Graphene ripples generated by grain boundaries in highly ordered pyrolytic graphite

Atomic scale periodic ripples that extend for several nanometers on the surface of adjacent graphitic grains have been observed for the first time on highly ordered pyrolitic graphite by UHV-STM. The ripples emanate from a grain boundary, and are explained in terms of a mechanical deformation due to the elastic strain accumulated along the GB, which is relieved out-of-plane in the topmost graphene layer. We present a molecular dynamics model that accounts for the formation of similar ripples as result of the lattice mismatch induced by two different grain orientations.

Modelling survival data to account for model uncertainty: a single model or model averaging?

This study considered the problem of predicting survival, based on three alternative models: a single Weibull, a mixture of Weibulls and a cure model. Instead of the common procedure of choosing a single “best” model, where “best” is defined in terms of goodness of fit to the data, a Bayesian model averaging (BMA) approach was adopted to account for model uncertainty. This was illustrated using a case study in which the aim was the description of lymphoma cancer survival with covariates given by phenotypes and gene expression. The results of this study indicate that if the sample size is sufficiently large, one of the three models emerge as having highest probability given the data, as indicated by the goodness of fit measure; the Bayesian information criterion (BIC). However, when the sample size was reduced, no single model was revealed as “best”, suggesting that a BMA approach would be appropriate. Although a BMA approach can compromise on goodness of fit to the data (when compared to the true model), it can provide robust predictions and facilitate more detailed investigation of the relationships between gene expression and patient survival. Keywords: Bayesian modelling; Bayesian model averaging; Cure model; Markov Chain Monte Carlo; Mixture model; Survival analysis; Weibull distribution

Locally weighted learning model predictive control for nonlinear and time varying dynamics

This paper proposes an online learning control system that uses the strategy of Model Predictive Control (MPC) in a model based locally weighted learning framework. The new approach, named Locally Weighted Learning Model Predictive Control (LWL-MPC), is proposed as a solution to learn to control robotic systems with nonlinear and time varying dynamics. This paper demonstrates the capability of LWL-MPC to perform online learning while controlling the joint trajectories of a low cost, three degree of freedom elastic joint robot. The learning performance is investigated in both an initial learning phase, and when the system dynamics change due to a heavy object added to the tool point. The experiment on the real elastic joint robot is presented and LWL-MPC is shown to successfully learn to control the system with and without the object. The results highlight the capability of the learning control system to accommodate the lack of mechanical consistency and linearity in a low cost robot arm.

Spatial prediction of N2O emissions in pasture : a Bayesian model averaging analysis

Nitrous oxide (N2O) is one of the greenhouse gases that can contribute to global warming. Spatial variability of N2O can lead to large uncertainties in prediction. However, previous studies have often ignored the spatial dependency to quantify the N2O - environmental factors relationships. Few researches have examined the impacts of various spatial correlation structures (e.g. independence, distance-based and neighbourhood based) on spatial prediction of N2O emissions. This study aimed to assess the impact of three spatial correlation structures on spatial predictions and calibrate the spatial prediction using Bayesian model averaging (BMA) based on replicated, irregular point-referenced data. The data were measured in 17 chambers randomly placed across a 271 m(2) field between October 2007 and September 2008 in the southeast of Australia. We used a Bayesian geostatistical model and a Bayesian spatial conditional autoregressive (CAR) model to investigate and accommodate spatial dependency, and to estimate the effects of environmental variables on N2O emissions across the study site. We compared these with a Bayesian regression model with independent errors. The three approaches resulted in different derived maps of spatial prediction of N2O emissions. We found that incorporating spatial dependency in the model not only substantially improved predictions of N2O emission from soil, but also better quantified uncertainties of soil parameters in the study. The hybrid model structure obtained by BMA improved the accuracy of spatial prediction of N2O emissions across this study region.

Supplementary information : weighted tree kernels for sequence analysis

Genomic sequences are fundamentally text documents, admitting various representations according to need and tokenization. Gene expression depends crucially on binding of enzymes to the DNA sequence at small, poorly conserved binding sites, limiting the utility of standard pattern search. However, one may exploit the regular syntactic structure of the enzyme's component proteins and the corresponding binding sites, framing the problem as one of detecting grammatically correct genomic phrases. In this paper we propose new kernels based on weighted tree structures, traversing the paths within them to capture the features which underpin the task. Experimentally, we and that these kernels provide performance comparable with state of the art approaches for this problem, while offering significant computational advantages over earlier methods. The methods proposed may be applied to a broad range of sequence or tree-structured data in molecular biology and other domains.

