821 resultados para motivation-opportunity-ability (MOA)
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Heavy metal pollution is a matter of concern in industrialised countries. Contrary to organic pollutants, heavy metals are not metabolically degraded. This fact has two main consequences: its bioremediation requires another strategy and heavy metals can be indefinitely recycled. Yeast cells of Saccharomyces cerevisiae are produced at high amounts as a by-product of brewing industry constituting a cheap raw material. In the present work, the possibility of valorising this type of biomass in the bioremediation of real industrial effluents containing heavy metals is reviewed. Given the autoaggregation capacity (flocculation) of brewing yeast cells, a fast and off-cost yeast separation is achieved after the treatment of metal-laden effluent, which reduces the costs associated with the process. This is a critical issue when we are looking for an effective, eco-friendly, and low-cost technology. The possibility of the bioremediation of industrial effluents linked with the selective recovery of metals, in a strategy of simultaneous minimisation of environmental hazard of industrial wastes with financial benefits from reselling or recycling the metals, is discussed.
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Projeto de Intervenção apresentado à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em Educação Especial, especialidade em Multideficiência
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Trabalho Final de Mestrado para obtenção de grau de Mestre em Engenharia Mecânica na Especialidade de Manutenção e Produção
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Dissertação de Mestrado Apresentado ao Instituto de Contabilidade e Administração do Porto para a obtenção do grau de Mestre em Marketing Digital, sob orientação de Professor Doutor Freitas Santos
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The IEEE 802.15.4 protocol has the ability to support time-sensitive Wireless Sensor Network (WSN) applications due to the Guaranteed Time Slot (GTS) Medium Access Control mechanism. Recently, several analytical and simulation models of the IEEE 802.15.4 protocol have been proposed. Nevertheless, currently available simulation models for this protocol are both inaccurate and incomplete, and in particular they do not support the GTS mechanism. In this paper, we propose an accurate OPNET simulation model, with focus on the implementation of the GTS mechanism. The motivation that has driven this work is the validation of the Network Calculus based analytical model of the GTS mechanism that has been previously proposed and to compare the performance evaluation of the protocol as given by the two alternative approaches. Therefore, in this paper we contribute an accurate OPNET model for the IEEE 802.15.4 protocol. Additionally, and probably more importantly, based on the simulation model we propose a novel methodology to tune the protocol parameters such that a better performance of the protocol can be guaranteed, both concerning maximizing the throughput of the allocated GTS as well as concerning minimizing frame delay.
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This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the 1H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the 1H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the 1H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions and mixtures of reactions. Genome-scale classification of enzymatic reactions from their reaction equation. The MOLMAP descriptor relies on a Kohonen SOM that defines types of bonds on the basis of their physico-chemical and topological properties. The MOLMAP descriptor of a molecule represents the types of bonds available in that molecule. The MOLMAP descriptor of a reaction is defined as the difference between the MOLMAPs of the products and the reactants, and numerically encodes the pattern of bonds that are broken, changed, and made during a chemical reaction. The automatic perception of chemical similarities between metabolic reactions is required for a variety of applications ranging from the computer validation of classification systems, genome-scale reconstruction (or comparison) of metabolic pathways, to the classification of enzymatic mechanisms. Catalytic functions of proteins are generally described by the EC numbers that are simultaneously employed as identifiers of reactions, enzymes, and enzyme genes, thus linking metabolic and genomic information. Different methods should be available to automatically compare metabolic reactions and for the automatic assignment of EC numbers to reactions still not officially classified. In this study, the genome-scale data set of enzymatic reactions available in the KEGG database was encoded by the MOLMAP descriptors, and was submitted to Kohonen SOMs to compare the resulting map with the official EC number classification, to explore the possibility of predicting EC numbers from the reaction equation, and to assess the internal consistency of the EC classification at the class level. A general agreement with the EC classification was observed, i.e. a relationship between the similarity of MOLMAPs and the similarity of EC numbers. At the same time, MOLMAPs were able to discriminate between EC sub-subclasses. EC numbers could be assigned at the class, subclass, and sub-subclass levels with accuracies up to 92%, 80%, and 70% for independent test sets. The correspondence between chemical similarity of metabolic reactions and their MOLMAP descriptors was applied to the identification of a number of reactions mapped into the same neuron but belonging to different EC classes, which demonstrated the ability of the MOLMAP/SOM approach to verify the internal consistency of classifications in databases of metabolic reactions. RFs were also used to assign the four levels of the EC hierarchy from the reaction equation. EC numbers were correctly assigned in 95%, 90%, 85% and 86% of the cases (for independent test sets) at the class, subclass, sub-subclass and full EC number level,respectively. Experiments for the classification of reactions from the main reactants and products were performed