Towards a physics of Internet traffic in a geographic network

A set of equations from a biased random walk are shown to describe the time-based Gaussian distributions of Internet traffic relative to the Earth’s time zones. The Internet is an example of a more general physical problem dealing with motion near the speed of light relative to different time frames of reference. The second order differential equation (DE) takes the form of ‘time diffusion’ near the speed of light or alternatively considered as a complex variable with real time and imaginary longitudinal components. Congestion waves are generated by peak global traffic from different time zones following the Earth’s revolution. The DE is divided into space and time operators for discussion and each component solution, including constants, is illustrated using data from a global network compiled by the Stanford Linear Accelerator Centre (SLAC). Indices of global and regional phase congestion for the monitoring sites are calculated from standardised regressions from the Earth’s rotation. There is also a J-curve limit to transferring information by the Internet and this is expressed as an inequality underpinned by the speed of light with examples from US and European traffic. The research returns to an often little known theme of Isaac Newton’s: mixing physics with geography. In our case, the equations define trajectories of information packets travelling near the speed of light, navigating within networks and between longitudes, relative to the Earth’s rotation.     

Partial least squares for discrimination in fMRI data

Multivariate methods for discrimination were used in the comparison of brain activation patterns between groups of cognitively normal women who are at either high or low Alzheimer's disease risk based on family history and apolipoprotein-E4 status. Linear discriminant analysis (LDA) was preceded by dimension reduction using principal component analysis (PCA), partial least squares (PLS) or a new oriented partial least squares (OrPLS) method. The aim was to identify a spatial pattern of functionally connected brain regions that was differentially expressed by the risk groups and yielded optimal classification accuracy. Multivariate dimension reduction is required prior to LDA when the data contain more feature variables than there are observations on individual subjects. Whereas PCA has been commonly used to identify covariance patterns in neuroimaging data, this approach only identifies gross variability and is not capable of distinguishing among-groups from within-groups variability. PLS and OrPLS provide a more focused dimension reduction by incorporating information on class structure and therefore lead to more parsimonious models for discrimination. Performance was evaluated in terms of the cross-validated misclassification rates. The results support the potential of using functional magnetic resonance imaging as an imaging biomarker or diagnostic tool to discriminate individuals with disease or high risk.     

How to obtain magnetocapacitance effects at room temperature: The case of Mn-doped BiFeO3

The magnetoelectric properties of a rhombohedrally distorted perovskite BiFe_0.7Mn_0.3O₃ are reported. An anomaly in the dielectric constant, related to enhanced thermal fluctuations around the antiferromagnetic transition, was induced near room temperature by the substitution of Mn for Fe in BiFeO₃. This substitution also brings about non-trivial magnetocapacitance effects at room temperature.     

Effect of signal intensity normalization on the multivariate analysis of spectral data in complex ‘real‐world’ datasets

Spectral signal intensities, especially in ‘real‐world’ applications with nonstandardized sample presentation due to uncontrolled variables/factors, commonly require additional spectral processing to normalize signal intensity in an effective way. In this study, we have demonstrated the complexity of choosing a normalization routine in the presence of multiple spectrally distinct constituents by probing a dataset of Raman spectra. Variation in absolute signal intensity (90.1% of total variance) of the Raman spectra of these complex biological samples swamps the variation in useful signals (9.4% of total variance), degrading its diagnostic and evaluative potential. Using traditional spectral band choices, it is shown that normalization results are more complex than generally encountered in traditionally designed sample sets investigating limited chemical species. We demonstrate that no choice of a single band proves to be appropriate for predicting all the reference parameters, instead requiring a tailored normalization routine for each parameter. Of the reference parameters studied in the chosen system, signals from pathogenic adducts in ocular tissues called advanced glycation endproducts were most prominent when normalizing about the 1550–1690 cm⁻¹ region of the spectrum (17.5% of total variance, compared with 0.3% for unnormalized), while prediction of pentosidine and gender were optimized by normalization about the 1570 (R² = 0.97 vs 0.57 for unnormalized) and 1003 cm⁻¹ (p < 0.0000001 vs p < 0.01 for unnormalized) bands, respectively. The data obtained point to the extreme sensitivity of multivariate analysis to signal intensity normalization. Some general guidelines for making appropriate band choices are given, including the use of peak‐finding routines. Copyright © 2008 John Wiley & Sons, Ltd.     

