Using social media to find places of interest: a case study

In this paper, we show how the large amount of geographically annotated data in social media can be used to complement existing place databases. After explaining our method, we illustrate how this approach can be used to discover new instances of a given semantic type, using London as a case study. In particular, for several place types, our method finds places in London that are not yet contained in the databases used by Foursquare, Google, LinkedGeoData and Geonames. Encouraged by these results, we briefly sketch how similar techniques could potentially be used to identify likely errors in existing databases, to estimate the spatial extent of places, to discover semantic relationships between place types, and to recommend tags to users who are uploading photos

A Comprehensive Survey of Pelagic Megafauna: Their Distribution, Densities, and Taxonomic Richness in the Tropical Southwest Indian Ocean

The distribution and density of pelagic megafauna (marine mammals, seabirds, elasmobranches, and sea turtles) are important indicators of marine biodiversity, reflecting the condition of the underlying ecosystems. A dedicated aerial survey was conducted in the tropical Southwest Indian Ocean to map their distribution, the taxonomic diversity, and to estimate their densities to serve as a baseline for the area. This large survey across three ecological sub-regions revealed contrasting spatial distributions: maps of taxonomic richness of marine mammals and seabirds revealed different “hotspots” in the area. Densities were estimated for eight cetacean taxa with small and large Delphininae, or small Globicephalinae dominating, and for seven seabird taxa, with terns and noddies dominating. At the community level, the Southwest Indian Ocean megafauna was structured by the marine environment with strong differences between the Mozambique Channel and the Mascarene Islands, or between shelf and slope/oceanic habitats. Our results illustrate how multi-taxa aerial surveys are relevant and cost-effective monitoring tools for marine megafauna, allowing a community-wide approach

Abundance of baleen whales in the European Atlantic

The abundance of fin whales (Balaenoptera physalus), sei whales (B. borealis) and minke whales (B. acutorostrata) was estimated from data collected during shipboard sightings surveys conducted as part of CODA and TNASS (Faroese block) in July 2007 in offshore waters of the European Atlantic west of the UK, Ireland, France and Spain, combined with data collected from shipboard and aerial surveys of European Atlantic continental shelf waters conducted as part of SCANS-II in July 2005. Double platform methods employing the trial-configuration method (BT-method) were used in all shipboard surveys. Analysis used Mark-Recapture Distance Sampling to account for animals missed on the transect line. Density surface modelling was undertaken to generate model-based abundance estimates and maps of predicted density. Estimates are presented for the SCANS-II and CODA survey areas. Estimates for the Faroese block of TNASS have been presented elsewhere. The abundance of fin whales in the CODA and SCANS-II areas was estimated as 19,354 (CV 0.24) for identified sightings and 29,512 (CV 0.26) when adjusted to include a proportion of unidentified large whale abundance (which included large baleen and sperm whales), prorated by number of sightings, because there were a large number of such sightings in one of the CODA survey blocks. The model-based estimate of identified fin whales was 19,751 (CV 0.17), more precise than the design-based estimate. Fin whales were mainly found in the southern part of the CODA survey area. Estimates based on identified sightings were comparable to those from the Spanish survey conducted as part of 1989 NASS but were larger if adjusted for a proportion of unidentified large whales. Sei whales were rare except in the southwest of the survey area; the estimate of abundance was 619 (CV 0.34) for identified sightings and 765 (CV 0.43) adjusted for a proportion of unidentified large whales. Minke whale abundance was estimated for shelf and offshore European Atlantic waters as 30,410 (CV 0.34). The model-based estimate was less precise and considerably larger

Large‐scale modelling of deep‐diving cetacean habitats

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Lenalidomide in combination with dexamethasone at first relapse in comparison with its use as later salvage therapy in relapsed or refractory multiple myeloma

This subset analysis of data from two phase III studies in patients with relapsed or refractory multiple myeloma (MM) evaluated the benefit of initiating lenalidomide plus dexamethasone at first relapse. Multivariate analysis showed that fewer prior therapies, along with β2-microglobulin (≤2.5 mg/L), predicted a better time to progression (TTP; study end-point) with lenalidomide plus dexamethasone treatment. Patients with one prior therapy showed a significant improvement in benefit after first relapse compared with those who received two or more therapies. Patients with one prior therapy had significantly prolonged median TTP (17.1 vs. 10.6 months; P=0.026) and progression-free survival (14.1 vs. 9.5 months, P=0.047) compared with patients treated in later lines. Overall response rates were higher (66.9% vs. 56.8%, P=0.06), and the complete response plus very good partial response rate was significantly higher in first relapse (39.8% vs. 27.7%, P=0.025). Importantly, overall survival was significantly prolonged for patients treated with lenalidomide plus dexamethasone with one prior therapy, compared with patients treated later in salvage (median of 42.0 vs. 35.8 months, P=0.041), with no differences in toxicity, dose reductions, or discontinuations despite longer treatment. Therefore, lenalidomide plus dexamethasone is both effective and tolerable for second-line MM therapy and the data suggest that the greatest benefit occurs with earlier use

The stranding anomaly as population indicator: the case of Harbour Porpoise <i>Phocoena phocoena</i> in North-Western Europe

Ecological indicators for monitoring strategies are expected to combine three major characteristics: ecological significance, statistical credibility, and cost-effectiveness. Strategies based on stranding networks rank highly in cost-effectiveness, but their ecological significance and statistical credibility are disputed. Our present goal is to improve the value of stranding data as population indicator as part of monitoring strategies by constructing the spatial and temporal null hypothesis for strandings. The null hypothesis is defined as: small cetacean distribution and mortality are uniform in space and constant in time. We used a drift model to map stranding probabilities and predict stranding patterns of cetacean carcasses under H-0 across the North Sea, the Channel and the Bay of Biscay, for the period 1990-2009. As the most common cetacean occurring in this area, we chose the harbour porpoise <i>Phocoena phocoena</i> for our modelling. The difference between these strandings expected under H-0 and observed strandings is defined as the stranding anomaly. It constituted the stranding data series corrected for drift conditions. Seasonal decomposition of stranding anomaly suggested that drift conditions did not explain observed seasonal variations of porpoise strandings. Long-term stranding anomalies increased first in the southern North Sea, the Channel and Bay of Biscay coasts, and finally the eastern North Sea. The hypothesis of changes in porpoise distribution was consistent with local visual surveys, mostly SCANS surveys (1994 and 2005). This new indicator could be applied to cetacean populations across the world and more widely to marine megafauna

Using social media to find places of interest

In this paper, we show how the large amount of geographically annotated data in social media can be used to complement existing place databases. After explaining our method, we illustrate how this approach can be used to discover new instances of a given semantic type, using London as a case study. In particular, for several place types, our method finds places in London that are not yet contained in the databases used by Foursquare, Google, LinkedGeoData and Geonames. Encouraged by these results, we briefly sketch how similar techniques could potentially be used to identify likely errors in existing databases, to estimate the spatial extent of places, to discover semantic relationships between place types, and to recommend tags to users who are uploading photos