Bills Favor Mining and Threaten Conservation of Brazilian Merganser (Mergus octosetaceus) at Serra da Canastra National Park, Minas Gerais, Brazil

Serra da Canastra National Park (SCNP) is one of the most important protected areas in the Cerrado biome. Despite its importance to the conservation of rare and endangered species like Brazilian Merganser, two bills were approved in 2010 by Brazil's Chamber of Deputies aiming to reduce SCNP's official boundaries and to transform some of its parts into an Environmental Protection Area (EPA). We evaluated whether such changes would facilitate mining areas to be legally exploited within the park's area, and if those mining areas would represent a threat to Brazilian Merganser populations at SCNP. Results showed that 55% of the mining areas currently within the National Park will be located within the new EPA, and six hydrographic micro-basins inhabited by Brazilian Merganser could be affected by environmental impacts caused by mineral exploitation in those areas. For these reasons, we recommend the two bills be refused at the Federal Senate.

Partitioning and extraction of collagenase from Penicillium aurantiogriseum in poly(ethylene glycol)/phosphate aqueous two-phase system

Purification of collagenase produced by Penicillium aurantiogriseum URM4622 was carried using a PEG/phosphate aqueous two-phase system (ATPS). A 2(3)-full experimental design was used to investigate the influence of PEG molar mass, PEG concentration and phosphate concentration on the selected responses, namely partition coefficient, activity yield and purification factor. The ATPS was composed of PEG (molar mass of 550, 1500 and 4000 g/mol) at concentrations of 15.0, 17.5 and 20.0% (w/w) and phosphate at concentrations of 12.5, 15.0 and 17.5% (w/w). The best results of one-step extraction of collagenase from the fermentation broth (partition coefficient of 1.01, activity yield of 242% and purification factor of 23.5) were obtained at pH 6.0 using 20.0% (w/w) PEG 550 and 17.5% (w/w) phosphate. The results of this preliminary study demonstrate that the selected ATPS is satisfactorily selective for the extraction of such a collagenase. (C) 2012 Elsevier B.V. All rights reserved.

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.

Soil compressibility and least limiting water range of a constructed soil under cover crops after coal mining in Southern Brazil

The use of cover crops affects the support capacity of soil and least limiting water range to crop growth. The objective of this study was to quantify preconsolidation pressure (sigma(p)), compression index (CI) and least limiting water range (LLWR) of a reclaimed coal mining soil under different cover crops, in Candiota, RS, Brazil. In the experiment, with randomized blocks design and four replicates, the following cover crops (treatments) were evaluated: Hemarthria altissima (Poir.) Stapf & C.E. Hubbard, treatment 1 (T1), Paspalum notatum Flugge, treatment 4 (T4), Cynodon dactilon (L) Pers., treatment 5 (T5), control Brachiaria brizantha (Hochst.) Stapf, treatment 7 (T7) and without cover crop treatment 8 (reference treatment, T8). Soil compression and least limiting water range were evaluated with undisturbed samples at a depth of 0.00-0.05 m. In order to evaluate parameters of soil compressibility, the soil samples were saturated with water and subjected to -10 kPa matric potential and then submitted to a uniaxial compression test under the following pressures: 25, 50, 100, 200, 400, 800 and 1600 kPa. Cover crops decreased the preconsolidation pressure of constructed soils after coal mining and the greatest soil reclamation was obtained with the H. altissima cover crop, where the lowest degree of soil compactness and soil load capacity were observed. Soils cultivated under H. altissima or B. brizantha presented the highest least limiting water range and these two cover crops generated similar soil critical bulk density obtained by least limiting water range and soil load support capacity. (C) 2012 Elsevier B.V. All rights reserved.

Comparison of extraction and transesterification methods on the determination of the fatty acid contents of three Brazilian seaweed species

Seaweeds are photosynthetic organisms important to their ecosystem and constitute a source of compounds with several different applications in the pharmaceutical, cosmetic and biotechnology industries, such as triacylglycerols, which can be converted to fatty acid methyl esters that make up biodiesel, an alternative source of fuel applied in economic important areas. This study evaluates the fatty acid profiles and concentrations of three Brazilian seaweed species, Hypnea musciformis (Wulfen) J.V. Lamouroux (Rhodophya), Sargassum cymosum C. Agardh (Heterokontophyta), and Ulva lactuca L. (Chlorophyta), comparing three extraction methods (Bligh & Dyer - B&D; AOAC Official Methods - AOM; and extraction with methanol and ultrasound - EMU) and two transesterification methods (7% BF3 in methanol - BF3; and 5% HCl in methanol - HCl). The fatty acid contents of the three species of seaweeds were significantly different when extracted and transesterified by the different methods. Moreover, the best method for one species was not the same for the other species. The best extraction and transesterification methods for H. musciformis, S. cymosum and U. lactuca were, respectively, AOM-HCl, B&D-BF3 and B&D-BF3/B&D-HCl. These results point to a matrix effect and the method used for the analysis of the fatty acid content of different organisms should be selected carefully.

