Phryssonotus novaehollandiae Silvestri, 1923 : the sole Australian representative of the millipede Family Synxenidae

Examination of synxenid millipedes from a number of collections confirms that Phryssonotus novaehollandiae is the sole representative of the genus and family in Australia. P. novaehollandiae was found to have the most widespread distribution of any native Australian millipede species. It occurs in a range of well-drained habitats including heathlands, woodlands and coastal scrub. Several thelytokous (female only) populations were found in coastal areas of south eastern Australia.

The millipedes of Barrow Island, Western Australia (Diplopoda)

Six species of millipedes are recorded from Barrow Island, including three species of pin-cushion millipedes of the order Polyxenida, Lophoturus madecassus (Marquet and Condé, 1950) (Lophoproctidae), Unixenus mjoebergi (Verhoeff, 1924) (Polyxenidae) and Phryssonotus novaehollandiae (Silvestri, 1923) (Synxenidae), a single species of the order Spirobolida, Speleostrophus nesiotes Hoffman, 1994 (Trigoniulidae), and two species of the order Polydesmida, Boreohesperus dubitalis Car and Harvey, 2013 (Paradoxosomatidae) and one species of the family Haplodesmidae (genus and species indet.). Lophoturus madecassus is circum-tropical in distribution, Unixenus mjoebergi and Phryssonotus novaehollandiae are found also on mainland Australia, but the other three species are endemic to the island. Speleostrophus nesiotes is a highly modified troglobiotic species, currently listed as threatened by the Western Australian government. It is unclear at present whether the haplodesmid specimen is a troglobite.

Overcoming data scarcity of Twitter: using tweets as bootstrap with application to autism-related topic content analysis

Notwithstanding recent work which has demonstrated the potential of using Twitter messages for content-specific data mining and analysis, the depth of such analysis is inherently limited by the scarcity of data imposed by the 140 character tweet limit. In this paper we describe a novel approach for targeted knowledge exploration which uses tweet content analysis as a preliminary step. This step is used to bootstrap more sophisticated data collection from directly related but much richer content sources. In particular we demonstrate that valuable information can be collected by following URLs included in tweets. We automatically extract content from the corresponding web pages and treating each web page as a document linked to the original tweet show how a temporal topic model based on a hierarchical Dirichlet process can be used to track the evolution of a complex topic structure of a Twitter community. Using autism-related tweets we demonstrate that our method is capable of capturing a much more meaningful picture of information exchange than user-chosen hashtags.