From Design to Production Control Through the Integration of Engineering Data Management and Workflow Management Systems

At a time when many companies are under pressure to reduce "times-to-market" the management of product information from the early stages of design through assembly to manufacture and production has become increasingly important. Similarly in the construction of high energy physics devices the collection of (often evolving) engineering data is central to the subsequent physics analysis. Traditionally in industry design engineers have employed Engineering Data Management Systems (also called Product Data Management Systems) to coordinate and control access to documented versions of product designs. However, these systems provide control only at the collaborative design level and are seldom used beyond design. Workflow management systems, on the other hand, are employed in industry to coordinate and support the more complex and repeatable work processes of the production environment. Commercial workflow products cannot support the highly dynamic activities found both in the design stages of product development and in rapidly evolving workflow definitions. The integration of Product Data Management with Workflow Management can provide support for product development from initial CAD/CAM collaborative design through to the support and optimisation of production workflow activities. This paper investigates this integration and proposes a philosophy for the support of product data throughout the full development and production lifecycle and demonstrates its usefulness in the construction of CMS detectors.Comment: 18 pages, 13 figure

Payments for Ecosystem Services: Legal and Institutional Frameworks

Analysis and engagement with partners working on ecosystem services transactions, policies and laws over the past 10 years have demonstrated a clear need to better understand the legal and institutional frameworks that have the potential to promote or hinder the development of payments for ecosystem services (PES) schemes, as well as the complex legal considerations that affect ecosystem services projects. In response, the IUCN Environmental Law Centre and The Katoomba Group have worked on a joint initiative to analyze the legal and institutional frameworks of water-related PES schemes and projects in four Andean countries: South America (Northeastern)-Brazil; Bolivia, Colombia and Peru. It has resulted in this report. Country-based analysts with experience in ecosystem services transactions have developed country and project assessments to define existing and recommend future regulatory and institutional frameworks that enable equitable and long-lasting ecosystem services transactions. Partners from North America (Central America)-Costa Rica; North America-Mexico; Ecuador and the North America-United States provided feedback on the assessments. The country assessments yielded lessons which were used to develop a set of recommendations on legal frameworks, property rights, enabling institutions, PES contracts, and governance issues supporting the future development of PES schemes

Resolving the Sin(I) degeneracy in Low-Mass Multi-Planet Systems

Long-term orbital evolution of multi-planet systems under tidal dissipation often converges to a stationary state, known as the tidal fixed point. The fixed point is characterized by a lack of oscillations in the eccentricities and apsidal alignment among the orbits. Quantitatively, the nature of the fixed point is dictated by mutual interactions among the planets as well as non-Keplerian effects. We show that if a roughly coplanar system hosts a hot, sub-Saturn mass planet, and is tidally relaxed, separation of planet-planet interactions and non-Keplerian effects in the equations of motion leads to a direct determination of the true masses of the planets. Consequently, a "snap-shot" observational determination of the orbital state resolves the sin(I) degeneracy, and opens up a direct avenue towards identification of the true lowest-mass exo-planets detected. We present an approximate, as well as a general, mathematical framework for computation of the line of sight inclination of secular systems, and apply our models illustratively to the 61 Vir system. We conclude by discussing the observability of planetary systems to which our method is applicable and we set our analysis into a broader context by presenting a current summary of the various possibilities for determining the physical properties of planets from observations of their orbital states.Comment: 9 pages, 7 figures, 1 table, Accepted to the Astrophysical Journa

Effective potential in three-dimensional O(N) models

We consider the effective potential in three-dimensional models with O(N) symmetry. For generic values of N, and in particular for the physically interesting cases N=0,1,2,3, we determine the six-point and eight-point renormalized coupling constants which parametrize its small-field expansion. These estimates are obtained from the analysis of their $\epsilon$-expansion, taking into account the exact results in one and zero dimensions, and, for the Ising model (i.e. N=1), the accurate high-temperature estimates in two dimensions. They are compared with the available results from other approaches. We also obtain corresponding estimates for the two-dimensional O($N$) models.Comment: 22 pages, revtex, 2 fig

The Complex Structure of the Multi-Phase Galactic Wind in a Starburst Merger

Neutral outflows have been detected in many ultraluminous infrared galaxies (ULIRGs) via the Na I D $\lambda\lambda 5890, 5896$ absorption-line doublet. For the first time, we have mapped and analyzed the 2-D kinematics of a cool neutral outflow in a ULIRG, F10565+2448, using the integral field unit (IFU) on Gemini North to observe the Na I D feature. At the same time we have mapped the ionized outflow with the [NII] and H$\alpha$ emission lines. We find a systemic rotation curve that is consistent with the rotation of the molecular disk determined from previous CO observations. The absorption lines show evidence of a nuclear outflow with a radial extent of at least 3 kpc, consistent with previous observations. The strength of the Na I D lines have a strong, spatially resolved correlation with reddening, suggesting that dust is present in the outflow. Surprisingly, the outflow velocities of the neutral gas show a strong asymmetry in the form of a major-axis gradient that is opposite in sign to disk rotation. This is inconsistent with entrained material rotating along with the galaxy or with a tilted minor-axis outflow. We hypothesize that this unusual behavior is due to an asymmetry in the distribution of the ambient gas. We also see evidence of asymmetric ionized outflow in the emission-line velocity map, which appear to be decoupled from the neutral outflow. Our results strengthen the hypothesis that ULIRG outflows differ in morphology from those in more quiescent disk galaxies.Comment: Accepted to Ap

