Development of an integrative approach for the characterization of ecological risk on marine transition ecosystems: the Sado Estuary as a case study

Estuaries and other transitional waters are complex ecosystems critically important as nursery and shelter areas for organisms. Also, humans depend on estuaries for multiple socio-economical activities such as urbanism, tourism, heavy industry, (taking advantage of shipping), fisheries and aquaculture, the development of which led to strong historical pressures, with emphasis on pollution. The degradation of estuarine environmental quality implies ecologic, economic and social prejudice, hence the importance of evaluating environmental quality through the identification of stressors and impacts. The Sado Estuary (SW Portugal) holds the characteristics of industrialized estuaries, which results in multiple adverse impacts. Still, it has recently been considered moderately contaminated. In fact, many studies were conducted in the past few years, albeit scattered due to the absence of true biomonitoring programmes. As such, there is a need to integrate the information, in order to obtain a holistic perspective of the area able to assist management and decision-making. As such, a geographical information system (GIS) was created based on sediment contamination and biomarker data collected from a decade-long time-series of publications. Four impacted and a reference areas were identified, characterized by distinct sediment contamination patterns related to different hot spots and diffuse sources of toxicants. The potential risk of sediment-bound toxicants was determined by contrasting the levels of pollutants with available sediment quality guidelines, followed by their integration through the Sediment Quality guideline Quotient (SQG-Q). The SQG-Q estimates per toxicant or class was then subjected to georreferencing and statistical analyses between the five distinct areas and seasons. Biomarker responses were integrated through the Biomarkers Consistency Indice and georreferenced as well through GIS. Overall, in spite of the multiple biological traits surveyed, the biomarker data (from several organisms) are accordant with sediment contamination. The most impacted areas were the shipyard area and adjacent industrial belt, followed by urban and agricultural grounds. It is evident that the estuary, although globally moderately impacted, is very heterogeneous and affected by a cocktail of contaminants, especially metals and polycyclic aromatic hydrocarbon. Although elements (like copper, zinc and even arsenic) may originate from the geology of the hydrographic basin of the Sado River, the majority of the remaining contaminants results from human activities. The present work revealed that the estuary should be divided into distinct biogeographic units, in order to implement effective measures to safeguard environmental quality.

Photochemical degradation of triclosan: a comparison between different light sources

New emerging contaminants could represent a danger to the environment and Humanity with repercussions not yet known. One of the major worldwide pharmaceutical and personal care productions are antimicrobials products, triclosan, is an antimicrobial agent present in most products. Despite the high removal rate of triclosan present in wastewater treatments, triclosan levels are on the rise in the environment through disposal of wastewater effluent and use of sewage sludge in land application. Regulated in the EC/1272/2008 (annex VI, table 3.1), this compound is considered very toxic to aquatic life and it has been reported that photochemical transformation of triclosan produces dioxins. In the current work it was defined three objectives; determination of the most efficient process in triclosan degradation, recurring to photochemical degradation methods comparing different sources of light; identification of the main by-products formed during the degradation and the study of the influence of the Fenton and photo-Fenton reaction. Photochemical degradation methods such as: photocatalysis under florescent light (UV), photocatalysis under visible light (sunlight), photocatalysis under LEDs, photo-Fenton and Fenton reaction have been compared in this work. The degradation of triclosan was visualized through gas chromatography/mass spectrometry (GC/MS). In this study photo-Fenton reaction has successfully oxidized triclosan to H2O and CO2 without any by-products within 2 hours. Photocatalysis by titanium dioxide (TiO2) under LEDs was possible, having a degradation rate of 53% in an 8 hours essay. The degradation rate of the Fenton reaction, UV light and sunlight showed degradation between 90% and 95%. The results are reported to the data observed without statistic support, since this was not possible during the work period. Hydroquinone specie and 2,4-dichlorophenol by-products were identified in the first hour of photocatalysis by UV. A common compound, possibly identified has C7O4H , was present at the degradation by UV, sunlight and LEDs and was concluded to be a contaminant. In the future more studies in the use of LEDs should be undertaken given the advantages of long durability and low consumption of energy of these lamps and that due to their negative impact on the environment fluorescent lamps are being progressively made unavailable by governments, requiring new solutions to be found. Fenton and photo-Fenton reactions can also be costly processes given the expensive reagents used.

