Ortodontia baseada no genoma: prognatismo mandibular

Uma das questões centrais da ortodontia moderna é: como as descobertas na área da genética afetarão diretamente conceitos e abordagens no tratamento ortodôntico e de que forma os fatores genómicos e epigenéticos podem ser manipulados e introduzidos no tratamento individual de cada paciente. O objetivo deste trabalho é demonstrar a importância da genética na previsão do crescimento mandibular. Esta dissertação é de índole teórica, estando desta forma isenta de qualquer tipo de trabalho prático experimental. Trata-se de uma revisão sistemática de trabalhos que estudaram o tema. A ortodontia baseada no genoma usa a informação genética para melhorar o diagnóstico e tratamento de distúrbios dentários e deformidades dentofaciais. Nos últimos 20 anos houve uma convergência de princípios e conceitos entre a genética e a ortodontia que levará a um avanço significativo dos tratamentos ortodonticos, contudo a sua aplicação prática não será imediata.The central question in orthodontics in this millennium is: how discoveries in the field of genetics will directly affect concepts and approaches in orthodontic treatment and how genomic and epigenetic factors can be manipulated and introduced into the individual treatment of each patient. The aim of this study is to demonstrate the importance of genetics in the prediction of mandibular growth. This dissertation is of a theoretical nature, being thus exempt of any type of practical experimental work. This is a systematic review of papers that have studied the theme. Genome based orthodontics uses genetic information to improve the diagnosis and treatment of dental disorders and dentofacial deformities. In the last 20 years there has been a convergence of principles and concepts between genetics and orthodontics that will lead to a significant advance in orthodontic treatments, however, its practical application will not be immediate

Integration of a model for volatile release in the CFD simulation of an industrial biomass boiler

