Optimal Perturbations Triggering Weather Regime Transitions:Onset of Blocking and Strong Zonal Flow

In this paper, the approach proposed by Mu and Jiang （2008） to obtain the optimal perturbations for triggering blocking （BL） onset is generalized to seek the optimal perturbations triggering onset of the strong zonal flow （SZF） regime. The BL and SZF regimes are characterized by the same dipole-like anomaly pattern superposed on the climatological flow, but with opposite sign. The results show that this method is also superior at finding the initial optimal perturbations triggering onset of the SZF regime, especially in the medium range. Furthermore, by comparing the two kinds of conditional nonlinear optimal perturbations （CNOPs） trig-gering onset of BL and SZF regimes, we find that in the linear approximation, there is symmetry in the sensitivities for BL and SZF onset, and the perturbations that optimally trigger onset of BL and SZF regimes at times when linear approximation is valid are also characterized by the same spatial pattern but with opposite sign. Whereas when the optimization time is extended to 6 days, the two kinds of CNOPs lose their out-of-phase behavior. The nonlinearity results in an asymmetry between the sensitivity for BL and SZF onset. Additionally, we find that the optimal perturbations have one common property, which is that the second baroclinic mode contributes more to the initial perturbations while the barotropic mode dominates the final structures.

Stochastic resonance in a single-mode laser driven by quadratic pump noise and amplitude-modulated signal

This paper investigates the phenomenon of stochastic resonance in a single-mode laser driven by quadratic pump noise and amplitude-modulated signal. A new linear approximation approach is advanced to calculate the signal-to-noise ratio. In the linear approximation only the drift term is linearized, the multiplicative noise term is unchangeable. It is found that there appears not only the standard form of stochastic resonance but also the broad sense of stochastic resonance, especially stochastic multiresonance appears in the curve of signal-to-noise ratio as a function of coupling strength A between the real and imaginary parts of the pump noise.

Viewing the noise propagation mechanism in a unidirectional transition cascade from the perspective of stability

Noise and noise propagation are inevitable and play a constructive role in various biological processes.The stability of cell homeostasis is also a critical issue.In the unidirectional transition cascade of colon cells,stem cells(SCs)are the source.They differentiate into transit-amplifying cells(TACs),and TACs differentiate into fully differentiated cells(FDCs).Two differentiation processes are irreversible.The stability factor is introduced so that the noise propagation mechanism from the perspective of stability is studied according to the noise propagation formulas.It is found that the value of the stability factor corresponding to the minimum noise in FDCs may be the best choice to enable colon cells to maintain high stability and low noise of the cascade.Moreover,for the source cell,the total noise only includes intrinsic noise;for the downstream cell with self-proliferation capability,the total noise mainly depends on its intrinsic noise and transmitted noise from upstream cells,and its intrinsic noise is dominant.For the downstream cell without self-proliferation capability,the total noise is mainly determined by transmitted noises from upstream cells,and there is a minimum value.This work provides a new approach for studying the mechanism of noise propagation while considering the stability of cell homeostasis in biological systems.

Composite Control of Nonlinear Singularly Perturbed Systems via Approximate Feedback Linearization

This article is devoted to the problem of composite control design for continuous nonlinear singularly perturbed(SP)system using approximate feedback linearization(AFL)method.The essence of AFL method lies in the feedback linearization only of a certain part of the original nonlinear system.According to AFL approach,we suggest to solve feedback linearization problems for continuous nonlinear SP system by reducing it to two feedback linearization problems for slow and fast subsystems separately.The resulting AFL control is constructed in the form of asymptotic composition(composite control).Standard procedure for the composite control design consists of the following steps:1)system decomposition,2)solution of control problem for fast subsystem,3)solution of control problem for slow subsystem,4)construction of the resulting control in the form of the composition of slow and fast controls.The main difficulty during system decomposition is associated with dynamics separation condition for nonlinear SP system.To overcome this,we propose to change the sequence of the design procedure:1)solving the control problem for fast state variables part,2)system decomposition,3)solving the control problem for slow state variables part,4)construction of the resulting composite control.By this way,fast feedback linearizing control is chosen so that the dynamics separation condition would be met and the fast subsystem would be stabilizable.The application of the proposed approach is illustrated through several examples.

