中国P2P小额信贷企业的法律规制

基于当前中国P2P小额信贷行业的发育状况和制度需求,未来P2P小额信贷行业立法应以鼓励、扶持、保护、促进为基本目的,逐步放松管制。针对其主要经营主体P2P小额信贷企业,应在对其法律性质进行准确定位的基础上,在最低注册资本、主要从业人员任职资格、网络经营许可等方面加强准入规制;其广告宣传应当真实适度,要有必要的用户信用评级,合同签订和履行时应充分考虑到借贷双方的利益;在资金管理方面,要严控贷款用途和借贷利率,资金要有第三方托管;应加强对用户个人信息的保护,不得侵犯或泄露用户的个人隐私。     

“美”与“丑”的对称与不对称及其解释

"美"与"丑"是一对相对词,前者具有正面意义,后者具有负面意义。它们在词汇、短语和句法层面,既能体现出对称性,又能体现出不对称性。其中的原因就在于客观世界的复杂性,主观世界的能动性,以及语言本身的制约性。     

A Note on Sufficient Conditions for Valid Unmodified t Testing in Correlation Analysis with Autocorrelated and Heteroscedastic Sample Data

Traditionally, sphericity (i.e., independence and homoscedasticity for raw data) is put forward as the condition to be satisfied by the variance–covariance matrix of at least one of the two observation vectors analyzed for correlation, for the unmodified t test of significance to be valid under the Gaussian and constant population mean assumptions. In this article, the author proves that the sphericity condition is too strong and a weaker (i.e., more general) sufficient condition for valid unmodified t testing in correlation analysis is circularity (i.e., independence and homoscedasticity after linear transformation by orthonormal contrasts), to be satisfied by the variance–covariance matrix of one of the two observation vectors. Two other conditions (i.e., compound symmetry for one of the two observation vectors; absence of correlation between the components of one observation vector, combined with a particular pattern of joint heteroscedasticity in the two observation vectors) are also considered and discussed. When both observation vectors possess the same variance–covariance matrix up to a positive multiplicative constant, the circularity condition is shown to be necessary and sufficient. “Observation vectors” may designate partial realizations of temporal or spatial stochastic processes as well as profile vectors of repeated measures. From the proof, it follows that an effective sample size appropriately defined can measure the discrepancy from the more general sufficient condition for valid unmodified t testing in correlation analysis with autocorrelated and heteroscedastic sample data. The proof is complemented by a simulation study. Finally, the differences between the role of the circularity condition in the correlation analysis and its role in the repeated measures ANOVA (i.e., where it was first introduced) are scrutinized, and the link between the circular variance–covariance structure and the centering of observations with respect to the sample mean is emphasized.     

Estimating and Testing a Structured Covariance Matrix for Three-Level Multivariate Data

This article considers an approach to estimating and testing a new Kronecker product covariance structure for three-level (multiple time points (p), multiple sites (u), and multiple response variables (q)) multivariate data. Testing of such covariance structure is potentially important for high dimensional multi-level multivariate data. The hypothesis testing procedure developed in this article can not only test the hypothesis for three-level multivariate data, but also can test many different hypotheses, such as blocked compound symmetry, for two-level multivariate data as special cases. The tests are implemented with two real data sets.     

对称性咪唑类离子液体结构与熔点关系的探讨

本文研究了对称性的离子液体结构和熔点之间的关系,结构参数包括：阴离子的大小、阳离子取代基碳链的长度和取代基的性质．运用量子化学从头算方法优化了离子液体的结构．根据优化结果,深入探讨了结构参数影响熔点变化的根本规律．     

广义Kdv-Burgers方程新情形下的古典对称分类

本文对广义Kdv-Burgers方程把方程系数看作自变量的古典对称进行了讨论。借助吴-微分特征列算法程序包,我们给出了该方程8种不同类型的古典对称分类.该结论说明了在我们讨论的情况下能够扩充方程的古典对称.     

从翻译角度论语言间的对称性

翻译归根结底是两种语言间信息文化内涵的转换,是一种异语语际交换过程。一般说来,用任何语言表达的信息都可以译成另一种语言,这是由人类的共性和语言的共性(universals)决定的,这也是语言间对称性这一构想的基础。本文从语言学和跨文化角度对翻译进行了科学的分析与探讨,提出语言间的不同的对称性(symmetry)及其相应的翻译策略,从科学的角度论述了无论异语间的言语行为形式多么千差万别,语言间对称性这一本质规律总像一只“看不见的手”蕴含其中。在翻译的过程中,只有将这一科学规律与在一定区间浮动的最宽泛的模糊现象相结合,才能达到科学与艺术的完美统一。     

Strategy-proof and Symmetric Social Choice Functions for Public Good Economies

We study economies with one private good and one pure public good, and consider the following axioms of social choice functions. Strategy-proofness says that no agent can benefit by misrepresenting his preferences, regardless of whether the other agents misrepresent or not, and whatever his preferences are. Symmetry says that if two agents have the same preference, they must be treated equally. Anonymity says that when the preferences of two agents are switched, their consumption bundles are also switched. Individual rationality says that a social choice function never assigns an allocation which makes some agent worse off than he would be by consuming no public good and paying nothing. In Theorem 1, we characterize the class of strategy-proof, budget-balancing, and symmetric social choice functions, assuming convexity of the cost function of the public good. In Theorem 2, we characterize the class of strategy-proof, budget-balancing, and anonymous social choice functions. In Theorem 3, we characterize the class of strategy-proof, budget-balancing, symmetric, and individually rational social choice functions.     

Tests for symmetry with right censoring

Permutation tests for symmetry are suggested using data that are subject to right censoring. Such tests are directly relevant to the assumptions that underlie the generalized Wilcoxon test since the symmetric logistic distribution for log-errors has been used to motivate Wilcoxon scores in the censored accelerated failure time model. Its principal competitor is the log-rank (LGR) test motivated by an extreme value error distribution that is positively skewed. The proposed one-sided tests for symmetry against the alternative of positive skewness are directly relevant to the choice between usage of these two tests.

The permutation tests use statistics from the weighted LGR class normally used for making two-sample comparisons. From this class, the test using LGR weights (all weights equal) showed the greatest discriminatory power in simulations that compared the possibility of logistic errors versus extreme value errors.

In the test construction, a median estimate, determined by inverting the Kaplan–Meier estimator, is used to divide the data into a “control” group to its left that is compared with a “treatment” group to its right. As an unavoidable consequence of testing symmetry, data in the control group that have been censored become uninformative in performing this two-sample test. Thus, early heavy censoring of data can reduce the effective sample size of the control group and result in diminished power for discriminating symmetry in the population distribution.     

A nonparametric test of symmetry based on the overlapping coefficient

In this paper, we introduce a new nonparametric test of symmetry based on the empirical overlap coefficient using kernel density estimation. Our investigation reveals that the new test is more powerful than the runs test of symmetry proposed by McWilliams [31]. Intensive simulation is conducted to examine the power of the proposed test. Data from a level I Trauma center are used to illustrate the procedures developed in this paper.