A avaliação da comunicação da criança com perturbação do espetro do autismo: perspetiva de pais e de profissionais

Dissertação de mestrado em Educação Especial (área de especialização Intervenção Precoce)

From a NoSQL data source to a business intelligence solution: An experiment

We are living in the era of Big Data. A time which is characterized by the continuous creation of vast amounts of data, originated from different sources, and with different formats. First, with the rise of the social networks and, more recently, with the advent of the Internet of Things (IoT), in which everyone and (eventually) everything is linked to the Internet, data with enormous potential for organizations is being continuously generated. In order to be more competitive, organizations want to access and explore all the richness that is present in those data. Indeed, Big Data is only as valuable as the insights organizations gather from it to make better decisions, which is the main goal of Business Intelligence. In this paper we describe an experiment in which data obtained from a NoSQL data source (database technology explicitly developed to deal with the specificities of Big Data) is used to feed a Business Intelligence solution.

Reconstructing transcriptional regulatory networks using data integration and text mining

Transcriptional Regulatory Networks (TRNs) are powerful tool for representing several interactions that occur within a cell. Recent studies have provided information to help researchers in the tasks of building and understanding these networks. One of the major sources of information to build TRNs is biomedical literature. However, due to the rapidly increasing number of scientific papers, it is quite difficult to analyse the large amount of papers that have been published about this subject. This fact has heightened the importance of Biomedical Text Mining approaches in this task. Also, owing to the lack of adequate standards, as the number of databases increases, several inconsistencies concerning gene and protein names and identifiers are common. In this work, we developed an integrated approach for the reconstruction of TRNs that retrieve the relevant information from important biological databases and insert it into a unique repository, named KREN. Also, we applied text mining techniques over this integrated repository to build TRNs. However, was necessary to create a dictionary of names and synonyms associated with these entities and also develop an approach that retrieves all the abstracts from the related scientific papers stored on PubMed, in order to create a corpora of data about genes. Furthermore, these tasks were integrated into @Note, a software system that allows to use some methods from the Biomedical Text Mining field, including an algorithms for Named Entity Recognition (NER), extraction of all relevant terms from publication abstracts, extraction relationships between biological entities (genes, proteins and transcription factors). And finally, extended this tool to allow the reconstruction Transcriptional Regulatory Networks through using scientific literature.

Spatial-temporal variation of dissolved inorganic material in the Amazon basin

The Amazon River basin is important in the contribution of dissolved material to oceans (4% worldwide). The aim of this work was to study the spatial and the temporal variability of dissolved inorganic materials in the main rivers of the Amazon basin. Data from 2003 to 2011 from six gauging stations of the ORE-HYBAM localized in Solimões, Purus, Madeira and Amazon rivers were used for this study. The concentrations of Ca2+, Na+, K+, Mg2+, Cl-, SO4 -2, HCO3 - and SiO2 were analyzed. At the stations of Solimões and Amazon rivers, the concentrations of Ca2+, Mg2+, HCO3 - and SO4 -2 had heterogeneous distribution over the years and did not show seasonality. At the stations of Madeira river, the concentration of these ions had seasonality inversely proportional to water discharge (dilution-concentration effect). Similar behavior was observed for the concentrations of Cl- and Na+ at the stations of the Solimões, Amazon and Madeira rivers, indicating almost constant release of Cl- and Na+ fluxes during the hydrological cycle. K+ and SiO2 showed almost constant concentrations throughout the years and all the stations, indicating that their flows depend on the river discharge variation. Therefore, the temporal variability of the dissolved inorganic material fluxes in the Solimões and Amazon rivers depends on the hydro-climatic factor and on the heterogeneity of the sources. In the Madeira and Purus rivers there is less influence of these factors, indicating that dissolved load fluxes are mainly associated to silicates weathering. As the Solimões basin contributes approximately 84% of the total flux of dissolved materials in the basin and is mainly under the influence of a hydro-climatic factor, we conclude that the temporal variability of this factor controls the temporal variability of the dissolved material fluxes of the Amazon basin.

Evaluation of geostatistical techniques to estimate the spatial distribution of aboveground biomass in the Amazon rainforest using high-resolution remote sensing data

ABSTRACT The spatial distribution of forest biomass in the Amazon is heterogeneous with a temporal and spatial variation, especially in relation to the different vegetation types of this biome. Biomass estimated in this region varies significantly depending on the applied approach and the data set used for modeling it. In this context, this study aimed to evaluate three different geostatistical techniques to estimate the spatial distribution of aboveground biomass (AGB). The selected techniques were: 1) ordinary least-squares regression (OLS), 2) geographically weighted regression (GWR) and, 3) geographically weighted regression - kriging (GWR-K). These techniques were applied to the same field dataset, using the same environmental variables derived from cartographic information and high-resolution remote sensing data (RapidEye). This study was developed in the Amazon rainforest from Sucumbíos - Ecuador. The results of this study showed that the GWR-K, a hybrid technique, provided statistically satisfactory estimates with the lowest prediction error compared to the other two techniques. Furthermore, we observed that 75% of the AGB was explained by the combination of remote sensing data and environmental variables, where the forest types are the most important variable for estimating AGB. It should be noted that while the use of high-resolution images significantly improves the estimation of the spatial distribution of AGB, the processing of this information requires high computational demand.