Accurate measurement of the molecular thickness of thin organic shells on small inorganic cores using dynamic light scattering

Dynamic light scattering (DLS) has become a primary nanoparticle characterization technique with applications from materials characterization to biological and environmental detection. With the expansion in DLS use from homogeneous spheres to more complicated nanostructures, comes a decrease in accuracy. Much research has been performed to develop different diffusion models that account for the vastly different structures but little attention has been given to the effect on the light scattering properties in relation to DLS. In this work, small (core size < 5 nm) core-shell nanoparticles were used as a case study to measure the capping thickness of a layer of dodecanethiol (DDT) on Au and ZnO nanoparticles by DLS. We find that the DDT shell has very little effect on the scattering properties of the inorganic core and hence can be ignored to a first approximation. However, this results in conventional DLS analysis overestimating the hydrodynamic size in the volume and number weighted distributions. By introducing a simple correction formula that more accurately yields hydrodynamic size distributions a more precise determination of the molecular shell thickness is obtained. With this correction, the measured thickness of the DDT shell was found to be 7.3 ± 0.3 Å, much less than the extended chain length of 16 Å. This organic layer thickness suggests that on small nanoparticles, the DDT monolayer adopts a compact disordered structure rather than an open ordered structure on both ZnO and Au nanoparticle surfaces. These observations are in agreement with published molecular dynamics results.

Indemnity costs - whether indemnity costs can be ordered in Magistrates Court

In Asset Loan Management v Mamap Pty Ltd [2005] QDC 295, McGill DCJ held that costs may be recovered in Magistrates Courts on the indemnity basis. His Honour was satisfied his conclusion in this respect was not precluded by the decision of the Court of Appeal in Beardmore v Franklins Management Services Pty Ltd [2002] QCA 60

Mixed data types and the use of pattern analysis on the Australian groundnut germplasm data

Data in germplasm collections contain a mixture of data types; binary, multistate and quantitative. Given the multivariate nature of these data, the pattern analysis methods of classification and ordination have been identified as suitable techniques for statistically evaluating the available diversity. The proximity (or resemblance) measure, which is in part the basis of the complementary nature of classification and ordination techniques, is often specific to particular data types. The use of a combined resemblance matrix has an advantage over data type specific proximity measures. This measure accommodates the different data types without manipulating them to be of a specific type. Descriptors are partitioned into their data types and an appropriate proximity measure is used on each. The separate proximity matrices, after range standardisation, are added as a weighted average and the combined resemblance matrix is then used for classification and ordination. Germplasm evaluation data for 831 accessions of groundnut (Arachis hypogaea L.) from the Australian Tropical Field Crops Genetic Resource Centre, Biloela, Queensland were examined. Data for four binary, five ordered multistate and seven quantitative descriptors have been documented. The interpretative value of different weightings - equal and unequal weighting of data types to obtain a combined resemblance matrix - was investigated by using principal co-ordinate analysis (ordination) and hierarchical cluster analysis. Equal weighting of data types was found to be more valuable for these data as the results provided a greater insight into the patterns of variability available in the Australian groundnut germplasm collection. The complementary nature of pattern analysis techniques enables plant breeders to identify relevant accessions in relation to the descriptors which distinguish amongst them. This additional information may provide plant breeders with a more defined entry point into the germplasm collection for identifying sources of variability for their plant improvement program, thus improving the utilisation of germplasm resources.

Should the court direct that costs ordered to be recovered on the indemnity basis be assessed by reference to a costs agreement between the successful party and their solicitors?

The decision in Hook v Boreham & QBE Insurance (Australia) Limited [2006] QDC 304 considered whether the court should go further than order that costs be assessed on the indemnity basis, but should also specify the basis by which those indemnity costs should be determined. The decision makes it clear that under r704(3) of the Uniform Civil Procedure Rules, questions of that nature are ordinarily preserved to the discretion of the Registrar.

Inductively coupled Ar/CH₄/H₂plasmas for low-temperature deposition of ordered carbon nanostructures

The study of inductively coupled Ar/CH 4/H 2 plasmas in the plasma enhanced chemical vapor deposition (PECVD) of self-assembled carbon nanostructures (CN) was presented. A spatially averaged (global) discharge model was developed to study the densities and fluxes of the radical neutrals and charged species, the effective electron temperature, and methane conversion factors under various conditions. It was found that the deposited cation fluxes in the PECVD of CNs generally exceed those of the radical neutrals. The agreement with the optical emission spectroscopy (OES) and quadrupole mass spectrometry (QMS) was also derived through numerical results.

