跨国主义视角下高校海归知识移民的回流与地方嵌入

知识经济时代,地理学与世界移民研究越来越重视知识移民及其流动。本文以广州市高校海外留学回国的知识移民为例,采用深度访谈等质性研究方法,从多维视角探讨其回流和嵌入母国和回流地的动态过程及结果。研究发现：① 高校海归知识移民的回流动力机制主要包括工作机会和跨国比较发展优势,以及家庭关系和文化归属等;② 回流后高校知识移民面临着工作、生活、社会关系网络等方面的再嵌入;再嵌入的过程和结果受到工作及工作环境等结构因素和日常生活等非制度情感因素的共同作用;③ 由于拥有较高的跨境智力资本和较强的跨地方社会关系网络,其地方嵌入过程体现出较强的能动性。跨国流动背景下,他们的身份认同表现为混合文化身份的跨地方主体性,其“家”的意义建构也呈现出一种多元的特征。研究指出,多地方的社会嵌入通过跨地方的社会关系使得海归知识移民产生归属感,而并不完全依附于有边界的地理空间,这一定程度上打破了以往地理位置所定义的“地方”,而将关注点放置于基础的工作、社会关系网络与日常的生活实践。从微观和主体视角细致探究海归人才回流嵌入的过程与结果,可以进一步完善转型期知识移民的理论和研究框架,也可以为中国人才政策和发展战略提出指导建议。     

“家”“业”可否兼得：青年农民工回流意愿研究

基于个体心理决策视角,使用定量研究与定性研究相结合的方法,分析流出地的“家”和“业”对青年农民工回流意愿的影响过程。研究发现：文化意义上的“家”是影响青年农民工回流意愿的深层因素,但其影响还需要“业”的强化。流出地的“家”和“业”共同作用,形塑青年农民工的回流意愿。“家”的文化观念通过新的人生节点、具有挑战性的家庭责任和规划中的家庭发展触发青年农民工回流;“业”的想象则通过选择新的就业地点、渴望好的就业条件、寻找独特的创业资源和改变旧的发展路径增强青年农民工回流意愿,由此实现回流决策中的“家”“业”兼得。在中国区域发展不平衡、不充分的情况下,流出地政府既要大力发展经济、增加就业机会、提升收入水平,又要加大对回流的青年农民工的创业扶持,使他们的“业”得到持续强化,“家”“业”可以持续兼得。在对农民工群体进行研究时,可以把“家”作为一个关键的切入点,从“家”出发构建中国话语的分析框架,这蕴含了创建中国本土人口流动理论的可能性。     

多维邻近性对流动人口回流意愿的影响——基于中国流动人口动态监测数据的实证

随着城市产业转型升级和县域经济快速发展,人口回流已成为现阶段中国人口迁移与流动过程中的重要组成部分,回流劳动力是乡村振兴和新型城镇化的重要力量,对于区域协调发展意义重大。距离是人口流动空间选择的核心解释变量,在多维邻近性视角下探究多种距离对流动人口回流的影响,有利于深化对人口回流机制的理解。论文借鉴多维邻近性分析框架,基于2016年中国流动人口动态监测调查数据,采用二元Logistic回归模型探究地理、制度和社会邻近性对流动人口回流意愿的影响。研究表明：① 回流群体主要是受教育水平较低的大龄已婚流动人口,其在劳动力市场不占优势,但家庭对其情感需求与依赖较大,回流意愿明显。② 不同维度邻近性均对流动人口回流意愿有较强解释力,地理、制度和社会邻近性对回流意愿均有显著负向影响,长距离跨省或跨方言区迁移的劳动力回流意愿更为强烈。③ 不同邻近性对回流意愿的影响存在群体异质性。高学历群体回流意愿受其所在流入地参保情况的抑制,同时受到方言和地理距离的不同影响;新生代流动人口则较易受非正式制度邻近性影响而选择回流;长期外出劳动力的回流意愿会因其已熟悉流入地方言并在流入地积极参保而降低。     

Nonstationary analysis of the extreme temperatures in Turkey

Record-breaking extreme temperatures have been measured in the last two decades all over Turkey, with recent studies detecting positive trends in extreme temperature time series. In this study, nonstationary extreme value analysis was performed on extreme temperature time series obtained from fifty stations scattered over the seven geographical regions of Turkey. Basic characterization of the data set was defined through outlier detection, homogeneity, trend detection, and stationarity tests. Trend-including non-stationary extreme temperature time series were analyzed with non-stationary Generalized Extreme Value distribution. Three main physical drivers were considered as the leading causes that trigger the observed trends in extreme temperatures over Turkey: time, teleconnection patterns of the Arctic Oscillations, and those of the North Atlantic Oscillations. The results showed that most of the absolute annual minimum and maximum temperature time series are inhomogeneous while the possible breakpoints date back to the1970s and 1990s, respectively. More than half of the absolute annual maximum time series (26/50 and many of the absolute annual minimum time series (21/50) showed a positive trend. No negative trend was detected in the extreme temperature time series. Based on the frequency analysis of the 21 annual maximum time series, the non-stationary estimations of 50-year return levels were detected to be higher than in the stationary model (between 0.44 °C and 3.73 °C). The return levels in 15 of the 20 minimum temperature time series increased from 0.11 °C up to 12.28 °C. Elevation increases the nonstationarity impact on absolute minimum temperatures and decreases it on absolute maximums. The findings in this study indicate that the consideration of non-stationarity in extreme temperature time series is a necessity during return level estimations over the study area.     

