Performance assessment of electrically small antennas for implantable microsystems with wireless power and communications

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Eletrónica Médica)

A modular traffic sampling architecture for flexible network measurements

Dissertação de Mestrado (Programa Doutoral em Informática)

Toxicity measurement techniques for building materials with wastes

The innovative Horizon 2020 program sponsored by the European Union (EU) aims to promote and develop processes of waste integration in construction materials. However, several potential health hazards caused by building materials have been identified and, there-fore, there is an ongoing need to develop new recycling methods for hazardous wastes and effi-cient barriers in order to prevent toxic releases from the new construction solutions with wastes. This paper presents an overview that focus on two main aspects: the identification of the health risks related to radioactivity and heavy metals present in building materials and identification of these toxic substances in new construction solutions that contain recycled wastes. Different waste materials were selected and distinct methodologies of toxicity evaluation are presented to analyse the potential hazardous, the feasibility of using those wastes and the achievement of op-timal construction solutions involving wastes.

Towards effective control of P2P traffic aggregates in network infrastructures

Nowadays, many P2P applications proliferate in the Internet. The attractiveness of many of these systems relies on the collaborative approach used to exchange large resources without the dependence and associated constraints of centralized approaches where a single server is responsible to handle all the requests from the clients. As consequence, some P2P systems are also interesting and cost-effective approaches to be adopted by content-providers and other Internet players. However, there are several coexistence problems between P2P applications and In- ternet Service Providers (ISPs) due to the unforeseeable behavior of P2P traffic aggregates in ISP infrastructures. In this context, this work proposes a collaborative P2P/ISP system able to underpin the development of novel Traffic Engi- neering (TE) mechanisms contributing for a better coexistence between P2P applications and ISPs. Using the devised system, two TE methods are described being able to estimate and control the impact of P2P traffic aggregates on the ISP network links. One of the TE methods allows that ISP administrators are able to foresee the expected impact that a given P2P swarm will have in the underlying network infrastructure. The other TE method enables the definition of ISP friendly P2P topologies, where specific network links are protected from P2P traffic. As result, the proposed system and associated mechanisms will contribute for improved ISP resource management tasks and to foster the deployment of innovative ISP-friendly systems.

Automated network resilience optimization using computational intelligence methods

This paper presents an automated optimization framework able to provide network administrators with resilient routing configurations for link-state protocols, such as OSPF or IS-IS. In order to deal with the formulated NP-hard optimization problems, the devised framework is underpinned by the use of computational in- telligence optimization engines, such as Multi-objective Evolutionary Algorithms (MOEAs). With the objective of demonstrating the framework capabilities, two il- lustrative Traffic Engineering methods are described, allowing to attain routing con- figurations robust to changes in the traffic demands and maintaining the network stable even in the presence of link failure events. The presented illustrative results clearly corroborate the usefulness of the proposed automated framework along with the devised optimization methods.

Modeling microbes: New methods for integrated metabolic and regulatory network reconstruction

PhD Thesis in Bioengineering

Jet energy measurement and its systematic uncertainty in proton-proton collisions at s√=7 TeV with the ATLAS detector

The jet energy scale (JES) and its systematic uncertainty are determined for jets measured with the ATLAS detector using proton–proton collision data with a centre-of-mass energy of s√=7 TeV corresponding to an integrated luminosity of 4.7 fb −1 . Jets are reconstructed from energy deposits forming topological clusters of calorimeter cells using the anti- kt algorithm with distance parameters R=0.4 or R=0.6 , and are calibrated using MC simulations. A residual JES correction is applied to account for differences between data and MC simulations. This correction and its systematic uncertainty are estimated using a combination of in situ techniques exploiting the transverse momentum balance between a jet and a reference object such as a photon or a Z boson, for 20≤pjetT<1000 GeV and pseudorapidities |η|<4.5 . The effect of multiple proton–proton interactions is corrected for, and an uncertainty is evaluated using in situ techniques. The smallest JES uncertainty of less than 1 % is found in the central calorimeter region ( |η|<1.2 ) for jets with 55≤pjetT<500 GeV . For central jets at lower pT , the uncertainty is about 3 %. A consistent JES estimate is found using measurements of the calorimeter response of single hadrons in proton–proton collisions and test-beam data, which also provide the estimate for pjetT>1 TeV. The calibration of forward jets is derived from dijet pT balance measurements. The resulting uncertainty reaches its largest value of 6 % for low- pT jets at |η|=4.5 . Additional JES uncertainties due to specific event topologies, such as close-by jets or selections of event samples with an enhanced content of jets originating from light quarks or gluons, are also discussed. The magnitude of these uncertainties depends on the event sample used in a given physics analysis, but typically amounts to 0.5–3 %.