Doctoral Thesis for PhD degree in Leaders for Technical IndustriesMotivada por sua disponibilidade, abundância generalizada e preocupações ambientais, a biomassa sólida tornou-se uma opção competitiva para diversificar a produção de eletricidade entre os recursos de energia renovável. Este trabalho tem como objetivo caraterizar o comportamento da combustão de espécies de biomassa frequentemente utilizadas em centrais termoelétricas para suportar o desenvolvimento de um modelo numérico para modelação eficiente e precisa da conversão de biomassa numa caldeira industrial a grelha. A eficiência da caldeira numa central de 35 MWth foi calculada como sendo aproximadamente 80%. Amostras selecionadas de biomassa de eucalipto, pinheiro, acácia e oliveira foram testadas com o analisador térmico Hot Disk TPS 2500S. A condutividade térmica ficou compreendida entre 0,239 e 0,404 W/mK. Além disso, a capacidade calorífica apresentou uma variação entre 0,855 e 2,442 MJ/m3K, e a difusividade térmica entre 0,187 e 0,258 mm2/s. Para a análise final e aproximada foram utilizados os equipamentos LECO TruSpec CHN Macro e LECO CS-200 e uma mufla, respetivamente. Os dados revelaram uma maior reatividade do eucalipto, cerca de 2 vezes superior aos outros combustíveis, e a propensão da acácia a produzir emissões poluentes (principalmente à base de azoto) e problemas de deposição de cinzas devido à sua composição química. Amostras de pequenas dimensões (cerca de 10 mg) foram usadas para medir a perda de massa e a sua reatividade num analisador termogravimétrico (TGA) da TA Instruments, modelo SDT 2960. Os testes foram realizados em atmosfera oxidante, a uma taxa de aquecimento entre 5 e 100 ºC/min, até 900 ºC. Observou-se que numa ampla faixa de temperaturas, a conversão do combustível segue uma sequência de secagem, desvolatilização e combustão do resíduo carbonoso. Amostras de maiores dimensões foram testadas num reator construído para esse fim, e que simula o processo de desvolatilização de forma controlável. Neste, a perda de massa foi medida continuamente ao longo do tempo enquanto os compostos da fase gasosa foram recolhidos em sacos para posterior análise num cromatógrafo gasoso da Bruker Scion 456-GC equipado com um detetor de condutividade térmica. Ao contrário dos dados do TGA, concluiu-se que na oxidação de biomassas, utilizando partículas maiores, não é possível distinguir as sucessivas etapas de conversão, devido à maior resistência interna de difusão. Avaliando a influência da esbelteza da amostra (rácio comprimento/espessura), concluiu-se que a taxa de desvolatilização depende apenas da sua espessura e não do volume. Além disso, para temperaturas mais altas do reator, a taxa de perda de massa é independente do tipo de biomassa. Os compostos gasosos libertados durante a conversão térmica do eucalipto apresentaram forte correlação com a temperatura do reator, sendo CO2 e CO sempre os principais produtos de desvolatilização. A dependência da temperatura de ambos os compostos apresentam, para o CO, um aumento de 8 a 13% entre 600 e 800°C, enquanto o de CO2 aumenta apenas ligeiramente de 11 a 12%. O modelo eXtended Discrete Element Method foi usado para descrever a desvolatilização no reator. Os resultados foram comparados com os dados experimentais e, embora tenha sido observada uma boa concordância, concluiu-se que a oxidação do resíduo carbonoso necessita de um modelo de difusão. A simulação do escoamento no interior da caldeira foi feita utilizando o software ANSYS Fluent. Neste, um modelo empírico externo para prever a conversão de biomassa ao longo da grelha é acoplado a um modelo CFD para prever o escoamento reativo dentro da caldeira. Os resultados destacaram a contribuição da contração na seção intermédia da fornalha, e a necessidade de um maior caudal de ar secundário para reduzir as emissões de CO. Os resultados mostram que modificando a razão entre o ar primário e secundário de 79/21 para 40/60, obteve-se uma redução da fração mássica de CO de 0.009 para 0.0003.Motivated by their availability, widespread abundance, and environmental concerns, solid biomass has become a competitive option to diversify electricity production amongst the renewable energy resources. This work aims to characterize the combustion behavior of solid biomass species frequently used in power plants as a route to support the development of a numerical model for efficient and accurate modeling of biomass conversion in an industrial grate-fired boiler. The boiler efficiency of a power plant rated at 35 MWth was calculated as approximately 80%. Selected samples of biomass (eucalyptus, pine, acacia, and olive) were tested with a Hot Disk Thermal Constants Analyzer TPS 2500S. The thermal conductivity, varied in the range of 0.239 to 0.404 W/mK. In addition, the heat capacity is within 0.855 to 2.442 MJ/m3K, and the thermal diffusivity is between 0.187 and 0.258 mm2/s. The ultimate and proximity analysis was carried out on the fuel samples using LECO TruSpec CHN Macro and LECO CS-200 equipment and a muffle furnace, respectively. The data revealed a higher reactivity of eucalyptus, which is around 2 times higher than that of other fuels, and the propensity of the acacia to produce pollutant emissions (mostly Nitrogen based) and ash deposition problems due to their chemical composition. Small size samples (around 10 mg each) were used to measure the mass loss and their reactivity in a thermogravimetric analyzer (TGA) from TA Instruments, model SDT 2960. The tests were carried out on an oxidizing atmosphere at a heating rate between 5 and 100 ºC/min up to 900 ºC. It was observed that over a wide range of temperatures, fuel conversion follows a sequence of drying, devolatilization, and char combustion. Larger samples of heartwood were tested in a purpose built reactor that simulates the devolatilization process under a controllable manner. In this, the mass loss was continuously measured along the time while the gas phase compounds were collected in bags for subsequent analysis in a gas chromatograph Bruker Scion 456-GC equipped with a thermal conductivity detector. As opposed to the TGA data, it was concluded that all fuels show that the combustion of large particles does not exhibit separate consecutive conversion stages, due to internal diffusion resistance. This was further highlighted by varying the sample aspect ratio. It was concluded that the devolatilization rate depends on the smallest dimension and not on the bulk size. Furthermore, at higher reactor temperatures, the mass loss profile is independent of the biomass. The gas compounds released with eucalyptus presented a strong correlation with the reactor temperature, being CO2 and CO always the main devolatilization products. The temperature dependence of both compounds shows, for CO, an increase from 8 to 13% between 600 and 800 °C, while the CO2 yield is only slightly increasing from 11 to 12%. The eXtended Discrete Element Method model was implemented to describe the devolatilization inside the reactor. The results were compared with the experimental data and, while a good agreement was observed, it was concluded that the char oxidation needs to be also represented by a diffusion model. The numerical model was developed using the ANSYS Fluent software. In this, a user defined empirical model to predict the biomass conversion along the grate was coupled with a freeboard model to predict reactive flow inside the boiler. The results highlighted the contribution of the converging sections in the middle section of the furnace and the need for a higher secondary air flow rate to reduce CO emissions. The results show that a reduction of the CO mass fraction from 0.009 to 0.0003 was possible with a modification of the primary to secondary air split ratio from 79/21 to 40/60.Fundação para a Ciência e a Tecnologia for sponsoring my research, through the grant SFRH/BD/130588/2017