Unusual behavior detection and object ranking from movement trajectories in target regions

Unusual behavior detection has been of interest in video analysis, transportation systems, movement trajectories, and so on. In movement trajectories, only a few works identify unusual behavior of objects around pre-defined points of interest (POI), such as surveillance cameras, commercial buildings, etc., that may be interesting for several application domains, mainly for security. In this article, we define new types of unusual behaviors of moving objects in relation to POI, including surround, escape, and return. Based on these types of unusual behavior, we (i) present an algorithm to compute these behaviors, (ii) define a set of functions to weight the degree of unusual behavior of every moving object in the database, and (iii) rank the moving objects according to the degree of unusual behavior in relation to a set of POIs. We evaluate the proposed method with real trajectory data and show that the closest work does not detect the proposed behaviors and ranks objects considering only one type of unusual movement.     

基于Copulas函数的二维干旱变量联合分布

通过构建干旱变量的联合分布揭示干旱演变规律,可作为干旱分析的重要手段。基于8种单参数族的Copulas函数进行新疆乌鲁木齐和石河子气象站二维干旱变量的联合分布。经拟合优度评价:Frank Copula对干旱历时和干旱烈度、干旱历时和烈度峰值的拟合度最好;Clayton Copula对于干旱烈度和烈度峰值的拟合效果最好。二维变量联合超越概率值随单变量值的减小而增大;单变量的重现期介于二维变量联合重现期与同现重现期之间。表明Copulas函数能够描述二维干旱特征变量的联合分布。     

龙口市人工岛周边海域波浪场和水动力场的数值模拟

为了科学的分析离岸人工岛群对周边海岸动力的影响,本文以龙口市人工岛为例,运用MIKE21数值模拟软件建立了龙口离岸人工岛及附近海域的水动力模型和波浪模型,根据波浪的生成、成长和传播原理,针对最有可能形成较大波浪的W、WNW、NW三个方向,采用频率为0.5%(重现期为200a)的高潮位叠加频率为0.5%(重现期为200a)的W、WNW和NW向风作用下的波浪场和水动力场进行数值模拟研究,给出了高潮位条件下人工岛周边不同波向对应的有效波高和最大波高值,以及最大流速和流向数据,可为人工岛群的地坪标高确立和防浪建筑物的布设提供科学依据。     

基于危险率分析的风浪联合重现期研究

采用二维逻辑冈贝尔分布,基于工程使用期和危险率,提出海洋工程结构设计过程中海洋环境要素(风速和波高)联合重现期的确定方法,并且以某海区资料为例,介绍基于危险率分析的风浪联合重现期分析过程.通过此例,在考虑工程使用期和危险率的基础上进行联合重现期的计算使海洋工程结构物设计过程中重现期的选取更加合理,安全性以及投资建造成本更加明确.     

Assessing and modelling changes in rainfall erosivity at different climate scales

An understanding of the weather drivers of soil erosion necessitates an extended instrumental meteorological series and knowledge of the processes linking climate and hydrology. The nature of such linkages remains poorly understood for the Mediterranean region. This gap is addressed through a composite analysis of long‐term climatic controls on rain erosivity in the Calore River Basin (southern Italy) for the period 1869–2006. Based on a parsimonious interpretation of rainstorm processes, a model (comparable with the Revised Universal Soil Loss Equation) was adapted to generate erosivity values on different time‐aggregation scales (yearly and seasonal). The evolution of the generated series of cumulated and extreme erosivity events was assessed by two return period (T) quantiles via a 22‐year moving window analysis (low return period, T = 2 years; high return period, T = 50 years). Erosivity extremes are shown to be characterized by increasing yearly trends (at a 100‐year rate of ～150 MJ mm ha^–1 h^–1 for T = 2 years and ～800 MJ mm ha^–1 h^–1 for T = 50 years), especially during the spring and autumn seasons. Quantile patterns on the extremes are also shown to be decoupled from trends in the cumulated values. The Buishand test was applied to detect the presence of temporal change points, and a wavelet spectrum analysis used for time‐frequency localization of climate signals. A change‐point in the evolution of climate is revealed over the 1970s in the spring series, which correlates to a distinct rain erosivity increase. The results indicate that soil erosion risk tends to rise as a consequence of an escalation of the climate erosive hazard, predominantly between April and November (associated with cultivation and tillage practices). Copyright © 2009 John Wiley & Sons, Ltd.     

卫星激光测距回波探测成功概率统计分析

通过对国内外部分观测量较多的卫星激光测距站夜间和白天观测资料的统计,分析了激光测距回波探测成功率实际值和理论分析的差别,探讨了影响夜间、白天激光测距探测率的各种因素,为进一步提高数据探测成功率提供了实践依据。本文还介绍了近几年兴起的高重复频率卫星测距的方法,应用此测距方法可以获得更多的观测数据,有效地提高标准点精度。