Quantitative historical analysis uncovers a single dimension of complexity that structures global variation in human social organization.

Do human societies from around the world exhibit similarities in the way that they are structured, and show commonalities in the ways that they have evolved? These are long-standing questions that have proven difficult to answer. To test between competing hypotheses, we constructed a massive repository of historical and archaeological information known as "Seshat: Global History Databank." We systematically coded data on 414 societies from 30 regions around the world spanning the last 10,000 years.

On the unsupervised analysis of domain-specific Chinese texts.

With the growing availability of digitized text data both publicly and privately, there is a great need for effective computational tools to automatically extract information from texts. Because the Chinese language differs most significantly from alphabet-based languages in not specifying word boundaries, most existing Chinese text-mining methods require a prespecified vocabulary and/or a large relevant training corpus, which may not be available in some applications. We introduce an unsupervised method, top-down word discovery and segmentation (TopWORDS), for simultaneously discovering and segmenting words and phrases from large volumes of unstructured Chinese texts, and propose ways to order discovered words and conduct higher-level context analyses.

[Sarcoidosis].

Sarcoidosis is a chronic generalized benign granulomatous disorder of perhaps an autoimmune character which can afflict many organs. The insidious form prevails, a (sub)acute onset covers about one third of cases. In most patients the lungs are involved; tissue damage by granulomas and inflammatory cells causes a reduction of respiratory capacity, with dyspnoea as a result.