with RFs - EC numbers were assigned at the class, subclass and sub-subclass level with accuracies of 78%, 74% and 63%, respectively. In the course of the experiments with metabolic reactions we suggested that the MOLMAP / SOM concept could be extended to the representation of other levels of metabolic information such as metabolic pathways. Following the MOLMAP idea, the pattern of neurons activated by the reactions of a metabolic pathway is a representation of the reactions involved in that pathway - a descriptor of the metabolic pathway. This reasoning enabled the comparison of different pathways, the automatic classification of pathways, and a classification of organisms based on their biochemical machinery. The three levels of classification (from bonds to metabolic pathways) allowed to map and perceive chemical similarities between metabolic pathways even for pathways of different types of metabolism and pathways that do not share similarities in terms of EC numbers. Mapping of PES by neural networks (NNs). In a first series of experiments, ensembles of Feed-Forward NNs (EnsFFNNs) and Associative Neural Networks (ASNNs) were trained to reproduce PES represented by the Lennard-Jones (LJ) analytical potential function. The accuracy of the method was assessed by comparing the results of molecular dynamics simulations (thermal, structural, and dynamic properties) obtained from the NNs-PES and from the LJ function. The results indicated that for LJ-type potentials, NNs can be trained to generate accurate PES to be used in molecular simulations. EnsFFNNs and ASNNs gave better results than single FFNNs. A remarkable ability of the NNs models to interpolate between distant curves and accurately reproduce potentials to be used in molecular simulations is shown. The purpose of the first study was to systematically analyse the accuracy of different NNs. Our main motivation, however, is reflected in the next study: the mapping of multidimensional PES by NNs to simulate, by Molecular Dynamics or Monte Carlo, the adsorption and self-assembly of solvated organic molecules on noble-metal electrodes. Indeed, for such complex and heterogeneous systems the development of suitable analytical functions that fit quantum mechanical interaction energies is a non-trivial or even impossible task. The data consisted of energy values, from Density Functional Theory (DFT) calculations, at different distances, for several molecular orientations and three electrode adsorption sites. The results indicate that NNs require a data set large enough to cover well the diversity of possible interaction sites, distances, and orientations. NNs trained with such data sets can perform equally well or even better than analytical functions. Therefore, they can be used in molecular simulations, particularly for the ethanol/Au (111) interface which is the case studied in the present Thesis. Once properly trained, the networks are able to produce, as output, any required number of energy points for accurate interpolations.
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The aim of this essay is to discuss the thesis of the German Sociologist Günter Burkhart that in modern societies a phenomenon appeared which he calls “handymania”, an excessive and nearly addictive use of the mobile phones especially from adolescents. After a short overview about the history of the cell phone, I will relate this development to Jürgen Habermas “theory of communicative action”, more precisely to his diagnosis of a pathological society (“lifeworld”) to find out if the “handymania” could be one expression of it. Adjacent I will present social-psychological theories from E.H.Erikson and Tilmann Habermas to ascertain whether juveniles could really be a high-risk group for this kind of addiction. I will focus on the ability to communicate in an Habermasian way that could be seriously harmed by the unregulated usage of cell phones.
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OBJECTIVE To analyze the perception of and motivation for the chronic use of benzodiazepine among older adults. METHODS A qualitative study was conducted on 22 older adults living in Bambuí, MG, Southeastern Brazil, who were taking benzodiazepines and had the clinical and cognitive ability to respond to interview questions. The collected data were analyzed on the basis of the “signs, meanings, and actions” model. RESULTS The main reasons pointed out for the use of benzodiazepines were “nervousness”, “sleep problems”, and “worry” due to family and financial problems, everyday problems, and existential difficulties. None of the interviewees said that they used benzodiazepines in a dose higher than that recommended or had been warned by health professionals about any risks of their continuous use. Different strategies were used to obtain the prescription for the medication, and any physician would prescribe it, indicating that a bond was established with the drug and not with the health professional or healthcare service. Obtaining and consuming the medication turned into a crucial issue because benzodiazepine assumes the status of an essential food, which leads users to not think but sleep. It causes a feeling of relief from their problems such as awareness of human finitude and fragility, existential difficulties, and family problems. CONCLUSIONS Benzodiazepine assumes the characteristics of polyvalence among older adults, which extrapolate specific clinical indications, and of essentiality to deal with life’s problems in old age. Although it relieves the “nerves”, the chronic use of benzodiazepines buffers suffering and prevents older adults from going through the suffering. This shows important difficulties in the organization and planning of strategies that are necessary for minimizing the chronic use in this population.
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This paper presents a novel phase correction technique for Passive Radar which uses targets of opportunity present in the target area as references. The proposed methodology is quite simple and enables the use of low cost hardware with independent oscillators for the reference and surveillance channels which can be geographically distributed. © 2014 IEEE.