Tapping the wealth of microbial data in high-throughput metabolic model reconstruction

Genome-scale metabolic models are valuable tools in the metabolic engineering process, based on the ability of these models to integrate diverse sources of data to produce global predictions of organism behavior. At the most basic level, these models require only a genome sequence to construct, and once built, they may be used to predict essential genes, culture conditions, pathway utilization, and the modifications required to enhance a desired organism behavior. In this chapter, we address two key challenges associated with the reconstruction of metabolic models: (a) leveraging existing knowledge of microbiology, biochemistry, and available omics data to produce the best possible model; and (b) applying available tools and data to automate the reconstruction process. We consider these challenges as we progress through the model reconstruction process, beginning with genome assembly, and culminating in the integration of constraints to capture the impact of transcriptional regulation. We divide the reconstruction process into ten distinct steps: (1) genome assembly from sequenced reads; (2) automated structural and functional annotation; (3) phylogenetic tree-based curation of genome annotations; (4) assembly and standardization of biochemistry database; (5) genome-scale metabolic reconstruction; (6) generation of core metabolic model; (7) generation of biomass composition reaction; (8) completion of draft metabolic model; (9) curation of metabolic model; and (10) integration of regulatory constraints. Each of these ten steps is documented in detail.

A design of experiments to assess phosphorous removal and crystal properties in struvite precipitation of source separated urine using different Mg sources

Supplementary data associated with this article can be found, in the online version, at: http://dx.doi.org/10.1016/j.cej.2016.03.148.

Non root feeding with two sources of zinc on Coffea arábica L. 'mundo novo'(B.Rodr.) Choussy

A trial was carried out on an eight old coffee plantation with visible zinc problems. The plantation was situated nearly the city of Jaú (22º30'S, 48º30'W). State of São Paulo, Brazil. The soil is classified as medium texture Oxisol of low base saturation (Latossol Vermelho Amarelo - fase arenosa). The pulverization program started in november 1977, followed in march and July 1978 (heavy harvest) and ended in march and July 1979 (light harvest). Is should be mentioned that a well reconized characteristic of arábica coffe is its habit of biennial bearing, a very heavy harvest is most often followed by a light load the next year. The following treatments and amounts of chemicals per cova hole (4 trees) were tested in accordance with a random block design: 1. 1 g of zinc (zinc sulphate, 0.5%) 2. 3 g of nitrogen (urea, 1.3%) 3. 1 g of zinc + 3 g of nitrogen (zinc sulphate 0.5% + urea 1.3%) 4. 0.25 g, 0.50 g, 1.00 g, 2.00 g of zinc plus 0.75 g, 1.50 g, 3.00 g and 6.00 of nitrogen (correspondent to NZN* 15-0-0-5 as 0.75%, 1-5%, 3.0% and 6.0% by v/v). Foliar absorption data were obtained by collecting the 3rd and 4th pairs of the coffee leaves and analysed them for N, P, K, Ca, Mg, S, B, Cu, Fe, Mn, and Zn. The main results may be summarized as follows: 1. The maximum calculated yields of clean coffee were obtained by the applications of 5.84 1 of NZN (1.13%) per hectare. 2. The applications of zinc sulphate (0.5%) and urea (1.3%) together or separate did not affected the coffee bean production. 3. The applications of 15.0 1 of NZN per hectare reduced the coffee yields. 4. Leaf damages and burning symptoms were observed by the applications of urea (1.3%) plus zinc sulphate (0.5%) and larger doses than 7.5 1 of NZN per hectare. 5. Leaf tissue analysis show that the concentrations of the elements were affecred by the age of the leaves and by the yields of the coffee trees. 6. The applications of increasing doses of NZN causes an increase in the concentration of zinc, manganese and boron in the leaves and decreased the concentration in calcium and potassium the leaves. 7. The concentration of zinc in the leaves associated with the heavy harvest, in July, was 70.0 ppm.

