Dynamic adaptation of interaction models for stateful web services

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Porous structures for the purification of biopharmaceuticals

This work aimed at the development of a (bio)polymeric monolithic support for biopharmaceuticals purification and/or capture. For that, it was assured that functional groups on its surface were ready to be involved in a plethora of chemical reactions for incorporation of the desired and most suitable ligand. Using cryogelation as preparation method a screening on multiple combinations of materials was performed in order to create a potentially efficient support with the minimal footprint, i.e. a monolithic support with reasonable mechanical properties, highly permeable, biocompatible, ready to use, with gravitational performance and minimal unspecific interactions towards the target molecules, but also biodegradable and produced from renewable materials. For the pre-selection all monoliths were characterized physico-chemically and morphologically; one agarose-based and two chitosan-based monoliths were then subjected to further characterizations before and after their modification with magnetic nanoparticles. These three specimens were finally tested towards adenovirus and the recovery reached 84% for the chitosan-GMA plain monolith prepared at -80°C. Monoliths based on chitosan and PVA were prepared in the presence and absence of magnetic particles, and tested for the isolation of GFP directly from crude cellular extracts. The affinity ligand A4C7 previously selected for GFP purification was synthesized on the monolith. The results indicated that the solid-phase synthesis of the ligand directly onto the monolith might require optimization and that the large pores of the monoliths are unsuitable for the purification of small proteins, such as GFP.

Experimental Gravimetric Adsorption Equilibrium of n-Alkanes and Alkenes, Carbon Dioxide and Nitrogen in MIL-53(Al) and Zeolite 5A

Dissertação para obtenção do Grau de Mestre em Engenharia Química e Bioquímica

Captura e armazenamento de CO2

Dissertação para obtenção do Grau de Mestre em Energia e Bioenergia

Undrestanding postoperative cognitive dysfunction: novel insights

ABSTRACT: Background: Sleep is integral to biological function and sleep disruption can result in both physiological and psychological dysfunction. The acute cognitive consequences of sleep loss has been an active field of recent investigation, evidence suggests that sleep disruption in critically ill older adults can result in acute decrements in cognitive functioning. Surgery activates the innate immune system, inducing neuroinflammatory changes that interfere with cognition. The fact that patients with sleep disorders have an increased likelihood of exhibiting postoperative delirium encourages us to investigate the contribution of perioperative SF to the neuroinflammatory and cognitive responses of surgery. Methods: The effects of 24h sleep fragmentation (SF) and surgery were explored on adult C57BL/6J male mice. SF procedure started at 7 am with the home-cages being placed on a large platform orbital shaker cycled every 120 seconds (30 sec on/90 sec off). This procedure lasted for 24h. Stabilized tibia fracture was performed either before or after the 24h SF procedure. Separate cohorts of mice were tested for systemic and hippocampal inflammation and cognition. Results: Twenty-four hours of SF induced non-hippocampal memory dysfunction and increase in systemic IL-6. SF and surgery caused hippocampal-dependent memory impairment, although memory impairment was not exacerbated by combining SF with surgery. One day after either SF or surgery there was a significant increase in IL6 mRNA and TNF-alpha mRNA. These increments were more pronounced when either pre or post operative SF was combined with surgery. Conclusions: We show that while SF and surgery can independently produce significant memory impairment, perioperative SF significantly increased hippocampal inflammation without further cognitive impairment. The dissociation between neuroinflammation and cognitive decline may relate to our use of a sole memory paradigm that does not capture other aspects of cognition, especially learning.

Thermo-hydro-mechanical analysis of CO2 injection into deep aquifers

One of the biggest challenges for humanity is global warming and consequently, climate changes. Even though there has been increasing public awareness and investments from numerous countries concerning renewable energies, fossil fuels are and will continue to be in the near future, the main source of energy. Carbon capture and storage (CCS) is believed to be a serious measure to mitigate CO2 concentration. CCS briefly consists of capturing CO2 from the atmosphere or stationary emission sources and transporting and storing it via mineral carbonation, in oceans or geological media. The latter is referred to as carbon capture and geological storage (CCGS) and is considered to be the most promising of all solutions. Generally it consists of a storage (e.g. depleted oil reservoirs and deep saline aquifers) and sealing (commonly termed caprock in the oil industry) formations. The present study concerns the injection of CO2 into deep aquifers and regardless injection conditions, temperature gradients between carbon dioxide and the storage formation are likely to occur. Should the CO2 temperature be lower than the storage formation, a contractive behaviour of the reservoir and caprock is expected. The latter can result in the opening of new paths or re-opening of fractures, favouring leakage and compromising the CCGS project. During CO2 injection, coupled thermo-hydro-mechanical phenomena occur, which due to their complexity, hamper the assessment of each relative influence. For this purpose, several analyses were carried out in order to evaluate their influences but focusing on the thermal contractive behaviour. It was finally concluded that depending on mechanical and thermal properties of the pair aquifer-seal, the sealing caprock can undergo significant decreases in effective stress.