Economic potential of human motion for electricity production in gymnasiums

With the continuous rise of energy demand at a global scale and, the significant environmental impacts that the current energy sector causes, political decision-makers feel the need to increasingly invest in renewable energy sources, such as solar and wind energy, and find new ways to produce electricity with minimal environmental impact. The use of human movement to produce energy has already been a study subject, but with very few applications in the current market. This is mainly due to the relation between the investment costs and the electric output that current generators are able to produce. A scarcity of studies about the economic potential of these technologies is noted, which contributes to the weak interest of potential investors in their implementation. In this work an attempt is made to synthesize the results related to the analysis of the economic aspects associated to the technologies that use human motion, which already have real-life applications and have been extensively studied. Simultaneously the concept is developed, and a prototype is constructed of a system capable of using linear human movement, of which the performance is evaluated. As such, it becomes possible to compare the electric output of the rotational system, based on existing literature, with the output of the linear system based on the results acquired during the preliminary tests of a developed prototype. These values are used to calculate the reduction of greenhouse gas emissions that these systems enable. The experiments with the prototype were developed in a gymnasium, because these establishments concentrate a considerable amount of daily human motion. Currently, that movement is wasted in the machine’s resistance. Meanwhile, the economic analysis and potential GHG savings of these systems are studied in four different gymnasiums with varying characteristics. It was determined that the use of rotational human motion to produce electric energy has a considerable economic potential in the current market, which is supported by the fact that a few establishments have already incorporated equipment that permit their exploitation. However, linear human movement is incapable of reaching an acceptable return period in almost all scenarios. Only large-scale gymnasium, such as Be-Fit Setúbal, possess the capacity to adopt this technology and reach a return period with economic viabilit

Equity valuation dissertation Walt Disney Company

This dissertation aims to evaluate Walt Disney Company (ticker: DIS US Equity). The evaluation process is done through three different mechanisms in order to achieve a more accurate and complete valuation exercise. The first valuation method is the Discounted Cash Flows model, in which each company’s segment is valued separately, therefore obtaining the company’s overall valuation by combining them all. This model provides a Walt Disney share price estimation of $88,52 which, compared to its market price of$85,38, represents a buying opportunity. The second valuation method is the Economic Value Added model. Through this valuation technique, the Walt Disney share price is estimated as of $77,89 which, compared to its market price, represents a selling opportunity. The third and last valuation method presented is the relative valuation. By applying the Enterprise Value to EBITDA multiple, it is achieved a company share price of$83,96 which also represents a selling opportunity. Lastly, it is compared the valuation obtained through this dissertation to the one accomplished by J.P.Morgan, in which the Walt Disney share price is estimated as $90,00. By doing so, one can conclude that the valuation in this dissertation is more conservative, being the different assumptions made examined further in this report