External sources of innovation and industry-university interaction:evidence from Spanish firms

This paper is about the firm innovation process and the cooperation of the innovative firms with other firms and public institutions. A special attention is paid to the cooperation with universities. We use the Technological Innovation Survey (TIS) from the Instituto Nacional de Estadística (Spain) in order to obtain data for 4,159 innovative firms. Our results show that firm's cooperation activities are closely linked to the characteristics of the industry and the firm as well as to the origin of public funds for R&D activities. Key words: Innovation, universities, Spanish economy. JEL code: O31, I20, L60

Human capital in growth regressions: how much difference does data quality make? An update and further results

We construct estimates of educational attainment for a sample of OECD countries using previously unexploited sources. We follow a heuristic approach to obtain plausible time profiles for attainment levels by removing sharp breaks in the data that seem to reflect changes in classification criteria. We then construct indicators of the information content of our series and a number of previously available data sets and examine their performance in several growth specifications. We find a clear positive correlation between data quality and the size and significance of human capital coefficients in growth regressions. Using an extension of the classical errors in variables model, we construct a set of meta-estimates of the coefficient of years of schooling in an aggregate Cobb-Douglas production function. Our results suggest that, after correcting for measurement error bias, the value of this parameter is well above 0.50.

Labor productivity in Europe: evidence from a sample of regions

The present paper aims at analyzing the sources of productivity in Europe to account for its recent underperformance and identify potential geographic idiosyncracies. We study the productivity performance and its sources in a sample of ten European regions belonging to four countries (France, Germany, Italy and Spain). Exploiting the increasing availability of disaggregated data at regional level in Europe, we propose both a descriptive statistics and an econometric analysis of productivity sources since 1995. Our main finding is that the sources of labor productivity are rather heterogeneous across our sample but may be associated with regional or national idiosyncracies.

Addressing Sea Surface Salinity retrieval at different spatial resolution. Feasibility study using OCCAM data within SEPS simulator and L2 processor tools

Projecte de recerca elaborat a partir d’una estada a la National Oceanography Centre of Southampton (NOCS), Gran Bretanya, entre maig i juliol del 2006. La possibilitat d’obtenir una estimació precissa de la salinitat marina (SSS) és important per a investigar i predir l’extensió del fenòmen del canvi climàtic. La missió Soil Moisture and Ocean Salinity (SMOS) va ser seleccionada per l’Agència Espacial Europea (ESA) per a obtenir mapes de salinitat de la superfície marina a escala global i amb un temps de revisita petit. Abans del llençament de SMOS es preveu l’anàlisi de la variabilitat horitzontal de la SSS i del potencial de les dades recuperades a partir de mesures de SMOS per a reproduir comportaments oceanogràfics coneguts. L’objectiu de tot plegat és emplenar el buit existent entre les fonts de dades d’entrada/auxiliars fiables i les eines desenvolupades per a simular i processar les dades adquirides segons la configuració de SMOS. El SMOS End-to-end Performance Simulator (SEPS) és un simulador adhoc desenvolupat per la Universitat Politècnica de Catalunya (UPC) per a generar dades segons la configuració de SMOS. Es va utilitzar dades d’entrada a SEPS procedents del projecte Ocean Circulation and Climate Advanced Modeling (OCCAM), utilitzat al NOCS, a diferents resolucions espacials. Modificant SEPS per a poder fer servir com a entrada les dades OCCAM es van obtenir dades de temperatura de brillantor simulades durant un mes amb diferents observacions ascendents que cobrien la zona seleccionada. Les tasques realitzades durant l’estada a NOCS tenien la finalitat de proporcionar una tècnica fiable per a realitzar la calibració externa i per tant cancel•lar el bias, una metodologia per a promitjar temporalment les diferents adquisicions durant les observacions ascendents, i determinar la millor configuració de la funció de cost abans d’explotar i investigar les posibiltats de les dades SEPS/OCCAM per a derivar la SSS recuperada amb patrons d’alta resolució.

Innovation sources and productivity in Catalonian firms: a quantile regression analysis

This paper explores the effects of two main sources of innovation -intramural and external R&D- on the productivity level in a sample of 3,267 Catalonian firms. The data set used is based on the official innovation survey of Catalonia which was a part of the Spanish sample of CIS4, covering the years 2002-2004. We compare empirical results by applying usual OLS and quantile regression techniques both in manufacturing and services industries. In quantile regression, results suggest different patterns at both innovation sources as we move across conditional quantiles. The elasticity of intramural R&D activities on productivity decreased when we move up the high productivity levels both in manufacturing and services sectors, while the effects of external R&D rise in high-technology industries but are more ambiguous in low-technology and knowledge-intensive services. JEL codes: O300, C100, O140. Keywords: Innovation sources, R&D, Productivity, Quantile regression