Modelado orientado a objetos del sistema de control de la presión arterial en pacientes sometidos al tratamiento de hemodiálisis

Se ha realizado el modelado orientado a objetos del sistema de control cardiovascular en situaciones de diálisis aplicando una analogía eléctrica en el que se emplean componentes conectados mediante interconexiones. En este modelado se representan las ecuaciones diferenciales del sistema cardiovascular y del sistema de control barorreceptor así como las ecuaciones dinámicas del intercambio de fluidos y solutos del sistema hemodializador. A partir de este modelo se ha realizado experiencias de simulación en condiciones normales y situaciones de hemorragias, transfusiones de sangre y de ultrafiltración e infusión de fluido durante tratamiento de hemodiálisis. Los resultados obtenidos muestran en primer lugar la efectividad del sistema barorreceptor para compensar la hipotensión arterial inducida por los episodios de hemorragia y transfusión de sangre. En segundo lugar se muestra la respuesta del sistema de control ante diferentes tasas de ultrafiltración durante la hemodiálisis y se sugieren valores óptimos para la adecuada operación.

Análise das mudanças espaciais e temporais nos padrões de paisagem na região do oeste da Bahia sobre a formação do grupo urucuia (1988-2011) e suas implicações para a conservação do Cerrado

Tese (doutorado)—Universidade de Brasília, Instituto de Ciências Humanas, Departamento de Geografia, Programa de Pós Graduação em Geografia, 2015.

O Festival Internacional de Teatro de Almada : um estudo de caso

O presente Trabalho de Projecto assenta na análise da programação e da evolução espacial e temporal do Festival Internacional de Teatro de Almada, de modo a perceber quais as linhas gerais em que se baseia a sua programação. Procura-se perceber, ao longo do trabalho, de que forma o Festival se ligou à cidade de Almada, contribuindo para a sua evolução ao nível de equipamentos culturais, recuperação urbanística e reestruturação da esfera pública. A par destes assuntos, dá-se conta igualmente da expansão geográfica do Festival de Almada para cidades como Lisboa e Porto, tentando-se perceber o que esteve nas bases da mesma e de que forma o Festival equilibrou esta necessidade de crescimento com a manutenção do vínculo com Almada.

Avoiding staff removal stage in optical music recognition: application to scores written in white mensural notation

Staff detection and removal is one of the most important issues in optical music recognition (OMR) tasks since common approaches for symbol detection and classification are based on this process. Due to its complexity, staff detection and removal is often inaccurate, leading to a great number of errors in posterior stages. For this reason, a new approach that avoids this stage is proposed in this paper, which is expected to overcome these drawbacks. Our approach is put into practice in a case of study focused on scores written in white mensural notation. Symbol detection is performed by using the vertical projection of the staves. The cross-correlation operator for template matching is used at the classification stage. The goodness of our proposal is shown in an experiment in which our proposal attains an extraction rate of 96 % and a classification rate of 92 %, on average. The results found have reinforced the idea of pursuing a new research line in OMR systems without the need of the removal of staff lines.

Ambiente computacional paradesenvolvimento de aplicações de controladores lógicos programáveis baseado em linguagens SFC e ST

This work proposes an environment for programming programmable logic controllers applied to oil wells with BCP type method of artificially lifting. The environment will have an editor based in the diagram of sequential functions for programming of PLCs. This language was chosen due to the fact of being high-level and accepted by the international standard IEC 61131-3. The use of these control programs in real PLC will be possible with the use of an intermediate level of language based on XML specification PLCopen T6 XML. For the testing and validation of the control programs, an area should be available for viewing variables obtained through communication with a real PLC. Thus, the main contribution of this work is to develop a computational environment that allows: modeling, testing and validating the controls represented in SFC and applied in oil wells with BCP type method of artificially lifting

Programmazione ad Agenti - Un Caso di Studio nel Linguaggio Sarl

Agent-oriented programming (AOP) è un paradigma di programmazione che concepisce un software come insieme di agenti che possiedono caratteristiche di autonomia, proattività e che sono in grado di comunicare con altri agenti. Sebbene sia stato impiegato soprattutto nell'ambito dell'intelligenza artificiale questo tipo di programmazione si rivela utile per lo sviluppo di sistemi distribuiti riuscendo a gestire agilmente problemi di concorrenza. Lo scopo di questa tesi è analizzare le caratteristiche del paradigma e dei software basati su agenti, utilizzando come caso di studio Sarl, un linguaggio general-purpose molto recente. La parte principale del lavoro consiste nella descrizione dei modelli teorici che hanno portato alla nascita della programmazione ad agenti, in particolare del modello BDI, e dei principali framework per lo sviluppo di sistemi multi-agente.

