Embodied bicycle commuters in a car world

As an initiative to increase cycling, bike to work (BTW) events emphasize a pragmatic approach in which people learn through sensory experience. Pragmatism contends that the lived experience of the commuter within fluid geographies of social and physical conditions informs commuting knowledge and behavior. I researched how bicyclists participate in the 2012 BTW event in Lake Tahoe (USA) and how these experiences facilitate the process of becoming bicycle commuters. My study included participant observations, interviews, video observations, and route mapping. I analyzed this data with thematic and narrative analyses. I find that the BTW event illuminates bicycling, a normally invisible practice in a car world, and creates temporary bicycle-friendly spaces that provide the embodied experience and knowledge of bicycle commuting within context. Through this lived experience, participants can break free from unconscious car-based patterns and become embodied bicycle commuters who engage in active renegotiations of their commuting practices.     

Probabilistic Regionalization via Evidence Accumulation with Random Spanning Trees as Weak Spatial Representations

Spatial clusters contain biases and artifacts, whether they are defined via statistical algorithms or via expert judgment. Graph-based partitioning of spatial data and associated heuristics gained popularity due to their scalability but can define suboptimal regions due to algorithmic biases such as chaining. Despite the broad literature on deterministic regionalization methods, approaches that quantify regionalization probability are sparse. In this article, we propose a local method to quantify regionalization probabilities for regions defined via graph-based cuts and expert-defined regions. We conceptualize spatial regions as consisting of two types of spatial elements: core and swing. We define three distinct types of regionalization biases that occur in graph-based methods and showcase the use of the proposed method to capture these types of biases. Additionally, we propose an efficient solution to the probabilistic graph-based regionalization problem via performing optimal tree cuts along random spanning trees within an evidence accumulation framework. We perform statistical tests on synthetic data to assess resulting probability maps for varying distinctness of underlying regions and regionalization parameters. Lastly, we showcase the application of our method to define probabilistic ecoregions using climatic and remotely sensed vegetation indicators and apply our method to assign probabilities to the expert-defined Bailey's ecoregions.     

论东下冯类型的族属

东下冯类型作为二里头文化的一个地方类型,其分布的晋西南地区是古九州的一部分,依托于九州之一险太岳或四岳.所以,东下冯类型与文献中记载的姜姓四岳族关系密切,应属姜姓四岳族的文化遗存.这一族在夏代与夏人为同盟关系,夏亡之后与部分夏人一起陆续西迁,成为沟通西部地区与中原地区文化的重要媒介.同时,它也是构成华夏族的重要组成部分.