Molecular simulation of gas adsorption equilibria in nanoporous materials

This work is divided into two distinct parts. The first part consists of the study of the metal organic framework UiO-66Zr, where the aim was to determine the force field that best describes the adsorption equilibrium properties of two different gases, methane and carbon dioxide. The other part of the work focuses on the study of the single wall carbon nanotube topology for ethane adsorption; the aim was to simplify as much as possible the solid-fluid force field model to increase the computational efficiency of the Monte Carlo simulations. The choice of both adsorbents relies on their potential use in adsorption processes, such as the capture and storage of carbon dioxide, natural gas storage, separation of components of biogas, and olefin/paraffin separations. The adsorption studies on the two porous materials were performed by molecular simulation using the grand canonical Monte Carlo (μ,V,T) method, over the temperature range of 298-343 K and pressure range 0.06-70 bar. The calibration curves of pressure and density as a function of chemical potential and temperature for the three adsorbates under study, were obtained Monte Carlo simulation in the canonical ensemble (N,V,T); polynomial fit and interpolation of the obtained data allowed to determine the pressure and gas density at any chemical potential. The adsorption equilibria of methane and carbon dioxide in UiO-66Zr were simulated and compared with the experimental data obtained by Jasmina H. Cavka et al. The results show that the best force field for both gases is a chargeless united-atom force field based on the TraPPE model. Using this validated force field it was possible to estimate the isosteric heats of adsorption and the Henry constants. In the Grand-Canonical Monte Carlo simulations of carbon nanotubes, we conclude that the fastest type of run is obtained with a force field that approximates the nanotube as a smooth cylinder; this approximation gives execution times that are 1.6 times faster than the typical atomistic runs.

Reactive hybrid knowledge bases

Hybrid knowledge bases are knowledge bases that combine ontologies with non-monotonic rules, allowing to join the best of both open world ontologies and close world rules. Ontologies shape a good mechanism to share knowledge on theWeb that can be understood by both humans and machines, on the other hand rules can be used, e.g., to encode legal laws or to do a mapping between sources of information. Taking into account the dynamics present today on the Web, it is important for these hybrid knowledge bases to capture all these dynamics and thus adapt themselves. To achieve that, it is necessary to create mechanisms capable of monitoring the information flow present on theWeb. Up to today, there are no such mechanisms that allow for monitoring events and performing modifications of hybrid knowledge bases autonomously. The goal of this thesis is then to create a system that combine these hybrid knowledge bases with reactive rules, aiming to monitor events and perform actions over a knowledge base. To achieve this goal, a reactive system for the SemanticWeb is be developed in a logic-programming based approach accompanied with a language for heterogeneous rule base evolution having as its basis RIF Production Rule Dialect, which is a standard for exchanging rules over theWeb.

ClearPhoto - augmented photography

The widespread use of mobile devices has made known to the general public new areas that were hitherto confined to specialized devices. In general, the smartphone came to give all users the ability to execute multiple tasks, and among them, take photographs using the integrated cameras. Although these devices are continuously receiving improved cameras, their manufacturers do not take advantage of their full potential, since the operating systems normally offer simple APIs and applications for shooting. Therefore, taking advantage of this environment for mobile devices, we find ourselves in the best scenario to develop applications that help the user obtaining a good result when shooting. In an attempt to provide a set of techniques and tools more applied to the task, this dissertation presents, as a contribution, a set of tools for mobile devices that provides information in real-time on the composition of the scene before capturing an image. Thus, the proposed solution gives support to a user while capturing a scene with a mobile device. The user will be able to receive multiple suggestions on the composition of the scene, which will be based on rules of photography or other useful tools for photographers. The tools include horizon detection and graphical visualization of the color palette presented on the scenario being photographed. These tools were evaluated regarding the mobile device implementation and how users assess their usefulness.

Development of new membranes based on ionic liquid materials for gas separation

In the field of energy, natural gas is an essential bridge to a clean, low carbon, renewable energy era. However, natural gas processing and transportation regulation require the removal of contaminant compounds such as carbon dioxide (CO2). Regarding clean air, the increasing atmospheric concentrations of greenhouse gases, specifically CO2, is of particular concern. Therefore, new costeffective, high performance technologies for carbon capture have been researched and the design of materials with the ability to efficiently separate CO2 from other gases is of vital importance.(...)

