Web 2.0, PC e EFA: impactes de uma oficina de formação de professores

As competências em Tecnologia da Informação e Comunicação (TIC) e o Pensamento Crítico (PC) são duas das linhas orientadoras da Aprendizagem ao Longo da Vida (ALV) que reconhecendo que todos os contextos (informais, não-formais e formais) podem ser de aprendizagem, assumiram no quadro da Educação e Formação de Adultos (EFA), em Portugal, uma expressividade plasmada no Referencial de Competências-Chave de Educação e Formação de Adultos, nível secundário (EFA-NS). Contudo a orientação PC/TIC não tem sido explicitamente conciliada nas práticas de educação e formação de adultos. Neste contexto desenvolveu-se uma Oficina de Formação para professores/formadores de cursos EFA-NS, na qual se trabalhou a integração de ferramentas da Web 2.0 com a infusão de PC em materiais/atividades para cursos EFA-NS. No desenvolvimento da Oficina foram consideradas três vertentes. Primeira, conceções dos professores sobre EFA/TIC e EFA/PC. Segunda, a formação sobre PC/TIC. Terceira, produção e implementação de materiais/atividades com orientação PC/TIC. A componente de trabalho autónomo da Oficina passou essencialmente pela dinâmica de uma comunidade online de nome EF@. O grupo de formação era constituído por 17 professores do ensino secundário, e pela investigadora/formadora, autora deste estudo. Acrescente-se que no conjunto das 10 sessões de trabalho presencial a investigadora/formadora foi coadjuvada por mais três formadores. Estudar os impactes da Oficina no desenvolvimento profissional dos professores, conjuntamente com a avaliação da influência dos materiais/atividades produzidos (na Oficina) no nível de PC dos alunos, assumiram-se como as duas questões de investigação a que este estudo pretendeu dar resposta. Neste sentido estudámos o grupo de professores em formação – estudo de caso – e o grupo de alunos – plano quasi experimental do tipo grupo de controlo/experimental, pré/pós-teste, pelo que o enquadramento da metodologia num estudo misto, predominantemente de natureza qualitativa, foi a adotada. A recolha e o tratamento de dados foram feitos mediante várias técnicas – observação, inquérito, análise e testagem – associadas a diferentes instrumentos: dois questionários, diário de investigador e Teste de Pensamento Crítico – Cornell (Nível X). A análise dos dados recolhidos possibilitou a compreensão de como a Oficina contribui para a reflexão: (i) nas práticas anteriores dos professores; (ii) nas competências adquiridas na Oficina e (iii) nas práticas implementadas. Ao nível do PC dos alunos, podemos dizer que os materiais/atividades produzidos na Oficina influenciaram o nível de PC dos alunos, já que os resultados da média do PC do pós-teste foram estatisticamente significativos para o grupo experimental, quando comparado com a média do PC no grupo de controlo.

A frequency-domain receiver for asynchronous systems employing CP-assisted DS-CDMA schemes

In this paper we consider the uplink transmission within CP-assisted (Cyclic Pre¯x) DS-CDMA (Direct Sequence Code Division Multiple Access) systems and we present a frequency-domain MUD (MultiUser Detection) receiver with iterative estimation and compensation of residual frequency errors. The proposed receiver is suitable for broadband wireless systems, with performances that can be close to the single-user MFB (Matched Filter Bound), even for fully loaded systems and/or in the presence of strong interfering signals. The receiver is powerful enough for typical asynchronous scenarios, requiring only a coarse synchronization between users.

B-splines neural network assisted PID autotuning

This papers describes an extantion of previous works on the subject of neural network proportional, integral and derivative (PID) autotuning. Basically, neural networks are employed to supply the three PID parameters, according to the integral of time multiplied by the absolute error (ITAE) criterion, to a standard PID controller.