ISOLATION AND CHARACTERISTICS OF EIGHT NOVEL POLYMORPHIC MICROSATELLITE LOCI IN LIPPIA ALBA (VERBENACEAE)

Premise of the study: A set of eight microsatellite (simple sequence repeat [SSR]) markers for Lippia alba, an important medicinal and cosmetic plant, was developed to aid studies of genetic diversity and to define efficient strategies for breeding programs. Methods and Results: Using a (CT)(8)- and (GT)(8)-enriched library, a total of 11 SSR loci were developed and optimized in L. alba. Of the 11 loci, eight were found to be polymorphic after screening 61 accessions from two populations. The parameters used to characterize loci were expected heterozygosity (H-e) and number of alleles. A total of 44 alleles were identified, with an average of 5.5 alleles per loci, which were moderately to highly informative according to H-e. Conclusions: These new SSR markers have potential for informing genetic diversity, allele mining, and mapping studies and will be used to generate information for breeding programs of L. alba

Sedimentary processes on the NW Iberian Continental Shelf since the Little Ice Age

The OMEX core CD110 W90, retrieved from the Douro Mud Patch (DMP) off the River Douro in the north of Portugal, records the period since the beginning of Little Ice Age (LIA). The core chronology is based upon the data attributes for Pb-210, Cs-137 and a C-14 dating from a level near the core base. Geochemical, granulometric, microfaunal (benthic foraminifera) and compositional data suggest the occurrence of precipitation changes which may have been, at least partially, influenced by the North Atlantic Oscillation (NAO), that contributes to the regulation of the ocean-atmosphere dynamics in the North Atlantic. Southwesterly Atlantic storm track is associated with the negative phases of the NAO, when the Azores High is anomalously weak, higher oceanographic hydrodynamism, downwelling events and increased rainfall generally occurs. Prevalence of these characteristics during the LIA left a record that corresponds to phases of major floods. During these phases the DMP received a higher contribution of relatively coarse-grained terrigenous sediments, enriched in quartz particles, which diluted the contribution of other minerals, as indicated by reduced concentrations of several lithogenic chemical elements such as: Al, As, Ba, Ce, Co, Cu, Fe, K, La, Li, Mg, Mn, Mo, Na, Ni, P, Rb, Sc, Sn, Th, V and Y. The presence of biogenic carbonate particles also underwent dilution, as revealed by the smaller abundance of foraminifera and correlative lower concentrations of Ca and Sr. During this period, the DMP also received an increased contribution of organic matter, indicated by higher values of lignin remains and a benthic foraminifera high productivity index, or BFHP, which gave rise to early diagenetic changes with pyrite formation. Since the beginning of the 20th century this contribution diminished, probably due to several drier periods and the impact of human activities in the river basins, e.g. construction of dams, or, on the littoral areas, construction of hard-engineering structures and sand extraction activities. During the first half of the 20th century mainly positive phases of the NAO prevailed, caused by the above normal strengthening of the subtropical high pressure centre of the Azores and the deepening of the low pressure centre in Iceland. These phases may have contributed to the reduction in the supply of both terrigenous sediments and organic matter from shallow water to the DMP. During the positive phases of the NAO, sedimentation became finer. The development of mining and industrial activities during the 20th century is marked, in this core, by higher concentrations of Pb. Furthermore, the erosion of heaps resulting from wolfram exploitation leaves its signature as a peak of W concentrations recorded in the sediments of the DMP deposited between the 1960s and the 1990s. Wolfram exploitation was an important activity in the middle part of the 20th century, particularly during the period of the Second World War. (C) 2012 Elsevier Ltd. All rights reserved.

Hollow-fiber liquid-phase microextraction of amphetamine-type stimulants in human hair samples

A fast method was optimized and validated in order to quantify amphetamine-type stimulants (amphetamine, AMP; methamphetamine, MAMP; fenproporex, FPX; 3,4-methylenedioxymethamphetamine, MDMA; and 3,4-methylenedioxyamphetamine, MDA) in human hair samples. The method was based in an initial procedure of decontamination of hair samples (50 mg) with dichloromethane, followed by alkaline hydrolysis and extraction of the amphetamines using hollow-fiber liquid-phase micro extraction (HF-LPME) in the three-phase mode. Gas chromatography-mass spectrometry (GC-MS) was used for identification and quantification of the analytes. The LoQs obtained for all amphetamines (around 0.05 ng/mg) were below the cut-off value (0.2 ng/mg) established by the Society of Hair Testing (SoHT). The method showed to be simple and precise. The intra-day and inter-day precisions were within 10.6% and 11.4%, respectively, with the use of only two deuteratecl internal standards (AMP-d5 and MDMA-d5). By using the weighted least squares linear regression (1/x(2)), the accuracy of the method was satisfied in the lower concentration levels (accuracy values better than 87%). Hair samples collected from six volunteers who reported regular use of amphetamines were submitted to the developed method. Drug detection was observed in all samples of the volunteers. (c) 2012 Elsevier B.V. All rights reserved.