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Supramolecular chirality was achieved in solutions and thin films of a calixarene-containing chiral aryleneethynylene copolymer. The observed chiroptical activity, which is primarily allied with the formation of aggregates of high molecular weight polymer chains, is the result of a combination of intrachain and interchain effects. The former arises by the adoption of an induced helix-sense by the polymer main-chain while the latter comes from the exciton coupling of aromatic backbone transitions. The co-existence of bulky bis-calixKlarene units and chiral side-chains on the polymer skeleton prevents efficient pi-stacking of neighbouring chains, keeping the chiral assembly highly emissive. In contrast, for a model polymer lacking calixarene moieties, the chiroptical activity is dominated by strong interchain exciton couplings as a result of more favourable packing of polymer chains, leading to a marked decrease of photoluminescence in the aggregate state. The enantiomeric recognition abilities of both polymers towards (R)- and (S)-alpha-methylbenzylamine were examined. It was found that a significant enantiodiscrimination is exhibited by the calixarene-based polymer in the aggregate state.
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Between 2000/01 and 2006/07, the approval rate of a Thermodynamics course in a Mechanical Engineer graduation was 25%. However, a careful analysis of the results showed that 41% of the students chosen not to attend or dropped out, missing the final examination. Thus, a continuous assessment methodology was developed, whose purpose was to reduce drop out, motivating students to attend this course, believing that what was observed was due, not to the incapacity to pass, but to the anticipation of the inevitability of failure by the students. If, on one hand, motivation is defined as a broad construct pertaining to the conditions and processes that account for the arousal, direction, magnitude, and maintenance of effort, on the other hand, assessment is one of the most powerful tools to change the will that students have to learn, motivating them to learn in a quicker and permanent way. Some of the practices that were implemented, included: promoting learning goal orientation rather than performance goal orientation; cultivating intrinsic interest in the subject and put less emphasis on grades but make grading criteria explicit; emphasizing teaching approaches that encourage collaboration among students and cater for a range of teaching styles; explaining the reasons for, and the implications of, tests; providing feedback to students about their performance in a form that is non-egoinvolving and non-judgemental and helping students to interpret it; broadening the range of information used in assessing the attainment of individual students. The continuous assessment methodology developed was applied in 2007/08 and 2008/09, having found an increase in the approval from 25% to 55% (30%), accompanied by a decrease of the drop out from 41% to 23,5% (17,5%). Flunking with a numerical grade lowered from 34,4% to 22,0% (12,4%). The perception by the students of the continuous assessment relevance was evaluated with a questionnaire. 70% of the students that failed the course respond that, nevertheless, didn’t repent having done the continuous assessment.
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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia do Ambiente, perfil Gestão de Sistemas Ambientais
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Educação Médica. 1994, 5(3):178-181.
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Empowered by virtualisation technology, cloud infrastructures enable the construction of flexi- ble and elastic computing environments, providing an opportunity for energy and resource cost optimisation while enhancing system availability and achieving high performance. A crucial re- quirement for effective consolidation is the ability to efficiently utilise system resources for high- availability computing and energy-efficiency optimisation to reduce operational costs and carbon footprints in the environment. Additionally, failures in highly networked computing systems can negatively impact system performance substantially, prohibiting the system from achieving its initial objectives. In this paper, we propose algorithms to dynamically construct and readjust vir- tual clusters to enable the execution of users’ jobs. Allied with an energy optimising mechanism to detect and mitigate energy inefficiencies, our decision-making algorithms leverage virtuali- sation tools to provide proactive fault-tolerance and energy-efficiency to virtual clusters. We conducted simulations by injecting random synthetic jobs and jobs using the latest version of the Google cloud tracelogs. The results indicate that our strategy improves the work per Joule ratio by approximately 12.9% and the working efficiency by almost 15.9% compared with other state-of-the-art algorithms.
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The Polytechnic Institute of Oporto (IPP), which has a solid history of online education and innovation through the use of technology, has been particularly interested and focused on Massive Open Online Courses (MOOC) developments. The aim of this paper is to present the whole process from initial discussions to completion of the “Mathematics Without Limits” MOOC Project that exists in IPP and also to contribute for a change in the way as teaching and learning Mathematics is seen and practiced nowadays. In 2013, IPP developed its own platform, which gave us the opportunity to explore new educational techniques as a pedagogical resource as well as to enhance students’ motivation, through a set of interactive materials at their disposal, totally adapted to their needs. Students lack of motivation is mainly justified by their weak Math preparation, poor consolidated basis on the subject and different backgrounds of the students. To tackle this issue and based on our Math online courses teaching experience, we decided to create short duration MOOC, expecting to aid retention of students and also to reverse the path of students giving up on Math by giving them a friendly way of managing their own learning commitment. We also think that this MOOC will be a good approach to level out some math skills among freshmen.