Effect of solute on the growth rate and the constitutional undercooling ahead of the advancing interface during solidification of an alloy and the implications for nucleation

A framework is presented for modeling the nucleation in the constitutionally supercooled liquid ahead of the advancing solid/liquid interface. The effects of temperature gradient, imposed velocity, slope of liquidus, and initial concentration have been taken into account in this model by considering the effect of interface retardation, which is caused by solute buildup at the interface. Furthermore, the effect of solute concentration on the chemical driving force for nucleation has been considered in this model. The model is used for describing the nucleation of Al-Si and Al-Cu alloys. It was found that the solute of Si has a significant impact on the chemical driving force for nucleation in AI-Si alloys whereas Cu has almost no effect in Al-Cu alloys.

Is there a case for low inflation-induced productivity growth in selected Asian economies?

The authors examine the evidence on the relationship between inflation and productivity growth for nine Asian economies using causality analysis in a multivariate model with money supply as a possible effective monetary policy tool. The inflation-productivity growth relationship is found to be non-uniform, as the evidence of uni-directional, bi-directional, and no causality between the two variables is varied and significant for some countries and insignificant for others. An attempt is made to explain the inflation-productivity nexus for these countries and to discuss implications for anti-inflationary policies such as inflation targeting.

Overexpression of transforming growth factor-beta is associated with increased hyaluronan content and impairment of repair in Marfan syndrome aortic aneurysm

Background-Marfan syndrome (MFS), a condition caused by fibrillin-1 gene mutation is associated with aortic aneurysm that shows elastic lamellae disruption, accumulation of glycosaminoglycans, and vascular smooth muscle cell (VSMC) apoptosis with minimal inflammatory response. We examined aneurysm tissue and cultured cells for expression of transforming growth factor-beta1 to -beta3 (TGF beta 1 to 3), hyaluronan content, apoptosis, markers of cell migration, and infiltration of vascular progenitor cells (CD34). Methods and Results-MFS aortic aneurysm (6 males, 5 females; age 8 to 78 years) and normal aorta (5 males, 3 females; age 22 to 56 years) were used. Immunohistochemistry showed increased expression of TGF beta 1 to 3, hyaluronan, and CD34-positive microcapillaries in MFS aneurysm compared with control. There was increased expression of TGF beta 1 to 3 and hyaluronan in MFS cultured VSMCs, adventitial fibroblasts (AF), and skin fibroblasts (SF). Apoptosis was increased in MFS (VSMC: mean cell loss in MFS 29%, n of subjects = 5, versus control 8%, n = 3, P < 0.05; AF: 28%, n = 5 versus 7%, n = 5, P < 0.05; SF: 29%, n = 3 versus 4%, n = 3, not significant). In MFS, there was a 2-fold increase in adventitial microcapillaries containing CD34-positive cells compared with control tissue. Scratch wound assay showed absence of CD44, MT1-MMP, and beta-3 integrin at the leading edge of migration in MFS indicating altered directional migration. Western blot showed increased expression of TGF beta 1 to 3 in MFS but no change in expression of CD44, MT1-MMP, or beta-3 integrin compared with controls. Conclusions-There was overexpression of TGF-beta in MFS associated with altered hyaluronan synthesis, increased apoptosis, impaired progenitor cell recruitment, and abnormal directional migration. These factors limit tissue repair and are likely to contribute to aneurysm development.

Robo1 regulates the development of major axon tracts and interneuron migration in the forebrain

