Inward particle transport driven by biased endplate in a cylindrical magnetized plasma

The inward particle transport is associated with the formation of peaked density profiles,which contributes to improve the fusion rate and the realization of steady-state discharge.The active control of inward particle transport is considered as one of the most critical issues of magnetic confinement fusion.Recently,it is realized preliminarily by adding a biased endplate in the Peking University Plasma Test(PPT)device.The results reveal that the inward particle flux increases with the bias voltage of the endplate.It is also found that the profile of radial electric field(Er)shear is flattened by the increased bias voltage.Radial velocity fluctuations affect the inward particle more than density fluctuations,and the frequency of the dominant mode driving inward particle flux increases with the biased voltage applied to the endplate.The experimental results in the PPT device provide a method to actively control the inward particle flux using a biased endplate and enrich the understanding of the relationship between E_(r)×B shear and turbulence transport.

Why ecosystem characteristics predicted from remotely sensed data are unbiased and biased at the same time-and how this affects applications

Remotely sensed data are frequently used for predicting and mapping ecosystem characteristics,and spatially explicit wall-to-wall information is sometimes proposed as the best possible source of information for decisionmaking.However,wall-to-wall information typically relies on model-based prediction,and several features of model-based prediction should be understood before extensively relying on this type of information.One such feature is that model-based predictors can be considered both unbiased and biased at the same time,which has important implications in several areas of application.In this discussion paper,we first describe the conventional model-unbiasedness paradigm that underpins most prediction techniques using remotely sensed(or other)auxiliary data.From this point of view,model-based predictors are typically unbiased.Secondly,we show that for specific domains,identified based on their true values,the same model-based predictors can be considered biased,and sometimes severely so.We suggest distinguishing between conventional model-bias,defined in the statistical literature as the difference between the expected value of a predictor and the expected value of the quantity being predicted,and design-bias of model-based estimators,defined as the difference between the expected value of a model-based estimator and the true value of the quantity being predicted.We show that model-based estimators(or predictors)are typically design-biased,and that there is a trend in the design-bias from overestimating small true values to underestimating large true values.Further,we give examples of applications where this is important to acknowledge and to potentially make adjustments to correct for the design-bias trend.We argue that relying entirely on conventional model-unbiasedness may lead to mistakes in several areas of application that use predictions from remotely sensed data.

R-Factor Analysis of Data Based on Population Models Comprising R- and Q-Factors Leads to Biased Loading Estimates

Effects of performing an R-factor analysis of observed variables based on population models comprising R- and Q-factors were investigated. Although R-factor analysis of data based on a population model comprising R- and Q-factors is possible, this may lead to model error. Accordingly, loading estimates resulting from R-factor analysis of sample data drawn from a population based on a combination of R- and Q-factors will be biased. It was shown in a simulation study that a large amount of Q-factor variance induces an increase in the variation of R-factor loading estimates beyond the chance level. Tests of the multivariate kurtosis of observed variables are proposed as an indicator of possible Q-factor variance in observed variables as a prerequisite for R-factor analysis.

Numerical study of the radio-frequency biased accelerating system in ion thrusters

A 2D-3V implicit immersed-finite-element particle-in-cell(IFE-PIC)model is introduced to investigate the radio-frequency(RF)self-bias accelerating system applied in the RF ion thruster.A set of holes in a two-grid system with slit apertures is simulated in Cartesian coordinates.The characteristics of the plasma plume,such as the ion density,the neutralization rate and the ion and electron current density were investigated for different RF voltage amplitudes(600-1200V)and frequencies(6-30 MHz).Furthermore,the performance of the thruster was also carefully studied.The simulation results show that a well-focused plasma beam can be formed when the voltage amplitude is larger than 900 V and the frequency exceeds the reciprocal of ion transit time(≥12 MHz)in our simulation cases.The performance of the system can be evidently improved by increasing the voltage amplitude and the frequency,and the losses of the particle and thrust are reduced correspondingly.The bulk region of the plasma beam downstream shows good quasi-neutrality,and the ions are dominant in the peripheral region when a well-focused state is achieved.The high ion density beamlet in the periphery of the ion beam is closer to the axis when the voltage amplitude is increasing,while it is expanded radially when increasing the frequency.Backstream electrons have been observed upstream,and this mainly occurs in the phase in which the electron cannot escape.

