Spectroscopic Investigations of the Ablation Plume of Several Inorganic Materials

1992 ◽  
Vol 285 ◽  
Author(s):  
A. Rosenfeld ◽  
R. Mitzner ◽  
R. Konig
Keyword(s):  
Time Delay ◽  
Dimensional Space ◽  
Broad Band ◽  
Inorganic Materials ◽  
Ablation Plume ◽  
Atmospheric Conditions ◽  
Time Resolved ◽  
Temporal Behaviour ◽  
Space Resolution ◽  
Spectroscopic Investigations

ABSTRACTTime resolved absorption spectroscopic investigations of the KrF laser ablation of MgO-ceramics and sapphire on atmospheric conditions were carried out with a time resolution of about 5 ns and a two-dimensional space resolution of less than 100 μm. The time delay between the ablation pulse and the broad band probe pulse was varied from 10 ns up to 10 μs.Absolute particle densities of the species were determined in dependence on the time delay and on the distance to the surface. The spatial and temporal behaviour of the particles in the ablation plume near the surface was found to be strongly affected both by air atmosphere and the reaction dynamic in the plasma zone. In the case of sapphire the time evolution of the densities of Al, Al+ and AlO species are discussed in comparison to measurements on vacuum conditions.

scholarly journals Artifacts in Simultaneous hdEEG/fMRI Imaging: A Nonlinear Dimensionality Reduction Approach

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4454 ◽  
Author(s):  
Marek Piorecky ◽  
Vlastimil Koudelka ◽  
Jan Strobl ◽  
Martin Brunovsky ◽  
Vladimir Krajca
Keyword(s):  
Data Structure ◽  
Spatial Clustering ◽  
Dimensional Space ◽  
Head Movements ◽  
Nonlinear Dimensionality Reduction ◽  
Space Resolution ◽  
Additional Information ◽  
Nonlinear Dimension ◽  
The Time Domain ◽  
Low Dimensional

Simultaneous recordings of electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) are at the forefront of technologies of interest to physicians and scientists because they combine the benefits of both modalities—better time resolution (hdEEG) and space resolution (fMRI). However, EEG measurements in the scanner contain an electromagnetic field that is induced in leads as a result of gradient switching slight head movements and vibrations, and it is corrupted by changes in the measured potential because of the Hall phenomenon. The aim of this study is to design and test a methodology for inspecting hidden EEG structures with respect to artifacts. We propose a top-down strategy to obtain additional information that is not visible in a single recording. The time-domain independent component analysis algorithm was employed to obtain independent components and spatial weights. A nonlinear dimension reduction technique t-distributed stochastic neighbor embedding was used to create low-dimensional space, which was then partitioned using the density-based spatial clustering of applications with noise (DBSCAN). The relationships between the found data structure and the used criteria were investigated. As a result, we were able to extract information from the data structure regarding electrooculographic, electrocardiographic, electromyographic and gradient artifacts. This new methodology could facilitate the identification of artifacts and their residues from simultaneous EEG in fMRI.

Frequency domain, time-resolved and spectroscopic investigations of photosensitizers encapsulated in liposomal phantoms

2007 ◽  
Author(s):  
Ozzy Mermut ◽  
Jean-Pierre Bouchard ◽  
Jean-Francois Cormier ◽  
Kevin R. Diamond ◽  
Isabelle Noiseux ◽  
...  
Keyword(s):  
Frequency Domain ◽  
Time Resolved ◽  
Spectroscopic Investigations

scholarly journals A stochastic propagation model to the energy dependent rapid temporal behaviour of Cygnus X-1 as observed by AstroSat in the hard state

2019 ◽  
Vol 486 (2) ◽  
pp. 2964-2975 ◽  
Author(s):  
Bari Maqbool ◽  
Sneha Prakash Mudambi ◽  
R Misra ◽  
J S Yadav ◽  
S B Gudennavar ◽  
...  
Keyword(s):  
Time Lag ◽  
Broad Band ◽  
Propagation Model ◽  
Large Area ◽  
Temporal Behaviour ◽  
X Ray ◽  
Single Temperature ◽  
Hard State ◽  
Band Spectra ◽  
Energy Dependent

Abstract We report the results from analysis of six observations of Cygnus X-1 by Large Area X-ray Proportional Counter (LAXPC) and Soft X-ray Telescope (SXT) onboard AstroSat, when the source was in the hard spectral state as revealed by the broad-band spectra. The spectra obtained from all the observations can be described by a single-temperature Comptonizing region with disc and reflection components. The event mode data from LAXPC provides unprecedented energy dependent fractional root mean square (rms) and time-lag at different frequencies which we fit with empirical functions. We invoke a fluctuation propagation model for a simple geometry of a truncated disc with a hot inner region. Unlike other propagation models, the hard X-ray emission (>4 keV) is assumed to be from the hot inner disc by a single-temperature thermal Comptonization process. The fluctuations first cause a variation in the temperature of the truncated disc and then the temperature of the inner disc after a frequency dependent time delay. We find that the model can explain the energy dependent rms and time-lag at different frequencies.