Analysis of polycyclic aromatic hydrocarbons in fish: optimisation and validation of microwave-assisted extraction

An accurate and sensitive method for determination of 18 polycyclic aromatic hydrocarbons (PAHs) (16 PAHs considered by USEPA as priority pollutants, dibenzo[a,l]pyrene and benzo[j]fluoranthene) in fish samples was validated. Analysis was performed by microwave-assisted extraction and liquid chromatography with photodiode array and fluorescence detection. Response surface methodology was used to find the optimal extraction parameters. Validation of the overall methodology was performed by spiking assays at four levels and using SRM 2977. Quantification limits ranging from 0.15–27.16 ng/g wet weight were obtained. The established method was applied in edible tissues of three commonly consumed and commercially valuable fish species (sardine, chub mackerel and horse mackerel) originated from Atlantic Ocean. Variable levels of naphthalene (1.03–2.95 ng/g wet weight), fluorene (0.34–1.09 ng/g wet weight) and phenanthrene (0.34–3.54 ng/g wet weight) were detected in the analysed samples. None of the samples contained detectable amounts of benzo[a]pyrene, the marker used for evaluating the occurrence and carcinogenic effects of PAHs in food.

Determination of chlorfenvinphos in soils by microwave-assisted extraction and stripping voltammetry with an ultramicroelectrode

A methodology for the determination of the pesticide chlorfenvinphos by microwave-assisted solvent extraction and square-wave cathodic stripping voltammetry at a mercury film ultramicroelectrode in soil samples is proposed. Optimization of microwave solvent extraction performed with two soils, selected for having significantly different properties, indicated that the optimum solvent for extracting chlorfenvinphos is hexane-acetone (1:1, v/v). The voltammetric procedure is based on controlled adsorptive accumulation of the insecticide at the potential of -0.60 V (vs. Ag/AgCl) in the presence of Britton-Robinson buffer (pH 6.2). The detection limit obtained for a 10 s collection time was 3.0 x 10-8 mol l-1. The validity of the developed methodology was assessed by recovery experiments at the 0.100 µg g-1 level. The average recoveries and standard deviations for the global procedure reached byMASE-square-wave voltammetry were 90.2±2.8% and 92.1±3.4% for type I (soil rich in organic matter) and type II (sandy soil) samples, respectively. These results are in accordance to the expected values which show that the method has a good accuracy.

Determination of carbamate and urea pesticide residues in fresh vegetables using microwave-assisted extraction and liquid chromatography

An analytical multiresidue method for the simultaneous determination of seven pesticides in fresh vegetable samples, namely, courgette (Cucurbita pepo), cucumber (Cucumis sativus), lettuce (Lactuca sativa, Romaine and Iceberg varieties) and peppers (Capsicum sp.) is described. The procedure, based on microwave-assisted extraction (MAE) and analysis by liquid chromatography– photodiode array (LC–PDA) detection was applied to four carbamates (carbofuran, carbaryl, chlorpropham and EPTC) and three urea pesticides (monolinuron, metobromuron and linuron). Extraction solvent and the addition of anhydrous sodium sulphate to fresh vegetable homogenate before MAE were the parameters optimised for each commodity. Recovery studies were performed using spiked samples in the range 250–403 µgkg- 1 in each pesticide. The pesticide residues were extracted using 20mL acetonitrile at 60 ºC, for 10 min. Acceptable recoveries and RSDs were attained (overall average recovery of 77.2% and RSDs are lower than 11%). Detection limits ranged between 5.8 µgkg- 1 for carbaryl to 12.3 µgkg- 1 for carbofuran. The analytical protocol was applied for quality control of 41 fresh vegetable samples bought in Oporto Metropolitan Area (North Portugal). None of the samples contained any detectable amounts of the studied compounds.