Towards person-centered neuroimaging markers for resilience and vulnerability in Bipolar Disorder

Improved clinical care for Bipolar Disorder (BD) relies on the identification of diagnostic markers that can reliably detect disease-related signals in clinically heterogeneous populations. At the very least, diagnostic markers should be able to differentiate patients with BD from healthy individuals and from individuals at familial risk for BD who either remain well or develop other psychopathology, most commonly Major Depressive Disorder (MDD). These issues are particularly pertinent to the development of translational applications of neuroimaging as they represent challenges for which clinical observation alone is insufficient. We therefore applied pattern classification to task-based functional magnetic resonance imaging (fMRI) data of the n-back working memory task, to test their predictive value in differentiating patients with BD (n=30) from healthy individuals (n=30) and from patients' relatives who were either diagnosed with MDD (n=30) or were free of any personal lifetime history of psychopathology (n=30). Diagnostic stability in these groups was confirmed with 4-year prospective follow-up. Task-based activation patterns from the fMRI data were analyzed with Gaussian Process Classifiers (GPC), a machine learning approach to detecting multivariate patterns in neuroimaging datasets. Consistent significant classification results were only obtained using data from the 3-back versus 0-back contrast. Using contrast, patients with BD were correctly classified compared to unrelated healthy individuals with an accuracy of 83.5%, sensitivity of 84.6% and specificity of 92.3%. Classification accuracy, sensitivity and specificity when comparing patients with BD to their relatives with MDD, were respectively 73.1%, 53.9% and 94.5%. Classification accuracy, sensitivity and specificity when comparing patients with BD to their healthy relatives were respectively 81.8%, 72.7% and 90.9%. We show that significant individual classification can be achieved using whole brain pattern analysis of task-based working memory fMRI data. The high accuracy and specificity achieved by all three classifiers suggest that multivariate pattern recognition analyses can aid clinicians in the clinical care of BD in situations of true clinical uncertainty regarding the diagnosis and prognosis.

A Livestock-Associated, Multidrug-Resistant, Methicillin-Resistant Staphylococcus aureus Clonal Complex 97 Lineage Spreading in Dairy Cattle and Pigs in Italy

Pandemic methicillin-resistant Staphylococcus aureus (MRSA) clonal complex 97 (CC97) lineages originated from livestock-to-human host jumps. In recent years, CC97 has become one of the major MRSA lineages detected in Italian farmed animals. The aim of this study was to characterize and analyze differences in MRSA and methicillin-susceptible S. aureus (MSSA) mainly of swine and bovine origins. Forty-seven CC97 isolates, 35 MRSA isolates, and 6 MSSA isolates from different Italian pig and cattle holdings; 5 pig MRSA isolates from Germany; and 1 human MSSA isolate from Spain were characterized by macrorestriction pulsed-field gel electrophoresis (PFGE) analysis, multilocus sequence typing (MLST), spa typing, staphylococcal cassette chromosome mec (SCCmec) typing, and antimicrobial resistance pattern analysis. Virulence and resistance genes were investigated by PCR and microarray analysis. Most of the isolates were of SCCmec type V (SCCmec V), except for two German MRSA isolates (SCCmec III). Five main clusters were identified by PFGE, with the German isolates (clusters I and II) showing 60.5% similarity with the Italian isolates, most of which (68.1%) grouped into cluster V. All CC97 isolates were Panton-Valentine leukocidin (PVL) negative, and a few (n = 7) tested positive for sak or scn. All MRSA isolates were multidrug resistant (MDR), and the main features were erm(B)- or erm(C)-mediated (n = 18) macrolide-lincosamide-streptogramin B resistance, vga(A)-mediated (n = 37) pleuromutilin resistance, fluoroquinolone resistance (n = 33), tet(K) in 32/37 tet(M)-positive isolates, and blaZ in almost all MRSA isolates. Few host-associated differences were detected among CC97 MRSA isolates: their extensive MDR nature in both pigs and dairy cattle may be a consequence of a spillback from pigs of a MRSA lineage that originated in cattle as MSSA and needs further investigation. Measures should be implemented at the farm level to prevent spillover to humans in intensive farming areas.

