Low-frequency Drift Research Articles

Formation of the Blue Core in Argon Helicon Plasma

Helicon plasmas are typically associated with a core, a radially localized central area of strong ion light emission. Here, we investigate the role of electrostatic instabilities that lead to the formation of the classic blue core. We show that helicon plasma can also occur without the distinct core. In these conditions, the plasma is dominated by low-frequency resistive drift wave (RDW) instabilities propagating in the electron diamagnetic drift direction. When the intense sharp core is present, a new global equilibrium state is achieved where three radially separated plasma instabilities exist simultaneously. The density gradient driven RDWs separate the plasma radially into an edge region and a core region. The edge is dominated by strong, turbulent, shear-driven instabilities, while the core shows very coherent high azimuthal mode number fluctuations propagating in the ion diamagnetic drift direction and associated with enhanced ion emission. The particle flux is directed outward for small radii and inward for large radii, thus forming a radial particle transport barrier. The radial extent of the inner mode and radial location of the particle transport barrier is the same as the radius of the blue core. This new equilibrium, with the three coexisting radially separated plasma instabilities, leads to the formation of a very strong enhanced blue core. For a range of operating parameters, just prior to the blue core formation, the system undergoes incomplete intermittent transitions between the two equilibrium states, leading to the visual perception of a broad less intense helicon core. This is the first time that the development of the helicon core is shown to be associated with changes in radial transport driven by inherent low-frequency plasma instabilities.

Long-term variability of mid-latitude mesosphere-lower thermosphere winds over Collm (51°N, 13°E)

Radar observations of mesosphere/lower thermosphere (MLT) winds at middle latitudes obtained from meteor radar 2004–date and the low-frequency drift method 1979–2008 have been combined to obtain a homogeneous long-term data set of MLT dynamics at 90km altitude. The data are analyzed to obtain tendencies of prevailing winds during the last three decades. On a seasonal time scale, the zonal winds show positive trends towards more westerly winds throughout the year, while the meridional wind trends are negative in autumn/winter and positive in spring/summer. There is a tendency that the trends of both zonal and meridional summer prevailing winds are changing after 1995. Using a numerical circulation model with realistic ozone and carbon dioxide fields and with tropospheric/lower stratospheric circulation taken from ERA reanalyses, the observed trend changes can be reproduced qualitatively. The MLT wind trends are, according to the model, mainly due to the influence of changes in tropospheric and lower stratospheric dynamics.

Identifying single electron charge sensor events using wavelet edge detection

The operation of solid-state qubits often relies on single-shot readout using a nanoelectronic charge sensor, and the detection of events in a noisy sensor signal is crucial for high fidelity readout of such qubits. The most common detection scheme, comparing the signal to a threshold value, is accurate at low noise levels but is not robust to low-frequency noise and signal drift. We describe an alternative method for identifying charge sensor events using wavelet edge detection. The technique is convenient to use and we show that, with realistic signals and a single tunable parameter, wavelet detection can outperform thresholding and is significantly more tolerant to and low-frequency noise.

Using arterial spin labeling to examine mood states in youth.

IntroductionLittle is known about the neural correlates of mood states and the specific physiological changes associated with their valence and duration, especially in young people. Arterial spin labeling (ASL) imaging is particularly well-suited to study sustained cerebral states in young people, due to its robustness to low-frequency drift, excellent interscan reliability, and noninvasiveness. Yet, it has so far been underutilized for understanding the neural mechanisms underlying mood states in youth.MethodsIn this exploratory study, 21 healthy adolescents aged 16 to 18 took part in a mood induction experiment. Neutral, sad, and happy mood states were induced using film clips and explicit instructions. An ASL scan was obtained following presentation of each film clip.ResultsMood induction led to robust changes in self-reported mood ratings. Compared to neutral, sad mood was associated with increased regional cerebral blood flow (rCBF) in the left middle frontal gyrus and anterior prefrontal cortex, and decreased rCBF in the right middle frontal gyrus and the inferior parietal lobule. A decrease in self-reported mood from neutral to sad condition was associated with increased rCBF in the precuneus. Happy mood was associated with increased rCBF in medial frontal and cingulate gyri, the subgenual anterior cingulate cortex, and ventral striatum, and decreased rCBF in the inferior parietal lobule. The level of current self-reported depressive symptoms was negatively associated with rCBF change in the cerebellum and lingual gyrus following both sad and happy mood inductions.ConclusionsArterial spin labeling is sensitive to experimentally induced mood changes in healthy young people. The effects of happy mood on rCBF patterns were generally stronger than the effects of sad mood.

