Abstract computation in schizophrenia detection through artificial neural network based systems

Schizophrenia stands for a long-lasting state of mental uncertainty that may bring to an end the relation among behavior, thought, and emotion; that is, it may lead to unreliable perception, not suitable actions and feelings, and a sense of mental fragmentation. Indeed, its diagnosis is done over a large period of time; continuos signs of the disturbance persist for at least 6 (six) months. Once detected, the psychiatrist diagnosis is made through the clinical interview and a series of psychic tests, addressed mainly to avoid the diagnosis of other mental states or diseases. Undeniably, the main problem with identifying schizophrenia is the difficulty to distinguish its symptoms from those associated to different untidiness or roles. Therefore, this work will focus on the development of a diagnostic support system, in terms of its knowledge representation and reasoning procedures, based on a blended of Logic Programming and Artificial Neural Networks approaches to computing, taking advantage of a novel approach to knowledge representation and reasoning, which aims to solve the problems associated in the handling (i.e., to stand for and reason) of defective information.

Measurement of the forward-backward asymmetry of electron and muon pair-production in pp collisions at s√ = 7 TeV with the ATLAS detector

This paper presents measurements from the ATLAS experiment of the forward-backward asymmetry in the reaction pp→Z/γ∗→l+l−, with l being electrons or muons, and the extraction of the effective weak mixing angle. The results are based on the full set of data collected in 2011 in pp collisions at the LHC at s√ = 7 TeV, corresponding to an integrated luminosity of 4.8 fb−1. The measured asymmetry values are found to be in agreement with the corresponding Standard Model predictions. The combination of the muon and electron channels yields a value of the effective weak mixing angle of 0.2308±0.0005(stat.)±0.0006(syst.)±0.0009(PDF), where the first uncertainty corresponds to data statistics, the second to systematic effects and the third to knowledge of the parton density functions. This result agrees with the current world average from the Particle Data Group fit.

Measurement of three-jet production cross-sections in pp collisions at 7 TeV centre-of-mass energy using the ATLAS detector

Double-differential three-jet production cross-sections are measured in proton--proton collisions at a centre-of-mass energy of s√=7TeV using the ATLAS detector at the Large Hadron Collider. The measurements are presented as a function of the three-jet mass (mjjj), in bins of the sum of the absolute rapidity separations between the three leading jets (|Y∗|). Invariant masses extending up to 5 TeV are reached for 8<|Y∗|<10. These measurements use a sample of data recorded using the ATLAS detector in 2011, which corresponds to an integrated luminosity of 4.51fb−1. Jets are identified using the anti-kt algorithm with two different jet radius parameters, R=0.4 and R=0.6. The dominant uncertainty in these measurements comes from the jet energy scale. Next-to-leading-order QCD calculations corrected to account for non-perturbative effects are compared to the measurements. Good agreement is found between the data and the theoretical predictions based on most of the available sets of parton distribution functions, over the full kinematic range, covering almost seven orders of magnitude in the measured cross-section values.

Performance of the ATLAS muon trigger in pp collisions at s√=8 TeV

The performance of the ATLAS muon trigger system has been evaluated with proton--proton collision data collected in 2012 at the Large Hadron Collider at a centre-of-mass energy of 8 TeV. The performance was primarily evaluated using events containing a pair of muons from the decay of Z bosons. The efficiency is measured for the single-muon trigger for a kinematic region of the transverse momentum pT between 25 and 100 GeV, with a statistical uncertainty of less than 0.01% and a systematic uncertainty of 0.6%. The performance is also compared in detail to the predictions from simulation. The efficiency was measured over a wide pT range (a few GeV to several hundred GeV) by using muons from J/ψ mesons,W bosons, and top and antitop quarks. It showed highly uniform and stable performance.

Measurement of the top-quark mass in the fully hadronic decay channel from ATLAS data at s√=7 TeV

The mass of the top quark is measured in a data set corresponding to 4.6 fb−1 of proton--proton collisions with centre-of-mass energy s√=7 TeV collected by the ATLAS detector at the LHC. Events consistent with hadronic decays of top--antitop quark pairs with at least six jets in the final state are selected. The substantial background from multijet production is modelled with data-driven methods that utilise the number of identified b-quark jets and the transverse momentum of the sixth leading jet, which have minimal correlation. The top-quark mass is obtained from template fits to the ratio of three-jet to dijet mass. The three-jet mass is calculated from the three jets of a top-quark decay. Using these three jets the dijet mass is obtained from the two jets of the W boson decay. The top-quark mass obtained from this fit is thus less sensitive to the uncertainty in the energy measurement of the jets. A binned likelihood fit yields a top-quark mass of mt = 175.1 ± 1.4 (stat.) ± 1.2 (syst.) GeV.

Identification and energy calibration of hadronically decaying tau leptons with the ATLAS experiment in pp collisions at s√=8 TeV

This paper describes the trigger and offline reconstruction, identification and energy calibration algorithms for hadronic decays of tau leptons employed for the data collected from pp collisions in 2012 with the ATLAS detector at the LHC center-of-mass energy s√ = 8 TeV. The performance of these algorithms is measured in most cases with Z decays to tau leptons using the full 2012 dataset, corresponding to an integrated luminosity of 20.3 fb−1. An uncertainty on the offline reconstructed tau energy scale of 2% to 4%, depending on transverse energy and pseudorapidity, is achieved using two independent methods. The offline tau identification efficiency is measured with a precision of 2.5% for hadronically decaying tau leptons with one associated track, and of 4% for the case of three associated tracks, inclusive in pseudorapidity and for a visible transverse energy greater than 20 GeV. For hadronic tau lepton decays selected by offline algorithms, the tau trigger identification efficiency is measured with a precision of 2% to 8%, depending on the transverse energy. The performance of the tau algorithms, both offline and at the trigger level, is found to be stable with respect to the number of concurrent proton--proton interactions and has supported a variety of physics results using hadronically decaying tau leptons at ATLAS.

