Finite-Time Normal Mode Disturbances and Error Growth During Southern Hemisphere Blocking

The structural organization of initially random errors evolving in abarotropic tangent linear model, with time-dependent basic states taken from analyses, is examinedfor cases of block development, maturation and decay in the Southern Hemisphere atmosphere duringApril, November, and December 1989. The statistics of 100 evolved errors are studied for six-dayperiods and compared with the growth and structures of fast growing normal modes and finite-timenormal modes (FTNMs). The amplification factors of most initially random errors are slightly lessthan those of the fastest growing FTNM for the same time interval. During their evolution, thestandard deviations of the error fields become concentrated in the regions of rapid dynamicaldevelopment, particularly associated with developing and decaying blocks. We have calculatedprobability distributions and the mean and standard deviations of pattern correlations between eachof the 100 evolved error fields and the five fastest growing FTNMs for the same time interval. Themean of the largest pattern correlation, taken over the five fastest growing FTNMs, increases withincreasing time interval to a value close to 0.6 or larger after six days. FTNM 1 generally, but notalways, gives the largest mean pattern correlation with error fields. Corresponding patterncorrelations with the fast growing normal modes of the instantaneous basic state flow aresignificant' but lower than with FTNMs. Mean pattern correlations with fast growing FTNMs increasefurther when the time interval is increased beyond six days.

Phase Wise Supply Chain Model of EOQ with Normal Life Time for Queued Customers: A Computational Approach

In this paper, we mainly aim to compute the optimal inventory in the phase wise supply chain for queued customers in the interval of lower and upper bounds with particular life of the items. Important performance measures such as total optimal cost of the system and total expected delivery have also been computed by applying the dynamic programming and Drichlet theorem. Finally, numerical demonstration and sensitivity analysis have also been presented to gain the better perspective of the model.

Selection of Reference Genes in Equine White Blood Cells for Real Time PCR Normalization Following Extracorporeal Shock Wave Therapy

Selection of proper reference genes (RGs) is an essential step needed for accurate normalization of results from genomic studies. Expression of RGs is regulated by many factors such as species, age, gender, type of tissue, the presence of disease, and the administration of therapeutic treatment. The aim of the present study was to identify optimal RGs in a set of blood samples collected at different time points (0, 24, 48, 72 h) from horses following administration of extracorporeal shock wave therapy (ESWT). The mRNA expression of twelve RGs: HPRT1, ACTB, HSP90A, SDHA, GUSB, B2M, UBC, NONO, TBP, H6PD, RPL32, GAPDH was determined using real time quantitative polymerase chain reaction (qPCR). An SAS program developed on the algorithm of geNorm, SASqPCR, was used to determine stability of the expression and the number of optimal RGs. The results showed that the range of quantification cycle (Cq) values of the evaluated genes varied between 17 and 26 cycles, and that one optimal RG, ACTB, was sufficient for normalization of gene expression. Results of stability of expression demonstrated that ACTB was the optimal choice for all the samples studied. Notably, in samples collected at 72 h post ESWT, TBP showed a significant change in the expression level, and was not suitable for use as a RG. These results substantiate the importance of validating and selecting an appropriate RG.

Symmetry Violation of Time Reversal in Third Order Vertex Angle Renormalization Process of Electromagnetic Interaction

According to the current understanding, electromagnetic interaction is invariable under time reversal. However, the proof of time reversal symmetry in quantum theory of field has not considered the effects of high order perturbation normalizations. It is proved in the paper that when the renormalization effect of third order vertex angles process is taken into account, the symmetry of time reversal will be violated in electromagnetic interaction process. Because the magnitude order of symmetry violation is about 10–5, but the precision of current experiments on time reversal in particle physics is about 10–3, this kind of symmetry violation can not be found. The result reveals the micro-origin of asymmetry of time reversal and can be used to solve the famous irreversibility paradox in the evolution processes of macro- material systems.

