The Relationship between Authors and Main Thematic Categories in the Field of Knowledge Organization: A Bibliometric Approach

This is a study about the relationships between authors and the main thematic categories in the papers published in the last five International ISKO Conferences, held between 2002 and 2010. The aim is to map the domain as ISKO conferences are considered the most representative forum in the field. The published papers are considered to indicate the relationships between authors and themes. The Classification Scheme for Knowledge Organization Error! Bookmark not defined Literature (CSKOL) was used to categorize the papers. The theoretical and methodological foundations of the study can be found in the concept of domain analysis proposed by Hjorland. The analysis of the papers (n=146) led to the identification of the most productive authors, the networks representing the relationships between the authors as also the categories that constitute the primary areas of research.

Temporal analysis of the reduction in gas emission in areas of mechanically-harvested sugarcane using satellite imagery

The primary objective of this study was to estimate the amount of gas not emitted into the air in areas cultivated with sugarcane (Saccharum officinarum) that were mechanically harvested. Satellite images CBERS-2/CCD, from 08-13-2004, 08-14-2005, 08-15-2006 and 08-16-2007, of northwestern São Paulo State were processed using the Geographic Information System (GIS)-IDRISI 15.0. Areas of interest (the mechanically-harvested sugarcane fields) were identified and quantified based on the spectral response of the bands studied. Based on these data, the amount of gas that was not emitted was evaluated, according to the estimate equation proposed by the Intergovernmental Panel on Climate Change (IPCC). The results of 396.65 km(2) (5.91% for 2004); 447.56 km(2) (6.67% for 2005); 511.54 km(2) (7.62% in 2006); and 474.60 km(2) (7.07% for 2007), calculated from a total area of 6,710.89 km(2) with sugarcane, showed a significant increase of mechanical harvesting in the study area and a reduction of gas emissions of more than 300,000 t yr(-1).

Effect of acid etching time on demineralization of primary and permanent coronal dentin

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Precipitation chemistry in semi-arid areas of Southern Africa: A case study of a rural and an industrial site

Experimental data on the precipitation chemistry in the semi-arid savanna of South Africa is presented in this paper. A total of 901 rainwater samples were collected with automatic wet-only samplers at a rural site, Louis Trichardt, and at an industrial site, Amersfoort, from July 1986 to June 1999. The chemical composition of precipitation was analysed for seven inorganic and two organic ions, using ion chromatography. The most abundant ion was SO(4)(2-) and a large proportion of the precipitation is acidic, with 98% of samples at Amersfoort and 94% at Louis Trichardt having a pH below 5.6 ( average pH of 4.4 and 4.9, respectively). This acidity results from a mixture of mineral and organic acids, with mineral acids being the primary contributors to the precipitation acidity in Amersfoort, while at Louis Trichardt, organic and mineral acids contribute equal amounts of acidity. It was found that the composition of rainwater is controlled by five sources: marine, terrigenous, nitrogenous, biomass burning and anthropogenic sources. The relative contributions of these sources at the two sites were calculated. Anthropogenic sources dominate at Amersfoort and biomass burning at Louis Trichardt. Most ions exhibit a seasonal pattern at Louis Trichardt, with the highest concentrations occurring during the austral spring as a result of agricultural activities and biomass combustion, while at Amersfoort it is less pronounced due to the dominance of relatively constant industrial emissions. The results are compared to observations from other African regions.

Understorey fire propagation and tree mortality on adjacent areas to an Amazonian deforestation fire

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

An evaluation of ocean color model estimates of marine primary productivity in coastal and pelagic regions across the globe

