空间批评视角下的《生日》

从空间批评视角看,文本中的空间不再是静止的＂容器＂,而是一种蕴含多维文化信息的指涉系统,注重文本中空间的社会、文化属性。在美国华裔作家雷祖威的短篇小说《生日》中,与华裔青年华莱士·王的爱情故事相关的几个空间场景不仅再现了华裔的现实生活世界,更充分展示了他们居于社会边缘的处境与内心疏离的痛苦。     

Identifying radon-prone building typologies by marginal modelling

Radon is a naturally occurring decay product of uranium known to be the main contributor to natural background radiation exposure. It has been established that the health risk related to radon exposure is lung cancer. In fact, radon is considered to be a major leading cause of lung cancer, second only to smoking. In this paper, we identified building typologies that affect the probability of detecting indoor radon concentration above reference values, using the data collected within two monitoring campaigns recently conducted in Northern Italy. This information is fundamental both in prevention, i.e. when the construction of a new building is planned and in mitigation, i.e. when a high concentration detected inside buildings has to be reduced. A spatial regression approach for binary data was adopted for this goal where some relevant covariates on the soil were retrieved by linking external spatial databases.     

Identifying Latent Structures in Panel Data

This paper provides a novel mechanism for identifying and estimating latent group structures in panel data using penalized techniques. We consider both linear and nonlinear models where the regression coefficients are heterogeneous across groups but homogeneous within a group and the group membership is unknown. Two approaches are considered—penalized profile likelihood (PPL) estimation for the general nonlinear models without endogenous regressors, and penalized GMM (PGMM) estimation for linear models with endogeneity. In both cases, we develop a new variant of Lasso called classifier‐Lasso (C‐Lasso) that serves to shrink individual coefficients to the unknown group‐specific coefficients. C‐Lasso achieves simultaneous classification and consistent estimation in a single step and the classification exhibits the desirable property of uniform consistency. For PPL estimation, C‐Lasso also achieves the oracle property so that group‐specific parameter estimators are asymptotically equivalent to infeasible estimators that use individual group identity information. For PGMM estimation, the oracle property of C‐Lasso is preserved in some special cases. Simulations demonstrate good finite‐sample performance of the approach in both classification and estimation. Empirical applications to both linear and nonlinear models are presented.     

《八月之光》的空间批评解读

《八月之光》以美国南方封闭守旧的杰佛生镇为背景,作为福克纳独创“约克纳帕塔法”世系的坐标因子,该地理空间延续着内战的精神创伤,铺设了种族歧视与迫害的温床。空间批评学聚焦空间的社会文化属性,文学文本空间成为内含多维指涉意义的指示系统。运用列斐伏尔的“空间三元辩证法”,从物理、心理以及社会空间3个层面展开探索,通过主人公乔·克里斯默斯的视角投射出该地理空间下黑白聚居区的冲突与碰撞,个人心理空间中疑似“黑白混血儿”的主体意识的坍塌及白人主导的社会空间对“无身份”种族的围剿。     

碳排放约束下能源经济效率的区域空间分布研究——基于能源消费结构门槛视角

利用2000—2012年样本数据对全要素省际能源经济效率进行了测算,研究发现样本期间绝大部分省市自治区能源经济效率整体都呈不断下降的趋势,并且生产过程中低效率地区大幅增加,分布状态由“点状”向“面状”扩散,尤其是中西部地区下降较为明显,究其原因主要为:二氧化碳排放和能源消费结构是能源经济效率变化和地区差异的重要影响因素;据此运用门槛分析方法对其进行区域空间分布研究,将全国30个省市自治区划分为低排放—结构较合理、低排放—结构欠合理、高排放—结构较合理类群、高排放—结构欠合理和高排放—结构不合理5大类群,最后结合各类型区域自身发展特点,提出因地制宜的低碳绿色发展建议,并从需求侧和供给侧两方面提出能源经济效率改善的政策建议。     

社会资本对居民生活垃圾分类行为的影响机理分析

社会资本与环境保护合作行为的逻辑关系已经成为环境管理的一个重要研究方向。基于219户城镇居民调查数据的实证研究发现,除了年龄、受教育年限和中共党员身份外,以社会网络、社会规范和社会信任为要素的社会资本,对提高居民生活垃圾分类水平有显著的正向影响。具体而言,社会网络能够降低居民机会主义和“搭便车”的行为倾向;社会规范能够提高居民行为的可预测性,增强居民投资环境保护集体行动的信心;社会信任则通过降低交易成本,促进居民生活垃圾分类的自主合作行为。为从源头上化解我国生态环境管理面临的“垃圾围城”困境,政府应积极促进居民间的网络互动,完善互惠共享的社会规范,提升居民间的普遍信任,同时加大对生活垃圾分类知识和技巧的宣传力度、发挥党员在遵守社会规范中的带头作用,通过社会资本发展促进公众的自主环境保护合作行为。     

论数+形+量结构中量词的特点

现代汉语中数量词中插入形容词的结构即数+形+量结构比较常见,例如,一大张纸,一大群人,一长根铁丝。陆俭明先 生对这种语言现象进行了详细的描写,但是还是留下了一些问题给大家讨论。例如,为什么数量词中间可以插入形容词,插入 形容词对整个结构有什么影响。从量词的特点和形容词的语义指向来看,数+形+量结构中的量词具有空间性、物质性、描写 性的特点,使得形容词能够进入该结构,形容词的语义指向不同,使整个结构有不同的表达功能。     

城镇化背景下农产品物流发展模式研究

农产品物流作为物流业的一个分支,在促进农业产业化和城镇化发展方面发挥着重要作用。对原有农产品物流发展模式进行分析,构建四种农产品物流发展模式。从城镇化水平的角度出发,以辽宁省为例,运用主成分聚类分析法对辽宁省14个地区的城镇化水平进行评价及分类,并针对不同城镇化水平的地区进行农产品物流发展模式的选择,旨在为促进农产品物流的一体化发展提供借鉴。     

Visualization for Large‐scale Gaussian Updates

In geostatistics and also in other applications in science and engineering, it is now common to perform updates on Gaussian process models with many thousands or even millions of components. These large‐scale inferences involve modelling, representational and computational challenges. We describe a visualization tool for large‐scale Gaussian updates, the ‘medal plot’. The medal plot shows the updated uncertainty at each observation location and also summarizes the sharing of information across observations, as a proxy for the sharing of information across the state vector (or latent process). As such, it reflects characteristics of both the observations and the statistical model. We illustrate with an application to assess mass trends in the Antarctic Ice Sheet, for which there are strong constraints from the observations and the physics.     

空间面板杜宾模型的Bootstrap Wald-COMFAC检验研究

将共同因子约束(COMFAC)的Wald检验问题引入到空间面板模型中,讨论空间面板杜宾模型与空间面板误差模型的识别问题。蒙特卡洛模拟表明:在有限样本下,基于渐近临界值的Wald检验有着良好的检验功效,但存在着较为严重的尺度扭曲。进一步采用残差Bootstrap方法,在不损失检验功效的前提下,能够显著地降低检验的尺度扭曲。因此,残差Bootstrap方法是更为有效的检验方法。