1,531 research outputs found

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

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    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

    Geometry of lines and degeneracy loci of morphisms of vector bundles

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    Corrado Segre played a leading role in the foundation of line geometry. We survey some recent results on degeneracy loci of morphisms of vector bundles where he still is of profound inspiration.Comment: 10 pages. To appear in the proceedings of the conference "Homage to Corrado Segre

    Plant communities and landscape diversity in NW Sicily: The MEMOLA EU FP7 Project case study

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    The MEMOLA EU FP7 Project case study\u201d was presented at IV International Plant Science Conference (IPSC) held in Parma (Italy) on September 20-22, 2017. The poster focuses on the contribution of botany in the interdisciplinary debate of Memola Project and underline the role plant communities play in understanding the formative processes of the Mediterranean Landscapes

    Possible Patient Early Diagnosis by Ultrasonic Noninvasive Estimation of Thermal Gradients into Tissues Based on Spectral Changes Modeling

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    To achieve a precise noninvasive temperature estimation, inside patient tissues, would open promising research fields, because its clinic results would provide early-diagnosis tools. In fact, detecting changes of thermal origin in ultrasonic echo spectra could be useful as an early complementary indicator of infections, inflammations, or cancer. But the effective clinic applications to diagnosis of thermometry ultrasonic techniques, proposed previously, require additional research. Before their implementations with ultrasonic probes and real-time electronic and processing systems, rigorous analyses must be still made over transient echotraces acquired from well-controlled biological and computational phantoms, to improve resolutions and evaluate clinic limitations. It must be based on computing improved signal-processing algorithms emulating tissues responses. Some related parameters in echo-traces reflected by semiregular scattering tissues must be carefully quantified to get a precise processing protocols definition. In this paper, approaches for non-invasive spectral ultrasonic detection are analyzed. Extensions of author's innovations for ultrasonic thermometry are shown and applied to computationally modeled echotraces from scattered biological phantoms, attaining high resolution (better than 0.1°C). Computer methods are provided for viability evaluation of thermal estimation from echoes with distinct noise levels, difficult to be interpreted, and its effectiveness is evaluated as possible diagnosis tool in scattered tissues like liver

    Axisymmetric core collapse simulations using characteristic numerical relativity

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    We present results from axisymmetric stellar core collapse simulations in general relativity. Our hydrodynamics code has proved robust and accurate enough to allow for a detailed analysis of the global dynamics of the collapse. Contrary to traditional approaches based on the 3+1 formulation of the gravitational field equations, our framework uses a foliation based on a family of outgoing light cones, emanating from a regular center, and terminating at future null infinity. Such a coordinate system is well adapted to the study of interesting dynamical spacetimes in relativistic astrophysics such as stellar core collapse and neutron star formation. Perhaps most importantly this procedure allows for the unambiguous extraction of gravitational waves at future null infinity without any approximation, along with the commonly used quadrupole formalism for the gravitational wave extraction. Our results concerning the gravitational wave signals show noticeable disagreement when those are extracted by computing the Bondi news at future null infinity on the one hand and by using the quadrupole formula on the other hand. We have strong indication that for our setup the quadrupole formula on the null cone does not lead to physical gravitational wave signals. The Bondi gravitational wave signals extracted at infinity show typical oscillation frequencies of about 0.5 kHz.Comment: 17 pages, 18 figures, submitted to Phys. Rev.

    Studies of h/e Aharonov-Bohm Photovoltaic Oscillations in Mesoscopic Au Rings

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    We have investigated a mesoscopic photovoltaic (PV) effect in micron-size Au rings in which a dc voltage Vdc is generated in response to microwave radiation. The effect is due to the lack of inversion symmetry in a disordered system. Aharonov-Bohm PV oscillations with flux period h/e have been observed at low microwave intensities for temperatures ranging from 1.4 to 13 K. For moderate microwave intensities the h/e PV oscillations are completely quenched providing evidence that the microwaves act to randomize the phase of the electrons. Studies of the temperature dependence of Vdc also provide evidence of the dephasing nature of the microwave field. A complete theoretical explanation of the observed behavior seems to require a theory for the PV effect in a ring geometry.Comment: 10 pages (RevTex twocolumn style), 8 figures-2 pages (one postscript file) To be published in Phys. Rev.

    Endogenous Signaling by Omega-3 Docosahexaenoic Acid-derived Mediators Sustains Homeostatic Synaptic and Circuitry Integrity

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    The harmony and function of the complex brain circuits and synapses are sustained mainly by excitatory and inhibitory neurotransmission, neurotrophins, gene regulation, and factors, many of which are incompletely understood. A common feature of brain circuit components, such as dendrites, synaptic membranes, and other membranes of the nervous system, is that they are richly endowed in docosahexaenoic acid (DHA), the main member of the omega-3 essential fatty acid family. DHA is avidly retained and concentrated in the nervous system and known to play a role in neuroprotection, memory, and vision. Only recently has it become apparent why the surprisingly rapid increases in free (unesterified) DHA pool size take place at the onset of seizures or brain injury. This phenomenon began to be clarified by the discovery of neuroprotectin D1 (NPD1), the first-uncovered bioactive docosanoid formed from free DHA through 15-lipoxygenase-1 (15-LOX-1). NPD1 synthesis includes, as agonists, oxidative stress and neurotrophins. The evolving concept is that DHA-derived docosanoids set in motion endogenous signaling to sustain homeostatic synaptic and circuit integrity. NPD1 is anti-inflammatory, displays inflammatory resolving activities, and induces cell survival, which is in contrast to the pro-inflammatory actions of the many of omega-6 fatty acid family members. We highlight here studies relevant to the ability of DHA to sustain neuronal function and protect synapses and circuits in the context of DHA signalolipidomics. DHA signalolipidomics comprises the integration of the cellular/tissue mechanism of DHA uptake, its distribution among cellular compartments, the organization and function of membrane domains containing DHA phospholipids, and the precise cellular and molecular events revealed by the uncovering of signaling pathways regulated by docosanoids endowed with prohomeostatic and cell survival bioactivity. Therefore, this approach offers emerging targets for prevention, pharmaceutical intervention, and clinical translation involving DHA-mediated signaling

    A Hierarchical Approach to Multimodal Classification

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    Abstract. Data models that are induced in classifier construction often consists of multiple parts, each of which explains part of the data. Classi-fication methods for such models are called the multimodal classification methods. The model parts may overlap or have insufficient coverage. How to deal best with the problems of overlapping and insufficient cov-erage? In this paper we propose hierarchical or layered approach to this problem. Rather than seeking a single model, we consider a series of models under gradually relaxing conditions, which form a hierarchical structure. To demonstrate the effectiveness of this approach we imple-mented it in two classifiers that construct multi-part models: one based on the so-called lattice machine and the other one based on rough set rule induction. This leads to hierarchical versions of the classifiers. The classification performance of these two hierarchical classifiers is compared with C4.5, Support Vector Machine (SVM), rule based classifiers (with the optimisation of rule shortening) implemented in Rough Set Explo-ration System (RSES), and a method combining k-nn with rough set rule induction (RIONA in RSES). The results of the experiments show that this hierarchical approach leads to improved multimodal classifiers
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