Sequence-dependent clustering properties of nucleotides fragments in an ionic solution

The chemical nature of the DNA bases is an important factor in sequence-mediated association of DNA molecules. Nucleotides are the fundamental DNA elements and the base identity impacts the molecular properties of nucleotide fragments. It is interesting to study the fundamental nature of nucleotides in DNA, on the basis of base-specific interactions, association, and modes of standard atomic or molecular interactions. With all-atom molecular dynamics simulations of model dinucleotide and tetranucleotide systems having single-stranded dinucleotide or tetranucleotide fragments of varying sequences, we show how the base identity and interactions between the different bases as well as water may affect the clustering properties of nucleotides fragments in an ionic solution. Sequence-dependent differential interactions between the nucleotide fragments, ionic concentration, and elevated temperature are found to influence the clustering properties and dynamics of association. Well-known epigenetic modification of DNA, that is, cytosine methylation also promotes dinucleotide clustering in solution. These observations point to one possible chemical nature of the DNA bases, as well as the importance of the base pairing, base stacking, and ionic interactions in DNA structure formation, and DNA sequence-mediated association. Sequence- and the ionic environment-mediated self-association properties of the dinucleotides indicate its great potential to develop biological nanomaterials for desired applications.     

Review on the thickness measurement of ultrathin oxide films by mutual calibration method

Mutual calibration was suggested as a method to determine the absolute thickness of ultrathin oxide films. It was motivated from the large offset values in the reported thicknesses in the Consultative Committee for Amount of Substance (CCQM) pilot study P-38 for the thickness measurement of SiO₂ films on Si(100) and Si(111) substrates in 2004. Large offset values from 0.5 to 1.0 nm were reported in the thicknesses by ellipsometry, X-ray reflectometry (XRR), medium-energy ion scattering spectrometry (MEIS), Rutherford backscattering spectroscopy (RBS), nuclear reaction analysis (NRA), and transmission electron microscopy (TEM). However, the offset value for the thicknesses by X-ray photoelectron spectroscopy (XPS) was close to zero (−0.013 nm). From these results, the mutual calibration method was reported for the thickness measurement of SiO₂ films on Si(100) by combination of TEM and XPS. The mutual calibration method has been applied for the thickness measurements of hetero oxide films such as Al₂O₃ and HfO₂. Recently, the effect of surface contamination was reported to be critical to the thickness measurement of HfO₂ films by XPS. On the other hand, MEIS was proved to be a powerful zero offset method which is not affected by the surface contamination. As a result, the reference thicknesses in the CCQM pilot study P-190 for the thickness measurement of HfO₂ films on Si(100) substrate were determined by mutual calibration method from the average XRR data and MEIS analysis. Conclusively, the thicknesses of ultrathin oxide films can be traceably certified by mutual calibration method and most thickness measurement methods can be calibrated from the certified thicknesses.     

The mutual variational principle of free wave propagation in periodic structures

By taking infinite periodic beams as examples, the mutual variational principle for analyzing the free wave propagation in periodic structures is established and demonstrated through the use of the propagation constant in the present paper, and the corresponding hierarchical finite element formulation is then derived. Thus, it provides the numerical analysis of that problem with a firm theoretical basis of variational principles, with which one may conveniently illustrate the mathematical and physical mechanisms of the wave propagation in periodic structures and the relationship with the natural vibration. The solution is discussed and examples are given. Supported by Doctorate Training Fund of National Education Commission of China     

Determining Causal Skeletons with Information Theory

Modeling a causal association as arising from a communication process between cause and effect, simplifies the discovery of causal skeletons. The communication channels enabling these communication processes, are fully characterized by stochastic tensors, and therefore allow us to use linear algebra. This tensor-based approach reduces the dimensionality of the data needed to test for conditional independence, e.g., for systems comprising three variables, pair-wise determined tensors suffice to infer the causal skeleton. The only thing needed is a minor extension to information theory, namely the concept of path information.     

Information-Theoretic Generalization Bounds for Meta-Learning and Applications

Meta-learning, or “learning to learn”, refers to techniques that infer an inductive bias from data corresponding to multiple related tasks with the goal of improving the sample efficiency for new, previously unobserved, tasks. A key performance measure for meta-learning is the meta-generalization gap, that is, the difference between the average loss measured on the meta-training data and on a new, randomly selected task. This paper presents novel information-theoretic upper bounds on the meta-generalization gap. Two broad classes of meta-learning algorithms are considered that use either separate within-task training and test sets, like model agnostic meta-learning (MAML), or joint within-task training and test sets, like reptile. Extending the existing work for conventional learning, an upper bound on the meta-generalization gap is derived for the former class that depends on the mutual information (MI) between the output of the meta-learning algorithm and its input meta-training data. For the latter, the derived bound includes an additional MI between the output of the per-task learning procedure and corresponding data set to capture within-task uncertainty. Tighter bounds are then developed for the two classes via novel individual task MI (ITMI) bounds. Applications of the derived bounds are finally discussed, including a broad class of noisy iterative algorithms for meta-learning.     

