DESIGUALDADES SOCIOESPACIAIS

The text discusses some import traits of the question of the urban sociospatial inequality, namely issues of land property, appropriation of wealth and urban growth. The roles played by the capitalist State and by other agents that produce  socially-unequal urban space are emphasized. The main tenets of the World Declaration for the Right to the City are then presented, with special attention given to urban popular movements. The article also provides theoretical elements that allow us to evaluate the  divergences that exist between the so-called popular movements and neo-liberal agenda.O texto apresenta alguns elementos de reflexões sobre características da desigualdade socioespacial urbana. Aponta aspectos da propriedade, apropriação das riquezas produzidas e do aumento da área urbana quanto mais espaço urbano se produz. Enfatiza a atuação do Estado capitalista e dos agentes produtores do espaço para configurar a cidade real que expressa a desigualdade socioespacial. Expõe sinteticamente o processo de elaboração da Carta Mundial pelo Direito à Cidade no processo de organização dos movimentos populares urbanos. Fornece pistas para analisar a contraposição entre as propostas dos movimentos populares e a agenda neoliberal

The Synthetic Image TEsting Framework (SITEF) for the evaluation of multi-spectral image segmentation algorithms

ABSTRACT One of the most challenging tasks in Remote Sensing at present is how to handle the huge amounts of image data acquired every day by the existing Earth Observation Satellites (EOS). An alternative approach to the standard per-pixel analysis of multi-spectral EOS images has evolved over the last decade. Instead of focusing on individual image pixels, the object-based image analysis approach consists of partitioning an image into meaningful image-objects. One of the reasons for the development of object-based methods has been the dramatic increase in commercially available high resolution digital remote sensing imagery, with spatial resolutions of 5.0 m and finer [1]. Also it has been recognised that the image pixel is not a "natural" element of an image scene. A common element of all object-based image analysis systems is the segmentation stage, where the image is partitioned in a number of objects (or segments), which is clearly a critical stage of the whole process. If the segmentation fails to identify as an object a given element present in the image, the subsequent stages will generally be unable to recognise or to classify this element. An evaluation of the abilities and limitations of the segmentation algorithms used is therefore an important aspect of any object based image analysis system. However, there is no established standard procedure for the evaluation of the segmentation results produced for EOS images The purpose of this work is to present the Synthetic Image TEsting Framework (SITEF), a tool to evaluate the performance of segmentation algorithms on multi-spectral images. The method is based on the production of synthetic images with the spectral characteristics of the image pixels extracted from a signature multi-spectral image The methodology used here is an evolution of the method described in REFERENCES [1] G.J. Hay, G. Castilla, M.A. Wulder, J.R. Ruiz, "An automated object-based approach for the multiscale image segmentation of forest scene

Evolutionary and Experimental Assessment of Novel Markers for Detection of Xanthomonas euvesicatoria in Plant Samples

BACKGROUND: Bacterial spot-causing xanthomonads (BSX) are quarantine phytopathogenic bacteria responsible for heavy losses in tomato and pepper production. Despite the research on improved plant spraying methods and resistant cultivars, the use of healthy plant material is still considered as the most effective bacterial spot control measure. Therefore, rapid and efficient detection methods are crucial for an early detection of these phytopathogens. METHODOLOGY: In this work, we selected and validated novel DNA markers for reliable detection of the BSX Xanthomonas euvesicatoria (Xeu). Xeu-specific DNA regions were selected using two online applications, CUPID and Insignia. Furthermore, to facilitate the selection of putative DNA markers, a customized C program was designed to retrieve the regions outputted by both databases. The in silico validation was further extended in order to provide an insight on the origin of these Xeu-specific regions by assessing chromosomal location, GC content, codon usage and synteny analyses. Primer-pairs were designed for amplification of those regions and the PCR validation assays showed that most primers allowed for positive amplification with different Xeu strains. The obtained amplicons were labeled and used as probes in dot blot assays, which allowed testing the probes against a collection of 12 non-BSX Xanthomonas and 23 other phytopathogenic bacteria. These assays confirmed the specificity of the selected DNA markers. Finally, we designed and tested a duplex PCR assay and an inverted dot blot platform for culture-independent detection of Xeu in infected plants. SIGNIFICANCE: This study details a selection strategy able to provide a large number of Xeu-specific DNA markers. As demonstrated, the selected markers can detect Xeu in infected plants both by PCR and by hybridization-based assays coupled with automatic data analysis. Furthermore, this work is a contribution to implement more efficient DNA-based methods of bacterial diagnostics

