Indoor and outdoor atmospheric fungal spores in the So Paulo metropolitan area (Brazil): species and numeric concentrations

The aim of this study was to estimate the indoor and outdoor concentrations of fungal spores in the Metropolitan Area of Sao Paulo (MASP), collected at different sites in winter/spring and summer seasons. The techniques adopted included cultivation (samples collected with impactors) and microscopic enumeration (samples collected with impingers). The overall results showed total concentrations of fungal spores as high as 36,000 per cubic meter, with a large proportion of non culturable spores (around 91% of the total). Penicillium sp. and Aspergillus sp. were the dominant species both indoors and outdoors, in all seasons tested, occurring in more than 30% of homes at very high concentrations of culturable airborne fungi [colony forming units(CFU) m(-3)]. There was no significant difference between indoor and outdoor concentrations. The total fungal spore concentration found in winter was 19% higher than that in summer. Heat and humidity were the main factors affecting fungal growth; however, a non-linear response to these factors was found. Thus, temperatures below 16A degrees C and above 25A degrees C caused a reduction in the concentration (CFU m(-3)) of airborne fungi, which fits with MASP climatalogy. The same pattern was observed for humidity, although not as clearly as with temperature given the usual high relative humidity (above 70%) in the study area. These results are relevant for public health interventions that aim to reduce respiratory morbidity among susceptible populations.

Future change of climate in South America in the late twenty-first century: intercomparison of scenarios from three regional climate models

Regional climate change projections for the last half of the twenty-first century have been produced for South America, as part of the CREAS (Cenarios REgionalizados de Clima Futuro da America do Sul) regional project. Three regional climate models RCMs (Eta CCS, RegCM3 and HadRM3P) were nested within the HadAM3P global model. The simulations cover a 30-year period representing present climate (1961-1990) and projections for the IPCC A2 high emission scenario for 2071-2100. The focus was on the changes in the mean circulation and surface variables, in particular, surface air temperature and precipitation. There is a consistent pattern of changes in circulation, rainfall and temperatures as depicted by the three models. The HadRM3P shows intensification and a more southward position of the subtropical Pacific high, while a pattern of intensification/weakening during summer/winter is projected by the Eta CCS/RegCM3. There is a tendency for a weakening of the subtropical westerly jet from the Eta CCS and HadRM3P, consistent with other studies. There are indications that regions such of Northeast Brazil and central-eastern and southern Amazonia may experience rainfall deficiency in the future, while the Northwest coast of Peru-Ecuador and northern Argentina may experience rainfall excesses in a warmer future, and these changes may vary with the seasons. The three models show warming in the A2 scenario stronger in the tropical region, especially in the 5A degrees N-15A degrees S band, both in summer and especially in winter, reaching up to 6-8A degrees C warmer than in the present. In southern South America, the warming in summer varies between 2 and 4A degrees C and in winter between 3 and 5A degrees C in the same region from the 3 models. These changes are consistent with changes in low level circulation from the models, and they are comparable with changes in rainfall and temperature extremes reported elsewhere. In summary, some aspects of projected future climate change are quite robust across this set of model runs for some regions, as the Northwest coast of Peru-Ecuador, northern Argentina, Eastern Amazonia and Northeast Brazil, whereas for other regions they are less robust as in Pantanal region of West Central and southeastern Brazil.

The energy and water balance of a Eucalyptus plantation in southeast Brazil

The eddy covariance method was used to measure energy and water balance of a plantation of Eucalyptus (grandis x urophylla) hybrids over a 2 year period. The average daily evaporation rates were 5.4 (+/- 2.0) mm day(-1) in summer, but fell to 1.2 (+/- 0.3) mm day(-1) in winter. In contrast, the sensible heat flux was relatively low in summer but dominated the energy balance in winter. Evaporation accounted for 80% and 26% of the available energy, in summer and winter respectively. The annual evaporation was 82% (1124 mm) and 96% (1235 mm) of the annual rainfall recorded during the first and second year, respectively. Daily average canopy and aerodynamic conductance to water vapour were in the summer 51.9 (+/- 38.4) mm s(-1) 84.1 (+/- 25.6) mm s(-1), respectively; and in the winter 6.0 (+/- 10.5) mm s(-1) and 111.6 (+/- 24.6) mm s(-1), respectively. (C) 2010 Elsevier B.V. All rights reserved.

