833 resultados para display technologies


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Ureases are enzymes from plants, fungi and bacteria that catalyze the hydrolysis of urea to form ammonia and carbon dioxide. While fungal and plant ureases are homo-oligomers of 90-kDa subunits, bacterial ureases are multimers of two or three subunit complexes. We showed that some isoforms of jack bean urease, canatoxin and the classical urease, bind to glycoconjugates and induce platelet aggregation. Canatoxin also promotes release of histamine from mast cells, insulin from pancreatic cells and neurotransmitters from brain synaptosomes. In vivo it induces rat paw edema and neutrophil chemotaxis. These effects are independent of ureolytic activity and require activation of eicosanoid metabolism and calcium channels. Helicobacter pylori, a Gram-negative bacterium that colonizes the human stomach mucosa, causes gastric ulcers and cancer by a mechanism that is not understood. H. pylori produces factors that damage gastric epithelial cells, such as the vacuolating cytotoxin VacA, the cytotoxin-associated protein CagA, and a urease (up to 10% of bacterial protein) that neutralizes the acidic medium permitting its survival in the stomach. H. pylori whole cells or extracts of its water-soluble proteins promote inflammation, activate neutrophils and induce the release of cytokines. In this paper we review data from the literature suggesting that H. pylori urease displays many of the biological activities observed for jack bean ureases and show that bacterial ureases have a secretagogue effect modulated by eicosanoid metabolites through lipoxygenase pathways. These findings could be relevant to the elucidation of the role of urease in the pathogenesis of the gastrointestinal disease caused by H. pylori.

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The experiences of several healthcare organizations were considered to distinguish the most frequently used lean tools, the success and failure factors, and the obstacles that may appear while implementing lean. As a result, two approaches to “go lean” were defined, and analyzed from the prospective of the applicability to healthcare processes. Industrialization of healthcare was studied, and the most promising digital technology tools to improve healthcare process were highlighted. Finally, the analysis of healthcare challenges and feasible ways to address them was conducted and presented as the main result of this work. The possible ways of implementation of the findings and limitations were described in the conclusion.

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The shift towards a knowledge-based economy has inevitably prompted the evolution of patent exploitation. Nowadays, patent is more than just a prevention tool for a company to block its competitors from developing rival technologies, but lies at the very heart of its strategy for value creation and is therefore strategically exploited for economic pro t and competitive advantage. Along with the evolution of patent exploitation, the demand for reliable and systematic patent valuation has also reached an unprecedented level. However, most of the quantitative approaches in use to assess patent could arguably fall into four categories and they are based solely on the conventional discounted cash flow analysis, whose usability and reliability in the context of patent valuation are greatly limited by five practical issues: the market illiquidity, the poor data availability, discriminatory cash-flow estimations, and its incapability to account for changing risk and managerial flexibility. This dissertation attempts to overcome these impeding barriers by rationalizing the use of two techniques, namely fuzzy set theory (aiming at the first three issues) and real option analysis (aiming at the last two). It commences with an investigation into the nature of the uncertainties inherent in patent cash flow estimation and claims that two levels of uncertainties must be properly accounted for. Further investigation reveals that both levels of uncertainties fall under the categorization of subjective uncertainty, which differs from objective uncertainty originating from inherent randomness in that uncertainties labelled as subjective are highly related to the behavioural aspects of decision making and are usually witnessed whenever human judgement, evaluation or reasoning is crucial to the system under consideration and there exists a lack of complete knowledge on its variables. Having clarified their nature, the application of fuzzy set theory in modelling patent-related uncertain quantities is effortlessly justified. The application of real option analysis to patent valuation is prompted by the fact that both patent application process and the subsequent patent exploitation (or commercialization) are subject to a wide range of decisions at multiple successive stages. In other words, both patent applicants and patentees are faced with a large variety of courses of action as to how their patent applications and granted patents can be managed. Since they have the right to run their projects actively, this flexibility has value and thus must be properly accounted for. Accordingly, an explicit identification of the types of managerial flexibility inherent in patent-related decision making problems and in patent valuation, and a discussion on how they could be interpreted in terms of real options are provided in this dissertation. Additionally, the use of the proposed techniques in practical applications is demonstrated by three fuzzy real option analysis based models. In particular, the pay-of method and the extended fuzzy Black-Scholes model are employed to investigate the profitability of a patent application project for a new process for the preparation of a gypsum-fibre composite and to justify the subsequent patent commercialization decision, respectively; a fuzzy binomial model is designed to reveal the economic potential of a patent licensing opportunity.