一种基于Normal矩阵的时间序列聚类方法

提出了一种基于Normal矩阵的时间序列聚类方法。该算法首先对时间序列数据进行向量形式转换,计算出各个时间序列间的相似度并构建复杂网络,然后利用基于Normal矩阵的方法进行复杂网络社团划分,同一类的时间序列被划分到一个社团,即实现对时间序列数据的聚类。为了验证该方法的可行性和有效性,将其应用于股票时间序列数据聚类分析中,并在两个实际的数据集上与其他方法相比较,取得了较好的实验结果。

一种基于NORMAL FORM变换的时间序列轨迹预测方法

随着基于GPS的功角测量技术在电力系统中的广泛应用,在线轨迹的预测成为了可能,其对于暂态稳定紧急控制具有重要意义。本文基于Normal Form分析,提出了一种复幂指数时间序列的预测方法;针对轨迹预测特点和各种预测模型对观测数据窗长短的要求不同,提出了一种变结构的思想。所提预测方法是基于Prony非线性拟合,Prony方法及其最近的研究显示了其在线应用的可能。轨迹预测过程和结果使用中国电科院8机36母线系统进行分析,其时域仿真结果验证了所提方法的有效性和可行性。

Correspondence normalized ghost imaging on compressive sensing

Ghost imaging （GI） offers great potential with respect to conventional imaging techniques. It is an open problem in GI systems that a long acquisition time is be required for reconstructing images with good visibility and signal-to-noise ratios （SNRs）. In this paper, we propose a new scheme to get good performance with a shorter construction time. We call it correspondence normalized ghost imaging based on compressive sensing （CCNGI）. In the scheme, we enhance the signal-to-noise performance by normalizing the reference beam intensity to eliminate the noise caused by laser power fluctuations, and reduce the reconstruction time by using both compressive sensing （CS） and time-correspondence imaging （CI） techniques. It is shown that the qualities of the images have been improved and the reconstruction time has been reduced using CCNGI scheme. For the two-grayscale ＂double-slit＂ image, the mean square error （MSE） by GI and the normalized GI （NGI） schemes with the measurement number of 5000 are 0.237 and 0.164, respectively, and that is 0.021 by CCNGI scheme with 2500 measurements. For the eight-grayscale ＂lena＂ object, the peak signal-to-noise rates （PSNRs） are 10.506 and 13.098, respectively using G1 and NGI schemes while the value turns to 16.198 using CCNGI scheme. The results also show that a high-fidelity GI reconstruction has been achieved using only 44% of the number of measurements corresponding to the Nyquist limit for the two-grayscale ＂double-slit＂ object. The qualities of the reconstructed images using CCNGI are almost the same as those from GI via sparsity constraints （GISC） with a shorter reconstruction time.

Assessing ecological vulnerability in western China based on Time-Integrated NDVI data

Arid and semi-arid areas are the most vulnerable regions to climate change. Clear understanding of the effects of climate change on ecosystems in arid and semi-arid regions and the ecosystem vulnerability is important for ecosystem management under the background of climate change. In this study, we conducted a vulnerability assessment on various ecosystems from 1982 to 2013 in western China with large areas of arid and semi-arid lands based on the Time-Integrated Normalized Difference Vegetation Index （TINDVI） data and climate data. The results indicated that grasslands were the most vulnerable ecosystem to climate change in western China, especially for those in Tibetan Plateau. Croplands in oases were not vulnerable to climate change compared to rain-fed croplands in semi-arid regions （e.g. Gansu and Inner Mongolia）, which was attributed to the well-developed drip irrigation technology in oases. Desert and Gobi ecosystems were slightly vulnerable to climate change during the past several decades. The assessment results, as revealed in this study, can provide a reference for taking appropriate actions to protect the ecosystems in western China.

FIXED-DESIGN REGRESSION FOR LINEARTIME SERIES

This paper obtains asymptotic normality for double array sum of linear time series zeta(t), and gives its application in the regression model. This generalizes the main results in [1].

Singularity analysis of Jeffcott rotor-magnetic bearing with time delays

A Jeffcott rotor-magnetic bearing with time delays is investigated in this paper. Firstly, it is found that the characteristic equation of the system satisfies the conditions of the singularity. Secondly, the center manifold reduction and normal form are employed to study the bifurcation from simple zero and zero-purely imaginary singularities. The results of this paper will help to understand the influence of the time delays in feedback loop on the dynamics of rotor-magnetic bearing system.

