DOCUMENT CONTROL OF NATIONAL MAPPING AND METRIC STUDIES CHARACTERIZING NATIONAL IDENTITY AND INDIVIDUAL. I STAGE

This is a project of the School of Library, Documentation and Information of the National University, is performed to support the initiative of UNESCO to build the Memory of the World (UNESCO, 1995) and to help provide universal access to documentation. To this end, the School of Library Science students has promoted the realization of final graduation work on documentary control of domestic production. This project has the following objectives:Objectives1. Conduct mapping national documentary through the identification, analysis, organization and access to documentary heritage of Costa Rica, to contribute to the Memory of the World.2. Perform bibliometric analysis of documentary records contained in the integrated databases.This project seeks to bring undergraduate students graduating from the school, in making final graduation work on document control. Students have the opportunity to make final graduation work on the documentary production of Costa Rica on a specific theme or on a country's geographical area.Desk audits aimed at identifying the document using access points and indicate its contents to allow recovery by the user.The result is the production of a new document, other than the original, a secondary document: the bibliography. The records in the database each control documentation completed work will be integrated into a single database to be placed on the website of EBDI, for consultation of researchers and interested users.

Development of single nucleotide polymorphism (SNP) markers from the mango (Mangifera indica) transcriptome for mapping and estimation of genetic diversity

The development of molecular markers for genomic studies in Mangifera indica (mango) will allow marker-assisted selection and identification of genetically diverse germplasm, greatly aiding mango breeding programs. We report here our identification of thousands of unambiguous molecular markers that can be easily assayed across genotypes of the species. With origin centered in Southeast Asia, mangos are grown throughout the tropics and subtropics as a nutritious fruit that exhibits remarkable intraspecific phenotypic diversity. With the goal of building a high density genetic map, we have undertaken discovery of sequence variation in expressed genes across a broad range of mango cultivars. A transcriptome sequence reference was built de novo from extensive sequencing and assembly of RNA from cultivar 'Tommy Atkins'. Single nucleotide polymorphisms (SNPs) in protein coding transcripts were determined from alignment of RNA reads from 24 mango cultivars of diverse origins: 'Amin Abrahimpur' (India), 'Aroemanis' (Indonesia), 'Burma' (Burma), 'CAC' (Hawaii), 'Duncan' (Florida), 'Edward' (Florida), 'Everbearing' (Florida), 'Gary' (Florida), 'Hodson' (Florida), 'Itamaraca' (Brazil), 'Jakarata' (Florida), 'Long' (Jamaica), 'M. Casturi Purple' (Borneo), 'Malindi' (Kenya), 'Mulgoba' (India), 'Neelum' (India), 'Peach' (unknown), 'Prieto' (Cuba), 'Sandersha' (India), 'Tete Nene' (Puerto Rico), 'Thai Everbearing' (Thailand), 'Toledo' (Cuba), 'Tommy Atkins' (Florida) and 'Turpentine' (West Indies). SNPs in a selected subset of protein coding transcripts are currently being converted into Fluidigm assays for genotyping of mapping populations and germplasm collections. Using an alternate approach, SNPs (144) discovered by sequencing of candidate genes in 'Kensington Pride' have already been converted and used for genotyping.

Geological Evolution of Coastal and Marine Environments off the Campania Continental Shelf Through Marine Geological Mapping - The Example of the Cilento Promontory

The geological evolution of coastal and marine environments offshore the Cilento Promontory through marine geological mapping is discussed here. The marine geological map n. 502 “Agropoli,” located offshore the Cilento Promontory (southern Italy), is described and put in regional geologic setting. The study area covers water depths ranging between 30 and 200 m isobaths. The geologic map has been constructed in the frame of a research program financed by the National Geological Survey of Italy (CARG Project), finalized to the construction of an up-to-date cartography of the Campania region. Geological and geophysical data on the continental shelf and slope offshore the southern Campania region have been acquired in an area bounded northward by the Gulf of Salerno and southward by the Gulf of Policastro. A high-resolution multibeam bathymetry has permitted the construction of a digital elevation model (DEM). Sidescan sonar profiles have also been collected and interpreted, and their merging with bathymetric data has allowed for the realization of the base for the marine geologic cartography. The calibration of geophysical data has been attempted through sea-bottom samples. The morpho-structures and the seismic sequences overlying the outcrops of acoustic basement reported in the cartographic representation have been studied in detail using single-channel seismics. The interpretation of seismic profiles has been a support for the reconstruction of the stratigraphic and structural setting of the Quaternary continental shelf successions and the outcrops of rocky acoustic basement in correspondence to the Licosa Cape morphostructural high. These areas result from the seaward prolongation of the stratigraphic and structural units, widely cropping out in the surrounding emerged sector of the Cilento Promontory. The cartographic approach is based on the recognition of laterally coeval depositional systems, interpreted in the frame of system tracts of the Late Quaternary depositional sequence.

