Development of a novel 3D simulation modelling system for distributed manufacturing

This paper describes a novel 3D simulation modelling system for supporting our distributed machine design and control paradigm with respect to simulating and emulating machine behaviour on the Internet. The system has been designed and implemented using Java2D and Java3D. An easy assembly concept of drag-and-drop assembly has been realised and implemented by the introduction of new connection features (unified interface assembly features) between two assembly components (modules). The system comprises a hierarchical geometric modeller, a behavioural editor, and two assemblers. During modelling, designers can combine basic modelling primitives with general extrusions and integrate CAD geometric models into simulation models. Each simulation component (module) model can be visualised and animated in VRML browsers. It is reusable. This makes machine design re-configurable and flexible. A case study example is given to support our conclusions

A framework of web-based conceptual design

A web-based conceptual design prototype system is presented. The system consists of four parts which interpret on-line sketches as 2D and 3D geometry, extract 3D hierarchical configurations, allow editing of component behaviours, and produce VRML-based behavioural simulations for design verification and web-based application. In the first part, on-line freehand sketched input is interpreted as 2D and 3D geometry, which geometrically represents conceptual design. The system then infers 3D configuration by analysing 3D modelling history. The configuration is described by a parent–child hierarchical relationship and relative positions between two geometric components. The positioning information is computed with respect to the VRML97 specification. In order to verify the conceptual design of a product, the behaviours can be specified interactively on different components. Finally, the system creates VRML97 formatted files for behavioural simulation and collaborative design application over the Internet. The paper gives examples of web-based applications. This work forms a part of a research project into the design and establishing of modular machines for automation manufacture. A consortium of leading automotive companies is collaborating on the research project

Predicting evolution and visualizing high-dimensional fitness landscapes

The tempo and mode of an adaptive process is strongly determined by the structure of the fitness landscape that underlies it. In order to be able to predict evolutionary outcomes (even on the short term), we must know more about the nature of realistic fitness landscapes than we do today. For example, in order to know whether evolution is predominantly taking paths that move upwards in fitness and along neutral ridges, or else entails a significant number of valley crossings, we need to be able to visualize these landscapes: we must determine whether there are peaks in the landscape, where these peaks are located with respect to one another, and whether evolutionary paths can connect them. This is a difficult task because genetic fitness landscapes (as opposed to those based on traits) are high-dimensional, and tools for visualizing such landscapes are lacking. In this contribution, we focus on the predictability of evolution on rugged genetic fitness landscapes, and determine that peaks in such landscapes are highly clustered: high peaks are predominantly close to other high peaks. As a consequence, the valleys separating such peaks are shallow and narrow, such that evolutionary trajectories towards the highest peak in the landscape can be achieved via a series of valley crossingsComment: 12 pages, 7 figures. To appear in "Recent Advances in the Theory and Application of Fitness Landscapes" (A. Engelbrecht and H. Richter, eds.). Springer Series in Emergence, Complexity, and Computation, 201

Theory of coherent acoustic phonons in InGaN/GaN multi-quantum wells

A microscopic theory for the generation and propagation of coherent LA phonons in pseudomorphically strained wurzite (0001) InGaN/GaN multi-quantum well (MQW) p-i-n diodes is presented. The generation of coherent LA phonons is driven by photoexcitation of electron-hole pairs by an ultrafast Gaussian pump laser and is treated theoretically using the density matrix formalism. We use realistic wurzite bandstructures taking valence-band mixing and strain-induced piezo- electric fields into account. In addition, the many-body Coulomb ineraction is treated in the screened time-dependent Hartree-Fock approximation. We find that under typical experimental conditions, our microscopic theory can be simplified and mapped onto a loaded string problem which can be easily solved.Comment: 20 pages, 17 figure

Loss of vascular CD34 results in increased sensitivity to lung injury

Survival during lung injury requires a coordinated program of damage limitation and rapid repair. CD34 is a cell surface sialomucin expressed by epithelial, vascular and stromal cells that promotes cell adhesion, coordinates inflammatory cell recruitment, and drives angiogenesis. To test whether CD34 also orchestrates pulmonary damage and repair, we induced acute lung injury in wild type (WT) and Cd34-/- mice by bleomycin (BLM) administration. We found that Cd34-/- mice displayed severe weight loss and early mortality compared to WT controls. Despite equivalent early airway inflammation to WT mice, CD34-deficient animals developed interstitial edema and endothelial delamination, suggesting impaired endothelial function. Chimeric Cd34-/- mice reconstituted with WT hematopoietic cells exhibited early mortality compared to WT mice reconstituted with Cd34-/- cells, supporting an endothelial defect. CD34-deficient mice were also more sensitive to lung damage caused by influenza infection, showing greater weight loss and more extensive pulmonary remodeling. Together our data suggest that CD34 plays an essential role in maintaining vascular integrity in the lung in response to chemical- and infection-induced, tissue damage