The Slit genes encode secreted ligands that regulate axon branching, commissural axon pathfinding and neuronal migration. The principal identified receptor for Slit is Robo ( Roundabout in Drosophila). To investigate Slit signalling in forebrain development, we generated Robo1 knockout mice by targeted deletion of exon 5 of the Robo1 gene. Homozygote knockout mice died at birth, but prenatally displayed major defects in axon pathfinding and cortical interneuron migration. Axon pathfinding defects included dysgenesis of the corpus callosum and hippocampal commissure, and abnormalities in corticothalamic and thalamocortical targeting. Slit2 and Slit1/2 double mutants display malformations in callosal development, and in corticothalamic and thalamocortical targeting, as well as optic tract defects. In these animals, corticothalamic axons form large fasciculated bundles that aberrantly cross the midline at the level of the hippocampal and anterior commissures, and more caudally at the medial preoptic area. Such phenotypes of corticothalamic targeting were not observed in Robo1 knockout mice but, instead, both corticothalamic and thalamocortical axons aberrantly arrived at their respective targets at least 1 day earlier than controls. By contrast, in Slit mutants, fewer thalamic axons actually arrive in the cortex during development. Finally, significantly more interneurons ( up to twice as many at E12.5 and E15.5) migrated into the cortex of Robo1 knockout mice, particularly in both rostral and parietal regions, but not caudal cortex. These results indicate that Robo1 mutants have distinct phenotypes, some of which are different from those described in Slit mutants, suggesting that additional ligands, receptors or receptor partners are likely to be involved in Slit/Robo signalling.

Using circular statistics to analyse time patterns in crime incidence

A set of techniques referred to as circular statistics has been developed for the analysis of directional and orientational data. The unit of measure for such data is angular (usually in either degrees or radians), and the statistical distributions underlying the techniques are characterised by their cyclic nature-for example, angles of 359.9 degrees are considered close to angles of 0 degrees. In this paper, we assert that such approaches can be easily adapted to analyse time-of-day and time-of-week data, and in particular daily cycles in the numbers of incidents reported to the police. We begin the paper by describing circular statistics. We then discuss how these may be modified, and demonstrate the approach with some examples for reported incidents in the Cardiff area of Wales. (c) 2005 Elsevier Ltd. All rights reserved.

PhotoVoltaic DC-DC module integrated converter for novel cascaded and bypass grid connection topologies - design and optimisation

Grid connected PhotoVoltaic (PV) inverters fall into three broad categories — Central, String and Module Integrated Converers (MICs). MICs offer any avantaes in performance and flexibility, but are at a cost disadvantage. Two alternative novel approaches proposed by the author — cascaded dc-dc MICs and bypass dc-dc MICs — integrate a simple non-isolated intelligent dc-dc converter with each PV module to provide the advantages of dc-ac MICs at a lower cost. A suitable universal 150W 5A dc-dc converter design is presented based on two interleaved MOSFET half bridges. Testing shows Zero Voltage Switching (ZVS) keeps losses under 1W for bi-directional power flows up to 15W between two adjacent 12V PV modules for the bypass application, and efficiencies over 94% for most of the operational power range for the cascaded converter application. Based on the experimental results, potential optimizations to further reduce losses are discussed.

UQ RoboRoos: Achieving power and agility in a small size robot

The UQ RoboRoos have been developed to participate in the RoboCup robot soccer small size league over several years. RoboCup 2001 saw a focus on the mechanical design of the RoboRoos, with the introduction of an omni-directional drive system and a high power kicker. The change in mechanical design had implications for the rest of the system particularly navigation and multi-robot planning. In addition, the overhead vision system was upgraded to improve reliability and robustness.

Data visualization during the early stages of drug discovery

Multidimensional compound optimization is a new paradigm in the drug discovery process, yielding efficiencies during early stages and reducing attrition in the later stages of drug development. The success of this strategy relies heavily on understanding this multidimensional data and extracting useful information from it. This paper demonstrates how principled visualization algorithms can be used to understand and explore a large data set created in the early stages of drug discovery. The experiments presented are performed on a real-world data set comprising biological activity data and some whole-molecular physicochemical properties. Data visualization is a popular way of presenting complex data in a simpler form. We have applied powerful principled visualization methods, such as generative topographic mapping (GTM) and hierarchical GTM (HGTM), to help the domain experts (screening scientists, chemists, biologists, etc.) understand and draw meaningful decisions. We also benchmark these principled methods against relatively better known visualization approaches, principal component analysis (PCA), Sammon's mapping, and self-organizing maps (SOMs), to demonstrate their enhanced power to help the user visualize the large multidimensional data sets one has to deal with during the early stages of the drug discovery process. The results reported clearly show that the GTM and HGTM algorithms allow the user to cluster active compounds for different targets and understand them better than the benchmarks. An interactive software tool supporting these visualization algorithms was provided to the domain experts. The tool facilitates the domain experts by exploration of the projection obtained from the visualization algorithms providing facilities such as parallel coordinate plots, magnification factors, directional curvatures, and integration with industry standard software. © 2006 American Chemical Society.