Instantaneous contribution in time-resolved four-wave mixing from GaAs quantum wells near zero time delay

1994 ◽  
Vol 50 (20) ◽  
pp. 15086-15094 ◽  
Author(s):  
D. S. Kim ◽  
J. Shah ◽  
T. C. Damen ◽  
Wilfred Schäfer ◽  
L. N. Pfeiffer ◽  
...  
Keyword(s):  
Time Delay ◽  
Quantum Wells ◽  
Four Wave Mixing ◽  
Wave Mixing ◽  
Time Resolved ◽  
Zero Time

scholarly journals Non-steady wind turbine response to daytime atmospheric turbulence

2017 ◽  
Vol 375 (2091) ◽  
pp. 20160103 ◽  
Author(s):  
Tarak N. Nandi ◽  
Andreas Herrig ◽  
James G. Brasseur
Keyword(s):  
Field Experiment ◽  
Wind Turbine ◽  
Atmospheric Turbulence ◽  
Time Scales ◽  
Leading Edge ◽  
Turbine Rotor ◽  
Atmospheric Conditions ◽  
Time Resolved ◽  
Eddy Simulation ◽  
Large Eddy

Relevant to drivetrain bearing fatigue failures, we analyse non-steady wind turbine responses from interactions between energy-dominant daytime atmospheric turbulence eddies and the rotating blades of a GE 1.5 MW wind turbine using a unique dataset from a GE field experiment and computer simulation. Time-resolved local velocity data were collected at the leading and trailing edges of an instrumented blade together with generator power, revolutions per minute, pitch and yaw. Wind velocity and temperature were measured upwind on a meteorological tower. The stability state and other atmospheric conditions during the field experiment were replicated with a large-eddy simulation in which was embedded a GE 1.5 MW wind turbine rotor modelled with an advanced actuator line method. Both datasets identify three important response time scales: advective passage of energy-dominant eddies (≈25–50 s), blade rotation (once per revolution (1P), ≈3 s) and sub-1P scale (<1 s) response to internal eddy structure. Large-amplitude short-time ramp-like and oscillatory load fluctuations result in response to temporal changes in velocity vector inclination in the aerofoil plane, modulated by eddy passage at longer time scales. Generator power responds strongly to large-eddy wind modulations. We show that internal dynamics of the blade boundary layer near the trailing edge is temporally modulated by the non-steady external flow that was measured at the leading edge, as well as blade-generated turbulence motions. This article is part of the themed issue ‘Wind energy in complex terrains’.

PREDICTING UNKNOWN MOTION FOR MODEL INDEPENDENT VISUAL SERVOING

2001 ◽  
Vol 01 (03) ◽  
pp. 287-302 ◽  
Author(s):  
PATRICE WIRA ◽  
JEAN-PHILIPPE URBAN
Keyword(s):  
Kalman Filter ◽  
Time Delay ◽  
Real Time ◽  
Visual Servoing ◽  
Dimensional Space ◽  
Tracking Error ◽  
State Model ◽  
Divide And Conquer ◽  
Image Feature ◽  
Robot Arm

Prediction in real-time image sequences is a key-feature for visual servoing applications. It is used to compensate for the time-delay introduced by the image feature extraction process in the visual feedback loop. In order to track targets in a three-dimensional space in real-time with a robot arm, the target's movement and the robot end-effector's next position are predicted from the previous movements. A modular prediction architecture is presented, which is based on the Kalman filtering principle. The Kalman filter is an optimal stochastic estimation technique which needs an accurate system model and which is particularly sensitive to noise. The performances of this filter diminish with nonlinear systems and with time-varying environments. Therefore, we propose an adaptive Kalman filter using the modular framework of mixture of experts regulated by a gating network. The proposed filter has an adaptive state model to represent the system around its current state as close as possible. Different realizations of these state model adaptive Kalman filters are organized according to the divide-and-conquer principle: they all participate to the global estimation and a neural network mediates their different outputs in an unsupervised manner and tunes their parameters. The performances of the proposed approach are evaluated in terms of precision, capability to estimate and compensate abrupt changes in targets trajectories, as well as to adapt to time-variant parameters. The experiments prove that, without the use of models (e.g. the camera model, kinematic robot model, and system parameters) and without any prior knowledge about the targets movements, the predictions allow to compensate for the time-delay and to reduce the tracking error.