ONE LINEAR ANALYTIC APPROXIMATION FOR STOCHASTIC INTEGRODIFFERENTIAL EQUATIONS

This article concerns the construction of approximate solutions for a general stochastic integrodifferential equation which is not explicitly solvable and whose coeffcients functionally depend on Lebesgue integrals and stochastic integrals with respect to martingales. The approximate equations are linear ordinary stochastic differential equations, the solutions of which are defined on sub-intervals of an arbitrary partition of the time interval and connected at successive division points. The closeness of the initial and approximate solutions is measured in the L^p-th norm, uniformly on the time interval. The convergence with probability one is also given.

A statistical RCL interconnect delay model taking account of process variations

As the feature size of the CMOS integrated circuit continues to shrink, process variations have become a key factor affecting the interconnect performance. Based on the equivalent Elmore model and the use of the polynomial chaos theory and the Galerkin method, we propose a linear statistical RCL interconnect delay model, taking into account process variations by successive application of the linear approximation method. Based on a variety of nano-CMOS process parameters, HSPICE simulation results show that the maximum error of the proposed model is less than 3.5%. The proposed model is simple, of high precision, and can be used in the analysis and design of nanometer integrated circuit interconnect systems.

Influences of quantum noises on direct-modulated properties of 1.3-μm InGaAsP/InP laser diodes

Due to the zero dispersion point at 1.3μm in optical fibres, 1.3-μm InGaAsP/InP laser diodes have become main light sources in fibre communication systems recently. Influences of quantum noises on direct-modulated properties of single-mode 1.3-μm InGaAsP/InP laser diodes are investigated in this article. Considering the carrier and photon noises and the cross-correlation between the two noises, the power spectrum of the photon density and the signal-to-noise ratio （SNR） of the direct-modulated single-mode laser system are calculated using the linear approximation method. We find that the stochastic resonance （SR） always appears in the dependence of the SNR on the bias current density, and is strongly affected by the cross-correlation coefficient between the carrier and photon noises, the frequency of modulation signal, and the photon lifetime in the laser cavity. Hence, it is promising to use the SR mechanism to enhance the SNR of direct-modulated InGaAsP/InP laser diodes and improve the quality of optical fibre communication systems.

Intrinsic noise analysis and stochastic simulation on transforming growth factor beta signal pathway

A typical biological cell lives in a small volmne at room temperature; the noise effect on the cell signal transduction pathway may play an important role in its dynamics. Here, using the transforming growth factor-β signal transduction pathway as an example, we report our stochastic simulations of the dynamics of the pathway and introduce a linear noise approximation method to calculate the transient intrinsic noise of pathway components. We compare the numerical solutions of the linear noise approximation with the statistic results of chemical Langevin equations, and find that they are quantitatively in agreement with the other. When transforming growth factor-β dose decreases to a low level, the time evolution of noise fluctuation of nuclear Smad2-Smad4 complex indicates the abnormal enhancement in the transient signal activation process.

Improved response surface method based on sample point selection strategies

In the reliability analysis of complex structures,response surface method(RSM)has been suggested as an efficient technique to estimate the actual but implicit limit state function.A set of sample points are needed to fit to the implicit function.It has been noted that the accuracy of RSM depends highly on the so-called sample points.However,the technique for point selection has had little attention.In the present study,an improved response surface method(IRSM)based on two sample point selection techniques,named the direction cosines projected strategy(DCS)and the limit step length iteration strategy(LSS),is investigated.Since it uses the sampling points selected to be located in the region close to the original failure surface,and since it needs only one response surface,the IRSM should be accurate and simple in practical structural problems.Applications to several typical examples have helped to elucidate the successful working of the IRSM.

Stochastic resonance in a gain-noise model of a single-mode laser driven by pump noise and quantum noise with cross-correlation between real and imaginary parts under direct signal modulation

Stochastic resonance （SR） is studied in a gain-noise model of a single-mode laser driven by a coloured pump noise and a quantum noise with cross-correlation between real and imaginary parts under a direct signal modulation. By using a linear approximation method, we find that the SR appears during the variation of signal-to-noise ratio （SNR） separately with the pump noise self-correlation time τ, the noise correlation coefficient between the real part and the imaginary part of the quantum noise λq, the attenuation coefficient γ＇ and the deterministic steady-state intensity I0. In addition, it is found that the SR can be characterized not only by the dependence of SNR on the noise variables of and λq, but also by the dependence of SNR on the laser system variables of γ and I0. Thus our investigation extends the characteristic quantity of SR proposed before.