Predicting Grapevine Water Status Based on Hyperspectral Reflectance Vegetation Indices

Several vegetation indices (VI) derived from handheld spectroradiometer reflectance data in the visible spectral region were tested for modelling grapevine water status estimated by the predawn leaf water potential (Ψpd). The experimental trial was carried out in a vineyard in Douro wine region, Portugal. A statistical approach was used to evaluate which VI and which combination of wavelengths per VI allows the best correlation between VIs and Ψpd. A linear regression was defined using a parameterization dataset. The correlation analysis between Ψpd and the VIs computed with the standard formulation showed relatively poor results, with values for squared Pearson correlation coefficient (r2) smaller than 0.67. However, the results of r2 highly improved for all VIs when computed with the selected best combination of wavelengths (optimal VIs). The optimal Visible Atmospherically Resistant Index (VARI) and Normalized Difference Greenness Vegetation Index (NDGI) showed the higher r2 and stability index results. The equations obtained through the regression between measured Ψpd (Ψpd_obs) and optimal VARI and between Ψpd_obs and optimal NDGI when using the parameterization dataset were adopted for predicting Ψpd using a testing dataset. The comparison of Ψpd_obs with Ψpd predicted based on VARI led to R2 = 0.79 and a regression coefficient b = 0.96. Similar R2 was achieved for the prediction based on NDGI, but b was smaller (b = 0.93). Results obtained allow the future use of optimal VARI and NDGI for estimating Ψpd, supporting vineyards irrigation management

Neighbor-Joining Tree based on the concatenated sequences of four housekeeping genes of several <i>Xanthomonas</i>.

<p>The sequences of the housekeeping genes <i>atpD</i>, <i>dnaK</i>, <i>efp</i> and <i>gyrB</i> were concatenated and used to infer the MLST profile of <i>X. euvesicatoria</i> and <i>X. vesicatoria</i> strains used in this study, which are highlighted in yellow. The Neighbor-Joining tree was derived from the TN93+G+I model and a bootstrap analysis of 1000 replicates.</p

Dot blot validation of selected probes.

<p>Nine probes were evaluated with total DNA from a collection of BSX, consisting of 19 <i>Xeu</i>, five <i>Xv</i>, three <i>Xg</i> and two <i>Xp</i> strains. Probability values, obtained with a customized MATLAB algorithm for the automatic data analysis, are detailed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0037836#pone-0037836-t003" target="_blank">Table 3</a>.</p

PCR validation.

<p>The selected primer-pairs were tested for efficiency using eight different <i>Xeu</i> strains. For each assay, three different annealing temperatures were tested: 57°C, 59°C and 61°C.</p

Detection of BSX in infected plant material using an inverted dot blot platform.

<p>Crude bacterial suspensions, obtained from tomato and pepper plants leaves after one and two weeks of infection with <i>Xeu</i> 905, were used as templates for PCR enrichment using the markers' primer pairs. PCR products corresponding to each plant were labeled with Digoxigenin and used as probes. Purified DNA from <i>Xeu</i> 905 was used as positive control. Negative controls consisted of tomato plants infected with <i>Pst</i> DC3000 for 2 weeks and uninfected plants. The raw ChemiDoc captures and processed images, using the automatic image analysis algorithm, are shown.</p

Detection of BSX in infected plant material using a duplex PCR (markers XV7 and XV11).

<p>Tomato and pepper plants inoculated with <i>Xeu</i> 905, <i>Xv</i> 919, <i>Xg</i> 962 and <i>Xp</i> 4321were processed after one and two weeks to obtain crude bacterial suspensions used as PCR templates. Plants inoculated with <i>Pst</i> DC3000 were used as controls. M – DNA marker (GeneRuler DNA Ladder Mix); Ø-Duplex PCR using distilled water as template; C- healthy tomato and pepper plants.</p