980 resultados para event-driven


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Diagnostic based modelling (DBM) actively combines complementary advantages of numerical plasma simulations and relatively simple optical emission spectroscopy (OES). DBM is employed to determine absolute atomic oxygen ground state densities in a helium–oxygen radio-frequency driven atmospheric pressure plasma jet. A comparatively simple one-dimensional simulation yields detailed information on electron properties governing the population dynamics of excited states. Important characteristics of the electron dynamics are found to be largely insensitive to details of the chemical composition and to be in very good agreement with space and phase-resolved OES. Benchmarking the time and space resolved simulation allows us to subsequently derive effective excitation rates as the basis for DBM with simple space and time integrated OES. The population dynamics of the upper O 3p 3P (? = 844 nm) atomic oxygen state is governed by direct electron impact excitation, dissociative excitation, radiation losses and collisional induced quenching. Absolute values for atomic oxygen densities are obtained through tracer comparison with the upper Ar 2p1 (? = 750.4 nm) state. The presented results for the atomic oxygen density show excellent quantitative agreement with independent two-photon laser-induced fluorescence measurements.

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Plasma ionization, and associated mode transitions, in dual radio-frequency driven atmospheric pressure plasmas are governed through nonlinear frequency coupling in the dynamics of the plasma boundary sheath. Ionization in low-power mode is determined by the nonlinear coupling of electron heating and the momentary local plasma density. Ionization in high-power mode is driven by electron avalanches during phases of transient high electric fields within the boundary sheath. The transition between these distinctly different modes is controlled by the total voltage of both frequency components.

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The influence of the relative phase between the driving voltages on electron heating in asymmetric phase-locked dual frequency capacitively coupled radio frequency plasmas operated at 2 and 14 MHz is investigated. The basis of the analysis is a nonlinear global model with the option to implement a relative phase between the two driving voltages. In recent publications it has been reported that nonlinear electron resonance heating can drastically enhance the power dissipation to electrons at moments of sheath collapse due to the self-excitation of nonlinear plasma series resonance (PSR) oscillations of the radio frequency current. This work shows that depending on the relative phase of the driving voltages, the total number and exact moments of sheath collapse can be influenced. In the case of two consecutive sheath collapses a substantial increase in dissipated power compared with the known increase due to a single PSR excitation event per period is observed. Phase resolved optical emission spectroscopy (PROES) provides access to the excitation dynamics in front of the driven electrode. Via PROES the propagation of beam-like energetic electrons immediately after the sheath collapse is observed. In this work we demonstrate that there is a close relation between moments of sheath collapse, and thus excitation of the PSR, and beam-like electron propagation. A comparison of simulation results to experiments in a single and dual frequency discharge shows good agreement. In particular the observed influence of the relative phase on the dynamics of a dual frequency discharge is described by means of the presented model. Additionally, the analysis demonstrates that the observed gain in dissipation is not accompanied by an increase in the electrode’s dc-bias voltage which directly addresses the issue of separate control of ion flux and ion energy in dual frequency capacitively coupled radio frequency plasmas.

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Nonreflexive responses to a noxious event and prolonged memory are key criteria of a pain experience. In a previous study, hermit crabs, Pagurus bernhardus, that received a small electric shock within their shell often temporarily evacuated the shell and some groomed their abdomen and/or moved away from their vital resource. Most, however, returned to the shell. When offered a new shell 20 s later, shocked crabs were more likely than nonshocked crabs to approach and move into a new shell and did so more quickly (Elwood & Appel 2009, Animal Behaviour, 77, 1243-1246). Here we examined how increasing the time between the shock and the offering of a new shell influences the response. There was evidence of a memory of the aversive shock that lasted at least 1 day. Crabs tested after 30 min and 1 day were more likely to approach the shell and new shells were more likely to be taken 30 min after the shock. Shocked crabs approached the new shell more quickly and used fewer probes of the chelipeds prior to moving in and these results were stable over time and significant for specific times up to 1 day. Females were more likely than males to evacuate shells and did so after fewer shocks. These results extend previous work and demonstrate an extended memory of having been shocked. The findings are consistent with respect to criteria for pain that are accepted for vertebrates.

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Atomic oxygen formation in a radio-frequency driven micro-atmospheric pressure plasma jet is investigated using both advanced optical diagnostics and numerical simulations of the dynamic plasma chemistry. Laser spectroscopic measurements of absolute densities of ground state atomic oxygen reveal steep gradients at the interface between the plasma core and the effluent region. Spatial profiles resolving the interelectrode gap within the core plasma indicate that volume processes dominate over surface reactions. Details of the production and destruction processes are investigated in numerical simulations benchmarked by phase-resolved optical emission spectroscopy. The main production mechanisms are electron induced and hence most efficient in the vicinity of the plasma boundary sheath, where electrons are energized. The destruction is driven through chemical heavy particle reactions. The resulting spatial profile of atomic oxygen is relatively flat. The power dependence of the atomic oxygen density obtained by the numerical simulation is in very good agreement with the laser spectroscopic measurements.

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Fluctuations in Holocene atmospheric radiocarbon concentrations have been shown to be due to variations in solar activity. Analyses of both Be-10 and C-14 nuclides confirm that production-rate changes during the Holocene were largely modulated by solar activity. Analyses of peat samples from two intact European ombrotrophic bogs show that climatic deteriorations during the 'Little Ice Age' are associated with transitions to increasing atmospheric C-14 content due to greater C-14 production. Both ombrotrophic mires, which are positioned c. 800 km apart, register reactions to globally recorded C-14 fluctuations between AD 1449 and 1464 and an almost identical reaction between AD 1601 and 1604.

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In the last decade, data mining has emerged as one of the most dynamic and lively areas in information technology. Although many algorithms and techniques for data mining have been proposed, they either focus on domain independent techniques or on very specific domain problems. A general requirement in bridging the gap between academia and business is to cater to general domain-related issues surrounding real-life applications, such as constraints, organizational factors, domain expert knowledge, domain adaption, and operational knowledge. Unfortunately, these either have not been addressed, or have not been sufficiently addressed, in current data mining research and development.Domain-Driven Data Mining (D3M) aims to develop general principles, methodologies, and techniques for modeling and merging comprehensive domain-related factors and synthesized ubiquitous intelligence surrounding problem domains with the data mining process, and discovering knowledge to support business decision-making. This paper aims to report original, cutting-edge, and state-of-the-art progress in D3M. It covers theoretical and applied contributions aiming to: 1) propose next-generation data mining frameworks and processes for actionable knowledge discovery, 2) investigate effective (automated, human and machine-centered and/or human-machined-co-operated) principles and approaches for acquiring, representing, modelling, and engaging ubiquitous intelligence in real-world data mining, and 3) develop workable and operational systems balancing technical significance and applications concerns, and converting and delivering actionable knowledge into operational applications rules to seamlessly engage application processes and systems.