Rescaling effects on a low-frequency drift wave in dusty plasmas

The effect of dust on the low-frequency drift wave in inhomogeneous magnetized dusty plasmas is investigated. It is shown that a low-frequency drift wave can be modeled by the Hasegawa–Mima equation (HME) both in mobile and immobile dusty plasmas, which are dust-modified HME and HME in dusty background, respectively. The former is rescaled significantly by the presence of the dust and the space-time scale greatly increases with the increasing density and mass of dust, while the latter is not rescaled, but an additional driving force appears to drive the drift waves.

Dust gravitational drift wave in complex plasma under gravity

The dispersion relation of electrostatic waves in a complex plasma under gravity is presented. It is assumed that the waves propagate parallel to the external fields. The effects of weak electric field, neutral drag force, and ion drag force are also taken into account. The dispersion relation is numerically examined in an appropriate parameter space in which the gravity plays the dominant role in the dynamics of microparticles. The numerical results show that, in the low pressure complex plasma under gravity, a low frequency drift wave can be developed in the long wavelength limit. The stability state of this wave is switched at a certain critical wavenumber in such a way that the damped mode is transformed into a growing one. Furthermore, the influence of the external fields on the dispersion properties is analyzed. It is shown that the wave instability is essentially due to the electrostatic streaming of plasma particles. It is also found that by increasing the electric field strength, the stability switching occurs at smaller wavenumbers.

The MaPLE device: A linear machine for laboratory studies of the magnetized plasma physics phenomena

The Magnetized Plasma Linear Experimental (MaPLE) device is developed in the plasma physics laboratory of the Saha Institute of Nuclear Physics for studying basic plasma physics phenomena like waves, instabilities and their nonlinear behavior in magnetized plasma. Details description of the device and its plasma characteristics are presented. The machine provides flexibilities in terms of magnetic configuration and plasma sources. Recently, low frequency drift waves are excited in the weak density gradient region of electron cyclotron resonance (ECR) produced low density plasmas and their nonlinear coupling is studied. Results of this experiment and some more experiments done in the device are summarized. Reasoning behind a possible upgrade plan of the device for studying shear Alfven waves (SAW) and magnetic drift waves in future is also discussed.

Dust magneto-gravitational drift wave in g×B configuration

The dispersion relation of electrostatic waves in a magnetized complex plasma under gravity is presented. It is assumed that the waves propagate perpendicular to the external fields. The effects of weak electric field, neutral drag force, and ion drag force are also taken into account. The dispersion relation is numerically examined in an appropriate parameter space in which the gravity plays the dominant role in the dynamics of magnetized microparticles. The numerical results show that an unstable low frequency drift wave can be developed in the long wavelength limit. This unstable mode is transformed into an aperiodic stationary structure at a cut-off wavenumber. Furthermore, the influence of the external fields on the dispersion properties is analyzed. It is shown that the instability is essentially due to the E×B drift motion of plasma particles. However, in the absence of weak electric field, the g×B drift motion of microparticles can cause the instability in a wide range of wavenumbers. It is also found that by increasing the magnetic field strength, the wave frequency is first increased and then decreased. This behaviour is explained by the existence of an extremum point in the dust magneto-gravitational drift velocity.