Development and validation of a novel method for the analysis of chlorinated pesticides in soils using microwave-assisted extraction–headspace solid phase microextraction and gas chromatography–tandem mass spectrometry

A new procedure for determining eleven organochlorine pesticides in soils using microwave-assisted extraction (MAE) and headspace solid phase microextraction (HS-SPME) is described. The studied pesticides consisted of mirex, α- and γ-chlordane, p,p’-DDT, heptachlor, heptachlor epoxide isomer A, γ-hexachlorocyclohexane, dieldrin, endrin, aldrine and hexachlorobenzene. The HS-SPME was optimized for the most important parameters such as extraction time, sample volume and temperature. The present analytical procedure requires a reduced volume of organic solvents and avoids the need for extract clean-up steps. For optimized conditions the limits of detection for the method ranged from 0.02 to 3.6 ng/g, intermediate precision ranged from 14 to 36% (as CV%), and the recovery from 8 up to 51%. The proposed methodology can be used in the rapid screening of soil for the presence of the selected pesticides, and was applied to landfill soil samples.

Determination of ametryn in soils via microwave-assisted solvent extraction coupled to anodic stripping voltammetry with a gold ultramicroelectrode

An extraction-anodic adsorptive stripping voltammetric procedure using microwave-assisted solvent extraction and a gold ultramicroelectrode was developed for determining the pesticide ametryn in soil samples. The method is based on the use of acetonitrile as extraction solvent and on controlled adsorptive accumulation of the herbicide at the potential of 0.50 V (vs. Ag/AgCl) in the presence of Britton-Robinson buffer (pH 3.3). Soil sample extracts were analysed directly after drying and redissolution with the supporting electrolyte but without other pre-treatment. The limit of detection obtained for a 10 s collection time was 0.021 µg g-1. Recovery experiments for the global procedure, at the 0.500 µg g-1 level, gave satisfactory mean and standard deviation results which were comparable to those obtained by HPLC with UV detection.

Analysis of PCBs in soils and sediments by microwave-assisted extraction, headspace-SPME and high resolution gas chromatography with ion-trap tandem mass spectrometry

A procedure for the determination of seven indicator PCBs in soils and sediments using microwave-assisted extraction (MAE) and headspace solid-phase microextraction (HS-SPME) prior to GC-MS/MS is described. Optimization of the HS-SPME was carried out for the most important parameters such as extraction time, sample volume and temperature. The adopted methodology has reduced consumption of organic solvents and analysis runtime. Under the optimized conditions, the method detection limit ranged from 0.6 to 1 ng/g when 5 g of sample was extracted, the precision on real samples ranged from 4 to 21% and the recovery from 69 to 104%. The proposed method, which included the analysis of a certified reference material in its validation procedure, can be extended to several other PCBs and used in the monitoring of soil or sediments for the presence of PCBs.

Determination of ochratoxin A in bread: evaluation of microwave-assisted extraction using an orthogonal composite design coupled with response surface methodology

An analytical method using microwave-assisted extraction (MAE) and liquid chromatography (LC) with fluorescence detection (FD) for the determination of ochratoxin A (OTA) in bread samples is described. A 24 orthogonal composite design coupled with response surface methodology was used to study the influence of MAE parameters (extraction time, temperature, solvent volume, and stirring speed) in order to maximize OTA recovery. The optimized MAE conditions were the following: 25 mL of acetonitrile, 10 min of extraction, at 80 °C, and maximum stirring speed. Validation of the overall methodology was performed by spiking assays at five levels (0.1–3.00 ng/g). The quantification limit was 0.005 ng/g. The established method was then applied to 64 bread samples (wheat, maize, and wheat/maize bread) collected in Oporto region (Northern Portugal). OTAwas detected in 84 % of the samples with a maximum value of 2.87 ng/g below the European maximum limit established for OTA in cereal products of 3 ng/g.

