Forest fires cluster detection with space-time scan statistics

Forest fires are defined as uncontrolled fires often occurring in wildland areas, but that can also affect houses or agricultural resources. Causes are both natural (e.g.,lightning phenomena) and anthropogenic (human negligence or arsons).Major environmental factors influencing the fire ignition and propagation are climate and vegetation. Wildfires are most common and severe during drought period and on windy days. Moreover, under water-stress conditions, which occur after a long hot and dry period, the vegetation is more vulnerable to fire. These conditions are common in the United State and Canada, where forest fires represent a big problem. We focused our analysis on the state of Florida, for which a big dataset on forest fires detection is readily available. USDA Forest Service Remote Sensing Application Center, in collaboration with NASA-Goddard Space Flight Center and the University of Maryland, has compiled daily MODIS Thermal Anomalies (fires and biomass burning images) produced by NASA using a contextual algorithm that exploits the strong emission of mid-infrared radiation from fires. Fire classes were converted in GIS format: daily MODIS fire detections are provided as the centroids of the 1 kilometer pixels and compiled into daily Arc/INFO point coverage.

Qualité des statistiques de causes de décès: problèmes actuels et perspectives. [Quality of statistics on causes of death: current problems and perspectives].

Statistics of causes of death remain an important source of epidemiological data for the evaluation of various medical and health problems. The improvement of analytical techniques and, above all, the transformation of demographic and morbid structures of populations have prompted researchers in the field to give more importance to the quality of death certificates. After describing the data collection system presently used in Switzerland, the paper discusses various indirect estimations of the quality of Swiss data and reviews the corresponding international literature.

Adverse effects of industrial multiwalled carbon nanotubes on human pulmonary cells

The aim of this study was to evaluate adverse effects of multiwalled carbon nanotubes (MWCNT), produced for industrial purposes, on the human epithelial cell line A549. MWCNT were dispersed in dipalmitoyl lecithin (DPL), a component of pulmonary surfactant, and the effects of dispersion in DPL were compared to those in two other media: ethanol (EtOH) and phosphate-buffered saline (PBS). Effects of MWCNT were also compared to those of two asbestos fibers (chrysotile and crocidolite) and carbon black (CB) nanoparticles, not only in A549 cells but also in mesothelial cells (MeT5A human cell line), used as an asbestos-sensitive cell type. MWCNT formed agglomerates on top of both cell lines (surface area 15-35 μm2) that were significantly larger and more numerous in PBS than in EtOH and DPL. Whatever the dispersion media, incubation with 100 μg/ml MWCNT induced a similar decrease in metabolic activity without changing cell membrane permeability or apoptosis. Neither MWCNT cellular internalization nor oxidative stress was observed. In contrast, asbestos fibers penetrated into the cells, decreased metabolic activity but not cell membrane permeability, and increased apoptosis, without decreasing cell number. CB was internalized without any adverse effects. In conclusion, this study demonstrates that MWCNT produced for industrial purposes exert adverse effects without being internalized by human epithelial and mesothelial pulmonary cell lines. [Authors]