工业劳动力流动、资本创造与经济地理空间均衡

资本创造模型（CC模型）忽视了要素流动对产业空间分布的影响。而发展的新的资本创造模型则认为资本集聚的过程必然伴随着工业劳动力的流动过程。另外，是资本的实际收益而不是名义收益决定资本是否创造。研究结果表明，随着贸易自由度、工业品支出份额及资本贴现率的变大，替代弹性及资本折旧率的变小，将降低对称结构的稳定性，而提高中心-外围结构的稳定性；经济地理空间的产业均衡是集聚力和分散力相互作用的结果。当企业生产工业品的规模报酬递增程度足够显著，或者工业品支出份额很高时，市场拥挤效应将彻底消失，并转化成为促进产业集聚的动力；突破点与持续点的大小比较可以形成不同的关系，这意味着随着贸易自由度的变化，本文发展的资本创造模型可以体现出多样化的产业空间动态演化行为。     

Improved Transferability of Data‐Driven Damage Models Through Sample Selection Bias Correction

Damage models for natural hazards are used for decision making on reducing and transferring risk. The damage estimates from these models depend on many variables and their complex sometimes nonlinear relationships with the damage. In recent years, data‐driven modeling techniques have been used to capture those relationships. The available data to build such models are often limited. Therefore, in practice it is usually necessary to transfer models to a different context. In this article, we show that this implies the samples used to build the model are often not fully representative for the situation where they need to be applied on, which leads to a “sample selection bias.” In this article, we enhance data‐driven damage models by applying methods, not previously applied to damage modeling, to correct for this bias before the machine learning (ML) models are trained. We demonstrate this with case studies on flooding in Europe, and typhoon wind damage in the Philippines. Two sample selection bias correction methods from the ML literature are applied and one of these methods is also adjusted to our problem. These three methods are combined with stochastic generation of synthetic damage data. We demonstrate that for both case studies, the sample selection bias correction techniques reduce model errors, especially for the mean bias error this reduction can be larger than 30%. The novel combination with stochastic data generation seems to enhance these techniques. This shows that sample selection bias correction methods are beneficial for damage model transfer.     

巴渝古崖居的空间分布与景观特征

巴渝古崖居的分布与地理、地质、交通等诸多因素有关，以成渝交通要道、长江干流和支流为线，串起沿途各个点，由线成面，呈现出渝西、渝东北两头集中、整体北多南少的分布特征。巴渝古崖居大多开凿于明清晚期，这一时期巴渝许多地区战乱频繁、匪患猖獗。古崖居的集中分布与这些地区相吻合，从侧面印证了巴渝古崖居的空间分布特征。巴渝古崖居的广泛开凿体现了古人高超的建筑艺术以及社会历史文化的变迁。     

英文影片的中国方言版字幕翻译

2012年3D 版《泰坦尼克号》的华丽上映曾掀起影迷们对它的新一轮热捧。文章就同样备受中国观众喜爱的中国方言版《泰坦尼克号》为案例，结合功能目的论来探寻中国方言版字幕翻译的目的与性质，进而分析、总结英文影片字幕的中国方言版译制活动过程。     

德语空间性状形容词的时间映射特质研究

基于认知隐喻理论，选择德语中14个表征空间性状的形容词，探究其时间映射特质。研究发现:长/短、大/小、远/近、高、深可表征时间，其余则无法表征时间。具体特质如下:存在“一维＞二维＞三维”映射维度等级；存在“长短＞远近＞高深/大小”映射宽幅等级；正向形容词比负向更易表征时间。这种映射特质主要与时空相似性、认知思维及隐喻操作有关。     

Using local linear kernel smoothers to test the lack of fit of nonlinear regression models

Herein, we propose a data-driven test that assesses the lack of fit of nonlinear regression models. The comparison of local linear kernel and parametric fits is the basis of this test, and specific boundary-corrected kernels are not needed at the boundary when local linear fitting is used. Under the parametric null model, the asymptotically optimal bandwidth can be used for bandwidth selection. This selection method leads to the data-driven test that has a limiting normal distribution under the null hypothesis and is consistent against any fixed alternative. The finite-sample property of the proposed data-driven test is illustrated, and the power of the test is compared with that of some existing tests via simulation studies. We illustrate the practicality of the proposed test by using two data sets.     

基于定货合同的供应商柔性分析和选择模型

供应链及供应链管理是目前国内外学术界和工商企业管理者共同关心的课题,他们提出了众多分析方法和分析模型,但由于计算复杂,在实际操作中运用较少。实际上,在供应链业务流程中,供应合同是最关键的法律文件,合同信息分析能很好地减少不确定性,降低风险。因此,供应商和购货商选择模型应包括以下参数:单位供应价格、定货周期、最小定货提前期、每个周期最小定货量、临时配送补偿系数、定货量小于最小定货量补偿系数。     

论邓小平对选拔培养中青年干部的思想

建设有中国特色的社会主义市场经济 ,需要一大批杰出的人才。如何选拔培养中青年干部成为我们党和国家一项重大课题。运用邓小平理论中关于选拔培养中青年干部的观点并指导实践 ,将会对我国的四化建设起到积极作用     

成都市民旅游感应空间研究

旅游感应强度是研究旅游感应空间的一个角度。通过对《成都晚报》“旅游”专刊最近 6年的统计 ,得到全国 34个省级行政区及四川省内分地区作为旅游目的地的出现频次 ,以此频次来表征成都市民对国内及省内旅游目的地的感应强度。利用感应强度从省际和省内不同尺度揭示了成都市民旅游感应空间的特点 ,并发现旅游感应空间的一些新特征     

Spatial variation in soil inorganic nitrogen across an arid urban ecosystem

We explored variations in inorganic soil nitrogen (N) concentrations across metropolitan Phoenix, Arizona, and the surrounding desert using a probability-based synoptic survey. Data were examined using spatial statistics on the entire region, as well as for the desert and urban sites separately. Concentrations of both NO₃-N and NH₄-N were markedly higher and more heterogeneous amongst urban compared to desert soils. Regional variation in soil NO₃-N concentration was best explained by latitude, land use history, population density, along with percent cover of impervious surfaces and lawn, whereas soil NH₄-N concentrations were related to only latitude and population density. Within the urban area, patterns in both soil NO₃-N and NH₄-N were best predicted by elevation, population density and type of irrigation in the surrounding neighborhood. Spatial autocorrelation of soil NO₃-N concentrations explained 49% of variation among desert sites but was absent between urban sites. We suggest that inorganic soil N concentrations are controlled by a number of ‘local’ or ‘neighborhood’ human-related drivers in the city, rather than factors related to an urban-rural gradient.