Redes sociais, capital social e governança ambiental no Território Portal da Amazônia

O artigo trata de um estudo empírico em que a análise de redes sociais é utilizada para mapear o capital social de atores envolvidos em processos de governança ambiental na Amazônia brasileira. Por meio de entrevistas, foi mapeada a rede de relações de diálogo sobre questões socioambientais de um conjunto de 505 atores no Território Portal da Amazônia. Foram identificadas 3384 relações de diálogo, com uma média de 6,7 parceiros de diálogo por ator. A análise dos aspectos estruturais da rede de diálogo foi utilizada para construir indicadores de capital social de ligação, com mapeamento da organização interna dos atores de um mesmo município, e de conexão, com a caracterização das relações entre atores de municípios diferentes. Em nível municipal, a distribuição das duas formas de capital social permitiu caracterizar os grupos de atores de acordo com as suas atuações diferenciadas na governança ambiental do Território. Em nível territorial, o padrão de conectividade entre os 16 municípios mostra um equilíbrio entre as duas formas de capital social e revela o potencial de comunicação e organização dos atores, como demonstrado no exemplo dos projetos de Agendas 21 locais. Estes resultados demonstram como a análise de redes sociais pode contribuir na definição (ou redefinição) das fronteiras dos territórios de modo a incluir um conjunto de municípios cujos atores mantêm relações sociais efetivas. Ações de governança no Portal da Amazônia são propostas com potencial para fortalecer os processos de diálogo, diminuir os conflitos e promover o uso sustentável dos recursos naturais na Amazônia.

Using balanced scorecards to evaluate the data warehouse system utility

Dissertação de mestrado em Systems Engineering

Evaluating balance, stability and gait symmetry of stroke patients using kinematic and dynamic gait lab data

Dissertação de mestrado integrado em Engenharia Biomédica

OpenAIRE guidelines: supporting interoperability for Data Archives

OpenAIRE supports the European Commission Open Access policy by providing an infrastructure for researchers to comply with the European Union Open Access mandate. The current OpenAIRE infrastructure and services, resulting from OpenAIRE and OpenAIREplus FP7 projects, builds on Open Access research results from a wide range of repositories and other data sources: institutional or thematic publication repositories, Open Access journals, data repositories, Current Research Information Systems and aggregators. (...)

Poker learner: modelação de jogadores através de data mining

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

Data supporting the role of enzymes and polysaccharides during cassava postharvest physiological deterioration

This data article is referred to the research article entitled The role of ascorbate peroxidase, guaiacol peroxidase, and polysaccharides in cassava (Manihot esculenta Crantz) roots under postharvest physiological deterioration by Uarrota et al. (2015). Food Chemistry 197, Part A, 737746. The stress duo to PPD of cassava roots leads to the formation of ROS which are extremely harmful and accelerates cassava spoiling. To prevent or alleviate injuries from ROS, plants have evolved antioxidant systems that include non-enzymatic and enzymatic defence systems such as ascorbate peroxidase, guaiacol peroxidase and polysaccharides. In this data article can be found a dataset called newdata, in RData format, with 60 observations and 06 variables. The first 02 variables (Samples and Cultivars) and the last 04, spectrophotometric data of ascorbate peroxidase, guaiacol peroxidase, tocopherol, total proteins and arcsined data of cassava PPD scoring. For further interpretation and analysis in R software, a report is also provided. Means of all variables and standard deviations are also provided in the Supplementary tables (data.long3.RData, data.long4.RData and meansEnzymes.RData), raw data of PPD scoring without transformation (PPDmeans.RData) and days of storage (days.RData) are also provided for data analysis reproducibility in R software.

Use of anatomical root markers for species identification in Catasetum (Orchidaceae) at the Portal da Amazônia region, MT, Brazil

Orchidaceae is one of the largest botanical families, with approximately 780 genera. Among the genera of this family, Catasetum currently comprises 166 species. The aim of this study was to characterize the root anatomy of eight Catasetum species, verifying adaptations related to epiphytic habit and looking for features that could contribute to the vegetative identification of such species. The species studied were collected at the Portal da Amazônia region, Mato Grosso state, Brazil. The roots were fixed in FAA 50, cut freehand, and stained with astra blue/fuchsin. Illustrations were obtained with a digital camera mounted on a photomicroscope. The roots of examined species shared most of the anatomical characteristics observed in other species of the Catasetum genus, and many of them have adaptations to the epiphytic habit, such as presence of secondary thickening in the velamen cell walls, exodermis, cortex, and medulla. Some specific features were recognized as having taxonomic application, such as composition of the thickening of velamen cell walls, ornamentation of absorbent root-hair walls, presence of tilosomes, composition and thickening of the cortical cell walls, presence of mycorrhizae, endodermal cell wall thickening, the number of protoxylem poles, and composition and thickening of the central area of the vascular cylinder. These traits are important anatomical markers to separate the species within the genus and to generate a dichotomous identification key for Catasetum. Thus, providing a useful tool for taxonomists of this group