Monitoring long distance WDM communication lines using a high-loss loopback supervisory system

In this paper, we present experimental results for monitoring long distance WDM communication links using a line monitoring system suitable for legacy optically amplified long-haul undersea systems. This monitoring system is based on setting up a simple, passive, low cost high-loss optical loopback circuit at each repeater that provides a connection between the existing anti-directional undersea fibres, and can be used to define fault location. Fault location is achieved by transmitting a short pulse supervisory signal along with the WDM data signals where a portion of the overall signal is attenuated and returned to the transmit terminal by the loopback circuit. A special receiver is used at the terminal to extract the weakly returned supervisory signal where each supervisory signal is received at different times corresponding to different optical repeaters. Therefore, the degradation in any repeater appears on its corresponding supervisory signal level. We use a recirculating loop to simulate a 4600 km fibre link, on which a high-loss loopback supervisory system is implemented. Successful monitoring is accomplished through the production of an appropriate supervisory signal at the terminal that is detected and identified in a satisfactory time period after passing through up to 45 dB attenuation in the loopback circuit. © 2012 Elsevier B.V. All rights reserved.

Hierarchical GTM: Constructing localized non-linear projection manifolds in a principled way

It has been argued that a single two-dimensional visualization plot may not be sufficient to capture all of the interesting aspects of complex data sets, and therefore a hierarchical visualization system is desirable. In this paper we extend an existing locally linear hierarchical visualization system PhiVis ¸iteBishop98a in several directions: bf(1) We allow for em non-linear projection manifolds. The basic building block is the Generative Topographic Mapping. bf(2) We introduce a general formulation of hierarchical probabilistic models consisting of local probabilistic models organized in a hierarchical tree. General training equations are derived, regardless of the position of the model in the tree. bf(3) Using tools from differential geometry we derive expressions for local directional curvatures of the projection manifold. Like PhiVis, our system is statistically principled and is built interactively in a top-down fashion using the EM algorithm. It enables the user to interactively highlight those data in the parent visualization plot which are captured by a child model. We also incorporate into our system a hierarchical, locally selective representation of magnification factors and directional curvatures of the projection manifolds. Such information is important for further refinement of the hierarchical visualization plot, as well as for controlling the amount of regularization imposed on the local models. We demonstrate the principle of the approach on a toy data set and apply our system to two more complex 12- and 19-dimensional data sets.

Hierarchical GTM: constructing localized non-linear projection manifolds in a principled way

It has been argued that a single two-dimensional visualization plot may not be sufficient to capture all of the interesting aspects of complex data sets, and therefore a hierarchical visualization system is desirable. In this paper we extend an existing locally linear hierarchical visualization system PhiVis ¸iteBishop98a in several directions: bf(1) We allow for em non-linear projection manifolds. The basic building block is the Generative Topographic Mapping (GTM). bf(2) We introduce a general formulation of hierarchical probabilistic models consisting of local probabilistic models organized in a hierarchical tree. General training equations are derived, regardless of the position of the model in the tree. bf(3) Using tools from differential geometry we derive expressions for local directional curvatures of the projection manifold. Like PhiVis, our system is statistically principled and is built interactively in a top-down fashion using the EM algorithm. It enables the user to interactively highlight those data in the ancestor visualization plots which are captured by a child model. We also incorporate into our system a hierarchical, locally selective representation of magnification factors and directional curvatures of the projection manifolds. Such information is important for further refinement of the hierarchical visualization plot, as well as for controlling the amount of regularization imposed on the local models. We demonstrate the principle of the approach on a toy data set and apply our system to two more complex 12- and 18-dimensional data sets.