UNDERSTANDING ESSAY RATING AS A SOCIALLY MEDIATED ACTIVITY: THE CASE OF A HIGH-STAKES ENGLISH TEST IN CHINA

Thesis (Ph.D, Education) -- Queen's University, 2016-09-22 22:05:24.246

Umbrella pine above ground biomass estimation with very high spatial resolution satellite images

Above ground biomass is frequently estimated with forest inventory data and an extrapolation method for the per unit area evaluations. This procedure is labour demanding and costly. In this study above ground biomass functions, whose independent variable is crown horizontal projection, were developed. Multi-resolution segmentation method and object-oriented classification, based on very high spatial resolution satellite images, were used to obtain the area of tree crown horizontal projection for umbrella pine (Pinus pinea L.). A set of inventory plots were measured and with existing allometric functions for this species above ground biomass per tree and per plot were calculated. The two data sets were used to fit linear functions both for individual plot and their cumulative values. The results show a good performance of the models. Errors smaller than 10% are obtained for stand areas greater than 1.4 ha. These functions have the advantages of estimating above ground biomass for all the area under study or surveillance, not requiring forest inventory; allow monitoring in short time periods; and are easily implemented in a geographical information system environment.

Above ground biomass estimation in Mediterranean multiple use systems with high spatial resolution satellite images

Forest biomass has been having an increasing importance in the world economy and in the evaluation of the forests development and monitoring. It was identified as a global strategic reserve, due to its applications in bioenergy, bioproduct development and issues related to reducing greenhouse gas emissions. The estimation of above ground biomass is frequently done with allometric functions per species with plot inventory data. An adequate sampling design and intensity for an error threshold is required. The estimation per unit area is done using an extrapolation method. This procedure is labour demanding and costly. The mail goal of this study is the development of allometric functions for the estimation of above ground biomass with ground cover as independent variable, for forest areas of holm aok (Quercus rotundifolia), cork oak (Quercus suber) and umbrella pine (Pinus pinea) in multiple use systems. Ground cover per species was derived from crown horizontal projection obtained by processing high resolution satellite images, orthorectified, geometrically and atmospheric corrected, with multi-resolution segmentation method and object oriented classification. Forest inventory data were used to estimate plot above ground biomass with published allometric functions at tree level. The developed functions were fitted for monospecies stands and for multispecies stands of Quercus rotundifolia and Quercus suber, and Quercus suber and Pinus pinea. The stand composition was considered adding dummy variables to distinguish monospecies from multispecies stands. The models showed a good performance. Noteworthy is that the dummy variables, reflecting the differences between species, originated improvements in the models. Significant differences were found for above ground biomass estimation with the functions with and without the dummy variables. An error threshold of 10% corresponds to stand areas of about 40 ha. This method enables the overall area evaluation, not requiring extrapolation procedures, for the three species, which occur frequently in multispecies stands.

Jogo para aprender a programar

Neste documento foi feita a apresentação do conceito de Programação Visual, estudados alguns exemplos de Linguagens de Programação Visual e investigado vantagens e desvantagens sobre o seu uso comparativamente à programação tradicional (por texto) e, adicionalmente, foram estudados três jogos para aprender a programar com fortes características visuais. A partir desta investigação, foi criada uma nova Linguagem de Programação Visual(LPV) sendo a base de um prototipo de um jogo para aprender a programar. Este jogo é representado pela deslocação e execução de tarefas feitas por um robô dentro de uma casa, sendo o objetivo do programador colocar objetos nesta casa que manipulam a deslocação do robô dentro desta de forma a resolver um problema; Abstract: A game to learn programming Aplication of concepts of visual programming to create a game to learn how to program In this document we will explain the concept of Visual Programming, study some examples of Visual Programming Languages, analyze some arguments in favor and against its use in comparison to traditional programming (by text) and, additionally, study three games to learn programming with strong visual features. Using this research, a new Visual Programming Language(VPL) was created, being the basis of a prototype of a game to learn programming. This game is represented by the movement and execution of tasks done by a robot inside a house, being the goal of the programmer to place objects in this house that manipulate the movement of the robot inside of it in order to solve a problem.

