基于基金项目的“一带一路”研究格局与态势分析

以国家和有关部委的资助项目库为数据来源,检索2014-2016年“一带一路”的相关基金立项,运用文献计量和空间分析的方法从项目的负责人、科研单位、所属地域、学科、研究内容等多个角度进行解析,旨在揭示 “一带一路”研究的格局与态势.结果表明：（1）“一带一路”相关基金立项数目总体呈逐年上升趋势,增速平缓,国家社科基金主体地位明显.（2）项目所属单位、省份在空间上呈现集中分布趋势,体现了一定的区位优势、空间关联与地理邻近效应.（3）单个负责人的立项数目差异不大,分布较为平均.（4）“一带一路”、丝绸之路经济带、21世纪海上丝绸之路为目前学者主要的研究对象和议题.（5）各类基金高频词汇基本保持同步,五类基金研究的热门领域大体趋于一致,包括经济学、国际问题研究、民族问题研究和交叉学科研究等.最后,从研究数据、时间、空间及学科与合作前景上,对未来的研究趋势做了总结和展望.     

Quantum Probes for the Characterization of Nonlinear Media

Active optical media leading to interaction Hamiltonians of the form H=λ˜(a+a†)ζ represent a crucial resource for quantum optical technology. In this paper, we address the characterization of those nonlinear media using quantum probes, as opposed to semiclassical ones. In particular, we investigate how squeezed probes may improve individual and joint estimation of the nonlinear coupling λ˜ and of the nonlinearity order ζ. Upon using tools from quantum estimation, we show that: (i) the two parameters are compatible, i.e., the may be jointly estimated without additional quantum noise; (ii) the use of squeezed probes improves precision at fixed overall energy of the probe; (iii) for low energy probes, squeezed vacuum represent the most convenient choice, whereas for increasing energy an optimal squeezing fraction may be determined; (iv) using optimized quantum probes, the scaling of the corresponding precision with energy improves, both for individual and joint estimation of the two parameters, compared to semiclassical coherent probes. We conclude that quantum probes represent a resource to enhance precision in the characterization of nonlinear media, and foresee potential applications with current technology.     

日本遗弃化学武器销毁残渣中元素分析及砷形态分析

本文就日本遗弃在华化学武器销毁残渣元素分布进行了分类分析,并对残渣样品的砷形态进行检测。结果表明,黄剂及红剂销毁残渣样品中主要元素均为铁、铜、砷、钛、铅等,其中砷元素占比较大且危害最深。进一步对样品进行分析结果显示,残渣中砷形态主要为Fe-结合态、Ca-结合态、残渣态等。该实验结果为销毁残渣的二次处理提供了必要的技术支撑,在敦促日方改进销毁技术方面具有重要的现实意义。     

软段含羧基的水性聚氨酯物性研究

合成了单官能团小分子物质封端的软硬段皆含羧基的脂环族水性聚氨酯(PU),研究了反离子种类、固含量、外加小分子盐/酸、pH值对水性PU的粘度、粒径、CMC和电导率的影响,同时,比较了不同软段分子量水性PU分散液pH临界值和CMC的差异.实验结果表明,随固含量升高,PU分散液体系粘度增大,当固含量为30wt%时,粘度比固含量20wt%的体系粘度增大约20倍;随小分子盐NaCl的加入,PU分散液电粘滞效应逐渐消失,电导率呈现先减小后增大的趋势,随NaCl的加入/软段分子量提高,PU分散体系的CMC值减小,钙离子对PU粒子扩散双电层的破坏作用更加明显.随pH值的增大,PU分散液体系粒径减小,电导率则升高,随软段分子量提高,pH临界值增大,PU分散体对外加小分子酸存在缓冲作用.     

