High prevalence and low female/male ratio for validated centenarians are observed in Sardinia and these findings appear to be thus far unique to this island. Moreover a specific region on the island is characterized by exceptional male longevity. We calculated the extreme longevity index (ELI), defined as the percentage of persons born in Sardinia between 1880 and 1900, who became centenarians. A gaussian smoothing method was used in order to identify the so-called 'Blue Zone', where longevity is concentrated in the central-eastern part of the island and covers all the mountainous areas of central Sardinia. The estimated life expectancy in the 'Blue Zone' is longer than in the remaining territory of the island especially for men and the male to female ratio among centenarians born in this area is 1.35 compared to 2.43 in the rest of Sardinia. The specific mechanism by which persons living in this territory were more likely to reach extreme longevity remains unknown but it is interesting to note that most of the 'longevity hot spots' identified in various regions of the world over the years have been located in mountainous geographical areas even if none of these longevity regions have been fully validated. An alternative and interesting hypothesis is that the high rate of inbreeding determined by frequent marriages between consanguineous individuals and low immigration rates have progressively decreased the variability of the genetic pool and facilitated the emergence of genetic characteristics that protect individuals from diseases that are major causes of mortality particularly in older individuals. Given the exceptionally high prevalence of male centenarians in the 'Blue Zone', it is reasonable to assume that either the environmental characteristics or the genetic factors, or both, exert their favorable effect more strongly in men than in women. Thus, the mechanism involved may be modulated by the hormonal milieu, or may be associated with genes located in the sex chromosomes.
This article proposes a quantitative model of the circulation of foreign news based on a gravity-like model of spatial interaction disaggregated by time, media, and countries of interest. The analysis of international RSS news stories published by 31 daily newspapers in 2015 demonstrates, first, that many of the laws of circulation of international news predicted half a century ago by Galtung and Ruge and by Östgaard are still valid. The salience of countries in media remains strongly determined by size effects (area, population), with prominent coverage of rich countries (GDP/capita) with elite status (permanent members of United Nations Security Council, the Holy See). The effect of geographical distance and a common language remains a major factor of media coverage in newsrooms. Contradicting the flat world hypothesis, global journalism remains an exception, and provincialism is the rule. The disaggregation of the model by media demonstrates that newspapers are not following exactly the same rules and are more or less sensitive to distance, a common language or elite status. The disaggregation of the model by week suggests that the rules governing foreign news can be temporarily modified by exceptional events that eliminate the usual effects of salience and relatedness, producing short periods of “global consensus” that can benefit small, poor, and remote countries. The residuals of the model help to identify countries that are characterized by a permanent excess of media coverage (like the US or the Australia in our sample) or media that received a coverage more important than usual during several months (Yemen, Ukraine) or years (Syria, Greece) because a situation of long-term political or economic crisis.
The full integration of time dimensions in GIS still represents a research challenge. A number of systems provide ways to visualise harmonised timestamped geographical data onto maps, with interpolated curves representing how these data have changed over time. However, these systems frequently mask the concerns linked to changes in territorial organisations and the harmonisation of data. In fact, the development of a territory should be considered in connection with its neighbourhood, governance and genealogy relationships. This article focuses on the difficulties linked with the 'change of support problem', which can arise when conducting spatio-temporal analysis of data. First, we present a data model handling the changing relationships between territories. Then, we illustrate how this model can be instantiated using examples that have taken place in Europe. We show how the model can address questions such as that of change blindness. Finally, we explain how hierarchical and genealogical relationships can be used inside an interactive cartographic tool for spatio-temporal analysis. It provides various views of the same phenomena at multiple scales, through an approach that takes into account the changes in territorial organisation.
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