Seeing beyond reading: a survey on visual text analytics

We review recent visualization techniques aimed at supporting tasks that require the analysis of text documents, from approaches targeted at visually summarizing the relevant content of a single document to those aimed at assisting exploratory investigation of whole collections of documents.Techniques are organized considering their target input materialeither single texts or collections of textsand their focus, which may be at displaying content, emphasizing relevant relationships, highlighting the temporal evolution of a document or collection, or helping users to handle results from a query posed to a search engine.We describe the approaches adopted by distinct techniques and briefly review the strategies they employ to obtain meaningful text models, discuss how they extract the information required to produce representative visualizations, the tasks they intend to support and the interaction issues involved, and strengths and limitations. Finally, we show a summary of techniques, highlighting their goals and distinguishing characteristics. We also briefly discuss some open problems and research directions in the fields of visual text mining and text analytics.

Rehabilitation with forage grasses of an area degraded by urban solid waste deposits

Dry matter yield and chemical composition of forage grasses harvested from an area degraded by urban solid waste deposits were evaluated. A split-plot scheme in a randomized block design with four replicates was used, with five grasses in the plots and three harvests in the subplots. The mineral content and extraction and heavy metal concentration were evaluated in the second cut, using a randomized block design with five grasses and four replicates. The grasses were Brachiaria decumbens cv. Basilisk, Brachiaria ruziziensis, Brachiaria brizantha cv. Marandu and cv. Xaraés, and Panicum maximum cv. Tanzânia, cut at 42 days of regrowth. The dry matter yield per cut reached 1,480 kg ha-1; the minimum crude protein content was 9.5% and the average neutral detergent fiber content was 62.3%. The dry matter yield of grasses was satisfactory, and may be an alternative for rehabilitating areas degraded by solid waste deposits. The concentration of heavy metals in the plants was below toxicity levels; the chemical composition was appropriate, except for phosphorus. The rehabilitated areas may therefore be used for grazing.

The humankind genome: from genetic diversity to the origin of human diseases

Genome-wide association studies have failed to establish common variant risk for the majority of common human diseases. The underlying reasons for this failure are explained by recent studies of resequencing and comparison of over 1200 human genomes and 10 000 exomes, together with the delineation of DNA methylation patterns (epigenome) and full characterization of coding and noncoding RNAs (transcriptome) being transcribed. These studies have provided the most comprehensive catalogues of functional elements and genetic variants that are now available for global integrative analysis and experimental validation in prospective cohort studies. With these datasets, researchers will have unparalleled opportunities for the alignment, mining, and testing of hypotheses for the roles of specific genetic variants, including copy number variations, single nucleotide polymorphisms, and indels as the cause of specific phenotypes and diseases. Through the use of next-generation sequencing technologies for genotyping and standardized ontological annotation to systematically analyze the effects of genomic variation on humans and model organism phenotypes, we will be able to find candidate genes and new clues for disease’s etiology and treatment. This article describes essential concepts in genetics and genomic technologies as well as the emerging computational framework to comprehensively search websites and platforms available for the analysis and interpretation of genomic data.

CID: an efficient complexity-invariant distance for time series

The ubiquity of time series data across almost all human endeavors has produced a great interest in time series data mining in the last decade. While dozens of classification algorithms have been applied to time series, recent empirical evidence strongly suggests that simple nearest neighbor classification is exceptionally difficult to beat. The choice of distance measure used by the nearest neighbor algorithm is important, and depends on the invariances required by the domain. For example, motion capture data typically requires invariance to warping, and cardiology data requires invariance to the baseline (the mean value). Similarly, recent work suggests that for time series clustering, the choice of clustering algorithm is much less important than the choice of distance measure used.In this work we make a somewhat surprising claim. There is an invariance that the community seems to have missed, complexity invariance. Intuitively, the problem is that in many domains the different classes may have different complexities, and pairs of complex objects, even those which subjectively may seem very similar to the human eye, tend to be further apart under current distance measures than pairs of simple objects. This fact introduces errors in nearest neighbor classification, where some complex objects may be incorrectly assigned to a simpler class. Similarly, for clustering this effect can introduce errors by “suggesting” to the clustering algorithm that subjectively similar, but complex objects belong in a sparser and larger diameter cluster than is truly warranted.We introduce the first complexity-invariant distance measure for time series, and show that it generally produces significant improvements in classification and clustering accuracy. We further show that this improvement does not compromise efficiency, since we can lower bound the measure and use a modification of triangular inequality, thus making use of most existing indexing and data mining algorithms. We evaluate our ideas with the largest and most comprehensive set of time series mining experiments ever attempted in a single work, and show that complexity-invariant distance measures can produce improvements in classification and clustering in the vast majority of cases.