Inorganic arsenic in Chinese food and its cancer risk

Even moderate arsenic exposure may lead to health problems, and thus quantifying inorganic arsenic (iAs) exposure from food for different population groups in China is essential. By analyzing the data from the China National Nutrition and Health Survey (CNNHS) and collecting reported values of iAs in major food groups, we developed a framework of calculating average iAs daily intake for different regions of China. Based on this framework, cancer risks from As in food was deterministically and probabilistically quantified. The article presents estimates for health risk due to the ingestion of food products contaminated with arsenic. Both per individual and for total population estimates were obtained. For the total population, daily iAs intake is around 42 mu g day(-1), and rice is the largest contributor of total iAs intake accounting for about 60%. Incremental lifetime cancer risk from food iAs intake is 106 per 100,000 for adult individuals and the median population cancer risk is 177 per 100,000 varying between regions. Population in the Southern region has a higher cancer risk than that in the Northern region and the total population. Sensitive analysis indicated that cancer slope factor, ingestion rates of rice, aquatic products and iAs concentration in rice were the most relevant variables in the model, as indicated by their higher contribution to variance of the incremental lifetime cancer risk. We conclude that rice may be the largest contributor of iAs through food route for the Chinese people. The population from the South has greater cancer risk than that from the North and the whole population. (C) 2011 Elsevier Ltd. All rights reserved.

Il Piano della Performance 2011-2013 dei Comuni italiani di medie e grandi dimensioni: allineamento normativo e adeguatezza programmatica in ottica economico-aziendale

Il presente lavoro intende individuare le possibili configurazioni di Piano della Performance (PdP) utilizzabili dagli enti locali, provvedendo poi a delineare il livello di distribuzione e di allineamento dei PdP 2011-2013 dei Comuni medi e grandi rispetto alle suddette configurazioni. Inoltre, verrà valutato, tramite una griglia predisposta dagli autori, il livello di adeguatezza programmatica dei Piani della Performance dei Comuni medi e grandi, al fine di confermare le configurazioni esistenti o di proporne una nuova in caso di inadeguatezza delle prime.

Outgassing Behavior of C/2012 S1 (ISON) from 2011 September to 2013 June

We report photometric observations for comet C/2012 S1 (ISON) obtained during the time period immediately after discovery (r = 6.28 AU) until it moved into solar conjunction in mid-2013 June using the UH2.2 m, and Gemini North 8 m telescopes on Mauna Kea, the Lowell 1.8 m in Flagstaff, the Calar Alto 1.2 m telescope in Spain, the VYSOS-5 telescopes on Mauna Loa Hawaii and data from the CARA network. Additional pre-discovery data from the Pan STARRS1 survey extends the light curve back to 2011 September 30 (r = 9.4 AU). The images showed a similar tail morphology due to small micron sized particles throughout 2013. Observations at submillimeter wavelengths using the James Clerk Maxwell Telescope on 15 nights between 2013 March 9 (r = 4.52 AU) and June 16 (r = 3.35 AU) were used to search for CO and HCN rotation lines. No gas was detected, with upper limits for CO ranging between 3.5-4.5 × 1027 molecules s-1. Combined with published water production rate estimates we have generated ice sublimation models consistent with the photometric light curve. The inbound light curve is likely controlled by sublimation of CO2. At these distances water is not a strong contributor to the outgassing. We also infer that there was a long slow outburst of activity beginning in late 2011 peaking in mid-2013 January (r ~ 5 AU) at which point the activity decreased again through 2013 June. We suggest that this outburst was driven by CO injecting large water ice grains into the coma. Observations as the comet came out of solar conjunction seem to confirm our models.