R32/PAG润滑油体系的黏度和质扩散系数实验研究

本文采用光散射法对R32/PAG润滑油混合体系的动力黏度和质扩散系数进行了实验研究,温度范围从293.15~353.15 K,压力范围从0.09~1.26 MPa,共计获得16个数据点。R32/PAG体系的表面波散射特性属于过阻尼区,当温度一定时,R32/PAG混合物的黏度随着R32所占比例的升高而减小。本文黏度、质扩散系数实验数据与所获得模型的平均绝对偏差分别为1.17%、0.15%,可用于R32/PAG制冷系统的优化设计。     

Mutual Diffusion Driven NMR: a new approach for the analysis of mixtures by spatially resolved NMR spectroscopy

We introduce a new approach for resolving the NMR spectra of mixtures that relies on the mutual diffusion of dissolved species when a concentration gradient is established within the NMR tube. This is achieved by cooling down a biphasic mixture of triethylamine and deuterated water below its mixing temperature, where a single phase is expected. Until equilibrium is reached, a gradient of concentration, from ‘pure’ triethylamine to ‘pure’ water, establishes within the tube. The amount of time required to reach this equilibrium is controlled by the mutual diffusion coefficient of both species. Moreover, a gradient of concentration exists for each additional compound dissolved in this system, related to the partition coefficient for that compound in the original biphasic state. Using slice selective experiments, it was possible to measure these concentration gradients and use them to separate signals from all the present species. We show the results acquired for a mixture composed of n‐octanol, methanol, acetonitrile and benzene and compare them with those obtained by pulse field gradient NMR. Copyright © 2016 John Wiley & Sons, Ltd.     

Statistical inference and modelling of momentum in stock prices

The following results are obtained, (i) It is possible to obtain a time series of market data {y(t)} in which the fluctuations in fundamental value have been compensated for. An objective test of the efficient market hypothesis (EMH), which would predict random correlations about a constant value, is thereby possible, (ii) A time series procedure can be used to determine the extent to which the differences in the data and the moving averages are significant. This provides a model of the form y(t)-y(t-l)=0.5{y(t- l)-y(t-2)}+ε(t)+0.8ε(r-1) where ε(t) is the error at time t, and the coefficients 0.5 and 0.8 are determined from the data. One concludes that today's price is not a random perturbation from yesterday's; rather, yesterday's rate of change is a significant predictor of today's rate of change. This confirms the concept of momentum that is crucial to market participants. (iii) The model provides out-of-sample predictions that can be tested statistically. (iv) The model and coefficients obtained in this way can be used to make predictions on laboratory experiments to establish an objective and quantitative link between the experiments and the market data. These methods circumvent the central difficulty in testing market data, namely, that changes in fundamentals obscure intrinsic trends and autocorrelations. This procedure is implemented by considering the ratio of two similar funds (Germany and Future Germany) with the same manager and performing a set of statistical tests that have excluded fluctuations in fundamental factors. For the entire data of the first 1149 days beginning with the introduction of the latter fund, a standard runs test indicates that the data is 29 standard deviations away from that which would be expected under a hypothesis of random fluctuations about the fundamental value. This and other tests provide strong evidence against the efficient market hypothesis and in favour of autocorrelations in the data. An ARIMA time series finds strong evidence (9.6 and 21.6 standard deviations in the two coefficients) that the data is described by a model that involves the first difference, indicating that momentum is the significant factor. The first quarter's data is used to make out-of-sample predictions for the second quarter with results that are significant to 3 standard deviations. Finally, the ARIMA model and coefficients are used to make predictions on laboratory experiments of Porter and Smith in which the intrinsic value is clear. The model's forecasts are decidedly more accurate than that of the null hypothesis of random fluctuations about the fundamental value.     

互注入垂直腔表面发射激光器的多次偏振转换特性研究

基于垂直腔表面发射激光器(VCSELs)的自旋反转模型, 研究了互注入VCSELs系统中参数连续变化所引起的多次偏振转换(PS)特性. 研究结果表明: 连续改变互注入强度ξ、两个互注入VCSELs中一个激光器的激射频率以及同时连续改变两个激光器的激射频率, 均可产生多次的PS. 详细分析了上述三种参数连续变化所引起的多次PS的特性, 并讨论了耦合延时时间对多次PS特性的影响.     

Asymptotic Information-Theoretic Detection of Dynamical Organization in Complex Systems

The identification of emergent structures in complex dynamical systems is a formidable challenge. We propose a computationally efficient methodology to address such a challenge, based on modeling the state of the system as a set of random variables. Specifically, we present a sieving algorithm to navigate the huge space of all subsets of variables and compare them in terms of a simple index that can be computed without resorting to simulations. We obtain such a simple index by studying the asymptotic distribution of an information-theoretic measure of coordination among variables, when there is no coordination at all, which allows us to fairly compare subsets of variables having different cardinalities. We show that increasing the number of observations allows the identification of larger and larger subsets. As an example of relevant application, we make use of a paradigmatic case regarding the identification of groups in autocatalytic sets of reactions, a chemical situation related to the origin of life problem.