新常态下供销社经营模式的转型与创新研究

随着我国新型四化的深入推进,农村经济建设迈入了新阶段。在新常态下,供销社的迫切任务是加快转型升级,切实提高为农服务能力。因而这就要求我们既要把握好传统业务,又要善用改革和创新的思维开拓新型业务,用业务经营发展促使供销社转型升级。面对我国经济发展新常态,供销社过去长期积累起来的服务“三农”的宝贵经验遇到了很大的挑战,在经营过程中所暴露出的经营方式、手段等方面都存在着很多弊端,进而阻碍了供销社的生存与发展。供销社要想走为农服务的道路,转型与创新势在必行。基于经济发展新常态,分析供销社在发展中存在的突出问题;研究供销社进行转型与创新的必要性;最后归纳总结供销社经营模式的创新途径。     

西方文论研究与翻译视野

近期,国内的西方文论研究开始出现反思趋势,西方文论本身也成为反思对象之一。反思过程中出现了对西方文论的一些误读,原因之一在于部分研究者可能忽略了自身研究奠基于译文之上的事实,将译文直接等同于原文,因而也可以说是翻译视野的缺失。在西方文论研究中引入翻译视野,即意味着基于译本进行的文论研究须与译本拉开一定的距离。翻译视野又包括转换意识、语境意识、差异意识三重内涵。转换意识即意识到译文是语言转换的结果,同时意识到由转换所导致的信息不对称性;语境意识是指意识到西方文论扎根的特定时空的文化形态及理论家的认知形态;差异意识是指对原作与译作所处时空差异的意识。翻译视野促使我们主动去了解西方文论在原语语境中的起源及发展,辩证地探讨其在译语语境中的适用性,有助于我们在西方文论译介热持续上升的今天,真正深入地理解与反思西方文论的内涵,更好地吸取其精华,批判其糟粕,推动中国文学与文化研究的发展,建构中国自己的理论体系。     

新贫困视域下乡村转型的困厄与重构路径

中国社会转型的重要背景之一是全球消费社会的到来。 这使得新穷人现象日渐凸显,并成为影响甚至主导整个社会转型的核心线索。 作为新穷人的典型表现,乡村新贫困既包括在城乡二元结构下,村民难以获得以城市生活方式为参照的社会公认生活水准而引发的结构性贫困,也包括由消费欲望激发的社会心理性贫困。 由此,乡村消费转型表现为如下困境:私人消费中,个体消费认同在地和脱嵌的困境以及家庭消费规范物质化和人伦的两难;集体消费中,消费品“上移冶和“下乡冶的悖论。 为应对这些困境,必须从消费角度,破解“新穷困冶的结构性和文化困境,实行新型城镇化和新农村建设并举。     

Higher-order Bayesian Approximations for Pseudo-posterior Distributions

The theory of higher-order asymptotics provides accurate approximations to posterior distributions for a scalar parameter of interest, and to the corresponding tail area, for practical use in Bayesian analysis. The aim of this article is to extend these approximations to pseudo-posterior distributions, e.g., posterior distributions based on a pseudo-likelihood function and a suitable prior, which are proved to be particularly useful when the full likelihood is analytically or computationally infeasible. In particular, from a theoretical point of view, we derive the Laplace approximation for a pseudo-posterior distribution, and for the corresponding tail area, for a scalar parameter of interest, also in the presence of nuisance parameters. From a computational point of view, starting from these higher-order approximations, we discuss the higher-order tail area (HOTA) algorithm useful to approximate marginal posterior distributions, and related quantities. Compared to standard Markov chain Monte Carlo methods, the main advantage of the HOTA algorithm is that it gives independent samples at a negligible computational cost. The relevant computations are illustrated by two examples.     