Red Queen Coevolution on Fitness Landscapes

Species do not merely evolve, they also coevolve with other organisms. Coevolution is a major force driving interacting species to continuously evolve ex- ploring their fitness landscapes. Coevolution involves the coupling of species fit- ness landscapes, linking species genetic changes with their inter-specific ecological interactions. Here we first introduce the Red Queen hypothesis of evolution com- menting on some theoretical aspects and empirical evidences. As an introduction to the fitness landscape concept, we review key issues on evolution on simple and rugged fitness landscapes. Then we present key modeling examples of coevolution on different fitness landscapes at different scales, from RNA viruses to complex ecosystems and macroevolution.Comment: 40 pages, 12 figures. To appear in "Recent Advances in the Theory and Application of Fitness Landscapes" (H. Richter and A. Engelbrecht, eds.). Springer Series in Emergence, Complexity, and Computation, 201

Soil biochemistry and microbial activity in vineyards under conventional and organic management at Northeast Brazil.

The São Francisco Submedium Valley is located at the Brazilian semiarid region and is an important center for irrigated fruit growing. This region is responsible for 97% of the national exportation of table grapes, including seedless grapes. Based on the fact that orgThe São Francisco Submedium Valley is located at the Brazilian semiarid region and is an important center for irrigated fruit growing. This region is responsible for 97% of the national exportation of table grapes, including seedless grapes. Based on the fact that organic fertilization can improve soil quality, we compared the effects of conventional and organic soil management on microbial activity and mycorrhization of seedless grape crops. We measured glomerospores number, most probable number (MPN) of propagules, richness of arbuscular mycorrhizal fungi (AMF) species, AMF root colonization, EE-BRSP production, carbon microbial biomass (C-MB), microbial respiration, fluorescein diacetate hydrolytic activity (FDA) and metabolic coefficient (qCO2). The organic management led to an increase in all variables with the exception of EE-BRSP and qCO2. Mycorrhizal colonization increased from 4.7% in conventional crops to 15.9% in organic crops. Spore number ranged from 4.1 to 12.4 per 50 g-1 soil in both management systems. The most probable number of AMF propagules increased from 79 cm-3 soil in the conventional system to 110 cm-3 soil in the organic system. Microbial carbon, CO2 emission, and FDA activity were increased by 100 to 200% in the organic crop. Thirteen species of AMF were identified, the majority in the organic cultivation system. Acaulospora excavata, Entrophospora infrequens, Glomus sp.3 and Scutellospora sp. were found only in the organically managed crop. S. gregaria was found only in the conventional crop. Organically managed vineyards increased mycorrhization and general soil microbial activity

Low Complexity Regularization of Linear Inverse Problems

Inverse problems and regularization theory is a central theme in contemporary signal processing, where the goal is to reconstruct an unknown signal from partial indirect, and possibly noisy, measurements of it. A now standard method for recovering the unknown signal is to solve a convex optimization problem that enforces some prior knowledge about its structure. This has proved efficient in many problems routinely encountered in imaging sciences, statistics and machine learning. This chapter delivers a review of recent advances in the field where the regularization prior promotes solutions conforming to some notion of simplicity/low-complexity. These priors encompass as popular examples sparsity and group sparsity (to capture the compressibility of natural signals and images), total variation and analysis sparsity (to promote piecewise regularity), and low-rank (as natural extension of sparsity to matrix-valued data). Our aim is to provide a unified treatment of all these regularizations under a single umbrella, namely the theory of partial smoothness. This framework is very general and accommodates all low-complexity regularizers just mentioned, as well as many others. Partial smoothness turns out to be the canonical way to encode low-dimensional models that can be linear spaces or more general smooth manifolds. This review is intended to serve as a one stop shop toward the understanding of the theoretical properties of the so-regularized solutions. It covers a large spectrum including: (i) recovery guarantees and stability to noise, both in terms of $\ell^2$-stability and model (manifold) identification; (ii) sensitivity analysis to perturbations of the parameters involved (in particular the observations), with applications to unbiased risk estimation ; (iii) convergence properties of the forward-backward proximal splitting scheme, that is particularly well suited to solve the corresponding large-scale regularized optimization problem

Measurement of the B0-anti-B0-Oscillation Frequency with Inclusive Dilepton Events

The $B^0$-$\bar B^0$ oscillation frequency has been measured with a sample of 23 million \B\bar B pairs collected with the BABAR detector at the PEP-II asymmetric B Factory at SLAC. In this sample, we select events in which both B mesons decay semileptonically and use the charge of the leptons to identify the flavor of each B meson. A simultaneous fit to the decay time difference distributions for opposite- and same-sign dilepton events gives $\Delta m_d = 0.493 \pm 0.012{(stat)}\pm 0.009{(syst)}$ ps$^{-1}$.Comment: 7 pages, 1 figure, submitted to Physical Review Letter