Noise decomposition algorithm and propagation mechanism in feed-forward gene transcriptional regulatory loop

Feed-forward gene transcriptional regulatory networks, as a set of common signal motifs, are widely distributed in the biological systems. In this paper, the noise characteristics and propagation mechanism of various feed-forward gene transcriptional regulatory loops are investigated, including （i） coherent feed-forward loops with AND-gate, （ii） coherent feed-forward loops with OR-gate logic, and （iii） incoherent feed-forward loops with AND-gate logic. By introducing logarithmic gain coefficient and using linear noise approximation, the theoretical formulas of noise decomposition are derived and the theoretical results are verified by Gillespie simulation. From the theoretical and numerical results of noise decomposition algorithm, three general characteristics about noise transmission in these different kinds of feed-forward loops are observed, i） The two-step noise propagation of upstream factor is negative in the incoherent feed-forward loops with AND-gate logic, that is, upstream factor can indirectly suppress the noise of downstream factors, ii） The one-step propagation noise of upstream factor is non-monotonic in the coherent feed-forward loops with OR-gate logic, iii） When the branch of the feed-forward loop is negatively controlled, the total noise of the downstream factor monotonically increases for each of all feed-forward loops. These findings are robust to variations of model parameters. These observations reveal the universal rules of noise propagation in the feed-forward loops, and may contribute to our understanding of design principle of gene circuits.

Study on High-Speed Magnitude Approximation for Complex Vectors

High-speed magnitude approximation algorithms for complex vectors are discussed intensively. The performance and the convergence speed of these approximation algorithms are analyzed. For the polygon fitting algorithms, the approximation formula under the least mean square error criterion is derived. For the iterative algorithms, a modified CORDIC (coordinate rotation digital computer) algorithm is developed. This modified CORDIC algorithm is proved to be with a maximum relative error about one half that of the original CORDIC algorithm. Finally, the effects of the finite register length on these algorithms are also concerned, which shows that 9 to 12-bit coefficients are sufficient for practical applications.

Modeling Fast Diffusion Processes in Time Integration of Stiff Stochastic Differential Equations

Numerical algorithms for stiff stochastic differential equations are developed using lin-ear approximations of the fast diffusion processes,under the assumption of decoupling between fast and slow processes.Three numerical schemes are proposed,all of which are based on the linearized formulation albeit with different degrees of approximation.The schemes are of comparable complexity to the classical explicit Euler-Maruyama scheme but can achieve better accuracy at larger time steps in stiff systems.Convergence analysis is conducted for one of the schemes,that shows it to have a strong convergence order of 1/2 and a weak convergence order of 1.Approximations arriving at the other two schemes are discussed.Numerical experiments are carried out to examine the convergence of the schemes proposed on model problems.

ON CONSERVATIVE APPROXIMATION BY LINEAR POLYNOMIAL OPERATORS AN EXTENSION OF THE BERNSTEIN'S OPERATOR

In this work we slwly linear polynomial operators preserving some consecutive i-convexities and leaving in-verant the polynomtals up to a certain degree. First we study the existence of an incompatibility between the conservation of cenain i-cotivexities and the invariance of a space of polynomials. Interpolation properties are obtained and a theorem by Berens and DcVore about the Bernstein's operator ts extended. Finally, from these results a genera'ized Bernstein's operator is obtained.

QCM Sensors Based on PEI Films for CO_2 Detection

In this paper, quartz crystal microbalance（QCM） gas sensors coated with polyehtyleneimine（PEI）was utilized for carbon dioxide（CO2） detection. The sensing mechanism is based on the availability of reversible acid-base reactions between CO2 molecules and PEI at room temperature. The experimental results revealed that the PEI/starch sensor exhibited much higher sensitivity than that of pure PEI, and showed approximate linearity over a concentration region ranging from 500 ppm to 8000 ppm. The influence of humidity had also been investigated. Furthermore, the response and recovery time deceased as the operation temperatures increased. Finally, sensitivity loss after conservation for several days and reversibility of the sensors had been discussed.