A fast hybrid simulation approach of ion energy and angular distributions in biased inductively coupled Ar plasmas

In this work,a two-dimensional hybrid model,which consists of a bulk fluid module,a sheath module and an ion Monte-Carlo module,is developed to investigate the modulation of ion energy and angular distributions at different radial positions in a biased argon inductively coupled plasma.The results indicate that when the bias voltage amplitude increases or the bias frequency decreases,the ion energy peak separation width becomes wider.Besides,the widths of the ion energy peaks at the edge of the substrate are smaller than those at the center due to the lower plasma density there,indicating the nonuniformity of the ion energy distribution function(IEDF)along the radial direction.As the pressure increases from 1 to 10 Pa,the discrepancy of the IEDFs at different radial positions becomes more obvious,i.e.the IEDF at the radial edge is characterized by multiple low energy peaks.When a dual frequency bias source is applied,the IEDF exhibits three or four peaks,and it could be modulated efficiently by the relative phase between the two bias frequencies.The results obtained in this work could help to improve the radial uniformity of the IEDF and thus the etching process.

Robustifying Biased Estimation in Linear Model

The parameter estimation problem in linear model is considered when multicollinearity and outliers exist simultaneously.A class of new estimators,robust general shrunken estimators,are proposed by grafting the robust estimation techniques philosophy into the biased estimator,and their statistical properties are discussed.By appropriate choices of the shrinking parameter matrix,we obtain many useful and important estimators.A numerical example is used to illustrate that these new estimators can not only effectively overcome difficulty caused by multicollinearity but also resist the influence of outliers.

A New Class of Biased Linear Estimators in Deficient-rank Linear Models

In this paper, we define a new class of biased linear estimators of the vector of unknown parameters in the deficient_rank linear model based on the spectral decomposition expression of the best linear minimun bias estimator. Some important properties are discussed. By appropriate choices of bias parameters, we construct many interested and useful biased linear estimators, which are the extension of ordinary biased linear estimators in the full_rank linear model to the deficient_rank linear model. At last, we give a numerical example in geodetic adjustment.

Uplink Performance Analysis in Multi-Tier Heterogeneous Cellular Networks with Power Control and Biased User Association

A K-tier uplink heterogeneous cellular network is modelled and analysed by accounting for both truncated channel inversion power control and biased user association. Each user has a maximum transmit power constraint and transmits data when it has sufficient transmit power to perform channel inversion. With biased user association, each user is associated with a base station(BS) that provides the maximum received power weighted by a bias factor, but not their nearest BS. Stochastic geometry is used to evaluate the performances of the proposed system model in terms of the outage probability and ergodic rate for each tier as functions of the biased and power control parameters. Simulations validate our analytical derivations. Numerical results show that there exists a trade-off introduced by the power cut-off threshold and the maximum user transmit power constraint. When the maximum user transmit power becomes a binding constraint, the overall performance is independent of BS densities. In addition, we have shown that it is beneficial for the outage and rate performances by optimizing different network parameters such as the power cut-off threshold as well as the biased factors.

Optimal Generalized Biased Estimator in Linear Regression Model

The paper introduces a new biased estimator namely Generalized Optimal Estimator (GOE) in a multiple linear regression when there exists multicollinearity among predictor variables. Stochastic properties of proposed estimator were derived, and the proposed estimator was compared with other existing biased estimators based on sample information in the the Scalar Mean Square Error (SMSE) criterion by using a Monte Carlo simulation study and two numerical illustrations.

WAVE PROPAGATION IN ELECTROSTRICTIVE MATERIALS UNDER BIASED FIELDS

Constitutive relations for nonlinear, isotropic, electroelastic solids quadratic in the ?nite strain tensor and the referential electric ?eld are derived from the full nonlinearity theory of electroelasticity by tensor invariants, which can describe the behavior of electrostrictive ma- terials. The equations are linearized for small, dynamic ?elds superposed on ?nite, static biased ?elds. These linear equations are used to study plane waves propagating in an electroelastic body under various mechanical and/or electric biased ?elds. It is shown that the speed of the acoustic waves exhibits a strong dependence upon those material parameters in the nonlinear constitu- tive relations. Experimental determination of these material parameters using this dependence is discussed.