Modelling tyre-road noise with data mining techniques

The research aimed to establish tyre-road noise models by using a Data Mining approach that allowed to build a predictive model and assess the importance of the tested input variables. The data modelling took into account three learning algorithms and three metrics to define the best predictive model. The variables tested included basic properties of pavement surfaces, macrotexture, megatexture, and uneven- ness and, for the first time, damping. Also, the importance of those variables was measured by using a sensitivity analysis procedure. Two types of models were set: one with basic variables and another with complex variables, such as megatexture and damping, all as a function of vehicles speed. More detailed models were additionally set by the speed level. As a result, several models with very good tyre-road noise predictive capacity were achieved. The most relevant variables were Speed, Temperature, Aggregate size, Mean Profile Depth, and Damping, which had the highest importance, even though influenced by speed. Megatexture and IRI had the lowest importance. The applicability of the models developed in this work is relevant for trucks tyre-noise prediction, represented by the AVON V4 test tyre, at the early stage of road pavements use. Therefore, the obtained models are highly useful for the design of pavements and for noise prediction by road authorities and contractors.

The Data Mining applied for the prediction of highway roughness due to overloaded trucks

Currently, the quality of the Indonesian national road network is inadequate due to several constraints, including overcapacity and overloaded trucks. The high deterioration rate of the road infrastructure in developing countries along with major budgetary restrictions and high growth in traffic have led to an emerging need for improving the performance of the highway maintenance system. However, the high number of intervening factors and their complex effects require advanced tools to successfully solve this problem. The high learning capabilities of Data Mining (DM) are a powerful solution to this problem. In the past, these tools have been successfully applied to solve complex and multi-dimensional problems in various scientific fields. Therefore, it is expected that DM can be used to analyze the large amount of data regarding the pavement and traffic, identify the relationship between variables, and provide information regarding the prediction of the data. In this paper, we present a new approach to predict the International Roughness Index (IRI) of pavement based on DM techniques. DM was used to analyze the initial IRI data, including age, Equivalent Single Axle Load (ESAL), crack, potholes, rutting, and long cracks. This model was developed and verified using data from an Integrated Indonesia Road Management System (IIRMS) that was measured with the National Association of Australian State Road Authorities (NAASRA) roughness meter. The results of the proposed approach are compared with the IIRMS analytical model adapted to the IRI, and the advantages of the new approach are highlighted. We show that the novel data-driven model is able to learn (with high accuracy) the complex relationships between the IRI and the contributing factors of overloaded trucks

Early holocenic and historic mtDNA african signatures in the iberian peninsula: The andalusian region as a paradigm

Determining the timing, identity and direction of migrations in the Mediterranean Basin, the role of "migratory routes" in and among regions of Africa, Europe and Asia, and the effects of sex-specific behaviors of population movements have important implications for our understanding of the present human genetic diversity. A crucial component of the Mediterranean world is its westernmost region. Clear features of transcontinental ancient contacts between North African and Iberian populations surrounding the maritime region of Gibraltar Strait have been identified from archeological data. The attempt to discern origin and dates of migration between close geographically related regions has been a challenge in the field of uniparental-based population genetics. Mitochondrial DNA (mtDNA) studies have been focused on surveying the H1, H3 and V lineages when trying to ascertain north-south migrations, and U6 and L in the opposite direction, assuming that those lineages are good proxies for the ancestry of each side of the Mediterranean. To this end, in the present work we have screened entire mtDNA sequences belonging to U6, M1 and L haplogroups in Andalusians--from Huelva and Granada provinces--and Moroccan Berbers. We present here pioneer data and interpretations on the role of NW Africa and the Iberian Peninsula regarding the time of origin, number of founders and expansion directions of these specific markers. The estimated entrance of the North African U6 lineages into Iberia at 10 ky correlates well with other L African clades, indicating that U6 and some L lineages moved together from Africa to Iberia in the Early Holocene. Still, founder analysis highlights that the high sharing of lineages between North Africa and Iberia results from a complex process continued through time, impairing simplistic interpretations. In particular, our work supports the existence of an ancient, frequently denied, bridge connecting the Maghreb and Andalusia.

