中国“碳中和”目标的实现路径与模式选择

围绕中国碳中和目标的实现路径与模式选择问题，提出了一个中国应对气候变化整体治理模式，即多阶段混合主导型碳中和实现模式。这一模式是以国家为核心，在一定时期和内外环境约束下，通过减排和增汇路径，对中国境内由人类活动造成的CO2排放与人为CO2吸收量之间关系进行调整和平衡的过程；其内部由宏观、中观和微观三层结构组成，每层结构各不相同。多阶段混合主导型碳中和实现模式的提出，拓展和完善了气候变化整体治理理论，为气候变化治理提供了机制借鉴。     

基于技术多样性的专利申请人与审查员的引证行为差异

近年来，专利引文越来越多地被用于技术路径研究、技术会聚、技术扩散等技术领域间的知识活动研究，但并未有效区分申请人引用和审查员引用，现有技术领域层面对申请人和审查员引用差异的对比研究还停留在较为浅显的统计层面。将技术类别间的差异性引入到申请人引用和审查员引用的对比研究中，在技术类别分布基础上，探究专利技术类别多样性视角下申请人引用和审查员引用的知识来源差异，并对其开展相关性分析。研究结果表明:专利申请人引用涉及的技术类别范围更广，而审查员引用则更集中于本技术类别；对大部分技术类别，申请人引用的技术类别多样性要高于审查员引用，但两者呈现出显著的正相关性。     

基层党组织有限介入：农村社区“两委”候选人的当选逻辑——基于政策文本分析

作为农村社区“两委”换届选举的关键步骤，农村社区“两委”候选人的产生备受关注。借助街道党组织社区“两委”候选人换届政策文本，勾勒出社区“两委”候选人在基层党组织设定的双重候选条件下的当选逻辑，并以fs-QCA定性比较分析法对社区“两委”候选人胜出资质进行检验。结果显示，良好群众基础是潜在候选胜出的必要条件，同时具备群众基础和政绩两要素是潜在候选人胜出的有效途径；仅凭借经济实力或宗族势力等资源禀赋并不能使其成为“两委”正式候选人；街道组织部门受政治稳定逻辑驱使，往往采取多样化策略减少社区选举“变数”。因此，基层党组织对农村社区“两委”选举过程的有限介入并非有损基层民主质量，相反，它使农村社区选举表现出有别于乡村选举的优良特质。     

泌阳凹陷泌301 井区不同流动单元产能分析

在沉积微相、储层物性特征分析的基础上，选取孔隙度、渗透率、流动带指数等参数，对泌阳凹陷赵凹油田泌301 井区核三段油层组进行流动单元划分。依据流动带指数的大小，将研究区目的层段划分为A、B、C、D 和E 等5 类流动单元。通过研究发现，各类流动单元与物性、岩性、沉积微相之间具有较好的对应关系，同时对不同流动单元产能进行了分析。研究结果表明，流动单元的划分能够真实客观地反映储层物性差、非均质性强的地质特点，单井产能与流动带指数有较好的乘幂关系，不同流动单元产能差异较为明显，物性最好的A 类流动单元产能最高，物性最差的E类流动单元产能最低。     

Efficient Inference for Longitudinal Data Varying‐coefficient Regression Models

Informative identification of the within‐subject correlation is essential in longitudinal studies in order to forecast the trajectory of each subject and improve the validity of inferences. In this paper, we fit this correlation structure by employing a time adaptive autoregressive error process. Such a process can automatically accommodate irregular and possibly subject‐specific observations. Based on the fitted correlation structure, we propose an efficient two‐stage estimator of the unknown coefficient functions by using a local polynomial approximation. This procedure does not involve within‐subject covariance matrices and hence circumvents the instability of calculating their inverses. The asymptotic normality of resulting estimators is established. Numerical experiments were conducted to check the finite sample performance of our method and an example of an application involving a set of medical data is also illustrated.     