Global warming in Amazonia: impacts and Mitigation

Global warming has potentially catastrophic impacts in Amazonia, while at the same time maintenance of the Amazon forest offers one of the most valuable and cost-effective options for mitigating climate change. We know that the El Niño phenomenon, caused by temperature oscillations of surface water in the Pacific, has serious impacts in Amazonia, causing droughts and forest fires (as in 1997-1998). Temperature oscillations in the Atlantic also provoke severe droughts (as in 2005). We also know that Amazonian trees die both from fires and from water stress under hot, dry conditions. In addition, water recycled through the forest provides rainfall that maintains climatic conditions appropriate for tropical forest, especially in the dry season. What we need to know quickly, through intensified research, includes progress in representing El Niño and the Atlantic oscillations in climatic models, representation of biotic feedbacks in models used for decision-making about global warming, and narrowing the range of estimating climate sensitivity to reduce uncertainty about the probability of very severe impacts. Items that need to be negotiated include the definition of "dangerous" climate change, with the corresponding maximum levels of greenhouse gases in the atmosphere. Mitigation of global warming must include maintaining the Amazon forest, which has benefits for combating global warming from two separate roles: cutting the flow the emissions of carbon each year from the rapid pace of deforestation, and avoiding emission of the stock of carbon in the remaining forest that can be released by various ways, including climate change itself. Barriers to rewarding forest maintenance include the need for financial rewards for both of these roles. Other needs are for continued reduction of uncertainty regarding emissions and deforestation processes, as well as agreement on the basis of carbon accounting. As one of the countries most subject to impacts of climate change, Brazil must assume the leadership in fighting global warming.

Estudo da influência cultural no Design de Calçado

Dissertação de mestrado em Design e Marketing

An innovative framework for probabilistic-based structural assessment with an application to existing reinforced concrete structures

A novel framework for probabilistic-based structural assessment of existing structures, which combines model identification and reliability assessment procedures, considering in an objective way different sources of uncertainty, is presented in this paper. A short description of structural assessment applications, provided in literature, is initially given. Then, the developed model identification procedure, supported in a robust optimization algorithm, is presented. Special attention is given to both experimental and numerical errors, to be considered in this algorithm convergence criterion. An updated numerical model is obtained from this process. The reliability assessment procedure, which considers a probabilistic model for the structure in analysis, is then introduced, incorporating the results of the model identification procedure. The developed model is then updated, as new data is acquired, through a Bayesian inference algorithm, explicitly addressing statistical uncertainty. Finally, the developed framework is validated with a set of reinforced concrete beams, which were loaded up to failure in laboratory.

Formação e avaliação de desempenho: contributos para o desenvolvimento profissional

Tese de Doutoramento em Ciências da Educação (Especialidade em Desenvolvimento Curricular)

Redes interorganizacionais nas políticas públicas: atores, conexões e configurações organizacionais

Tese de Doutoramento em Sociologia

Tissue hyaluronan expression, as reflected in the sputum of lung cancer patients, is an indicator of malignancy

Hyaluronan (HA) shows promise for detecting cancerous change in pleural effusion and urine. However, there is uncertainty about the localization of HA in tumor tissue and its relationship with different histological types and other components of the extracellular matrix, such as angiogenesis. We evaluated the association between HA and degree of malignancy through expression in lung tumor tissue and sputum. Tumoral tissue had significantly increased HA compared to normal tissue. Strong HA staining intensity associated with cancer cells was significant in squamous cell carcinoma compared to adenocarcinoma and large cell carcinoma. A significant direct association was found between tumors with a high percentage of HA and MVD (microvessel density) in tumoral stroma. Similarly significant was the direct association between N1 tumors and high levels of HA in cancer cells. Cox multivariate analysis showed significant association between better survival and low HA. HA increased in sputum from lung cancer patients compared to cancer-free and healthy volunteers and a significant correlation was found between HA in sputum and HA in cancer tissue. Localization of HA in tumor tissue was related to malignancy and reflected in sputum, making this an emerging factor for an important diagnostic procedure in patients suspected to have lung cancer. Further study in additional patients in a randomized prospective trial is required to finalize these results and to validate our quantitative assessment of HA, as well as to couple it to gold standard sputum cytology.

Estudo da cabeceira da Sé do Porto

Dissertação de mestrado integrado em Engenharia Civil

Programa com abordagem probabilística do sistema de avaliação de qualidade de taludes Slope Quality Index (SQI)

Dissertação de mestrado integrado em Engenharia Civil

Stress induced risk-aversion is reverted by D2/D3 agonist in the rat

Stress exposure triggers cognitive and behavioral impairments that influence decision-making processes. Decisions under a context of uncertainty require complex reward-prediction processes that are known to be mediated by the mesocorticolimbic dopamine (DA) system in brain areas sensitive to the deleterious effects of chronic stress, in particular the orbitofrontal cortex (OFC). Using a decision-making task, we show that chronic stress biases risk-based decision-making to safer behaviors. This decision-making pattern is associated with an increased activation of the lateral part of the OFC and with morphological changes in pyramidal neurons specifically recruited by this task. Additionally, stress exposure induces a hypodopaminergic status accompanied by increased mRNA levels of the dopamine receptor type 2 (Drd2) in the OFC; importantly, treatment with a D2/D3 agonist quinpirole reverts the shift to safer behaviors induced by stress on risky decision-making. These results suggest that the brain mechanisms related to risk-based decision-making are altered after chronic stress, but can be modulated by manipulation of dopaminergic transmission.