An intelligent clustering scheme for distributed intrusion detection in vehicular cloud computing

In recent years, vehicular cloud computing (VCC) has emerged as a new technology which is being used in wide range of applications in the area of multimedia-based healthcare applications. In VCC, vehicles act as the intelligent machines which can be used to collect and transfer the healthcare data to the local, or global sites for storage, and computation purposes, as vehicles are having comparatively limited storage and computation power for handling the multimedia files. However, due to the dynamic changes in topology, and lack of centralized monitoring points, this information can be altered, or misused. These security breaches can result in disastrous consequences such as-loss of life or financial frauds. Therefore, to address these issues, a learning automata-assisted distributive intrusion detection system is designed based on clustering. Although there exist a number of applications where the proposed scheme can be applied but, we have taken multimedia-based healthcare application for illustration of the proposed scheme. In the proposed scheme, learning automata (LA) are assumed to be stationed on the vehicles which take clustering decisions intelligently and select one of the members of the group as a cluster-head. The cluster-heads then assist in efficient storage and dissemination of information through a cloud-based infrastructure. To secure the proposed scheme from malicious activities, standard cryptographic technique is used in which the auotmaton learns from the environment and takes adaptive decisions for identification of any malicious activity in the network. A reward and penalty is given by the stochastic environment where an automaton performs its actions so that it updates its action probability vector after getting the reinforcement signal from the environment. The proposed scheme was evaluated using extensive simulations on ns-2 with SUMO. The results obtained indicate that the proposed scheme yields an improvement of 10 % in detection rate of malicious nodes when compared with the existing schemes.

Electrochemical biosensor based on biomimetic material for myoglobin detection

A novel reusable molecularly imprinted polymer (MIP) assembled on a polymeric layer of carboxylated poly(vinyl chloride) (PVCsingle bondCOOH) for myoglobin (Myo) detection was developed. This polymer was casted on the gold working area of a screen printed electrode (Au-SPE), creating a novel disposable device relying on plastic antibodies. Electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV) and Fourier transform infrared spectroscopy (FTIR) studies confirmed the surface modification. The MIP/Au-SPE devices displayed a linear behaviour in EIS from 0.852 to 4.26 μg mL−1, of positive slope 6.50 ± 1.48 (kΩ mL μg−1). The limit of detection was 2.25 μg mL−1. Square wave voltammetric (SWV) assays were made in parallel and showed linear responses between 1.1 and 2.98 μg mL−1. A current decrease was observed against Myo concentration, producing average slopes of −0.28 ± 0.038 μA mL μg−1. MIP/Au-SPE also showed good results in terms of selectivity. The error% found for each interfering species were 7% for troponin T (TnT), 11% for bovine serum albumin (BSA) and 2% for creatine kinase MB (CKMB), respectively. Overall, the technical modification over the Au-SPE was found a suitable approach for screening Myo in biological fluids.

Creation of a web application for smart park system and parking prediction study for system integration

In the last few years, we have observed an exponential increasing of the information systems, and parking information is one more example of them. The needs of obtaining reliable and updated information of parking slots availability are very important in the goal of traffic reduction. Also parking slot prediction is a new topic that has already started to be applied. San Francisco in America and Santander in Spain are examples of such projects carried out to obtain this kind of information. The aim of this thesis is the study and evaluation of methodologies for parking slot prediction and the integration in a web application, where all kind of users will be able to know the current parking status and also future status according to parking model predictions. The source of the data is ancillary in this work but it needs to be understood anyway to understand the parking behaviour. Actually, there are many modelling techniques used for this purpose such as time series analysis, decision trees, neural networks and clustering. In this work, the author explains the best techniques at this work, analyzes the result and points out the advantages and disadvantages of each one. The model will learn the periodic and seasonal patterns of the parking status behaviour, and with this knowledge it can predict future status values given a date. The data used comes from the Smart Park Ontinyent and it is about parking occupancy status together with timestamps and it is stored in a database. After data acquisition, data analysis and pre-processing was needed for model implementations. The first test done was with the boosting ensemble classifier, employed over a set of decision trees, created with C5.0 algorithm from a set of training samples, to assign a prediction value to each object. In addition to the predictions, this work has got measurements error that indicates the reliability of the outcome predictions being correct. The second test was done using the function fitting seasonal exponential smoothing tbats model. Finally as the last test, it has been tried a model that is actually a combination of the previous two models, just to see the result of this combination. The results were quite good for all of them, having error averages of 6.2, 6.6 and 5.4 in vacancies predictions for the three models respectively. This means from a parking of 47 places a 10% average error in parking slot predictions. This result could be even better with longer data available. In order to make this kind of information visible and reachable from everyone having a device with internet connection, a web application was made for this purpose. Beside the data displaying, this application also offers different functions to improve the task of searching for parking. The new functions, apart from parking prediction, were: - Park distances from user location. It provides all the distances to user current location to the different parks in the city. - Geocoding. The service for matching a literal description or an address to a concrete location. - Geolocation. The service for positioning the user. - Parking list panel. This is not a service neither a function, is just a better visualization and better handling of the information.