Classification of Vegetation in North Tibet Plateau Based on MODIS Time-Series Data

Based on the 16d-composite MODIS （moderate resolution imaging spectroradiometer）-NDVI（normalized difference vegetation index） time-series data in 2004, vegetation in North Tibet Plateau was classified and seasonal variations on the pixels selected from different vegetation type were analyzed. The Savitzky-Golay filtering algorithm was applied to perform a filtration processing for MODIS-NDVI time-series data. The processed time-series curves can reflect a real variation trend of vegetation growth. The NDVI time-series curves of coniferous forest, high-cold meadow, high-cold meadow steppe and high-cold steppe all appear a mono-peak model during vegetation growth with the maximum peak occurring in August. A decision-tree classification model was established according to either NDVI time-series data or land surface temperature data. And then, both classifying and processing for vegetations were carried out through the model based on NDVI time-series curves. An accuracy test illustrates that classification results are of high accuracy and credibility and the model is conducive for studying a climate variation and estimating a vegetation production at regional even global scale.

Supplying Conditions for Having up to 1000 Degrees of Freedom in the Onset of Inflation, Instead of 2 to 3 Degrees of Freedom, Today, in Space-Time

The following document attempts to answer the role additional degrees of freedom have as to initial inflationary cosmology, i.e. the idea is to cut down on the number of independent variables to get as simple an emergent space time structure of entropy and its generation as possible. One parameter being initial degrees of freedom, the second the minimum allowed grid size in space time, and the final parameter being emergent space time temperature. In order to initiate this inquiry, a comparison is made to two representations of a scale evolutionary Friedman equation, with one of the equations based upon LQG, and another involving an initial Hubble expansion parameter with initial temperature used as an input into T4 times N(T). Initial assumptions as to the number of degrees of freedom have for a maximum value of N(T) ~ 103. Making that upper end approximation for the value of permissible degrees of freedom is dependent upon a minimum grid size length as of about centimeters. Should the minimum uncertainty grid size for space time be higher than centimeters, then top value degrees of freedom of phase space as given by a value N(T) ~ 103 drops. In addition, the issue of bits, i.e. information is shown to not only have temperature dependence, but to be affected by minimum “grid size” as well.

Turing Instability of Gray-Scott Reaction-Diffusion Model with Time Delay Effects

The reaction diffusion Gray-Scott model with time delay is put forward with the assumption of Neumann boundary condition is satisfied. Based on the Turing bifurcation condition, the Turing curves on two parameter plane are discussed without time delay. The normal form is computed via applying Lyapunov-Schmidt reduction method in system of PDE, and the bifurcating direction of pitchfork bifurcation underlying codimension-1 singularity of Turing point is computed. The continuation of Pitchfork bifurcation is simulated with varying free parameter continuously near the turing point, which is in coincidence with the theoritical analysis results. The wave pattern formation in the case of turing instability is also simulated which discover Turing oscillation phenomena from periodicity to irregularity.

A time fractional model to represent rainfall process

This paper deals with a stochastic representation of the rainfall process. The analysis of a rainfall time series shows that cumulative representation of a rainfall time series can be modeled as a non-Gaussian random walk with a log-normal jump distribution and a time-waiting distribution following a tempered a-stable probability law. Based on the random walk model, a fractional Fokker-Planck equation （FFPE） with tempered a-stable waiting times was obtained. Through the comparison of observed data and simulated results from the random walk model and FFPE model with tempered a-stable waiting times, it can be concluded that the behavior of the rainfall process is globally reproduced, and the FFPE model with tempered a-stable waiting times is more efficient in reproducing the observed behavior.

Formation, Propagation and Reflection of 1D Normal Shocks in Riemann Shock Tube

The purpose of this paper is to consider 1D Riemann shock tube to investigate the formation and propagation of compression waves leading to formation, propagation and reflection of 1D normal shocks using simplified mathematical models commonly used in the published work as well as using complete mathematical models based on Conservation and Balance Laws (CBL) of classical continuum mechanics and constitutive theories for compressible viscous medium derived using entropy inequality and representation theorem. This work is aimed at resolving compression waves, the shock structure, shock formation, propagation and reflection of fully formed shocks. Evolutions obtained from the mathematical models always satisfy differentiability requirements in space and time dictated by the highest order of the derivatives of the dependent variables in the mathematical models investigated. All solutions reported in this paper including boundary conditions and initial conditions are always analytic. Solutions of the mathematical models are obtained using the space-time finite element method in which the space-time integral forms are space-time variationally consistent ensuring unconditionally stable computations during the entire evolution. Solution for a space-time strip or slab is calculated and is time marched upon convergence to obtain complete evolution for the desired space-time domain, thus ensuring time accurate evolutions. The space-time local approximation over a space-time element of a space-time strip or slab is p-version hierarchical with higher-order global differentiability in space and time, i.e., we consider scalar product approximation spaces in which k = (k1, k2) are the order of the space in space and time and p = (p1, p2) are p-levels of the approximations in space and time. Model problem studies are presented for different mathematical models and are compared with solutions obtained from the complete mathematical model based on CBL and constitutive theories for viscous compressible medium to illustrate the deficiencies and shortcomings of the simplified and approximate models in simulating correct physics of normal shocks.