Performance of Existing Biased Estimators and the Respective Predictors in a Misspecified Linear Regression Model

In this paper, the performance of existing biased estimators (Ridge Estimator (RE), Almost Unbiased Ridge Estimator (AURE), Liu Estimator (LE), Almost Unbiased Liu Estimator (AULE), Principal Component Regression Estimator (PCRE), r-k class estimator and r-d class estimator) and the respective predictors were considered in a misspecified linear regression model when there exists multicollinearity among explanatory variables. A generalized form was used to compare these estimators and predictors in the mean square error sense. Further, theoretical findings were established using mean square error matrix and scalar mean square error. Finally, a numerical example and a Monte Carlo simulation study were done to illustrate the theoretical findings. The simulation study revealed that LE and RE outperform the other estimators when weak multicollinearity exists, and RE, r-k class and r-d class estimators outperform the other estimators when moderated and high multicollinearity exist for certain values of shrinkage parameters, respectively. The predictors based on the LE and RE are always superior to the other predictors for certain values of shrinkage parameters.

Structural and Electrical Properties of Cu Films by dc Biased Plasma-Sputter-Deposited on MgO(001)

Cu films of30nm and 15 nm thick were deposited on MgO(001) substrates at 185℃ by dc plasma-sputtering at 1.9kv and 8 mA in pure Ar gas. A dc bias voltage Vs, of 0 V or -80 V was applied to the substrate during deposition. Structural and electrical proper-ties have been investigated by cross-sectional transmission electron microscopy (XTEM), high resolution XTEM (XHRTEM) and by measuring temperature coefficient of electrical resistance (TCR;η) in the temperature interval of-135℃ to 0 ℃. The Cu film is pol- ycrystalline at Vs= 0 V while it epitaxially grows with Cu(00 )|| MgO(00 1) and Cu[0 10] || MgO[010] at Vs,=-80 V. However, the latter has a very rough surface. The change of η with film thickness and Vs is interpreted in terms of the structure change. Misfit dislocations and lattice expansion are induced along the MgO surface to relax the strain energy due to the lattice mismatch between Cu and MgO.

Biased Random Number Generator Based on Bell's Theorem

We propose a biased random number generation protocol whose randomness is based on the violation of the Clauser Home inequality. Non-maximally entangled state is used to maximize the Bell violation. Due to the rotational asymmetry of the quantum state, the ratio of Os to ls varies with the measurement bases. The experimental partners can then use their measurement outcomes to generate the biased random bit string. The bias of their bit string can be adjusted by altering their choices of measurement bases. When this protocol is implemented in a device-independent way, we show that the bias of the bit string can still be ensured under the collective attack.

Adaptive Region Boosting method with biased entropy for path planning in changing environment

Path planning in changing environments with difficult regions, such as narrow passages and obstacle boundaries, creates significant chal- lenges. As the obstacles in W-space move frequently, the crowd degree of C-space changes accordingly. Therefore, in order to dynamically improve the sampling quality, it is appreciated for a planner to rapidly approximate the crowd degree of different parts of the C-space, and boost sample densities with them based on their difficulty levels. In this paper, a novel approach called Adaptive Region Boosting （ARB） is proposed to increase the sampling density for difficult areas with different strategies. What＇s more, a new criterion, called biased entropy, is proposed to evaluate the difficult degree of a region. The new criterion takes into account both temporal and spatial information of a specific C-space region, in order to make a thorough assessment to a local area. Three groups of experiments are conducted based on a dual-manipulator system with 12 DoFs. Experimental results indicate that ARB effectively improves the success rate and outperforms all the other related methods in various dynamical scenarios.

