农地产权结构变迁视域下土地增值收益的公平分享

农地产权结构是搭建土地增值收益分配与宪法秩序有效链接的重要桥梁.从农地产权结构变迁的视角看,我国传统土地增值收益的国有化机制实际在很大程度上符合1982年宪法所确立的社会主义地租国有原则及地利共享秩序.然而,由于宪法土地条款一开始就被注入了地利分配具有倾向性的思想基因,长此以往便忽视了农民作为整体分享土地增值收益的"另一半宪法秩序".新型城镇化背景下,国家进行了"同地同权"、赋权于"民"的农村土地管理制度改革,其实质是宪法秩序的延续而非替代,我国土地增值收益分配的主要机制仍是征地补偿制度.要实现我国土地增值收益的公平分享,必须回到社会主义"国家—集体"一元论的完整地利共享秩序中来,并遵循实质平等的要求,通过以"人的城镇化"为目标对区片综合地价进行限定、采取倾向于农村及农业发展的"土地财政"政策、打破城乡户籍二元制实现城乡一体化发展等方案,推动农民全过程参与、共享土地利益.     

The ‘right time’ – negotiating the timing of interviews with vulnerable young people

Participant retention is a key factor in determining the success of longitudinal research. Challenges in re-locating and retaining participants over the long term are major issues for researchers working with young people who face adversity and experience frequent changes in circumstances. This article reports on a study of vulnerable young people and their transition into adulthood. Rather than the more conventional schedule-based approach to locating and re-interviewing young people, a relational process, the ‘right time’ framework, was used to facilitate young people's involvement in the study. Embedded in the ‘right time’ framework is recognition of the diverse and fluctuating circumstances that shape young people's availability for interviews. Several case examples are considered which amplify the way that the ‘right time’ framework allowed the research to navigate around these circumstances. The case examples highlight the value young people attached to being involved in the research, the influence on the ‘right time’ of wider relational tensions for young people and the need to negotiate researcher status as a different sort of adult. The ‘right time’ framework contributed to a high retention rate in the study generating a more representative sample and enhancing the subsequent data analysis by providing valuable insights into the lives of these vulnerable young people.     

A volume based approach to establish B-spline based expressions for density functions and its application to progressive hybrid censoring

We propose an approach to determine the distribution of particular linear combinations of hybrid censored order statistics which is based on the calculation of volumes of polytopes. For this purpose, we establish efficient and compact volume formulas in terms of B-splines. Further, we illustrate our approach for ten different progressive hybrid censoring schemes under an exponential assumption.     

Accurate computation of single and product moments of order statistics under progressive censoring

An accurate procedure is proposed to calculate approximate moments of progressive order statistics in the context of statistical inference for lifetime models. The study analyses the performance of power series expansion to approximate the moments for location and scale distributions with high precision and smaller deviations with respect to the exact values. A comparative analysis between exact and approximate methods is shown using some tables and figures. The different approximations are applied in two situations. First, we consider the problem of computing the large sample variance–covariance matrix of maximum likelihood estimators. We also use the approximations to obtain progressively censored sampling plans for log-normal distributed data. These problems illustrate that the presented procedure is highly useful to compute the moments with precision for numerous censoring patterns and, in many cases, is the only valid method because the exact calculation may not be applicable.     

Progressive censoring with fixed censoring times

In this paper, we revisit the progressive Type-I censoring scheme as it has originally been introduced by Cohen [Progressively censored samples in life testing. Technometrics. 1963;5(3):327–339]. In fact, original progressive Type-I censoring proceeds as progressive Type-II censoring but with fixed censoring times instead of failure time based censoring times. Apparently, a time truncation has been added to this censoring scheme by interpreting the final censoring time as a termination time. Therefore, not much work has been done on Cohens's original progressive censoring scheme with fixed censoring times. Thus, we discuss distributional results for this scheme and establish exact distributional results in likelihood inference for exponentially distributed lifetimes. In particular, we obtain the exact distribution of the maximum likelihood estimator (MLE). Further, the stochastic monotonicity of the MLE is verified in order to construct exact confidence intervals for both the scale parameter and the reliability.     