QTLs mapping for primary metabolites responsible of the organoleptic and nutritional characteristics of strawberry (Fragaria x ananassa)

The cultivated strawberry (Fragaria x ananassa) is the berry fruit most consumed worldwide and is well-known for its delicate flavour and nutritional properties. However, fruit quality attributes have been lost or reduced after years of traditional breeding focusing mainly on agronomical traits. To face the obstacles encountered in the improvement of cultivated crops, new technological tools, such as genomics and high throughput metabolomics, are becoming essential for the identification of genetic factors responsible of organoleptic and nutritive traits. Integration of “omics” data will allow a better understanding of the molecular and genetic mechanisms underlying the accumulation of metabolites involved in the flavour and nutritional value of the fruit. To identify genetic components affecting/controlling? fruit metabolic composition, here we present a quantitative trait loci (QTL) analysis using a 95 F1 segregating population derived from genotypes ‘1392’, selected for its superior flavour, and ‘232’ selected based in high yield (Zorrilla-Fontanesi et al., 2011; Zorrilla-Fontanesi et al., 2012). Metabolite profiling was performed on red stage strawberry fruits using gas chromatography hyphenated to time-of-flight mass spectrometry, which is a rapid and highly sensitive approach, allowing a good coverage of the central pathways of primary metabolism. Around 50 primary metabolites, including sugars, sugars derivatives, amino and organic acids, were detected and quantified after analysis in each individual of the population. QTL mapping was performed on the ‘232’ x ‘1392’ population separately over two successive years, based on the integrated linkage map (Sánchez-Sevilla et al., 2015). First, significant associations between metabolite content and molecular markers were identified by the non-parametric test of Kruskal-Wallis. Then, interval mapping (IM), as well as the multiple QTL method (MQM) allowed the identification of QTLs in octoploid strawberry. A permutation test established LOD thresholds for each metabolite and year. A total of 132 QTLs were detected in all the linkage groups over the two years for 42 metabolites out of 50. Among them, 4 (9.8%) QTLs for sugars, 9 (25%) for acids and 7 (12.7%) for amino acids were stable and detected in the two successive years. We are now studying the QTLs regions in order to find candidate genes to explain differences in metabolite content in the different individuals of the population, and we expect to identify associations between genes and metabolites which will help us to understand their role in quality traits of strawberry fruit.

Modeling and Mapping Agroforestry Aboveground Biomass in the Brazilian Amazon Using Airborne Lidar Data.

Agroforestry has large potential for carbon (C) sequestration while providing many economical, social, and ecological benefits via its diversified products. Airborne lidar is considered as the most accurate technology for mapping aboveground biomass (AGB) over landscape levels. However, little research in the past has been done to study AGB of agroforestry systems using airborne lidar data. Focusing on an agroforestry system in the Brazilian Amazon, this study first predicted plot-level AGB using fixed-effects regression models that assumed the regression coefficients to be constants. The model prediction errors were then analyzed from the perspectives of tree DBH (diameter at breast height)?height relationships and plot-level wood density, which suggested the need for stratifying agroforestry fields to improve plot-level AGB modeling. We separated teak plantations from other agroforestry types and predicted AGB using mixed-effects models that can incorporate the variation of AGB-height relationship across agroforestry types. We found that, at the plot scale, mixed-effects models led to better model prediction performance (based on leave-one-out cross-validation) than the fixed-effects models, with the coefficient of determination (R2) increasing from 0.38 to 0.64. At the landscape level, the difference between AGB densities from the two types of models was ~10% on average and up to ~30% at the pixel level. This study suggested the importance of stratification based on tree AGB allometry and the utility of mixed-effects models in modeling and mapping AGB of agroforestry systems.

Association mapping provides insights into the origin and the fine structure of the sorghum aluminum tolerance locus, AltSB.

2014

High spatial resolution land use and land cover mapping of the Brazilian Legal Amazon in 2008 using Landsat-5/TM and MODIS data.