Local composite quantile regression estimation of time-varying parameter vector for multidimensional time-inhomogeneous diffusion models

This paper is dedicated to the study of the composite quantile regression (CQR) estimations of time-varying parameter vectors for multidimensional diffusion models. Based on the local linear fitting for parameter vectors, we propose the local linear CQR estimations of the drift parameter vectors, and verify their asymptotic biases, asymptotic variances and asymptotic normality. Moreover, we discuss the asymptotic relative efficiency (ARE) of the local linear CQR estimations with respect to the local linear least-squares estimations. We obtain that the local estimations that we proposed are much more efficient than the local linear least-squares estimations. Simulation studies are constructed to show the performance of the estimations proposed.     

Multilevel maximum likelihood estimation with application to covariance matrices

The asymptotic variance of the maximum likelihood estimate is proved to decrease when the maximization is restricted to a subspace that contains the true parameter value. Maximum likelihood estimation allows a systematic fitting of covariance models to the sample, which is important in data assimilation. The hierarchical maximum likelihood approach is applied to the spectral diagonal covariance model with different parameterizations of eigenvalue decay, and to the sparse inverse covariance model with specified parameter values on different sets of nonzero entries. It is shown computationally that using smaller sets of parameters can decrease the sampling noise in high dimension substantially.     

Trend smoothness achieved by penalized least squares with the smoothing parameter chosen by optimality criteria

This work presents a study about the smoothness attained by the methods more frequently used to choose the smoothing parameter in the context of splines: Cross Validation, Generalized Cross Validation, and corrected Akaike and Bayesian Information Criteria, implemented with Penalized Least Squares. It is concluded that the amount of smoothness strongly depends on the length of the series and on the type of underlying trend, while the presence of seasonality even though statistically significant is less relevant. The intrinsic variability of the series is not statistically significant and its effect is taken into account only through the smoothing parameter.     

Confession Governance and Verdicts in China’s Criminal Justice

The objective phenomenon of reliance on confessions is the source of many problems in the practice of criminal justice in China. Although successive amendments to the law have endeavored to improve the handling of confessions, they have been unable to resolve the dilemma of a rigid management mode, incompatible management strategies, and conflicting attitudes towards management. This paper has made a multi-dimensional reinterpretation of it from the judges’ perspective, including functional analysis, cultural interpretation and immediate considerations. It reveals that behind its functions of offering moral comfort or allowing evasion of responsibility, confession, as a medium of physical and intellectual management, has the more important function of supplementing and improving the legitimacy of criminal verdicts. The remolding of the legitimacy of criminal verdicts with the coordinated improvement of the management of confessions will change the mode of association between those who currently govern confession and those they govern and will clash with the current closed mode of criminal justice management, thereby promoting a transformation in the governance of criminal justice.     

Into the IRIS: a model for analyzing identity dynamics in conflict

I propose a lens model for understanding how core identities (ethnic, sectarian, racial or national) are affected by past interactions and narratives increasing the chances of the outbreak of violent conflict. The model can be used to show how core identities are polarized during conflict escalation and how they might de-polarize during periods of de-escalation and conflict resolution, leading to potential transformation of core identities in post-conflict situations. Northern Ireland will be used to illustrate the Integrated Relational Identity Structure model, showing how conflicting identities have changed, or not, as a result of history, the conflict and the peace process.     

Optimal determination of the parameters of some biased estimators using genetic algorithm

In this paper, some new algorithms for estimating the biasing parameters of the ridge, Liu and two-parameter estimators are introduced with the help of genetic algorithm (GA). The proposed algorithms are based on minimizing some statistical measures such as mean square error (MSE), mean absolute error (MAE) and mean absolute prediction error (MAPE). At the same time, the new algorithms allow one to keep the condition number and variance inflation factors to be less than or equal to ten by means of the GA. A numerical example is presented to show the utility of the new algorithms. In addition, an extensive Monte Carlo experiment is conducted. The numerical findings prove that the proposed algorithms enable to eliminate the problem of multicollinearity and minimize the MSE, MAE and MAPE.