基于改进无迹卡尔曼滤波器算法的滞回模型参数识别研究

地震产生的周期荷载作用下,钢混桥墩结构表现出滞回行为。为描述滞回行为,研究者提出各类滞回模型,其中BWBN(Bouc-Wen-Baber-Noori)模型可以描述结构滞回行为的强度退化、刚度退化和捏拢效应等典型特征。此外,无迹卡尔曼滤波器UKF(unscented Kalman filter)算法是识别BWBN模型参数的高效方法,但当参数初始值与真实值的偏差过大及缺乏对系统的整体估计时,UKF算法识别过程受到局限。本文改进生成样本点规则,提出改进UKF算法。数值模拟结果表明,在无噪声条件下,改进UKF算法识别得到的参数估计值与准确值的误差平均为1.51%,最大误差为4%;在2%均方根RMS(root mean square)高斯白噪声条件下,误差平均为5.43%,最大误差为18%;在5%RMS高斯白噪声条件下,误差平均为8.9%,最大误差为26%和22%。改进UKF算法识别非线性滞回系统状态估计和BWBN模型参数更加准确和稳定。     

Maximum likelihood estimator for the drift of a Brownian flow

The maximum likelihood estimator for the drift of a Brownian flow on ℝ^d, d ⩾ 2, is found with the assumption that the covariance is known. By approximation of the drift with known functions, the statistical model is reduced to a parametric one that is a curved exponential family. The data is the n‐point motion of the Brownian flow throughout the time interval [0, T]. The asymptotic properties of the MLE are also investigated. Copyright © 2000 John Wiley & Sons, Ltd.     

A New Generator of Probability Models: The Exponentiated Sine-G Family for Lifetime Studies

In this article, we propose the exponentiated sine-generated family of distributions. Some important properties are demonstrated, such as the series representation of the probability density function, quantile function, moments, stress-strength reliability, and Rényi entropy. A particular member, called the exponentiated sine Weibull distribution, is highlighted; we analyze its skewness and kurtosis, moments, quantile function, residual mean and reversed mean residual life functions, order statistics, and extreme value distributions. Maximum likelihood estimation and Bayes estimation under the square error loss function are considered. Simulation studies are used to assess the techniques, and their performance gives satisfactory results as discussed by the mean square error, confidence intervals, and coverage probabilities of the estimates. The stress-strength reliability parameter of the exponentiated sine Weibull model is derived and estimated by the maximum likelihood estimation method. Also, nonparametric bootstrap techniques are used to approximate the confidence interval of the reliability parameter. A simulation is conducted to examine the mean square error, standard deviations, confidence intervals, and coverage probabilities of the reliability parameter. Finally, three real applications of the exponentiated sine Weibull model are provided. One of them considers stress-strength data.     

Sampling the Variational Posterior with Local Refinement

Variational inference is an optimization-based method for approximating the posterior distribution of the parameters in Bayesian probabilistic models. A key challenge of variational inference is to approximate the posterior with a distribution that is computationally tractable yet sufficiently expressive. We propose a novel method for generating samples from a highly flexible variational approximation. The method starts with a coarse initial approximation and generates samples by refining it in selected, local regions. This allows the samples to capture dependencies and multi-modality in the posterior, even when these are absent from the initial approximation. We demonstrate theoretically that our method always improves the quality of the approximation (as measured by the evidence lower bound). In experiments, our method consistently outperforms recent variational inference methods in terms of log-likelihood and ELBO across three example tasks: the Eight-Schools example (an inference task in a hierarchical model), training a ResNet-20 (Bayesian inference in a large neural network), and the Mushroom task (posterior sampling in a contextual bandit problem).     

Semiparametric smoothing splines

In regression analysis, when no previous information about the statistical model is available, non-parametric estimation methods are very useful since their requirements on the specification of the model are very few. However, if this information exists, these methods usually neglect to incorporate it. In this paper, we propose a non-parametric regression technique that accounts for information about the underlying statistical model when this information is introduced through a known function. We also provide some theoretical properties and examples of this estimator. © 1998 John Wiley & Sons, Ltd.     

Classical and Bayesian Inference of an Exponentiated Half-Logistic Distribution under Adaptive Type II Progressive Censoring

The point and interval estimations for the unknown parameters of an exponentiated half-logistic distribution based on adaptive type II progressive censoring are obtained in this article. At the beginning, the maximum likelihood estimators are derived. Afterward, the observed and expected Fisher’s information matrix are obtained to construct the asymptotic confidence intervals. Meanwhile, the percentile bootstrap method and the bootstrap-t method are put forward for the establishment of confidence intervals. With respect to Bayesian estimation, the Lindley method is used under three different loss functions. The importance sampling method is also applied to calculate Bayesian estimates and construct corresponding highest posterior density (HPD) credible intervals. Finally, numerous simulation studies are conducted on the basis of Markov Chain Monte Carlo (MCMC) samples to contrast the performance of the estimations, and an authentic data set is analyzed for exemplifying intention.