Measurement of the top pair production cross-section in 8 TeV proton-proton collisions using kinematic information in the lepton+jets final state with ATLAS

A measurement is presented of the tt¯ inclusive production cross section in pp collisions at a center-of-mass energy of s√=8  TeV using data collected by the ATLAS detector at the CERN Large Hadron Collider. The measurement was performed in the lepton+jets final state using a data set corresponding to an integrated luminosity of 20.3  fb−1. The cross section was obtained using a likelihood discriminant fit and b-jet identification was used to improve the signal-to-background ratio. The inclusive tt¯ production cross section was measured to be 260±1(stat)+22−23(stat)±8(lumi)±4(beam)  pb assuming a top-quark mass of 172.5 GeV, in good agreement with the theoretical prediction of 253+13−15  pb. The tt¯→(e,μ)+jets production cross section in the fiducial region determined by the detector acceptance is also reported.

Measurement of Spin Correlation in Top-Antitop Quark Events and Search for Top Squark Pair Production in pp Collisions at s√=8 TeV Using the ATLAS Detector

A measurement of spin correlation in tt¯ production is presented using data collected with the ATLAS detector at the Large Hadron Collider in proton-proton collisions at a center-of-mass energy of 8 TeV, corresponding to an integrated luminosity of 20.3 fb−1. The correlation between the top and antitop quark spins is extracted from dilepton tt¯ events by using the difference in azimuthal angle between the two charged leptons in the laboratory frame. In the helicity basis the measured degree of correlation corresponds to Ahelicity=0.38±0.04, in agreement with the Standard Model prediction. A search is performed for pair production of top squarks with masses close to the top quark mass decaying to predominantly right-handed top quarks and a light neutralino, the lightest supersymmetric particle. Top squarks with masses between the top quark mass and 191 GeV are excluded at the 95% confidence level.

Measurement of the transverse polarization of Λ and Λ ¯ hyperons produced in proton-proton collisions at s =7TeV using the ATLAS detector

The transverse polarization of Λ and Λ¯ hyperons produced in proton--proton collisions at a center-of-mass energy of 7 TeV is measured. The analysis uses 760 μb−1 of minimum bias data collected by the ATLAS detector at the LHC in the year 2010. The measured transverse polarization averaged over Feynman xF from 5×10−5 to 0.01 and transverse momentum pT from 0.8 to 15 GeV is −0.010±0.005(stat)±0.004(syst) for Λ and 0.002±0.006(stat)±0.004(syst) for Λ¯. It is also measured as a function of xF and pT, but no significant dependence on these variables is observed. Prior to this measurement, the polarization was measured at fixed-target experiments with center-of-mass energies up to about 40 GeV. The ATLAS results are compatible with the extrapolation of a fit from previous measurements to the xF range covered by this mesurement.

