Recent shift from forest to savanna burning in the Amazon Basin observed by satellite

The numbers of fires detected on forest, savanna and transition lands during the 2002-10 biomass burning seasons in Amazonia are shown using fire count data and co-located land cover classifications from the Moderate Resolution Imaging Spectroradiometer (MODIS). The ratio of forest fires to savanna fires has varied substantially over the study period, with a maximum ratio of 0.65:1 in 2005 and a minimum ratio of 0.27:1 in 2009, with the four lowest years occurring in 2007-10. The burning during the droughts of 2007 and 2010 is attributed to a higher number of savanna fires relative to the drought of 2005. A decrease in the regional mean single scattering albedo of biomass burning aerosols, consistent with the shift from forest to savanna burning, is also shown. During the severe drought of 2010, forest fire detections were lower in many areas compared with 2005, even though the drought was more severe in 2010. This result suggests that improved fire management practices, including stricter burning regulations as well as lower deforestation burning, may have reduced forest fires in 2010 relative to 2005 in some areas of the Amazon Basin.

Study of La2-xCaxCuO4 perovskites for the low temperature water gas shift reaction

The effects of small fractions of calcium (x = 0, 0.05, 0.1, 0.15, and 0.20) on the structure and the catalytic properties of La2-xCaxCuO4 peroviskites have been investigated. The samples have been synthesized using the co-precipitation method. Perovskite-type oxides were characterized by XRD, TPR, XPS, XANES, SEM, and TEM. Catalytic tests for the water gas shift reaction (WGSR) were carried out in a tubular reactor at 290 degrees C. All samples showed a well-defined perovskite structure with surface areas between 6 and 18 m(2) g(-1). The partial substitution of La by Ca enhanced the stability of the perovskites and increased their reduction temperature. All catalysts were actives for WGSR, and the best catalytic performance was obtained for the La1.85Ca0.15CuO4 catalyst, but the samples with 5 and 10% of Ca had the best TOF values for reaction. These results can be associated to promoter effect of calcium, the high surface area, and the reducible species Cu-0 and Cu1+. (C) 2011 Elsevier B.V. All rights reserved.

Spectral behavior of some modal soil profiles from São Paulo State, Brazil

Remote sensing has a high potential for environmental evaluation. However, a necessity exists for a better understanding of the relations between the soil attributes and spectral data. The objective of this work was to analyze the spectral behavior of some soil profiles from the region of Piracicaba, São Paulo State, using a laboratory spectroradiometer (400 to 2500 nm). The relations between the reflected electromagnetic energy and the soil physical, chemical and mineralogical attributes were analyzed, verifying the spectral variations of soil samples in depth along the profiles with their classification and discrimination. Sandy soil reflected more, presenting a spectral curve with an ascendant form, opposite to clayey soils. The 1900 nm band discriminated soil with 2:1 mineralogy from the 1:1 and oxidic soils. It was possible to detect the presence of kaolinite, gibbsite, hematite and goethite in the soils through the descriptive aspects of curves, absorption features and reflectance intensity. A relation exists between the weathering stage and spectral data. The evaluation of the superficial and subsuperficial horizon samples allowed characterizing and discriminating the analytical variability of the profile, helping to soil distinguishing and classification.

Natural blood feeding and temperature shift modulate the global transcriptional profile of Rickettsia rickettsii infecting its tick vector

Rickettsia rickettsii is an obligate intracellular tick-borne bacterium that causes Rocky Mountain Spotted Fever (RMSF), the most lethal spotted fever rickettsiosis. When an infected starving tick begins blood feeding from a vertebrate host, R. rickettsii is exposed to a temperature elevation and to components in the blood meal. These two environmental stimuli have been previously associated with the reactivation of rickettsial virulence in ticks, but the factors responsible for this phenotype conversion have not been completely elucidated. Using customized oligonucleotide microarrays and high-throughput microfluidic qRT-PCR, we analyzed the effects of a 10 degrees C temperature elevation and of a blood meal on the transcriptional profile of R. rickettsii infecting the tick Amblyomma aureolatum. This is the first study of the transcriptome of a bacterium in the genus Rickettsia infecting a natural tick vector. Although both stimuli significantly increased bacterial load, blood feeding had a greater effect, modulating five-fold more genes than the temperature upshift. Certain components of the Type IV Secretion System (T4SS) were up-regulated by blood feeding. This suggests that this important bacterial transport system may be utilized to secrete effectors during the tick vector's blood meal. Blood feeding also up-regulated the expression of antioxidant enzymes, which might correspond to an attempt by R. rickettsii to protect itself against the deleterious effects of free radicals produced by fed ticks. The modulated genes identified in this study, including those encoding hypothetical proteins, require further functional analysis and may have potential as future targets for vaccine development.

QuMinS: fast and scalable querying, mining and summarizing multi-modal databases

Given a large image set, in which very few images have labels, how to guess labels for the remaining majority? How to spot images that need brand new labels different from the predefined ones? How to summarize these data to route the user’s attention to what really matters? Here we answer all these questions. Specifically, we propose QuMinS, a fast, scalable solution to two problems: (i) Low-labor labeling (LLL) – given an image set, very few images have labels, find the most appropriate labels for the rest; and (ii) Mining and attention routing – in the same setting, find clusters, the top-'N IND.O' outlier images, and the 'N IND.R' images that best represent the data. Experiments on satellite images spanning up to 2.25 GB show that, contrasting to the state-of-the-art labeling techniques, QuMinS scales linearly on the data size, being up to 40 times faster than top competitors (GCap), still achieving better or equal accuracy, it spots images that potentially require unpredicted labels, and it works even with tiny initial label sets, i.e., nearly five examples. We also report a case study of our method’s practical usage to show that QuMinS is a viable tool for automatic coffee crop detection from remote sensing images.