Short-term forecasting of the portuguese economy

This Dissertation focuses on exploring Dynamic Factor Models methodologies allowing for an e ccient and reliable forecast of Quarterly real GDP growth rates on a timely maner. Alternative forecasting models will be described, together with the most recent litterature focusing on the ex- perience of the European Monetary Union (EMU), Spain and Portugal. The accuracy of the created Dynamic Factor Model will be compared with the Portuguese Statistical O ce preliminary announce- ment, 45 days after the end of the reference quarter. The nature of the economic variables to be used, their timeliness and the weight given by the model to their information content are analyzed, in the search for undoing the black box character of factor models. A wide range of future developments are identi ed while acquiring the understanding that a Forecaster will always have to deal with open questions

Design strategies for socio-environmentally adverse territories

In an inland southern region of Portugal, pathologies that intersect social and environmental problems have been identified, such as low density, aged and dispersed population, as well as low rainfall and high temperatures. An applied research and development initiative endorsing those problems was carried out by students and staff of the University of Lisbon along two years. This text reflects on this experience and the role of design on such predicaments. The research questions are: how and what kind of innovation can design bring to the community’s quality of life in territories under adverse conditions of that kind? A previous analysis, carried out between local authorities and our design school, allowed us to trace two lines of investigation, one aimed at intensifying the flow of people within the territory, and the other focused on promoting the relationship between Man and his environment. Considering that design can contribute to the process of social change, through design for social innovation and collaborative services, we reflect on the main characteristics that the design projects must contemplate, which are: a usercentered perspective; be a participatory process; to draft with a sustainability perspective; adopt a multilevel perspective; to endorse innovation; and sustain problem solving. The research methodology involves the transversal use of design methods and participatory processes, immersion in the territory, collection of primary and secondary data, definition of the concept, development of proposals, communication, and validation by the municipal authorities. The results are a set of projects with a wide range of solutions in the field of social innovation, with the aim of valuing social interaction, valuing culture and regenerating the local landscape, namely: a cultural caravan service; a Lab-desk service; a cultural project to reactivate community wood-fired bread ovens; a website to publicize local projects focused on agroecological food; a Center for the Intangible Cultural Heritage; a co-working and co-living service; an environmental festival; a research service aimed at better understanding the needs of the “silent population”; a garden at the historic urban center of Mértola town; a public botanical garden; and, the renovation of a public area in a small village. The relevance of this work lies in the assertion of the potential of design strategies for social innovation, particularly in a context of social and environmental adversity, where design can fulfill a key role valuing the daily lives of populations. This article demonstrates that there is an immense space for work involving the public institutions managing this type of territories and the design academia. From our experience, a transversal line stands out: the intersection between local knowledge and the external population. This converges it the idea that the value that design brings to this kind of community is the drafting of arenas of social interaction where the local social fabric is nurtured and, simultaneously, beholding people’s awareness of the surrounding environment’s frailty.info:eu-repo/semantics/publishedVersio

Image segmentation for human motion analysis: methods and applications

Human motion analysis is closely connected with the development of computational techniques capable of automatically identify objects represented in image sequences, track and analyse its movement. Feature extraction is generally the first step in the study of human motion in image sequences which is strictly related to human motion modelling [1]. Next step is feature correspondence, where the problem of matching features between two consecutives image frames is addressed. Finally high level processing can be used in several applications of Computer Vision like, for instance, in the recognition of human movements, activities or poses. This work will focus in the study of image segmentation methods and applications for human motion analysis. Image segmentation methods related to human motion need to deal with several challenges such as: dynamic backgrounds, for instance when the camera is in motion; lighting conditions that can change along the image sequences; occlusion problems, when the subject does not remain inside the workspace; or image sequences with more than one subject in the workspace at the same time. It is not easy to develop methods which can deal with all thes