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.

Constraints on new phenomena via Higgs boson couplings and invisible decays with the ATLAS detector

The ATLAS experiment at the LHC has measured the Higgs boson couplings and mass, and searched for invisible Higgs boson decays, using multiple production and decay channels with up to 4.7 fb−1 of pp collision data at √s=7 TeV and 20.3 fb−1 at √s=8 TeV. In the current study, the measured production and decay rates of the observed Higgs boson in the γγ, ZZ, W W , Zγ, bb, τ τ , and μμ decay channels, along with results from the associated production of a Higgs boson with a top-quark pair, are used to probe the scaling of the couplings with mass. Limits are set on parameters in extensions of the Standard Model including a composite Higgs boson, an additional electroweak singlet, and two-Higgs-doublet models. Together with the measured mass of the scalar Higgs boson in the γγ and ZZ decay modes, a lower limit is set on the pseudoscalar Higgs boson mass of m A > 370 GeV in the “hMSSM” simplified Minimal Supersymmetric Standard Model. Results from direct searches for heavy Higgs bosons are also interpreted in the hMSSM. Direct searches for invisible Higgs boson decays in the vector-boson fusion and associated production of a Higgs boson with W/Z (Z → ℓℓ, W/Z → jj) modes are statistically combined to set an upper limit on the Higgs boson invisible branching ratio of 0.25. The use of the measured visible decay rates in a more general coupling fit improves the upper limit to 0.23, constraining a Higgs portal model of dark matter.

Erratum to: Measurement of the inclusive jet cross-section in proton-proton collisions at s√=7 TeV using 4.5 fb−1 of data with the ATLAS detector

It was found that the non-perturbative corrections calculated using Pythia with the Perugia 2011 tune did not include the effect of the underlying event. The affected correction factors were recomputed using the Pythia 6.427 generator. These corrections are applied as baseline to the NLO pQCD calculations and thus the central values of the theoretical predictions have changed by a few percent with the new corrections. This has a minor impact on the agreement between the data and the theoretical predictions. Figures 2 and 6 to 13, and all the tables have been updated with the new values. A few sentences in the discussion in sections 5.2 and 9 were altered or removed.

Modelling Z→ττ processes in ATLAS with τ-embedded Z→μμ data

This paper describes the concept, technical realisation and validation of a largely data-driven method to model events with Z→ττ decays. In Z→μμ events selected from proton-proton collision data recorded at s√=8 TeV with the ATLAS experiment at the LHC in 2012, the Z decay muons are replaced by τ leptons from simulated Z→ττ decays at the level of reconstructed tracks and calorimeter cells. The τ lepton kinematics are derived from the kinematics of the original muons. Thus, only the well-understood decays of the Z boson and τ leptons as well as the detector response to the τ decay products are obtained from simulation. All other aspects of the event, such as the Z boson and jet kinematics as well as effects from multiple interactions, are given by the actual data. This so-called τ-embedding method is particularly relevant for Higgs boson searches and analyses in ττ final states, where Z→ττ decays constitute a large irreducible background that cannot be obtained directly from data control samples.

Search for new light gauge bosons in Higgs boson decays to four-lepton final states in pp collisions at s√=8TeV with the ATLAS detector at the LHC

This paper presents a search for Higgs bosons decaying to four leptons, either electrons or muons, via one or two light exotic gauge bosons Zd, H→ZZd→4ℓ or H→ZdZd→4ℓ. The search was performed using pp collision data corresponding to an integrated luminosity of about 20 fb−1 at the center-of-mass energy of s√=8TeV recorded with the ATLAS detector at the Large Hadron Collider. The observed data are well described by the Standard Model prediction. Upper bounds on the branching ratio of H→ZZd→4ℓ and on the kinetic mixing parameter between the Zd and the Standard Model hypercharge gauge boson are set in the range (1--9)×10−5 and (4--17)×10−2 respectively, at 95% confidence level assuming the Standard Model branching ratio of H→ZZ∗→4ℓ, for Zd masses between 15 and 55 GeV. Upper bounds on the effective mass mixing parameter between the Z and the Zd are also set using the branching ratio limits in the H→ZZd→4ℓ search, and are in the range (1.5--8.7)×10−4 for 15portal coupling parameter, controlling the strength of the coupling of the Higgs boson to dark vector bosons, are set in the range (2--3)×10−5 and (1--10)×10−4 respectively, at 95 % confidence level assuming the Standard Model Higgs boson production cross sections, for Zd masses between 15 and 60 GeV.