Nearly half of the earth's photosynthetically fixed carbon derives from the oceans. To determine global and region specific rates, we rely on models that estimate marine net primary productivity (NPP) thus it is essential that these models are evaluated to determine their accuracy. Here we assessed the skill of 21 ocean color models by comparing their estimates of depth-integrated NPP to 1156 in situ C-14 measurements encompassing ten marine regions including the Sargasso Sea, pelagic North Atlantic, coastal Northeast Atlantic, Black Sea, Mediterranean Sea, Arabian Sea, subtropical North Pacific, Ross Sea, West Antarctic Peninsula, and the Antarctic Polar Frontal Zone. Average model skill, as determined by root-mean square difference calculations, was lowest in the Black and Mediterranean Seas, highest in the pelagic North Atlantic and the Antarctic Polar Frontal Zone, and intermediate in the other six regions. The maximum fraction of model skill that may be attributable to uncertainties in both the input variables and in situ NPP measurements was nearly 72%. on average, the simplest depth/wavelength integrated models performed no worse than the more complex depth/wavelength resolved models. Ocean color models were not highly challenged in extreme conditions of surface chlorophyll-a and sea surface temperature, nor in high-nitrate low-chlorophyll waters. Water column depth was the primary influence on ocean color model performance such that average skill was significantly higher at depths greater than 250 m, suggesting that ocean color models are more challenged in Case-2 waters (coastal) than in Case-1 (pelagic) waters. Given that in situ chlorophyll-a data was used as input data, algorithm improvement is required to eliminate the poor performance of ocean color NPP models in Case-2 waters that are close to coastlines. Finally, ocean color chlorophyll-a algorithms are challenged by optically complex Case-2 waters, thus using satellite-derived chlorophyll-a to estimate NPP in coastal areas would likely further reduce the skill of ocean color models.

Delineation of specific management areas for coffee cultivation based on the soil-relief relationship and numerical classification

Predicting and mapping productivity areas allows crop producers to improve their planning of agricultural activities. The primary aims of this work were the identification and mapping of specific management areas allowing coffee bean quality to be predicted from soil attributes and their relationships to relief. The study area was located in the Southeast of the Minas Gerais state, Brazil. A grid containing a total of 145 uniformly spaced nodes 50 m apart was established over an area of 31. 7 ha from which samples were collected at depths of 0. 00-0. 20 m in order to determine physical and chemical attributes of the soil. These data were analysed in conjunction with plant attributes including production, proportion of beans retained by different sieves and drink quality. The results of principal component analysis (PCA) in combination with geostatistical data showed the attributes clay content and available iron to be the best choices for identifying four crop production environments. Environment A, which exhibited high clay and available iron contents, and low pH and base saturation, was that providing the highest yield (30. 4l ha-1) and best coffee beverage quality (61 sacks ha-1). Based on the results, we believe that multivariate analysis, geostatistics and the soil-relief relationships contained in the digital elevation model (DEM) can be effectively used in combination for the hybrid mapping of areas of varying suitability for coffee production. © 2012 Springer Science+Business Media New York.

Wavelets based Algorithm for the Evaluation of Enhanced Liver Areas

Hepatocellular carcinoma (HCC) is a primary tumor of the liver. After local therapies, the tumor evaluation is based on the mRECIST criteria, which involves the measurement of the maximum diameter of the viable lesion. This paper describes a computed methodology to measure through the contrasted area of the lesions the maximum diameter of the tumor by a computational algorithm 63 computed tomography (CT) slices from 23 patients were assessed. Non-contrasted liver and HCC typical nodules were evaluated, and a virtual phantom was developed for this purpose. Optimization of the algorithm detection and quantification was made using the virtual phantom. After that, we compared the algorithm findings of maximum diameter of the target lesions against radiologist measures. Computed results of the maximum diameter are in good agreement with the results obtained by radiologist evaluation, indicating that the algorithm was able to detect properly the tumor limits A comparison of the estimated maximum diameter by radiologist versus the algorithm revealed differences on the order of 0.25 cm for large-sized tumors (diameter > 5 cm), whereas agreement lesser than 1.0cm was found for small-sized tumors. Differences between algorithm and radiologist measures were accurate for small-sized tumors with a trend to a small increase for tumors greater than 5 cm. Therefore, traditional methods for measuring lesion diameter should be complemented with non-subjective measurement methods, which would allow a more correct evaluation of the contrast-enhanced areas of HCC according to the mRECIST criteria.