Humour, Hate Crimes and British Radical Right Users on Twitter: A longitudinal Post-Brexit study

This dissertation explores the link between hate crimes that occurred in the United Kingdom in June 2017, June 2018 and June 2019 through the posts of a robust sample of Conservative and radical right users on Twitter. In order to avoid the traditional challenges of this kind of research, I adopted a four staged research protocol that enabled me to merge content produced by a group of randomly selected users to observe the phenomenon from different angles. I collected tweets from thirty Conservative/right wing accounts for each month of June over the three years with the help of programming languages such as Python and CygWin tools. I then examined the language of my data focussing on humorous content in order to reveal whether, and if so how, radical users online often use humour as a tool to spread their views in conditions of heightened disgust and wide-spread political instability. A reflection on humour as a moral occurrence, expanding on the works of Christie Davies as well as applying recent findings on the behavioural immune system on online data, offers new insights on the overlooked humorous nature of radical political discourse. An unorthodox take on the moral foundations pioneered by Jonathan Haidt enriched my understanding of the analysed material through the addition of a moral-based layer of enquiry to my more traditional content-based one. This convergence of theoretical, data driven and real life events constitutes a viable “collection of strategies” for academia, data scientists; NGO’s fighting hate crimes and the wider public alike. Bringing together the ideas of Davies, Haidt and others to my data, helps us to perceive humorous online content in terms of complex radical narratives that are all too often compressed into a single tweet.

A take on complexity: bio-molecules and human metabolism interaction modelling for health and nutrition with machine learning

The advent of omic data production has opened many new perspectives in the quest for modelling complexity in biophysical systems. With the capability of characterizing a complex organism through the patterns of its molecular states, observed at different levels through various omics, a new paradigm of investigation is arising. In this thesis, we investigate the links between perturbations of the human organism, described as the ensemble of crosstalk of its molecular states, and health. Machine learning plays a key role within this picture, both in omic data analysis and model building. We propose and discuss different frameworks developed by the author using machine learning for data reduction, integration, projection on latent features, pattern analysis, classification and clustering of omic data, with a focus on 1H NMR metabolomic spectral data. The aim is to link different levels of omic observations of molecular states, from nanoscale to macroscale, to study perturbations such as diseases and diet interpreted as changes in molecular patterns. The first part of this work focuses on the fingerprinting of diseases, linking cellular and systemic metabolomics with genomic to asses and predict the downstream of perturbations all the way down to the enzymatic network. The second part is a set of frameworks and models, developed with 1H NMR metabolomic at its core, to study the exposure of the human organism to diet and food intake in its full complexity, from epidemiological data analysis to molecular characterization of food structure.

Digital 3D reconstruction as a research environment in art and architecture history: uncertainty classification and visualisation

The dissertation addresses the still not solved challenges concerned with the source-based digital 3D reconstruction, visualisation and documentation in the domain of archaeology, art and architecture history. The emerging BIM methodology and the exchange data format IFC are changing the way of collaboration, visualisation and documentation in the planning, construction and facility management process. The introduction and development of the Semantic Web (Web 3.0), spreading the idea of structured, formalised and linked data, offers semantically enriched human- and machine-readable data. In contrast to civil engineering and cultural heritage, academic object-oriented disciplines, like archaeology, art and architecture history, are acting as outside spectators. Since the 1990s, it has been argued that a 3D model is not likely to be considered a scientific reconstruction unless it is grounded on accurate documentation and visualisation. However, these standards are still missing and the validation of the outcomes is not fulfilled. Meanwhile, the digital research data remain ephemeral and continue to fill the growing digital cemeteries. This study focuses, therefore, on the evaluation of the source-based digital 3D reconstructions and, especially, on uncertainty assessment in the case of hypothetical reconstructions of destroyed or never built artefacts according to scientific principles, making the models shareable and reusable by a potentially wide audience. The work initially focuses on terminology and on the definition of a workflow especially related to the classification and visualisation of uncertainty. The workflow is then applied to specific cases of 3D models uploaded to the DFG repository of the AI Mainz. In this way, the available methods of documenting, visualising and communicating uncertainty are analysed. In the end, this process will lead to a validation or a correction of the workflow and the initial assumptions, but also (dealing with different hypotheses) to a better definition of the levels of uncertainty.