有机硼交联HPG压裂液超低温破胶剂室内研究

对埋藏浅,油层温度低的油藏进行压裂改造,需解决压裂液低温破胶水化的问题。采用活化剂来提高过硫酸铵(APS),酶,胶囊破胶剂的低温破胶能力。通过对有机硼交联的羟丙基瓜胶(HPG)压裂液低温下破胶后粘度损失率的测定,筛选出用于50℃下的APS/活化剂破胶系统及胶囊破胶剂。结果表明:在APS/活化剂破胶系统的作用下,采用有机硼作交联剂的HPG压裂液在较低温度条件下能彻底破胶水化。     

Mixed-effects Models with Skewed Distributions for Time-varying Decay Rate in HIV Dynamics

After initiation of treatment, HIV viral load has multiphasic changes, which indicates that the viral decay rate is a time-varying process. Mixed-effects models with different time-varying decay rate functions have been proposed in literature. However, there are two unresolved critical issues: (i) it is not clear which model is more appropriate for practical use, and (ii) the model random errors are commonly assumed to follow a normal distribution, which may be unrealistic and can obscure important features of within- and among-subject variations. Because asymmetry of HIV viral load data is still noticeable even after transformation, it is important to use a more general distribution family that enables the unrealistic normal assumption to be relaxed. We developed skew-elliptical (SE) Bayesian mixed-effects models by considering the model random errors to have an SE distribution. We compared the performance among five SE models that have different time-varying decay rate functions. For each model, we also contrasted the performance under different model random error assumptions such as normal, Student-t, skew-normal, or skew-t distribution. Two AIDS clinical trial datasets were used to illustrate the proposed models and methods. The results indicate that the model with a time-varying viral decay rate that has two exponential components is preferred. Among the four distribution assumptions, the skew-t and skew-normal models provided better fitting to the data than normal or Student-t model, suggesting that it is important to assume a model with a skewed distribution in order to achieve reasonable results when the data exhibit skewness.     

Power analysis for clustered non-continuous responses in multicenter trials

Power analysis for multi-center randomized control trials is quite difficult to perform for non-continuous responses when site differences are modeled by random effects using the generalized linear mixed-effects model (GLMM). First, it is not possible to construct power functions analytically, because of the extreme complexity of the sampling distribution of parameter estimates. Second, Monte Carlo (MC) simulation, a popular option for estimating power for complex models, does not work within the current context because of a lack of methods and software packages that would provide reliable estimates for fitting such GLMMs. For example, even statistical packages from software giants like SAS do not provide reliable estimates at the time of writing. Another major limitation of MC simulation is the lengthy running time, especially for complex models such as GLMM, especially when estimating power for multiple scenarios of interest. We present a new approach to address such limitations. The proposed approach defines a marginal model to approximate the GLMM and estimates power without relying on MC simulation. The approach is illustrated with both real and simulated data, with the simulation study demonstrating good performance of the method.     

Stochastic comparisons on sample extremes of dependent and heterogenous observations

Stochastic comparison on order statistics from heterogeneous-dependent observations has been paid lots of attention recently. This paper devotes to investigating the ordering properties of order statistics from dependent observations. We derive the usual stochastic order for sample minimums and the second smallest order statistic, the dispersive order and the star order for minimums of samples having proportional hazards and Archimedean survival copulas. Similar ordering results are also obtained for maximums and the second largest order statistic of samples having proportional reversed hazards and Archimedean copulas. Several examples illustrating the main results are presented as well.     

A Proportional Hazards Regression Model for the Subdistribution with Covariates‐adjusted Censoring Weight for Competing Risks Data

With competing risks data, one often needs to assess the treatment and covariate effects on the cumulative incidence function. Fine and Gray proposed a proportional hazards regression model for the subdistribution of a competing risk with the assumption that the censoring distribution and the covariates are independent. Covariate‐dependent censoring sometimes occurs in medical studies. In this paper, we study the proportional hazards regression model for the subdistribution of a competing risk with proper adjustments for covariate‐dependent censoring. We consider a covariate‐adjusted weight function by fitting the Cox model for the censoring distribution and using the predictive probability for each individual. Our simulation study shows that the covariate‐adjusted weight estimator is basically unbiased when the censoring time depends on the covariates, and the covariate‐adjusted weight approach works well for the variance estimator as well. We illustrate our methods with bone marrow transplant data from the Center for International Blood and Marrow Transplant Research. Here, cancer relapse and death in complete remission are two competing risks.     