Understanding spatial patterns of land use and land cover is essential for studies addressing biodiversity, climate change and environmental modeling as well as for the design and monitoring of land use policies. The aim of this study was to create a detailed map of land use land cover of the deforested areas of the Brazilian Legal Amazon up to 2008. Deforestation data from and uses were mapped with Landsat-5/TM images analysed with techniques, such as linear spectral mixture model, threshold slicing and visual interpretation, aided by temporal information extracted from NDVI MODIS time series. The result is a high spatial resolution of land use and land cover map of the entire Brazilian Legal Amazon for the year 2008 and corresponding calculation of area occupied by different land use classes. The results showed that the four classes of Pasture covered 62% of the deforested areas of the Brazilian Legal Amazon, followed by Secondary Vegetation with 21%. The area occupied by Annual Agriculture covered less than 5% of deforested areas; the remaining areas were distributed among six other land use classes. The maps generated from this project ? called TerraClass - are available at INPE?s web site (http://www.inpe.br/cra/projetos_pesquisas/terraclass2008.php)

Association of myocardial T1-mapping CMR with hemodynamics and RV performance in pulmonary hypertension

Early detection of right ventricular (RV) involvement in chronic pulmonary hypertension (PH) is essential due to prognostic implications. T1 mapping by cardiac magnetic resonance (CMR) has emerged as a noninvasive technique for extracellular volume fraction (ECV) quantification. We assessed the association of myocardial native T1 time and equilibrium contrast ECV (Eq-ECV) at the RV insertion points with pulmonary hemodynamics and RV performance in an experimental model of chronic PH. Right heart catheterization followed by immediate CMR was performed on 38 pigs with chronic PH (generated by surgical pulmonary vein banding) and 6 sham-operated controls. Native T1 and Eq-ECV values at the RV insertion points were both significantly higher in banded animals than in controls and showed significant correlation with pulmonary hemodynamics, RV arterial coupling, and RV performance. Eq-ECV values also increased before overt RV systolic dysfunction, offering potential for the early detection of myocardial involvement in chronic PH.

Mapping and modulating spatial attention asymmetries in young and older adults

Healthy young adults demonstrate a group-level, systematic preference for stimuli presented in the left side of space relative to the right (‘pseudoneglect’) (Bowers & Heilman, 1980). This results in an overestimation of features such as size, brightness, numerosity and spatial frequency in the left hemispace, probably as a result of right cerebral hemisphere dominance for visuospatial attention. This spatial attention asymmetry is reduced in the healthy older population, and can be shifted entirely into right hemispace under certain conditions. Although this rightward shift has been consistently documented in behavioural experiments, there is very little neuroimaging evidence to explain this effect at a neuroanatomical level. In this thesis, I used behavioural methodology and electroencephalography (EEG) to map spatial attention asymmetries in young and older adults. I then use transcranial direct current stimulation (tDCS) to modulate these spatial biases, with the aim of assessing age-related differences in response to tDCS. In the first of three experiments presented in this thesis, I report in Chapter Two that five different spatial attention tasks provide consistent intra-task measures of spatial bias in young adults across two testing days. There were, however, no inter-task correlations between the five tasks, indicating that pseudoneglect is at least partially driven by task-dependent patterns of neural activity. In Chapter Three, anodal tDCS was applied separately to the left (P5) and right (P6) posterior parietal cortex (PPC) in young and older adults, with an aim to improve the detection of stimuli appearing in the contralateral visual field. There were no age differences in response to tDCS, but there were significant differences depending on baseline performance. Relative to a sham tDCS protocol, tDCS applied to the right PPC resulted in maintained visual detection across both visual fields in adults who were good at the task at baseline. In contrast, left PPC tDCS resulted in reduced detection sensitivity across both visual fields in poor performers. Finally, in Chapter Four, I report a right-hemisphere lateralisation of EEG activity in young adults that was present for long (but not short) landmark task lines. In contrast, older adults demonstrated no lateralised activity for either line length, thus providing novel evidence of an age-related reduction of hemispheric asymmetry in older adults. The results of this thesis provide evidence of a highly complex set of factors that underlie spatial attention asymmetries in healthy young and older adults.

Mapping the likelihood of foot-and-mouth disease introduction along the border between Brazil and Paraguay.

The objective of this work was to apply fuzzy majority multicriteria group decision?making to determine risk areas for foot?and?mouth disease (FMD) introduction along the border between Brazil and Paraguay. The study was conducted in three municipalities in the state of Mato Grosso do Sul, Brazil, located along the border with Paraguay. Four scenarios were built, applying the following linguistic quantifiers to describe risk factors: few, half, many, and most. The three criteria considered to be most likely to affect the vulnerability to introduction of FMD, according to experts? opinions, were: the introduction of animals in the farm, the distance from the border, and the type of property settlements. The resulting maps show a strong spatial heterogeneity in the risk of FMD introduction. The used methodology brings out a new approach that can be helpful to policy makers in the combat and eradication of FMD.

Digital soil mapping using reference area and artificial neural networks.