Observation and measurement of Higgs boson decays to WW∗ with the ATLAS detector

We report the observation of Higgs boson decays to WW∗ based on an excess over background of 6.1 standard deviations in the dilepton final state, where the Standard Model expectation is 5.8 standard deviations. Evidence for the vector-boson fusion (VBF) production process is obtained with a significance of 3.2 standard deviations. The results are obtained from a data sample corresponding to an integrated luminosity of 25 pb−1 from s√=7 and 8 TeV pp collisions recorded by the ATLAS detector at the LHC. For a Higgs boson mass of 125.36 GeV, the ratio of the measured value to the expected value of the total production cross section times branching fraction is 1.09+0.16−0.15 (stat.)+0.17−0.14 (syst.). The corresponding ratios for the gluon fusion and vector-boson fusion production mechanisms are 1.02±0.19 (stat.)+0.22−0.18 (syst.) and 1.27+0.44−0.40 (stat.)+0.30−0.21 (syst.), respectively. At s√=8 TeV, the total production cross sections are measured to be σ(gg→ H→WW∗)=4.6±0.9(stat.)+0.8−0.7(syst.)pb and σ(VBF H→WW∗)=0.51+0.17−0.15(stat.)+0.13−0.08(syst.)pb. The fiducial cross section is determined for the gluon-fusion process in exclusive final states with zero or one associated jet.

Observation of top-quark pair production in association with a photon and measurement of the t t ¯ γ production cross section in pp collisions at s =7 TeV using the ATLAS detector

A search is performed for top-quark pairs (tt¯) produced together with a photon (γ) with transverse momentum >20 GeV using a sample of tt¯ candidate events in final states with jets, missing transverse momentum, and one isolated electron or muon. The dataset used corresponds to an integrated luminosity of 4.59 fb−1 of proton--proton collisions at a center-of-mass energy of 7 TeV recorded by the ATLAS detector at the CERN Large Hadron Collider. In total 140 and 222 tt¯γ candidate events are observed in the electron and muon channels, to be compared to the expectation of 79±26 and 120±39 non-tt¯γ background events respectively. The production of tt¯γ events is observed with a significance of 5.3 standard deviations away from the null hypothesis. The tt¯γ production cross section times the branching ratio (BR) of the single-lepton decay channel is measured in a fiducial kinematic region within the ATLAS acceptance. The measured value is σfidtt¯γ=63±8(stat.)+17−13(syst.)±1(lumi.) fb per lepton flavor, in good agreement with the leading-order theoretical calculation normalized to the next-to-leading-order theoretical prediction of 48±10 fb.

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.

Thrombophilia screening: An artificial neural network approach

Thrombotic disorders have severe consequences for the patients and for the society in general, being one of the main causes of death. These facts reveal that it is extremely important to be preventive; being aware of how probable is to have that kind of syndrome. Indeed, this work will focus on the development of a decision support system that will cater for an individual risk evaluation with respect to the surge of thrombotic complaints. The Knowledge Representation and Reasoning procedures used will be based on an extension to the Logic Programming language, allowing the handling of incomplete and/or default data. The computational framework in place will be centered on Artificial Neural Networks.

Ergosterol as a rapid measurement of Ganoderma rot of oil palm

Palm oil (PO) is a very important commodity for many countries and especially Indonesia and Malaysia who are the predominant producers. PO is used in ca. 30% of supermarket foods, cosmetics, cooking and as biodiesel. The growth of oil palms in plantations is controversial as the production methods contribute to climate change and cause environmental damage [1]. The plant is subjected to a devastating disease in these two countries caused by the white rot fungus Ganoderma. There are no satisfactory methods to diagnose the disease in the plant as they are too slow and/or inaccurate. The lipid compound ergosterol is unique to fungi and is used to measure growth especially in solid substrates. We report here on the use of ergosterol to measure the growth of Ganoderma in oil palms using HPLC and TLC methods [2]. The method is rapid and correlates well with other methods and is capable of being used on-site, hence improving the speed of analysis and allowing remedial action. Climate change will affect the health of OP [1] and rapid detection methods will be increasingly required to control the disease. [1] Paterson, RRM, Kumar, L, Taylor, S, Lima N. Future climate effects on suitability for growth of oil palms in Malaysia and Indonesia. Scientific Reports, 5, 2015, 14457. [2] Muniroh, MS, Sariah M, Zainal Abidin, MA, Lima, N, Paterson, RRM. Rapid detection of Ganoderma-infected oil palms by microwave ergosterol extraction with HPLC and TLC. Journal of Microbiological Methods, 100, 2014, 143–147.