Functional Partial Linear Single‐index Model

This paper deals with the problem of predicting the real‐valued response variable using explanatory variables containing both multivariate random variable and random curve. The proposed functional partial linear single‐index model treats the multivariate random variable as linear part and the random curve as functional single‐index part, respectively. To estimate the non‐parametric link function, the functional single‐index and the parameters in the linear part, a two‐stage estimation procedure is proposed. Compared with existing semi‐parametric methods, the proposed approach requires no initial estimation and iteration. Asymptotical properties are established for both the parameters in the linear part and the functional single‐index. The convergence rate for the non‐parametric link function is also given. In addition, asymptotical normality of the error variance is obtained that facilitates the construction of confidence region and hypothesis testing for the unknown parameter. Numerical experiments including simulation studies and a real‐data analysis are conducted to evaluate the empirical performance of the proposed method.     

概念、社会与规范性——黑格尔的规范性理论之争

罗尔斯等人对康德的道德哲学做出了建构论的解读,从此将建构论带入到规范性研究中。因为不满康德哲学自身的理论困境,以布兰顿、皮平为代表的社会建构论开始了对黑格尔的规范性研究,将之视为对康德哲学的社会化,把以相互承认为基础的社会视为规范的来源,这一解读方式被称之为“标准解读”。在社会建构论的影响下,斯特恩、莱蒂宁等人分别提出了对黑格尔哲学的规范性解读。一时间,对黑格尔规范性的研究产生了众多丰富的理论成果。考察这一时段理论得失,有助于我们推动黑格尔的规范性研究。     

提高效率、维护公平:产权四模式对深化我国集体林权改革的启示

回顾我国集体林权改革的主要进展,介绍产权四模式的主要观点,提出深化集体林权改革的思考和建议。研究发现,林权改革没有统一的格式,产权四模式总结了发展中国家林权改革的一些规律,可以为我国集体林改所借鉴;与其他模式相比,财产权模式对我国集体林改影响最大,明晰产权、提高效率一直是集体林改的目标;农业结构模式明确提出的市场机制可能带来产权不安全的问题需要引起重视;制度模式主张政府发挥产权改革的主导作用、制定法律法规巩固产权的主张对深化林权改革有重要借鉴意义;共有产权模式提出的保留共有森林资源为贫困人口提供"一席之地"的主张,为减贫和乡村振兴提供思路。在结束明晰产权主体改革任务之后,应将工作重点转向制定相关法律法规巩固产权改革成果、维护农户林权利益;在推动林地规模化经营中,要谨慎推进森林资源金融化,防止出现"代价高昂的不平等";充分认识集体林权改革的复杂性、艰巨性和长期性,将林改工作从工程式运作逐渐转向常规监管,加强林权管理。     

进口"油片"对我国取向硅钢市场的影响

介绍了变压器行业的生产形势、国内取向硅钢的生产及消费状况,重点研究了废旧变压器"油片"市场的经营及加工制作铁芯的情况,对国内取向硅钢提出了建议.     

后现代语境下我国马克思主义社会学批评境遇的思考

马克思主义的社会学批评在上个世纪中国的文学舞台上经历了两次的浮沉,但是社会学批评的这两次式微却存在着本质的不同。本文通过分析后现代语境对马克思主义"社会学批评"在创作主体、批评主体、真理、理性、"宏大的历史叙事"、文学经典、唯物史观、读者身份等方面的颠覆和消解,试图凸现马克思主义"社会学批评"在第二次式微过程中面临的理论挑战,提出重新定位和理论发展的问题。