Discrete-time Direct Model Reference Adaptive Control： A Systematic Approach

为直接模型引用的分离时间的系统，设计和分析的一个类，有规范的适应法律的适应控制(MRAC ) 被调查。我们责骂在输入和产量之间的 p 和 2 个关系性质上的分离时间的结论，和分离时间的交换词根 1 和 2。我们也建立分离时间的适应法律的性质，定义使正常化的信号，并且联系有在靠近环的系统的所有信号的信号。因此，分离时间的 MRAC 计划的稳定性和集中性质作为在连续时间的案例中以一种系统的方式严厉地被分析。

火山灰硅酸盐水泥粒径对水化反应的影响

通过不同细度的筛网和调整磨粉时间获得不同细度的火山灰硅酸盐水泥,试验结合X射线衍射(XRD)、扫描电子显微镜(SEM)技术从微观的角度研究了火山灰硅酸盐水泥的细度对火山灰硅酸盐水泥宏观性能、钙矾石晶体与C-H-S凝胶的影响.结果表明,随着火山灰硅酸盐水泥的细度从224.45 m^(2)·kg^(-1)增加至576.88 m^(2)·kg^(-1),抗压强度与抗折强度提高,火山灰硅酸盐的水泥凝结时间下降,标准稠度用水量提高.结合XRD、SEM进行微观分析,利用SEM技术观察出水化产物为钙矾石晶体与C-H-S凝胶,通过XRD技术物相分析发现随着细度的增加钙矾石晶体峰值与Ca(OH)_(2)峰值逐步提升,得出不同细度的火山灰硅酸盐水泥水化产物随着水泥细度的增大而增多.

Bifurcation Analysis of the Regulatory Modules of the Mammalian <i>M/G₁</i>Phase with Time Delay

G0/G1 “gaps” joint the S phase and M phase to form the cell cycle. The dynamics of enzyme reaction to drive the target protein production in M phase is analyzed mathematically. Time delay is introduced since the signal transmission need time in G0/G1 “gaps” phase. Hopf bifurcation of DDEs model is analyzed by applying geometrical analytical method. The instability oscillating periodic solutions arise as subcritical Hopf bifurcation occurs. The Hysteresis phenomena of the limit cycle are also observed underlying the saddle-node bifurcation of the limit cycle. Due to stability switching, interestingly, the bifurcating periodical solution dies out near the vicinity of Hopf lines. By Lyapunov-Schmidt reduction scheme, the normal form is computed on the center manifold. Finally, it is verified that the theory analytical results are in coincidence with the numerical simulation.

Direct model reference adaptive control using K_p = LDU factorization for multivariable discrete-time plants

For a large class of discrete-time multivariable plants with arbitrary relative degrees, the design and analysis of the direct model reference adaptive control scheme are investigated under less restrictive assumptions. The algorithm is based on a new parametrization derived from the high frequency gain matrix factorization Kp=LDU under the condition that the signs of the leading principal minors of/fp are known. By reproving the discrete-time Lp and L2σ norm relationship between inputs and outputs, establishing the properties of discrete-time adaptive law, defining the normalizing signal, and relating the signal with all signals in the closed-loop system, the stability and convergence of the discrete-time multivariable model reference adaptive control scheme are analyzed rigorously in a systematic fashion as in the continuous-time case.

A Systematic Analysis Approach to Discrete-time Indirect Model Reference Adaptive Control

这份报纸论述间接模型引用的设计和分析有为分离时间的系统的一个类的规范的适应法律的适应控制(MRAC ) 。主要工作包括三部分。第一，构造工厂参数评价算法不仅拥有传统的评价算法的象那些的一样的性质而且在零避免分割的可能性。第二，由发现在工厂参数之间的关系，估计和控制器参数估计并且用工厂参数的性质估计，控制器参数估计的类似的性质也被建立。第三，基于关系，在使正常化之间的性质发信号并且在靠近环的系统并且在分离时间的系统上的一些重要数学工具上的所有信号作为在连续时间的盒子中，到分离间接 MRAC 计划的系统的稳定性和集中分析途径严厉地被开发。