Image processing for displacement measurements

Since the invention of photography humans have been using images to capture, store and analyse the act that they are interested in. With the developments in this field, assisted by better computers, it is possible to use image processing technology as an accurate method of analysis and measurement. Image processing's principal qualities are flexibility, adaptability and the ability to easily and quickly process a large amount of information. Successful examples of applications can be seen in several areas of human life, such as biomedical, industry, surveillance, military and mapping. This is so true that there are several Nobel prizes related to imaging. The accurate measurement of deformations, displacements, strain fields and surface defects are challenging in many material tests in Civil Engineering because traditionally these measurements require complex and expensive equipment, plus time consuming calibration. Image processing can be an inexpensive and effective tool for load displacement measurements. Using an adequate image acquisition system and taking advantage of the computation power of modern computers it is possible to accurately measure very small displacements with high precision. On the market there are already several commercial software packages. However they are commercialized at high cost. In this work block-matching algorithms will be used in order to compare the results from image processing with the data obtained with physical transducers during laboratory load tests. In order to test the proposed solutions several load tests were carried out in partnership with researchers from the Civil Engineering Department at Universidade Nova de Lisboa (UNL).

Tool for spatial and dynamic representation of artistic performances

This proposal aims to explore the use of available technologies for video representation of sets and performers in order to serve as support for composition processes and artistic performer rehearsals, while focusing in representing the performer’s body and its movements, and its relation with objects belonging to the three-dimensional space of their performances. This project’s main goal is to design and develop a system that can spatially represent the performer and its movements, by means of capturing processes and reconstruction using a camera device, as well as enhance the three-dimensional space where the performance occurs by allowing interaction with virtual objects and by adding a video component, either for documentary purposes, or for live performances effects (for example, using video mapping video techniques in captured video or projection during a performance).

Crashes, volatility, and the equity premium: Lessons from S&P 500 options

We use a novel pricing model to imply time series of diffusive volatility and jump intensity from S&P 500 index options. These two measures capture the ex ante risk assessed by investors. Using a simple general equilibrium model, we translate the implied measures of ex ante risk into an ex ante risk premium. The average premium that compensates the investor for the ex ante risks is 70% higher than the premium for realized volatility. The equity premium implied from option prices is shown to significantly predict subsequent stock market returns.

Indicadores de qualidade na emergência médica pré-hospitalar : painel operacional para o INEM, I.P.

RESUMO - A Emergência Médica Pré-Hospitalar é uma parte importante na cadeia de cuidados de saúde, quer pela gravidade das situações a que atende, quer por funcionar como gatekeeper. O estudo é dedicado a instrumentos de medição e em simultâneo a medições de qualidade como processo de melhoria contínua da qualidade na EMPH. Existem projetos a nível internacional para implementação de painéis de indicadores, alguns atribuem significativa relevância aos processos assistenciais. O European Emergency Data Project (EDD) foi selecionado para servir como painel de indicadores a explorar neste trabalho. Porque a nível científico está bem desenhado, as definições e variáveis estão bem explicitadas e interessa ao INEM, I.P. utilizar um painel que lhe permita um benchmarking. Criou-se um dashboard para os indicadores selecionados e com ele analisaram-se os dados para aferir a qualidade do SEM. Não foi possível, pela sua inexistência, coletar dados para dois dos indicadores propostos. Foram apresentadas propostas de melhoria no sistema de captação de dados do INEM, I.P. para que a instituição possa monitorizar periodicamente os indicadores selecionados. A existência de dados e a sua fiabilidade para utilizar na medição por indicadores é algo que se explorou neste trabalho de campo, e as fraquezas encontradas foram matéria para oportunidades, recomendações, e caminho para discussão e o fortalecimento da instituição.

Knowledge management framework based on brain models and human physiology

The life of humans and most living beings depend on sensation and perception for the best assessment of the surrounding world. Sensorial organs acquire a variety of stimuli that are interpreted and integrated in our brain for immediate use or stored in memory for later recall. Among the reasoning aspects, a person has to decide what to do with available information. Emotions are classifiers of collected information, assigning a personal meaning to objects, events and individuals, making part of our own identity. Emotions play a decisive role in cognitive processes as reasoning, decision and memory by assigning relevance to collected information. The access to pervasive computing devices, empowered by the ability to sense and perceive the world, provides new forms of acquiring and integrating information. But prior to data assessment on its usefulness, systems must capture and ensure that data is properly managed for diverse possible goals. Portable and wearable devices are now able to gather and store information, from the environment and from our body, using cloud based services and Internet connections. Systems limitations in handling sensorial data, compared with our sensorial capabilities constitute an identified problem. Another problem is the lack of interoperability between humans and devices, as they do not properly understand human’s emotional states and human needs. Addressing those problems is a motivation for the present research work. The mission hereby assumed is to include sensorial and physiological data into a Framework that will be able to manage collected data towards human cognitive functions, supported by a new data model. By learning from selected human functional and behavioural models and reasoning over collected data, the Framework aims at providing evaluation on a person’s emotional state, for empowering human centric applications, along with the capability of storing episodic information on a person’s life with physiologic indicators on emotional states to be used by new generation applications.