scholarly journals Time- and Temperature-Dependent Luminescence of Manganese Ions in Ceramic Magnesium Aluminum Spinels

Materials ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 420
Author(s):  
Nicholas Khaidukov ◽  
Angela Pirri ◽  
Maria Brekhovskikh ◽  
Guido Toci ◽  
Matteo Vannini ◽  
...  
Keyword(s):  
Solid State ◽  
Solid State Reaction ◽  
Broad Band ◽  
Solid State Reaction Method ◽  
Luminescence Spectroscopy ◽  
Luminescence Spectra ◽  
Manganese Ions ◽  
Time Resolved ◽  
Synthesis Conditions ◽  
Magnesium Aluminum Spinel

Samples of magnesium aluminum spinel ceramics doped with manganese ions were prepared by a high-temperature solid-state reaction method; their potential as red-emitting phosphors was analyzed using a time-resolved luminescence spectroscopy technique, from room temperature to 10 K. It was found that in the red spectral range, the luminescence spectra of manganese ions in the MgAl2O4 spinel showed a narrow band peaking at 651 nm due to the emission of Mn4+ and a broader emission band in the region of 675 ÷ 720 nm; the ratio of intensities for these bands depends on the synthesis conditions. By applying a special multi-step annealing procedure, the MgAl2O4:Mn4+ phosphor containing only tetravalent manganese ions, Mn4+, was synthesized. Broad-band far-red emission observed from MgAl2O4:Mn and Mg1.25Al1.75O3.75F0.25:Mn phosphors, prepared by a conventional method of a solid-state reaction, was interpreted as coming from Mn3+ ions.

The airport-sCAle seveRe weather nowcastinG prOject (CARGO)

2020 ◽  
Author(s):  
Riccardo Biondi ◽  
Pierre-Yves Tournigand ◽  
Enrico Solazzo ◽  
Eugenio Realini ◽  
Corrado Cimarelli ◽  
...  
Keyword(s):  
Water Vapour ◽  
Heavy Rain ◽  
Severe Weather ◽  
Time Range ◽  
Atmospheric Parameter ◽  
Atmospheric Conditions ◽  
Temporal Behaviour ◽  
Convective Systems ◽  
Integrated Water Vapour ◽  
Deep Convective Systems

&lt;p&gt;Monitoring and predicting extreme atmospheric events, such as deep convective systems, is very challenging especially when they develop locally in a short time range. Despite the great improvement in model parametrization and the use of satellite measurements, there are still &lt;strong&gt;l&lt;/strong&gt;arge uncertainties on the knowledge of the dynamical processes of deep convective systems at local scale.&lt;/p&gt;&lt;p&gt;We use an innovative approach integrating a dense network of in situ measurements and satellite-based observations/products for the improvement of meteorological nowcasting at airport spatial scale focusing on the Malpensa airport (Italy). We add to the standard atmospheric parameters analysis, the information of integrated water vapour and lightning spatio-temporal behaviour (potential heavy rain precursors) during heavy rain phenomena detected by meteorological radars. The study is based on the anomaly of each atmospheric parameter during a convective event in comparison to its climatology in non-pre-convective environment, so that we are able to detect the variation with respect to the &amp;#8220;standard&amp;#8221; conditions. The ground based GNSS receivers (allowing the determination of the integrated water vapour trend before and during the storm), together with the lightning detectors, the weather stations (providing the trend of temperature, humidity and wind fields), the radiosondes and the GNSS radio occultations (allowing the estimation of vertical profiles of temperature, pressure and humidity) provide information on the pre-convective and non-pre-convective environment as a 3D picture of the atmospheric conditions.&lt;/p&gt;&lt;p&gt;The final goal is the test of a severe weather events nowcasting algorithm with high spatial resolution, and based on neural networks, for improving aviation safety. This is followed by the development of a user-friendly tailored final product, easily understandable by the Air Traffic Management stakeholder.&lt;/p&gt;&lt;p&gt;We have collected more than 600 cases suitable to develop the neural network algorithm. We show here the algorithm implementation and the meteorological characterization of deep convection usually developing on the Malpensa airport area.&lt;/p&gt;

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