Microscopic ion fluxes in plasma-aided nanofabrication of ordered carbon nanotip structures

Three-dimensional topography of microscopic ion fluxes in the reactive hydrocarbon-based plasma-aided nanofabrication of ordered arrays of vertically aligned single-crystalline carbon nanotip microemitter structures is simulated by using a Monte Carlo technique. The individual ion trajectories are computed by integrating the ion equations of motion in the electrostatic field created by a biased nanostructured substrate. It is shown that the ion flux focusing onto carbon nanotips is more efficient under the conditions of low potential drop Us across the near-substrate plasma sheath. Under low- Us conditions, the ion current density onto the surface of individual nanotips is higher for higher-aspect-ratio nanotips and can exceed the mean ion current density onto the entire nanopattern in up to approximately five times. This effect becomes less pronounced with increasing the substrate bias, with the mean relative enhancement of the ion current density ξi not exceeding ∼1.7. The value of ξi is higher in denser plasmas and behaves differently with the electron temperature Te depending on the substrate bias. When the substrate bias is low, ξi decreases with Te, with the opposite tendency under higher- Us conditions. The results are relevant to the plasma-enhanced chemical-vapor deposition of ordered large-area nanopatterns of vertically aligned carbon nanotips, nanofibers, and nanopyramidal microemitter structures for flat-panel display applications. © 2005 American Institute of Physics.

Comparison of block and event-related experimental designs in diffusion-weighted functional MRI

PURPOSE To compare diffusion-weighted functional magnetic resonance imaging (DfMRI), a novel alternative to the blood oxygenation level-dependent (BOLD) contrast, in a functional MRI experiment. MATERIALS AND METHODS Nine participants viewed contrast reversing (7.5 Hz) black-and-white checkerboard stimuli using block and event-related paradigms. DfMRI (b = 1800 mm/s2 ) and BOLD sequences were acquired. Four parameters describing the observed signal were assessed: percent signal change, spatial extent of the activation, the Euclidean distance between peak voxel locations, and the time-to-peak of the best fitting impulse response for different paradigms and sequences. RESULTS The BOLD conditions showed a higher percent signal change relative to DfMRI; however, event-related DfMRI showed the strongest group activation (t = 21.23, P < 0.0005). Activation was more diffuse and spatially closer to the BOLD response for DfMRI when the block design was used. DfMRIevent showed the shortest TTP (4.4 +/- 0.88 sec). CONCLUSION The hemodynamic contribution to DfMRI may increase with the use of block designs.

Low-temperature assembly of ordered carbon nanotip arrays in low-frequency, high-density inductively coupled plasmas

High-density inductively coupled plasma (ICP)-assisted self-assembly of the ordered arrays of various carbon nanostructures (NS) for the electron field emission applications is reported. Carbon-based nano-particles, nanotips, and pyramid-like structures, with the controllable shape, ordering, and areal density are grown under remarkably low process temperatures (260-350 °C) and pressures (below 0.1 Torr), on the same Ni-based catalyst layers, in a DC bias-controlled floating temperature regime. A high degree of positional and directional ordering, elevated sp2 content, and a well-structured graphitic morphology are achieved without the use of pre-patterned or externally heated substrates.

Contrast transfer function correction applied to cryo-electron tomography and sub-tomogram averaging

Cryo-electron tomography together with averaging of sub-tomograms containing identical particles can reveal the structure of proteins or protein complexes in their native environment. The resolution of this technique is limited by the contrast transfer function (CTF) of the microscope. The CTF is not routinely corrected in cryo-electron tomography because of difficulties including CTF detection, due to the low signal to noise ratio, and CTF correction, since images are characterised by a spatially variant CTF. Here we simulate the effects of the CTF on the resolution of the final reconstruction, before and after CTF correction, and consider the effect of errors and approximations in defocus determination. We show that errors in defocus determination are well tolerated when correcting a series of tomograms collected at a range of defocus values. We apply methods for determining the CTF parameters in low signal to noise images of tilted specimens, for monitoring defocus changes using observed magnification changes, and for correcting the CTF prior to reconstruction. Using bacteriophage PRDI as a test sample, we demonstrate that this approach gives an improvement in the structure obtained by sub-tomogram averaging from cryo-electron tomograms.