基于两部模型的组合惩罚似然估计方法研究及其应用

在统计学中,多借助零膨胀模型研究零膨胀数据潜在的模型结构及变量选择问题。然而,在多数情况下,响应变量的非零部分为定量数据,简单的零膨胀模型无法刻画这类数据的模型结构,对应的参数估计方法也不再适用。鉴于此,学者提出处理零膨胀半连续数据的两部模型。本文将组合惩罚似然估计方法引入两部模型,研究其变量选择问题。提出一种新的处理高维统计分析问题的惩罚似然估计方法:NCPM (New Combined Punishment Method),并将该方法应用于太原市降水量数据,分析其影响因素。模拟及实例分析结果均表明本文的方法行之有效,较传统的惩罚似然估计方法具有更高的预测精度。

Linear Momentum Approximation and Frontogenesis Caused by Baroclinic Ekman Momentum Flow

A method of linear momentum approximation is proposed that deals with weak nonlinear problems in an approximate manner. A motion of nonlinear nature is obtained in the system by assuming the motion to be in the form of linear momentum flow in the corresponding space introduced, followed by the transformation from the specified into a physical space. Significant results have been thereby derived in examining the effects of baroclinic Ekman momentum flow upon Eady-type baroclinic waves and frontogenesis. Also, this technique can be applied to investigate the dynamic characteristics of the weak nonlinear boundary layer including topography, stratification and non-Ekmantype friction for gaining further insight into the influence on the boundary layer inner parameters of terrain, baroclinicity and inhomogeneous process so that the classic theory is revised.

Dependence of the Plant Productivity on Optimal Food Regime and Density

It has been studied the dependence of vegetable crop yield on standing density of the plant. Field experiments have been conducted on plain Mughan of Azerbaijan Republic. For identifying the maximum value of crop yield it has been carried out approximation of the results of field works with special programs. The point of yield maximum for tomatoes, eggplant, and peppers has been calculated, and also it has been carried out the variation in the amount of nitrogen to decreasing direction in nutrition circuit and the impact of this variation on yield has been regarded. The obtained data are interpreted on the basis of two-substrate model of plant growth.

A Convex Approximation for a PDE Constrained Fractional Optimization Problem with an Application to Photonic Crystal Design

Based on a subspace method and a linear approximation method,a convex algorithm is designed to solve a kind of non-convex PDE constrained fractional optimization problem in this paper.This PDE constrained problem is an infinitedimensional Hermitian eigenvalue optimization problem with non-convex and low regularity.Usually,such a continuous optimization problem can be transformed into a large-scale discrete optimization problem by using the finite element methods.We use a subspace technique to reduce the scale of discrete problem,which is really effective to deal with the large-scale problem.To overcome the difficulties caused by the low regularity and non-convexity,we creatively introduce several new artificial variables to transform the non-convex problem into a convex linear semidefinite programming.By introducing linear approximation vectors,this linear semidefinite programming can be approximated by a very simple linear relaxation problem.Moreover,we theoretically prove this approximation.Our proposed algorithm is used to optimize the photonic band gaps of two-dimensional Gallium Arsenide-based photonic crystals as an application.The results of numerical examples show the effectiveness of our proposed algorithm,while they also provide several optimized photonic crystal structures with a desired wide-band-gap.In addition,our proposed algorithm provides a technical way for solving a kind of PDE constrained fractional optimization problems with a generalized eigenvalue constraint.

A Nonlinear Optimal Control Approach for Tracked Mobile Robots

The article proposes a nonlinear optimal(H-infinity)control approach for the model of a tracked robotic vehicle.The kinematic model of such a tracked vehicle takes into account slippage effects due to the contact of the tracks with the ground.To solve the related control problem,the dynamic model of the vehicle undergoes first approximate linearization around a temporary operating point which is updated at each iteration of the control algorithm.The linearization process relies on first-order Taylor series expansion and on the computation of the Jacobian matrices of the state-space model of the vehicle.For the approximately linearized description of the tracked vehicle a stabilizing H-infinity feedback controller is designed.To compute the controller’s feedback gains an algebraic Riccati equation is solved at each time-step of the control method.The stability properties of the control scheme are proven through Lyapunov analysis.It is also demonstrated that the control method retains the advantages of linear optimal control,that is fast and accurate tracking of reference setpoints under moderate variations of the control inputs.