Origin–destination (OD) of the interprovincial floating population of China

<p>China’s large floating population catalyzes economic development, redistributes the population, and promotes social changes to the social structure, lifestyle patterns, and cultural values. The floating population is a unique group faced with numerous problems stemming from cultural and lifestyle differences. Understanding and visualizing the distributional characteristics and patterns of the floating population is crucial for developing effective social policies. In this study, the origin–destination (OD) map and its adjustment destination–origin (DO) map are used to represent the interprovincial floating population. The OD or DO map can be regarded as a two-level spatial treemap representing the floating population recorded by pairs of locations. In accordance with the different hierarchy of the two-level spatial treemap, the OD and DO are distinguished. The migration volume of the floating population data is represented by the OD and DO maps to find the population’s direction of movement, magnitude, and hot-spots. The migration indicators including migration effectiveness, migration preference indexes, and sex ratios are represented by the OD and DO maps, which assist in to reviewing and studying the deep patterns of floating population.</p

A Map-Based Service Supporting Different Types of Geographic Knowledge for the Public

<div><p>The internet enables the rapid and easy creation, storage, and transfer of knowledge; however, services that transfer geographic knowledge and facilitate the public understanding of geographic knowledge are still underdeveloped to date. Existing online maps (or atlases) can support limited types of geographic knowledge. In this study, we propose a framework for map-based services to represent and transfer different types of geographic knowledge to the public. A map-based service provides tools to ensure the effective transfer of geographic knowledge. We discuss the types of geographic knowledge that should be represented and transferred to the public, and we propose guidelines and a method to represent various types of knowledge through a map-based service. To facilitate the effective transfer of geographic knowledge, tools such as auxiliary background knowledge and auxiliary map-reading tools are provided through interactions with maps. An experiment conducted to illustrate our idea and to evaluate the usefulness of the map-based service is described; the results demonstrate that the map-based service is useful for transferring different types of geographic knowledge.</p></div

Using SVG to render a map.

<p>Using SVG to render a map.</p

Work operator primitives [23].

<p>Work operator primitives [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0152881#pone.0152881.ref023" target="_blank">23</a>].</p

Chiral [Mo₈O₂₆]^4– Polyoxoanion-Induced Three-Dimensional Architectures With Homochiral Eight-Fold Interpenetrated Metal–Organic Frameworks

A pair of novel chiral compounds based on homochiral 8-fold interpenetrated metal–organic frameworks (MOFs) and chiral polyoxometalates (POMs), formulated as d-[Cu­(4,4′-bipy)_1.5]₄­[Mo₈O₂₆] (d-<b>1</b>) and l-[Cu­(4,4′-bipy)_1.5]₄­[Mo₈O₂₆] (l-<b>1</b>) (4,4′-bipy = 4,4′-bipyridine), have been successfully synthesized and characterized by single crystal X-ray diffraction, infrared, thermogravimetric analysis, elemental analysis, and solid circular dichroism spectra. Structural analysis indicates that two compounds are enantiomers. The connection of copper cations and 4,4′-bipy ligands generates helical infinite chains, while adjacent chains are further linked by Cu–N bonds to form a three-dimensional interpenetrating framework with a (10,3)-a topology. Interestingly, the chiral [Mo₈O₂₆]^4– polyanions are encapsulated in the chiral MOFs via sharing the oxygen atoms. Both d- and l-[Cu­(4,4′-bipy)_1.5]₄­[Mo₈O₂₆] crystallize in chiral space group <i>C</i>222₁. Additionally, two compounds represent new examples of chiral self-assembly

Results of two sample <i>t</i>-test on scores of two groups of participants.

<p>Results of two sample <i>t</i>-test on scores of two groups of participants.</p

Scores of the two groups.

<p>Scores of the two groups.</p

Causal knowledge: one of the factors that affect the population distribution in China.

<p>Factors influencing population distribution: socio-economic—GDP (data year: 2013, data source: the China statistical Yearbook. <a href="http://www.stats.gov.cn/tjsj/ndsj/2014/indexch.htm" target="_blank">http://www.stats.gov.cn/tjsj/ndsj/2014/indexch.htm</a>).</p

Relational knowledge: related geographic phenomena (data year: 2013, data source: the China statistical Yearbook. http://www.stats.gov.cn/tjsj/ndsj/2014/indexch.htm).

<p>Relational knowledge: related geographic phenomena (data year: 2013, data source: the China statistical Yearbook. <a href="http://www.stats.gov.cn/tjsj/ndsj/2014/indexch.htm" target="_blank">http://www.stats.gov.cn/tjsj/ndsj/2014/indexch.htm</a>).</p

Group statistics.

<p>Group statistics.</p