Drizzle and Fog Analysis in the Sao Paulo Metropolitan Area: Changes 1933-2005 and Correlations with other Climate Factors

In order to improve our understanding of climate change, the aim of this research project was to study the climatology and the time trends of drizzle and fog events in the Sao Paulo Metropolitan Area, and the possible connections of this variability with the sea surface temperature (SST) of the Atlantic and Pacific Oceans. The climatology of both phenomena presents differences and similarities. Fog shows a marked maximum frequency in winter and a minimum frequency in summer, while the seasonal differences of drizzle occurrence are less pronounced, there is a maximum in spring, whereas the other seasons present smaller and similar numbers of events. Both phenomena present a negative trend from 1933 to 2005 which is stronger for fog events. A multivariate statistical analysis indicates that the South Atlantic SST could increase warm temperature advection to the continent. This could be one of the responsible factors for the negative tendency in the number of both fog and drizzle events.

Kappaphycus alvarezii (Rhodophyta, Areschougiaceae) cultivated in subtropical waters in Southern Brazil

Four strains of Kappaphycus alvarezii were cultivated in the subtropical waters of Florianopolis, Santa Catarina State, Brazil (27 degrees 29`19 `` S/48 degrees 32` 28 `` W), from February 2009 to February 2010. Seaweeds were cultivated on floating raft near of mussel farms. Salinity ranged from 29 to 36 psu and temperature from 17.1 to 28.5 degrees C. Higher growth rates (5.12-4.29% day(-1)) were measured in summer and autumn, showing a positive correlation between growth rate and water temperature. Lower growth rates (0.54-0.32% day(-1)) occurred in winter, resulted mainly by biomass loss. Significant differences were observed among the strains in spring and the brown tetrasporophytic strain was the only one which failed to recover, being excluded of the experiments. The effect of cultivation periods (36, 42, and 97 days) on carrageenan yield, gel strength, and viscosity were analyzed. Carrageenan yields were higher for plants kept 42 days in the sea (28%), against 25% for 36 and 97 days. There were no significant differences in carrageenan yield among the strains analyzed. Viscosity increased with the increase of cultivation period, while gel strength seemed to vary at random. Tetrasporangia and cystocarps were not observed, and lost fragments did not attach outside the raft. In general, dissolved inorganic nitrogen concentration decreased around the cultivation area as compared to the mussel farm. Results show that cultivation of K. alvarezii is technically feasible in subtropical waters and can be associated with local mussel farms, mitigating the eutrophication and, eventually, increasing the economic return of the farmers.

Paracoccidioidomycosis-related mortality trend, state of Sao Paulo, Brazil: a study using multiple causes of death

Objective. To investigate mortality in which paracoccidioidomycosis appears on any line or part of the death certificate. Method. Mortality data for 1985-2005 were obtained from the multiple cause-of-death database maintained by the Sao Paulo State Data Analysis System (SEADE). Standardized mortality coefficients were calculated for paracoccidioidomycosis as the underlying cause-of-death and as an associated cause-of-death, as well as for the total number of times paracoccidioidomycosis was mentioned on the death certificates. Results. During this 21-year period, there were 1950 deaths related to paracoccidioidomycosis; the disease was the underlying cause-of-death in 1 164 cases (59.69%) and an associated cause-of-death in 786 (40.31%). Between 1985 and 2005 records show a 59.8% decline in the mortality coefficient due to paracoccidioidomycosis as the underlying cause and a 53.0% decline in the mortality as associated cause. The largest number of deaths occurred among men, in the older age groups, and among rural workers, with an upward trend in winter months. The main causes associated with paracoccidioidomycosis as the underlying cause-of-death were pulmonary fibrosis, chronic lower respiratory tract diseases, and pneumonias. Malignant neoplasms and AIDS were the main underlying causes when paracoccidioidomycosis was an associated cause-of-death. The decision tables had to be adapted for the automated processing of causes of death in death certificates where paracoccidioidomycosis was mentioned. Conclusions. Using the multiple cause-of-death method together with the traditional underlying cause-of-death approach provides a new angle on research aimed at broadening our understanding of the natural history of paracoccidioidomycosis.

A Road Following Approach Using Artificial Neural Networks Combinations

Navigation is a broad topic that has been receiving considerable attention from the mobile robotic community over the years. In order to execute autonomous driving in outdoor urban environments it is necessary to identify parts of the terrain that can be traversed and parts that should be avoided. This paper describes an analyses of terrain identification based on different visual information using a MLP artificial neural network and combining responses of many classifiers. Experimental tests using a vehicle and a video camera have been conducted in real scenarios to evaluate the proposed approach.