Using Privacy Calculus Theory To Assess Users´ Acceptance Of Video Conferencing Apps During The Covid-19 Pandemic

Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Information Systems and Technologies ManagementVideoconferencing (VC) applications (apps) are getting notable attention worldwide, from common citizens to professionals as an alternative to vis-à-vis communication specifically during COVID-19. The growth of VC apps is expected to rise even more in the future with the prediction that widespread adoption of remote work will continue to hold even after the pandemic. This research investigates the key drivers for individuals’ intentions into continuing to use this technology in professional settings. Considering the importance of professionals’ perceptions of privacy in professionals’ settings, this study proposes a conceptual model rooted in the theoretical foundations of privacy calculus theory, extended with the conceptualization of privacy concerns for mobile users (MUIPC), ubiquity, and theoretical underpinnings from social presence theory. The conceptual research model was empirically tested by using data collected from a survey of 487 actual users of videoconferencing apps across Europe. Structural equation modeling (SEM) is performed to test the model. The study revealed several findings (1) perceived value in using VC apps motivates the professionals to continue using VC apps and shapes their perception as they evaluate the risk-benefit trade-off they are making when using VC apps. (2) professionals’ indeed form and articulate their own assessment of value based on the perceived risks and benefits associated with using VC apps. However, professionals' perceptions of value are strongly influenced by potential benefits received from using VC apps than by potential risks associated with using VC apps. (3) professionals’ perceived risk is determined by MUIPC and trust. (4) professionals’ perceived benefits are shaped by ubiquity and social presence. For researchers, this study highlights the usefulness of integrating privacy calculus theory, social presence theory and trust in studying the individuals’ behavioral intentions towards new technologies. For practitioners, understanding the key determinants is pivotal to design and build mobile video-conferencing apps that achieve higher consumer acceptance and higher rates of continued usage of VC apps in professional settings

Eggs and eggshells of Crocodylomorpha from the Upper Jurassic of Portugal

Crocodylomorph eggs are relatively poorly known in the fossil record when compared with skeletal remains, which are found all over the world, or when compared with dinosaur eggs. Herein are described crocodiloid eggshells from the Upper Jurassic Lourinhã Formation of Portugal, recovered from five sites: Cambelas (clutch), Casal da Rola, Peralta (eggshell fragments), and Paimogo North and South (three partial crushed eggs and eggshell fragments). The clutch of Cambelas, composed of 13 eggs, is the only sample not found in association with dinosaur eggshells. Morphological characters of the eggshells described herein, such as shell units and microstructure, are consistent with the crocodiloid morphotype. As such, this material is assigned to the oofamily Krokolithidae, making them the oldest known crocodylomorph eggs so far and the best record for eggs of non-crocodylian crocodylomorphs. Two new ootaxa are erected, Suchoolithus portucalensis oogen. et oosp. nov, for the clutch of Cambelas, and Krokolithes dinophilus, oosp. nov., for the remaining eggshells. The basic structure of crocodilian eggshells has remained stable since at least the Late Jurassic. Additionally, the findings suggest previously unknown biological associations with contemporary archosaurs, shedding light on the poorly understood egg morphology, reproduction strategies and paleobiology of crocodylomorphs during the Late Jurassic

An hybrid approach based on neural networks and regression Tree Models for fast dynamic security assessment

This paper presents a new hybrid automatic learningapproach, which combines artificial neural networks (ANN) andregression trees (RT), to perform on-line dynamic securityassessment of power systems. In the proposed method, the RT isfirstly used to split the vast amount of knowledge data that describesa security problem into several less spread and disjoint problems.Then, an ANN is trained for each of these new smaller problems,resulting in a tree structure with an ANN predicting functionassociated to each leaf. Moreover, the capability of the RT to performfeature subset selection before ANN training is also tested. With thisnew method, the advantages of the two techniques are exploited inorder to obtained a more accurate model without compromisingprediction time. The quality of the approach is illustrated through itsapplication to a major security problem of the power system ofMadeira Island (Portugal)