The evolution of intellectual property strategy in innovation ecosystems: Uncovering complementary and substitute appropriability regimes

In this article, we attempt to extend and nuance the debate on intellectual property (IP) strategy, appropriation, and open innovation in dynamic and systemic innovation contexts. We present the case of four generations of mobile telecommunications systems (covering the period 1980–2015), and describe and analyze the co-evolution of strategic IP management and innovation ecosystems. Throughout this development, technologies and technological relationships were governed with different and shifting degrees of formality. Simultaneously, firms differentiated technology accessibility across actors and technologies to benefit from openness and appropriation of innovation. Our analysis shows that the discussion of competitiveness and appropriability needs to be expanded from the focal appropriability regime and complementary assets to the larger context of the innovation ecosystem and its cooperative and competitive actor relations, with dispersed complementary and substitute assets and technologies. Consequently, the shaping of complementary and substitute appropriability regimes is central when strategizing in dynamic and systemic innovation contexts. This holds important implications for the management of open innovation, innovation ecosystems, platforms, and coopetition.     

Inference and optimal design of multiple constant-stress testing for generalized half-normal distribution under type-II progressive censoring

The generalized half-normal (GHN) distribution and progressive type-II censoring are considered in this article for studying some statistical inferences of constant-stress accelerated life testing. The EM algorithm is considered to calculate the maximum likelihood estimates. Fisher information matrix is formed depending on the missing information law and it is utilized for structuring the asymptomatic confidence intervals. Further, interval estimation is discussed through bootstrap intervals. The Tierney and Kadane method, importance sampling procedure and Metropolis-Hastings algorithm are utilized to compute Bayesian estimates. Furthermore, predictive estimates for censored data and the related prediction intervals are obtained. We consider three optimality criteria to find out the optimal stress level. A real data set is used to illustrate the importance of GHN distribution as an alternative lifetime model for well-known distributions. Finally, a simulation study is provided with discussion.     

Estimating E-bayesian and hierarchical bayesian of scalar parameter of gompertz distribution under type II censoring schemes based on fuzzy data

In this study, the E-Bayesian and hierarchical Bayesian of the scalar parameter of a Gompertz distribution under Type II censoring schemes were estimated based on fuzzy data under the squared error (SE) loss function and the efficiency of the proposed methods was compared with each other and with the Bayesian estimator using Monte Carlo simulation.     

论被遗忘权的本土化移植

随着信息技术的高速发展，公民的个人信息和个人隐私极易遭受滥用和侵害。以达成数据主体对于个人信息的主动自决意愿为内驱动力的被遗忘权，欧美发达国家因符合其政治需求和价值主张而广泛确立。虽然被遗忘权权利本质亦与我国社会发展实际相契合，且国内的立法司法实践也为其培育了移植基础，但被遗忘权在我国的本土化移植仍然面临诸多障碍，如信息技术瓶颈、商业风险增加、现有制度衔接低效等。从厘清被遗忘权基本概念、建立专门信息保护机构、构建商业化个人信息储存及使用机制、明确被遗忘权救济渠道与规则以及升级信息保护技术等方面为切入点，寻求被遗忘权本土化移植的解决思路。     

Kernel Estimation of Rate Function for Recurrent Event Data

Abstract.  Recurrent event data are largely characterized by the rate function but smoothing techniques for estimating the rate function have never been rigorously developed or studied in statistical literature. This paper considers the moment and least squares methods for estimating the rate function from recurrent event data. With an independent censoring assumption on the recurrent event process, we study statistical properties of the proposed estimators and propose bootstrap procedures for the bandwidth selection and for the approximation of confidence intervals in the estimation of the occurrence rate function. It is identified that the moment method without resmoothing via a smaller bandwidth will produce a curve with nicks occurring at the censoring times, whereas there is no such problem with the least squares method. Furthermore, the asymptotic variance of the least squares estimator is shown to be smaller under regularity conditions. However, in the implementation of the bootstrap procedures, the moment method is computationally more efficient than the least squares method because the former approach uses condensed bootstrap data. The performance of the proposed procedures is studied through Monte Carlo simulations and an epidemiological example on intravenous drug users.