Response of the low-pressure hot-filament discharge plasma to a positively biased auxiliary disk electrode

In a steady-state plasma,the loss rate of plasma particles to the chamber wall and surfaces in contact with plasma is balanced by the ionization rate of background neutrals in the hot-filament discharges.The balance between the loss rate and ionization rate of plasma particles(electrons and ions)maintains quasi-neutrality of the bulk plasma.In the presence of an external perturbation,it tries to retain its quasi-neutrality condition.In this work,we studied how the properties of bulk plasma are affected by an external DC potential perturbation.An auxiliary biased metal disk electrode was used to introduce a potential perturbation to the plasma medium.A single Langmuir probe and an emissive probe,placed in the line of the discharge axis,were used for the characterization of the bulk plasma.It is observed that only positive bias to the auxiliary metal disk increases the plasma potential,electron temperature,and plasma density but these plasma parameters remain unaltered when the disk is biased with a negative potential with respect to plasma potential.The observed plasma parameters for two different-sized,positively as well as negatively biased,metal disks are compared and found inconsistent with the existing theoretical model at large positive bias voltages.The role of the primary energetic electrons population in determining the plasma parameters is discussed.The experimentally observed results are qualitatively explained on the basis of electrostatic confinement arising due to the loss of electrons to a biased metal disk electrode.

Biased Diffusive Search Triggered by ATP Binding During Kinesin's Stepping

In this paper, we present an asymmetry conformational potential with a reflecting boundary and an absorbing boundary, in which the diffusive search of the free head of kinesin motor can be biased toward its forward binding site. Under a wide range of condition, using first-passage time analysis we perform numerical simulation to the Langevin equation, and obtain the dependence of the dwell time for forward steps on the load force. And we calculate the expression for the dwell time by the Laplace transform method. Both numerical and analytical results show that the dwell times exponentially depend on the load force, which provide a simple physical explanation for experimental data. Our results suggest that ATP binding-conformation change in the neck linker plays an important role in unidirectional steps during kinesin＇s mechanochemical cycle.

Security of biased BB84 quantum key distribution with finite resource

In the original BB84 quantum key distribution protocol, the states are prepared and measured randomly, which lose the unmatched detection results. To improve the sifting efficiency, biased bases selection BB84 protocol is proposed. Meanwhile, a practical quantum key distribution protocol can only transmit a finite number of signals, resulting in keys of finite length. The previous techniques for finite-key analysis focus mainly on the statistical fluctuations of the error rates and yields of the qubits. However, the prior choice probabilities of the two bases also have fluctuations by taking into account the finite-size effect. In this paper, we discuss the security of biased decoy state BB84 protocol with finite resources by considering all of the statistical fluctuations. The results can be directly used in the experimental realizations.

An analytical variational method for the biased quantum Rabi model in the ultra-strong coupling regime

An analytical variational method for the ground state of the biased quantum Rabi model in the ultra-strong coupling regime is presented. This analytical variational method can be obtained by a unitary transformation or alternatively by assuming the form of the ground state wave function. The key of the method is to introduce a variational parameter λ,which can be determined by minimizing the energy functional. Using this method, we calculate the physical observables with high accuracy in comparison with the numerical exact ones. Our method evidently improves over the widely used general rotating-wave approximation（GRWA） in both qualitative and quantitative aspects.

Size Biased Lindley Distribution and Its Properties a Special Case of Weighted Distribution

The purpose of this paper is to introduce a size biased Lindley distribution which is a special case of weighted distributions. Weighted distributions have practical significance where some types of biased occur in a density function, i.e. probability is proportional to the size of the variate, that’s why the proposed version of size biased Lindley is designed for such situations more reasonably and more precisely. Principle properties of the density function are also discussed in this paper such as moments, measure of skewness, kurtosis, moment generating function, characteristics generating function, coefficient of variation, survival function and hazard function which are derived for understanding the structure of the proposed distribution more briefly.

A Class of Biased Estimators Based on SVD in Linear Model

In this paper, a class of new biased estimators for linear model is proposed by modifying the singular values of the design matrix so as to directly overcome the difficulties caused by ill_conditioning in the design matrix. Some important properties of these new estimators are obtained. By appropriate choices of the biased parameters, we construct many useful and important estimators. An application of these new estimators in three_dimensional position adjustment by distance in a spatial coordiate surveys is given. The results show that the proposed biased estimators can effectively overcome ill_conditioning and their numerical stabilities are preferable to ordinary least square estimation.