Second-order low-frequency drift motions of a floating body calculated by different approximation methods

The paper presents an experimental and numerical investigation of the low-frequency motions of a simple geometry floater subjected to bichromatic waves and to long crested irregular seas. The body is axis-symmetric about the vertical axis and it is restrained from drifting away by a linear mooring system. The investigation is carried out for three water depths representing deep water, intermediate water depth and shallow water. The objective is to assess the water depth influence on the second-order low-frequency motions. A second objective is to assess the results of different approximations for the second-order difference frequency wave exciting forces on the second-order motions. The quadratic transfer functions are calculated with a boundary element method using several levels of approximation for the second-order forces: (a) the most complete approximation solves the boundary value problem completely up to the second order, (b) the first-order approximation neglects the free surface forcing in the 2nd order boundary value problem solution, (c) Newman’s approximation is of zeroth-order with respect to the difference frequency, (d) a fourth method combines Newman’s approximation with a contribution from the second-order incident wave potential, (e) the fifth method is applied to the heave forces only and it combines Newman’s approximation corrected by an additional set down. This study shows that the contribution from the second-order velocity potential must be considered for shallow water calculations to achieve accurate results. For small difference frequencies, second-order scattering potential effects are small; therefore, in this case, a good practical approximation consists on considering the second-order potential is contributed by the incident waves only.

Co-robotic intra-row weed control system

The automation of intra-row weed control in row crop production systems is very challenging. This work describes the development and in-field assessment of an automatic intra-row, hoe-based weeding co-robot system with real-time pneumatic hoe actuation based on an accurate odometry sensing technique. The US National Science Foundation has identified a need for robots (called co-robots) that serve as co-workers and work beside, or cooperatively with, people. These co-robots have a symbiotic relationship with a human partner, where, as a team, they combine their relative strengths to jointly perform a task. Such co-robots should be relatively inexpensive and easy to use. In this work, mechanical weed control was achieved by a co-robot actuator that automatically positioned a pair of miniature hoes into the intra-row zone between crop plants. The design was tested in a precision transplanted row crop and may also be suitable for direct seeded row crops. Co-robot cost was minimised by limiting the system to a single, simple odometry sensor. Co-robot hoe actuation was controlled using pre-programmed knowledge of the crop planting pattern and real-time odometry data as the control input for hoe positioning. Low-frequency drift in the odometry control points relative to the actual plant locations was corrected occasionally as needed in real-time by a human partner monitoring system performance. The co-robot was evaluated in an experimental trial conducted on the UC Davis campus farm. Assessment was based upon the follow-up hand hoeing required after automated intra-row weeding in comparison to the labour required to manually hoe a control plot. The mean person hours required for hand hoeing weeds in the control were 0.241 h for the 100 m2 plot, while only 0.102 h 100 m−2 were required in follow-up labour to complete the weed removal in the plots weeded by the co-robot. This represents a 57.5% reduction in hand labour requirements for intra-row weed control and indicates that the co-robot could help reduce traditional hand hoeing labour requirements with mechanised weed control in intra-row areas between the crop plants.

Ultrasonic imaging of seismic physical models using a phase-shifted fiber Bragg grating.

We report what is to our knowledge the first ultrasonic imaging of seismic physical models by using a phase-shifted fiber Bragg grating (PS-FBG). Seismic models, which consist of multiple layer structures, were immersed in water. Piezoelectric (PZT) transducer was used to generate ultrasonic waves and a PS-FBG as a receiver. Two-dimensional (2D) ultrasonic images were reconstructed by scanning the PS-FBG with a high-precision position scanning device. In order to suppress the low-frequency drift of the Bragg wavelength during scanning, a tight wavelength tracking method was employed to lock the laser to the PS-FBG resonance in its reflection bandgap. The ultrasonic images captured by the PS-FBG have been compared with the images obtained by the geophysical imaging system, Sinopec, demonstrating the feasibility of our PS-FBG based imaging system in seismic modeling studies.

Effect of low-frequency noise on the threshold sensitivity of middle-IR photodetectors in a broad frequency range

Low-frequency noise of a photodiode-based photodetector (PD) implementing a transimpedance amplifier scheme has been analyzed. It is found that the low-frequency (drift) noise component in the input chains of modern operational amplifiers makes a decisive contribution to resultant noises of PDs based on A3B5 photodiodes at frequencies up to several hundred kilohertz. An illustrative “vector” method of description of the noise characteristics of PD elements is proposed for selecting the optimum type of operational amplifier so as to achieve the final sensitivity and accuracy characteristics at a given response speed.

