, i.e., Young's modulus was insensitive to different defects, but the critical stress showed evident reduction. Results from the bending deformation revealed that the current modified beam models with the considerations of surface effect, or both surface effect and axial extension effect were still experiencing certain inaccuracy, especially for the NW with ultra small cross-sectional size. Additionally, the flexural rigidity of the NW was found to be insensitive to different pre-existing defects, while the yield strength showed an evident decrease. For the resonance study, the first-order natural frequency of the NW with pre-existing surface defects was almost the same as that from the perfect NW, whereas a lower first-order natural frequency and a significantly degraded quality factor was observed for NWs with grain boundaries. Most importantly, the <110> FCC NWs were found to exhibit a novel beat phenomenon driven by a single actuation, which was resulted from the asymmetry in the lattice spacing in the (110) plane of the NW cross-section, and expected to exert crucial impacts on the in situ nanomechanical measurements. In particular, <110> Ag NWs with rhombic, truncated rhombic, and triangular cross-sections were found to naturally possess two first-mode natural frequencies, which were envisioned with applications in NEMS that could operate in a non-planar regime. The torsion results revealed that the torsional rigidity of the NW was insensitive to the presence of pre-existing defects and twin boundaries, but received evident reduction due to grain boundaries. Meanwhile, the critical angle decreased considerably for defected NWs. This study has provided a comprehensive and deep investigation on the mechanical properties and deformation mechanisms of perfect and defected NWs, which will greatly extend and enhance the existing knowledge and understanding of the properties/performance of NWs, and eventually benefit the realization of their full potential applications. All delineated MD models and theoretical analysis techniques that were established for the target NWs in this research are also applicable to future studies on other kinds of NWs. It has been suggested that MD simulation is an effective and excellent tool, not only for the characterization of the properties of NWs, but also for the prediction of novel or unexpected properties.

Spatio-temporal modelling of ultrafine particle number concentration

This thesis developed semi-parametric regression models for estimating the spatio-temporal distribution of outdoor airborne ultrafine particle number concentration (PNC). The models developed incorporate multivariate penalised splines and random walks and autoregressive errors in order to estimate non-linear functions of space, time and other covariates. The models were applied to data from the "Ultrafine Particles from Traffic Emissions and Child" project in Brisbane, Australia, and to longitudinal measurements of air quality in Helsinki, Finland. The spline and random walk aspects of the models reveal how the daily trend in PNC changes over the year in Helsinki and the similarities and differences in the daily and weekly trends across multiple primary schools in Brisbane. Midday peaks in PNC in Brisbane locations are attributed to new particle formation events at the Port of Brisbane and Brisbane Airport.

Analysis and prediction of the critical current density across [001]-tilt YBa2Cu3O7- grain boundaries of arbitrary misorientation angles

A qualitative analysis of the expected dilatation strain field in the vicinity of an array of grain-boundary (GB) dislocations is presented. The analysis provides a basis for the prediction of the critical current densities (jc) across low-angle YBa2Cu3O7- (YBCO) GBs as a function of their energy. The introduction of the GB energy allows the extension of the analysis to high-angle GBs using established models which predict the GB energy as a function of misorientation angle. The results are compared to published data for jc across [001]-tilt YBCO GBs for the full range of misorientations, showing a good fit. Since the GB energy is directly related to the GB structure, the analysis may allow a generalization of the scaling behavior of jc with the GB energy. © 1995 The American Physical Society.