Observation and characterization of laser-driven Phase Space Electron Holes

The direct observation and full characterization of a phase space electron hole (EH) generated during laser-matter interaction is presented. This structure, propagating in a tenuous, nonmagnetized plasma, has been detected via proton radiography during the irradiation with a ns laser pulse (I?2 ˜ 1014 W/cm2) of a gold hohlraum. This technique has allowed the simultaneous detection of propagation velocity, potential, and electron density spatial profile across the EH with fine spatial and temporal resolution allowing a detailed comparison with theoretical and numerical models.

Diagnostic based modelling of radio-frequency driven atmospheric pressure plasmas

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.

Nonlinear frequency coupling in dual radio-frequency driven atmospheric pressure plasmas

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.

Atomic oxygen formation in a radio-frequency driven micro-atmospheric pressure plasma jet

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.

Evidence from northwest European bogs shows 'Little Ice Age' climatic changes driven by variations in solar activity

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.

Introduction to Domain-Driven Data Mining Special Section

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.