Influences of laser source on phase-sensitivity optical time-domain reflectometer-based distributed intrusion sensor.

This paper investigates the influences of laser source on distributed intrusion sensor based on a phase-sensitivity optical time-domain reflectometer (φ-OTDR). A numerical simulation is performed to illustrate the relationships between trace-to-trace fluctuations and frequency drift rate as well as pulse width, and fluctuations ratio coefficient (FRC) is proposed to evaluate the level of trace-to-trace fluctuations. The simulation results show that the FRC grows with increasing frequency drift rate and pulse width, reaches, and maintains the peak value when the frequency drift rate and/or the pulse width are high enough. Furthermore, experiments are implemented using a φ-OTDR prototype with a low frequency drift laser (<5 MHz/min), of which the high frequency drift rate is simulated by frequency sweeping. The good agreement of experimental with simulated results in the region of high frequency drift rate validates the theoretical analysis, and the huge differences between them in the region of low frequency drift rate indicate the place of laser frequency drift among system noises. The conclusion is useful for choosing laser sources and improving the performance of φ-OTDR.

31. Simulations of fMRI data with usage of estimated physiological artifacts

Introduction Simulation of fMRI data is a useful tool to verify or to compare different processing methods. Typically simulated data are created using combination of modeled signals and regions of interest with addition of some noise (Gaussian, sometimes low-frequency noise, autocorrelation or polynomial drift). Our previous experiences indicated that such simplification is not enough to simulate 4D data suitable for independent component analysis (ICA). In this work, we introduced new approach which uses estimates of physiological artifacts from real data to create more realistic structure of simulated fMRI data. Methods Synthetic fMRI datasets were created using in-house fMRI simulator. We combined three regions of interest sharing the same signal fluctuation according to block stimulation, three other regions with low-frequency fluctuations and random events uncorrelated to stimulation, EPI template, Gaussian and low-frequency noise, and polynomial drift. RETROICOR algorithm was used to estimate spatial maps and temporal characteristics of cardiac and breathing processes from resting-state fMRI data. These estimates of physiological artifacts were combined with synthetic data in multiplicative manner to form the final 4D datasets. ICA was used to process both (1) pure synthetic datasets, and (2) datasets with physiological noise to compare the suitability of our process. Results Typically 4 components were estimated using ICA on pure synthetic data showing all modeled regions. Using more realistic datasets, typically 7 additional components related to physiological noise were estimated. Conclusion Using more realistic simulated data will enable us, for instance, to test classification algorithm and to make ICA calculation more realistic because using ICA with resting-state data results typically in 20 components (and more than half are probably related to artifacts). We proved that using spatiotemporal characteristics of physiological processes estimated from real data, it is possible to create more realistic simulations of fMRI data.

Signal-to-noise ratio enhancement of phase-sensitive optical time-domain reflectometry based on power spectrum analysis

A location technique based on power spectrum analysis for the phase-sensitive optical time-domain reflectometry is proposed. The frequency characteristics of the backscattered signal at a time interval over the sensing fiber are provided to discriminate the disturbance region from other regions. Compared with conventional location techniques, the proposed method significantly enhances the signal-to-noise ratio (SNR). Therefore, it can provide a high-performance and cost-effective solution avoiding the use of the laser with super low-frequency drift. Although the frequency drift of the laser utilized in the experiment is 230 MHz∕min, the average SNR is improved to be 20.3 dB and the maximum location error is 100 m over the monitored length of 9 km during 20 experiments. © 2014 Society of Photo-Optical Instrumentation Engineers (SPIE) (DOI: 10.1117/1.OE.53.2.026106)

Electrostatic instability in magnetically confined inhomogeneous plasma driven by nonlinear force

Abstract A theoretical investigation on amplification of electrostatic ion acoustic wave in magnetically confined plasma has been presented in this paper. This investigation considers nonlinear wave–particle interaction process, called plasma maser effect, in presence of drift wave turbulence supported by magnetically confined inhomogeneous plasma. The role of associated nonlinear dissipative force in this effect in a confined plasma has been analyzed. The nonlinear force, which arises as a result of resonant interaction between electrons and modulated fields, is shown to drive the instability. Using the ion fluid equation and the ion equation of continuity, the nonlinear dispersion relation of a test ion acoustic wave has been derived, and the growth rate of ion acoustic wave in presence of low frequency drift wave turbulence has been estimated using Helimak data.