Towards high-quality simultaneous EEG-fMRI at 7T: Detection and reduction of EEG artifacts due to head motion.

The enhanced functional sensitivity offered by ultra-high field imaging may significantly benefit simultaneous EEG-fMRI studies, but the concurrent increases in artifact contamination can strongly compromise EEG data quality. In the present study, we focus on EEG artifacts created by head motion in the static B0 field. A novel approach for motion artifact detection is proposed, based on a simple modification of a commercial EEG cap, in which four electrodes are non-permanently adapted to record only magnetic induction effects. Simultaneous EEG-fMRI data were acquired with this setup, at 7T, from healthy volunteers undergoing a reversing-checkerboard visual stimulation paradigm. Data analysis assisted by the motion sensors revealed that, after gradient artifact correction, EEG signal variance was largely dominated by pulse artifacts (81-93%), but contributions from spontaneous motion (4-13%) were still comparable to or even larger than those of actual neuronal activity (3-9%). Multiple approaches were tested to determine the most effective procedure for denoising EEG data incorporating motion sensor information. Optimal results were obtained by applying an initial pulse artifact correction step (AAS-based), followed by motion artifact correction (based on the motion sensors) and ICA denoising. On average, motion artifact correction (after AAS) yielded a 61% reduction in signal power and a 62% increase in VEP trial-by-trial consistency. Combined with ICA, these improvements rose to a 74% power reduction and an 86% increase in trial consistency. Overall, the improvements achieved were well appreciable at single-subject and single-trial levels, and set an encouraging quality mark for simultaneous EEG-fMRI at ultra-high field.

Advances in therapeutic risk management through signal detection and risk minimisation tool analyses

Les quatre principales activités de la gestion de risque thérapeutique comportent l’identification, l’évaluation, la minimisation, et la communication du risque. Ce mémoire aborde les problématiques liées à l’identification et à la minimisation du risque par la réalisation de deux études dont les objectifs sont de: 1) Développer et valider un outil de « data mining » pour la détection des signaux à partir des banques de données de soins de santé du Québec; 2) Effectuer une revue systématique afin de caractériser les interventions de minimisation de risque (IMR) ayant été implantées. L’outil de détection de signaux repose sur la méthode analytique du quotient séquentiel de probabilité (MaxSPRT) en utilisant des données de médicaments délivrés et de soins médicaux recueillis dans une cohorte rétrospective de 87 389 personnes âgées vivant à domicile et membres du régime d’assurance maladie du Québec entre les années 2000 et 2009. Quatre associations « médicament-événement indésirable (EI) » connues et deux contrôles « négatifs » ont été utilisés. La revue systématique a été faite à partir d’une revue de la littérature ainsi que des sites web de six principales agences réglementaires. La nature des RMIs ont été décrites et des lacunes de leur implémentation ont été soulevées. La méthode analytique a mené à la détection de signaux dans l'une des quatre combinaisons médicament-EI. Les principales contributions sont: a) Le premier outil de détection de signaux à partir des banques de données administratives canadiennes; b) Contributions méthodologiques par la prise en compte de l'effet de déplétion des sujets à risque et le contrôle pour l'état de santé du patient. La revue a identifié 119 IMRs dans la littérature et 1,112 IMRs dans les sites web des agences réglementaires. La revue a démontré qu’il existe une augmentation des IMRs depuis l’introduction des guides réglementaires en 2005 mais leur efficacité demeure peu démontrée.