页岩气开发环境风险的法律规制思考

目前，我国在页岩气开发的环境保护方面存在着大量的法律空白，往往只能参照环境保护法和矿产资源法中的相关规定进行规制，无法有效解决页岩气开发暴露出来的环境问题。页岩气开发环境风险的法律规制，核心目的就是解决当前页岩气开发中的环境风险，促进页岩气开发与环境保护相协调，实现能源开发的可持续发展。在页岩气开发环境风险的法律规制方面，英美两国已经探索出一些经验和制度。积极借鉴国外有益经验，努力改进和完善我国应对页岩气开发环境风险的法律规制，对实现我国页岩气开采的经济效益、社会效益和环境效益三者的统一具有重要的现实意义。     

对明初重刑主义的再思考

在中国的历来的历史上,重刑政策做为镇压人民,维护王朝专制统治的重要手段,为古来不少封建王朝所使用,但要伦用法之严、用刑之广,杀戮之盛,首屈一指的要属明初了.但是明初的重刑并未使得社会安定,相反得是犯罪率的高频发和人民的不断反抗.所以我们要对明初重刑主义的错误进行反思,纠正我国在立法和司法实践中的重刑倾向,使得在社会中刑法的作用能真正表现出来.     

Statistical testing strategies for assessing treatment efficacy and marker accuracy in phase III trials

When a candidate predictive marker is available, but evidence on its predictive ability is not sufficiently reliable, all‐comers trials with marker stratification are frequently conducted. We propose a framework for planning and evaluating prospective testing strategies in confirmatory, phase III marker‐stratified clinical trials based on a natural assumption on heterogeneity of treatment effects across marker‐defined subpopulations, where weak rather than strong control is permitted for multiple population tests. For phase III marker‐stratified trials, it is expected that treatment efficacy is established in a particular patient population, possibly in a marker‐defined subpopulation, and that the marker accuracy is assessed when the marker is used to restrict the indication or labelling of the treatment to a marker‐based subpopulation, ie, assessment of the clinical validity of the marker. In this paper, we develop statistical testing strategies based on criteria that are explicitly designated to the marker assessment, including those examining treatment effects in marker‐negative patients. As existing and developed statistical testing strategies can assert treatment efficacy for either the overall patient population or the marker‐positive subpopulation, we also develop criteria for evaluating the operating characteristics of the statistical testing strategies based on the probabilities of asserting treatment efficacy across marker subpopulations. Numerical evaluations to compare the statistical testing strategies based on the developed criteria are provided.     

A novel approach based on multiple correspondence analysis for monitoring social networks with categorical attributed data

In in most cases, the distribution of communications is unknown and one may summarize social network communications with categorical attributes in a contingency table. Due to the categorical nature of the data and a large number of features, there are many parameters to be considered and estimated in the model. Hence, the accuracy of estimators decreases. To overcome the problem of high dimensionality and unknown communications distribution, multiple correspondence analysis is used to reduce the number of parameters. Then the rescaled data are studied in a Dirichlet model in which the parameters should be estimated. Moreover, two control charts, Hotelling’s T² and multivariate exponentially weighted moving average (MEWMA), are developed to monitor the parameters of the Dirichlet distribution. The performance of the proposed method is evaluated through simulation studies in terms of average run length criterion. Finally, the proposed method is applied to a real case.     

Bayesian sample size determination for phase IIA clinical trials using historical data and semi‐parametric prior's elicitation

The Simon's two‐stage design is the most commonly applied among multi‐stage designs in phase IIA clinical trials. It combines the sample sizes at the two stages in order to minimize either the expected or the maximum sample size. When the uncertainty about pre‐trial beliefs on the expected or desired response rate is high, a Bayesian alternative should be considered since it allows to deal with the entire distribution of the parameter of interest in a more natural way. In this setting, a crucial issue is how to construct a distribution from the available summaries to use as a clinical prior in a Bayesian design. In this work, we explore the Bayesian counterparts of the Simon's two‐stage design based on the predictive version of the single threshold design. This design requires specifying two prior distributions: the analysis prior, which is used to compute the posterior probabilities, and the design prior, which is employed to obtain the prior predictive distribution. While the usual approach is to build beta priors for carrying out a conjugate analysis, we derived both the analysis and the design distributions through linear combinations of B‐splines. The motivating example is the planning of the phase IIA two‐stage trial on anti‐HER2 DNA vaccine in breast cancer, where initial beliefs formed from elicited experts' opinions and historical data showed a high level of uncertainty. In a sample size determination problem, the impact of different priors is evaluated.