一种中药荧光指纹图谱的光谱图像构建方法

利用液晶光谱仪通过光谱成像法对黄柏和人参总皂甙进行了荧光光谱图像检测,采用滤波器与像素点定位联用的方法提取有效像素点,获取它们的荧光光谱图像,绘制了相应的中药荧光指纹图谱.结合欧氏距离的判定方法,将滤波器与像素点定位联用法、像素点优选法和背景差分算法所得的荧光指纹图谱进行比较,三种方法的差异由小到大的排序为滤波器与像素点定位联用法,背景差分算法,像素点优选法.说明滤波器与像素点定位联用法所得荧光指纹图谱稳定性最好,谱线最优.实验结果表明该方法可以用于构建中药荧光指纹图谱,从而提出了一种新的用于中药指纹图谱构建中提取有效像素点的可行方法.     

Correspondence between quantum-optical transform and classical-optical transform explored by developing Dirac’s symbolic method

By virtue of the new technique of performing integration over Dirac’s ket–bra operators, we explore quantum optical version of classical optical transformations such as optical Fresnel transform, Hankel transform, fractional Fourier transform, Wigner transform, wavelet transform and Fresnel–Hadmard combinatorial transform etc. In this way one may gain benefit for developing classical optics theory from the research in quantum optics, or vice-versa. We cannot only find some new quantum mechanical unitary operators which correspond to the known optical transformations, deriving a new theorem for calculating quantum tomogram of density operators, but also can reveal some new classical optical transformations. For examples, we find the generalized Fresnel operator (GFO) to correspond to the generalized Fresnel transform (GFT) in classical optics. We derive GFO’s normal product form and its canonical coherent state representation and find that GFO is the loyal representation of symplectic group multiplication rule. We show that GFT is just the transformation matrix element of GFO in the coordinate representation such that two successive GFTs is still a GFT. The ABCD rule of the Gaussian beam propagation is directly demonstrated in the context of quantum optics. Especially, the introduction of quantum mechanical entangled state representations opens up a new area in finding new classical optical transformations. The complex wavelet transform and the condition of mother wavelet are studied in the context of quantum optics too. Throughout our discussions, the coherent state, the entangled state representation of the two-mode squeezing operators and the technique of integration within an ordered product (IWOP) of operators are fully used. All these have confirmed Dirac’s assertion: “...for a quantum dynamic system that has a classical analogue, unitary transformation in the quantum theory is the analogue of contact transformation in the classical theory”.     

Spectral shifts and spectral switches of spatially and spectrally partially coherent pulsed beams in Young’s interference experiment

Taking the Gaussian Schell-model pulsed (GSMP) beam as a typical example of spatially and spectrally partially coherent pulsed beams, an analytical expression for the far-field spectrum of diffracted GSMP beams in Young’s interference experiment is derived, and used to study the spectral shifts and spectral switches of GSMP beams in the far field. Numerical calculation results are given to illustrate the dependence of spectral shifts and spectral switches on the obscuration ratio ε, temporal coherent length T_c, spatial correlation parameter β and diffraction angle α. It is shown that the critical angle α_c of the first- and second-order spectral switches moves away from the z axis with increasing T_c, but α_c of the third-order spectral switch moves towards the z axis with increasing T_c. The spectral transition height Δ decreases and spectral minimum S_min increases as T_c increases. α_c decreases, Δ increases and S_min decreases as β increases. The potential application of spectral switches of spatially and spectrally partially coherent pulsed beams in information encoding and transmission is proposed.     

Chaos synchronization of unified chaotic systems via LMI

This Letter focuses on the master-slave synchronization problem of the unified chaotic systems. Based on Lyapunov stability theory and linear matrix inequality (LMI) formulation, a simple linear feedback control law is obtained to make the state of two identical unified chaotic systems asymptotically synchronized. Simulation results have illustrated the effectiveness of the proposed chaos synchronization solution.     

Bianchi Type V Cosmological Models with Constant Deceleration Parameter in General Relativity

We investigate Bianchi type V cosmological models with bulk viscous fluid source. Exact solutions of the Einstein field equations are presented via a suitable power law assumption for the Hubble parameter. We show that the corresponding solutions retain the well established features of the standard cosmology and in addition, are in accordance with recent type Ia supernovae observations. Some observational parameters for the models have also been discussed.     

Dependence of Nanofluid Viscosity on Particle Size and pH Value

We investigate the viscosity of silicon dioxide nanofluid at different particle sizes and pH values considering nanoparticle aggregation. The experimental and simulation results indicate that nanoparticle size is of crucial importance to the viscosity of the nanofluid due to aggregation. As the nanoparticle size decreases, the viscosity becomes much more dependent on the volume fraction. Moreover, when the nanoparticle diameter is smaller than 2Ohm, the viscosity is closely related to the pH of the nanofluid, and fluctuates with pH values from 5 and 7.