Moving glass phase of driven lattices

We study periodic lattices, such as vortex lattices, driven by an external force in a random pinning potential. We show that effects of static disorder persist even at large velocity. It results in a novel moving glass state with topological order analogous to the static Bragg glass. The lattice flows through well-defined, elastically coupled, {\it % static} channels. We predict barriers to transverse motion resulting in finite transverse critical current. Experimental tests of the theory are proposed.Comment: Revised version, shortened, 8 pages, REVTeX, no figure

Characterization of hexabundles: Initial results

New multi-core imaging fibre bundles -- hexabundles -- being developed at the University of Sydney will provide simultaneous integral field spectroscopy for hundreds of celestial sources across a wide angular field. These are a natural progression from the use of single fibres in existing galaxy surveys. Hexabundles will allow us to address fundamental questions in astronomy without the biases introduced by a fixed entrance aperture. We have begun to consider instrument concepts that exploit hundreds of hexabundles over the widest possible field of view. To this end, we have compared the performance of a 61-core fully-fused hexabundle and 5 lightly-fused bundles with 7 cores each. All fibres in the bundles have 100 micron cores. In the fully-fused bundle, the cores are distorted from a circular shape in order to achieve a higher fill fraction. The lightly-fused bundles have circular cores and five different cladding thicknesses which affect the fill fraction. We compare the optical performance of all 6 bundles and find that the advantage of smaller interstitial holes (higher fill fraction) is outweighed by the increase in modal coupling, cross-talk and the poor optical performance caused by the deformation of the fibre cores. Uniformly high throughput and low cross-talk are essential for imaging faint astronomical targets with sufficient resolution to disentangle the dynamical structure. Devices already under development will have between 100 and 200 lightly-fused cores, although larger formats are feasible. The light-weight packaging of hexabundles is sufficiently flexible to allow existing robotic positioners to make use of them.Comment: Accepted for publication in MNRAS. See also a complimentary paper on the development of hexabundles - Bland-Hawthorn et al. 2011, Optics Express, vol. 19, p. 2649 (http://www.opticsinfobase.org/abstract.cfm?URI=oe-19-3-2649

Verbal labels selectively bias brain responses to high-energy foods.

The influence of external factors on food preferences and choices is poorly understood. Knowing which and how food-external cues impact the sensory processing and cognitive valuation of food would provide a strong benefit toward a more integrative understanding of food intake behavior and potential means of interfering with deviant eating patterns to avoid detrimental health consequences for individuals in the long run. We investigated whether written labels with positive and negative (as opposed to 'neutral') valence differentially modulate the spatio-temporal brain dynamics in response to the subsequent viewing of high- and low-energetic food images. Electrical neuroimaging analyses were applied to visual evoked potentials (VEPs) from 20 normal-weight participants. VEPs and source estimations in response to high- and low- energy foods were differentially affected by the valence of preceding word labels over the ~260-300 ms post-stimulus period. These effects were only observed when high-energy foods were preceded by labels with positive valence. Neural sources in occipital as well as posterior, frontal, insular and cingulate regions were down-regulated. These findings favor cognitive-affective influences especially on the visual responses to high-energetic food cues, potentially indicating decreases in cognitive control and goal-adaptive behavior. Inverse correlations between insular activity and effectiveness in food classification further indicate that this down-regulation directly impacts food-related behavior

Generating Controlled Image Sets in Cognitive Neuroscience Research

The investigation of perceptual and cognitive functions with non-invasive brain imaging methods critically depends on the careful selection of stimuli for use in experiments. For example, it must be verified that any observed effects follow from the parameter of interest (e.g. semantic category) rather than other low-level physical features (e.g. luminance, or spectral properties). Otherwise, interpretation of results is confounded. Often, researchers circumvent this issue by including additional control conditions or tasks, both of which are flawed and also prolong experiments. Here, we present some new approaches for controlling classes of stimuli intended for use in cognitive neuroscience, however these methods can be readily extrapolated to other applications and stimulus modalities. Our approach is comprised of two levels. The first level aims at equalizing individual stimuli in terms of their mean luminance. Each data point in the stimulus is adjusted to a standardized value based on a standard value across the stimulus battery. The second level analyzes two populations of stimuli along their spectral properties (i.e. spatial frequency) using a dissimilarity metric that equals the root mean square of the distance between two populations of objects as a function of spatial frequency along x- and y-dimensions of the image. Randomized permutations are used to obtain a minimal value between the populations to minimize, in a completely data-driven manner, the spectral differences between image sets. While another paper in this issue applies these methods in the case of acoustic stimuli (Aeschlimann etal., Brain Topogr 2008), we illustrate this approach here in detail for complex visual stimul

Rice seed varietal purity inspection using hyperspectral imaging

When distributing rice seed to farmers, suppliers strive to ensure that all seeds delivered belong to the species that was ordered and that the batch is not contaminated by unhealthy seeds or seeds of a different species. A conventional method to inspect the varietal purity of rice seeds is based on manually selecting random samples of rice seed from a batch and evaluating the physical grain properties through a process of human visual inspection. This is a tedious, laborious, time consuming and extremely inefficient task where only a very small subset of the entire batch of the rice seed can be examined. There is, therefore, a need to automate this process to make it repeatable and more efficient while allowing a larger sample of rice seeds from any batch to be analysed. This paper presents an automatic rice seed inspection method which combines hyperspectral imaging and tools from machine learning to automatically detect seeds which are erroneously contained within a batch when they actually belong to a completely different species. Image data from Near-infrared (NIR) and Visible Light (VIS) hyperspectral cameras are acquired for six common rice seed varieties. Two different classifiers are applied to the data: a Support Vector Machine (SVM) and a Random Forest (RF), where each consists of six one-versus-rest binary classifiers. The results show that combining spectral and shape-based features derived from the rice seeds results in an increase in the precision (PPV) of the multi-label classification to 84% compared with 74% when only visual features are used