Digital soil mapping is an alternative for the recognition of soil classes in areas where pedological surveys are not available. The main aim of this study was to obtain a digital soil map using artificial neural networks (ANN) and environmental variables that express soillandscape relationships. This study was carried out in an area of 11,072 ha located in the Barra Bonita municipality, state of São Paulo, Brazil. A soil survey was obtained from a reference area of approximately 500 ha located in the center of the area studied. With the mapping units identified together with the environmental variables elevation, slope, slope plan, slope profile, convergence index, geology and geomorphic surfaces, a supervised classification by ANN was implemented. The neural network simulator used was the Java NNS with the learning algorithm "back propagation." Reference points were collected for evaluating the performance of the digital map produced. The occurrence of soils in the landscape obtained in the reference area was observed in the following digital classification: medium-textured soils at the highest positions of the landscape, originating from sandstone, and clayey loam soils in the end thirds of the hillsides due to the greater presence of basalt. The variables elevation and slope were the most important factors for discriminating soil class through the ANN. An accuracy level of 82% between the reference points and the digital classification was observed. The methodology proposed allowed for a preliminary soil classification of an area not previously mapped using mapping units obtained in a reference area

Mapping spatial and temporal potassium balances in Brazilian soils of south-west Goias.

Introduction: Brazil, is one of the main agricultural producers in the world ranking 1st in the production of sugarcane, coffee and oranges. It is also 2nd as world producer of soybeans and a leader in the harvested yields of many other crops. The annual consumption of mineral fertilizers exceeds 20 million mt, 30% of which corresponds to potash fertilizers (ANDA, 2006). From this statistic it may be supposed that fertilizer application in Brazil is rather high, compared with many other countries. However, even if it is assumed that only one fourth of this enormous 8.5 million km2 territory is used for agriculture, average levels of fertilizer application per hectare of arable land are not high enough for sustainable production. One of the major constraints is the relatively low natural fertility status of the soils which contain excessive Fe and Al oxides. Agriculture is also often practised on sandy soils so that the heavy rainfall causes large losses of nutrients through leaching. In general, nutrient removal by crops such as sugarcane and tropical fruits is much more than the average nutrient application via fertilization, especially in regions with a long history of agricultural production. In the recently developed areas, especially in the Cerrado (Brazilian savanna) where agriculture has expanded since 1980, soils are even poorer than in the "old" agricultural regions, and high costs of mineral fertilizers have become a significant input factor in determining soybean, maize and cotton planting. The consumption of mineral fertilizers throughout Brazil is very uneven. According to the 1995/96 Agricultural Census, only in eight of the total of 26 Brazilian states, were 50 per cent or more of the farms treated "systematically" with mineral fertilizers; in many states it was less than 25 per cent, and in five states even less than 12 per cent (Brazilian Institute for Geography and Statistics; Censo Agropecuario1995/96, Instituto Brazileiro de Geografia e Estadistica; IBGE, www.ibge.gov.br). The geographical application distribution pattern of mineral fertilizers may be considered as an important field of research. Understanding geographical disparities in fertilization level requires a complex approach. This includes evaluation of the availability of nutrients in the soil (and related soil properties e.g. CEC and texture), the input of nutrients with fertilizer application, and the removal of nutrients by harvested yields. When all these data are compiled, it is possible to evaluate the balance of particular nutrients for certain areas, and make conclusions as to where agricultural practices should be optimized. This kind of research is somewhat complicated, because it relies on completely different sources of data, usually from incomparable data sources, e.g. soil characteristics attributed to soil type areas, in contrast to yields by administrative regions, or farms. A priority tool in this case is the Geographical Information System (GIS), which enables attribution of data from different fields to the same territorial units, and makes possible integration of these data in an "inputoutput" model, where "input" is the natural availability of a nutrient in the soil plus fertilization, and "output" export of the same nutrient with the removed harvested yield.

Scene Mapping and Understanding by Robotic Vision

The first mechanical Automaton concept was found in a Chinese text written in the 3rd century BC, while Computer Vision was born in the late 1960s. Therefore, visual perception applied to machines (i.e. the Machine Vision) is a young and exciting alliance. When robots came in, the new field of Robotic Vision was born, and these terms began to be erroneously interchanged. In short, we can say that Machine Vision is an engineering domain, which concern the industrial use of Vision. The Robotic Vision, instead, is a research field that tries to incorporate robotics aspects in computer vision algorithms. Visual Servoing, for example, is one of the problems that cannot be solved by computer vision only. Accordingly, a large part of this work deals with boosting popular Computer Vision techniques by exploiting robotics: e.g. the use of kinematics to localize a vision sensor, mounted as the robot end-effector. The remainder of this work is dedicated to the counterparty, i.e. the use of computer vision to solve real robotic problems like grasping objects or navigate avoiding obstacles. Will be presented a brief survey about mapping data structures most widely used in robotics along with SkiMap, a novel sparse data structure created both for robotic mapping and as a general purpose 3D spatial index. Thus, several approaches to implement Object Detection and Manipulation, by exploiting the aforementioned mapping strategies, will be proposed, along with a completely new Machine Teaching facility in order to simply the training procedure of modern Deep Learning networks.