Modeling and Analysis of Low Frequency Noise in Ion-Field-Effect Transistors Sensors

Ions Sensitive Field Effect Transistors (ISFETs) are becoming the platform sensors for important chemical and biomedical applications. However, the accuracy of ISFET output measurement is greatly affected by the presences of low-frequency noise, drift and slow response of the device. This requires more safety in measured results and the tools of analysis. In this paper, we present fundamental limits on the sensitivity of ISFETs micro-sensors, arising from intrinsic and extrinsic noise sources. We developed an algorithm in MATLAB in order to model the frequency analysis of the 1/f noise in ISFET sensor using Hooge theory. We have shown that the 1/f noise of the ISFETs sensors is due to both the electrochemical system (pH solution) and the MOS component (canal size, insulator thickness). The temperature effect on the ISFET noise and the signal conditioning are also performed.

Prediction of cyclic and trend frequencies in time series using the Hilbert-Huang transform

Prediction of future security returns is possible by decomposing a securities price into weighted superpositions of underlying basis states, given stationary distributions of the basis states. The (ensemble) Hilbert–Huang transform (HHT) is an empirical two–step online methodology which carries out such a decomposition from a multi–component noisy time series. HHT allows estimation of each component's instantaneous phase, period and amplitude. A hypothesis is presented where markets exist in the binary states of trend or cycle. Switching between states is based on phase–shifting in a dyadic filter bank. A trading algorithm is presented which exploits this model by combining intra–day predictions for trend and cycle components along with a much lower frequency drift component. The algorithm is simulated on e–mini S&P 500 futures data from CME GLOBEX at one minute sampling frequency. Results are presented which show a combined strategy Sharpe ratio in excess of 3.

Accelerometer-based online reconstruction of vibrations in extremely large telescopes

Recent efforts to improve imaging quality of extremely large telescopes are based on compensating for structural vibrations with a compensation mirror canceling out the optical pathway deviations caused by vibrations of the telescope structure. To drive this mirror, the displacement of optical elements has to be reconstructed online from accelerometer measurements. The goal is to obtain high reconstruction accuracy and good disturbance rejection in spite of low-frequency drift and high-frequency noise highly deteriorating the measurements. A reconstructor based on double integration and filtering, a disturbance observer and a novel reconstruction approach based on adaptive resonators are implemented on a laboratory test setup simulating typical telescope vibrations. The true displacement is measured with a strain gauge and serves as a reference for reconstruction accuracy.

Displacement Estimation Using Multimetric Data Fusion

While displacement is valuable information for the structural behavior, measuring displacements from large civil structures is often challenging and costly. To overcome difficulties found in direct measurements such as using linear variable differential transformer and LASER-based methods, indirect displacement estimation approaches are alternatively developed. Such indirect approaches in general rely on acceleration or strain that is relatively cost effective and convenient to measure. However, these measurements have own characteristics that limit wider application of the indirect estimation. For example, as the double integration of acceleration results in the low-frequency drift in the estimated displacement, high-pass filters are often used to suppress the drift, assuming displacements are close to a zero mean process; strain is difficult to use for high-frequency modes. These types of limitations can be resolved by the fusion of different types of measurements. This study develops an indirect displacement estimation method based on the multimetric data (i.e., acceleration and strain) that can estimate nonzero mean, dynamic displacements. The proposed approach is numerically validated, showing better estimation than the single measurement-based methods. Furthermore, the performance of the proposed approach is verified using dynamic response data measured from the Sorok Bridge, a cable-stayed bridge in Korea.