A principled approach to interactive hierarchical non-linear visualization of high-dimensional data

Hierarchical visualization systems are desirable because a single two-dimensional visualization plot may not be sufficient to capture all of the interesting aspects of complex high-dimensional data sets. We extend an existing locally linear hierarchical visualization system PhiVis [1] in several directions: bf(1) we allow for em non-linear projection manifolds (the basic building block is the Generative Topographic Mapping -- GTM), bf(2) we introduce a general formulation of hierarchical probabilistic models consisting of local probabilistic models organized in a hierarchical tree, bf(3) we describe folding patterns of low-dimensional projection manifold in high-dimensional data space by computing and visualizing the manifold's local directional curvatures. Quantities such as magnification factors [3] and directional curvatures are helpful for understanding the layout of the nonlinear projection manifold in the data space and for further refinement of the hierarchical visualization plot. Like PhiVis, our system is statistically principled and is built interactively in a top-down fashion using the EM algorithm. We demonstrate the visualization system principle of the approach on a complex 12-dimensional data set and mention possible applications in the pharmaceutical industry.

miniDVMS v1.8 : A user manual(The data visualization and modeling system)

Today, the data available to tackle many scientific challenges is vast in quantity and diverse in nature. The exploration of heterogeneous information spaces requires suitable mining algorithms as well as effective visual interfaces. miniDVMS v1.8 provides a flexible visual data mining framework which combines advanced projection algorithms developed in the machine learning domain and visual techniques developed in the information visualisation domain. The advantage of this interface is that the user is directly involved in the data mining process. Principled projection methods, such as generative topographic mapping (GTM) and hierarchical GTM (HGTM), are integrated with powerful visual techniques, such as magnification factors, directional curvatures, parallel coordinates, and user interaction facilities, to provide this integrated visual data mining framework. The software also supports conventional visualisation techniques such as principal component analysis (PCA), Neuroscale, and PhiVis. This user manual gives an overview of the purpose of the software tool, highlights some of the issues to be taken care while creating a new model, and provides information about how to install and use the tool. The user manual does not require the readers to have familiarity with the algorithms it implements. Basic computing skills are enough to operate the software.

Evidence for dissociation between the perceptual and visuomotor systems in humans

When a visual stimulus is continuously moved behind a small stationary window, the window appears displaced in the direction of motion of the stimulus. In this study we showed that the magnitude of this illusion is dependent on (i) whether a perceptual or visuomotor task is used for judging the location of the window, (ii) the directional signature of the stimulus, and (iii) whether or not there is a significant delay between the end of the visual presentation and the initiation of the localization measure. Our stimulus was a drifting sinusoidal grating windowed in space by a stationary, two-dimensional, Gaussian envelope (σ=1 cycle of sinusoid). Localization measures were made following either a short (200 ms) or long (4.2 s) post-stimulus delay. The visuomotor localization error was up to three times greater than the perceptual error for a short delay. However, the visuomotor and perceptual localization measures were similar for a long delay. Our results provide evidence in support of the hypothesis that separate cortical pathways exist for visual perception and visually guided action and that delayed actions rely on stored perceptual information.

Colour and luminance interactions in the visual perception of motion

We sought to determine the extent to which red–green, colour–opponent mechanisms in the human visual system play a role in the perception of drifting luminance–modulated targets. Contrast sensitivity for the directional discrimination of drifting luminance–modulated (yellow–black) test sinusoids was measured following adaptation to isoluminant red–green sinusoids drifting in either the same or opposite direction. When the test and adapt stimuli drifted in the same direction, large sensitivity losses were evident at all test temporal frequencies employed (1–16 Hz). The magnitude of the loss was independent of temporal frequency. When adapt and test stimuli drifted in opposing directions, large sensitivity losses were evident at lower temporal frequencies (1–4 Hz) and declined with increasing temporal frequency. Control studies showed that this temporal–frequency–dependent effect could not reflect the activity of achromatic units. Our results provide evidence that chromatic mechanisms contribute to the perception of luminance–modulated motion targets drifting at speeds of up to at least 32°s-1. We argue that such mechanisms most probably lie within a parvocellular–dominated cortical visual pathway, sensitive to both chromatic and luminance modulation, but only weakly selective for the direction of stimulus motion.