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Resilience is the property of a system to remain trustworthy despite changes. Changes of a different nature, whether due to failures of system components or varying operational conditions, significantly increase the complexity of system development. Therefore, advanced development technologies are required to build robust and flexible system architectures capable of adapting to such changes. Moreover, powerful quantitative techniques are needed to assess the impact of these changes on various system characteristics. Architectural flexibility is achieved by embedding into the system design the mechanisms for identifying changes and reacting on them. Hence a resilient system should have both advanced monitoring and error detection capabilities to recognise changes as well as sophisticated reconfiguration mechanisms to adapt to them. The aim of such reconfiguration is to ensure that the system stays operational, i.e., remains capable of achieving its goals. Design, verification and assessment of the system reconfiguration mechanisms is a challenging and error prone engineering task. In this thesis, we propose and validate a formal framework for development and assessment of resilient systems. Such a framework provides us with the means to specify and verify complex component interactions, model their cooperative behaviour in achieving system goals, and analyse the chosen reconfiguration strategies. Due to the variety of properties to be analysed, such a framework should have an integrated nature. To ensure the system functional correctness, it should rely on formal modelling and verification, while, to assess the impact of changes on such properties as performance and reliability, it should be combined with quantitative analysis. To ensure scalability of the proposed framework, we choose Event-B as the basis for reasoning about functional correctness. Event-B is a statebased formal approach that promotes the correct-by-construction development paradigm and formal verification by theorem proving. Event-B has a mature industrial-strength tool support { the Rodin platform. Proof-based verification as well as the reliance on abstraction and decomposition adopted in Event-B provides the designers with a powerful support for the development of complex systems. Moreover, the top-down system development by refinement allows the developers to explicitly express and verify critical system-level properties. Besides ensuring functional correctness, to achieve resilience we also need to analyse a number of non-functional characteristics, such as reliability and performance. Therefore, in this thesis we also demonstrate how formal development in Event-B can be combined with quantitative analysis. Namely, we experiment with integration of such techniques as probabilistic model checking in PRISM and discrete-event simulation in SimPy with formal development in Event-B. Such an integration allows us to assess how changes and di erent recon guration strategies a ect the overall system resilience. The approach proposed in this thesis is validated by a number of case studies from such areas as robotics, space, healthcare and cloud domain.

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Campylobacteriosis is an infection frequently acquired through the consumption of animal origin products. Chicken can be considered the main responsible cause in the transmission chain of this disease. Ionizing radiation was used to verify the reduction of the microbiological load of Campylobacter jejuni present in chicken liver, which, in natura, can present contamination in up to 100% of the cases. The doses of irradiation used were: 0.20 kGy, 0.27 kGy, 0.30 kGy and 0.35 kGy. The samples of chicken liver were acquired in aviaries, local supermarkets and large chain supermarkets. The samples were analyzed for Campylobacter at FIOCRUZ. Irradiation was performed at COPPE/UFRJ, using a Gamma Cell Irradiator with a 60Co gamma source. Only the frozen sample acquired at the local supermarket did not contain the bacterium. Campylobacter sp. was present in all other samples, even when using procedures and technologies that aimed at the impediment of the presence of this bacterium in food and, consequently, at the protection of human health. On the whole, the results were satisfactory; nevertheless, it is known that the bacterial growth conditions required by this bacterium are uncommon when compared to other enteropathogenic bacteria.

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The application of technologies to extend the postharvest life of mangosteen fruit was studied and compared to storage at 25 °C/70-75%R.H (25 °C control treatment). The fruits were packed in expanded polystyrene (EPS) trays (5 fruits/tray). Five treatments were carried out at 13 °C/ 90-95% RH: application of carnauba wax coating, lecithin + CMC (carboxymethyl cellulose) coating, 50 µm LDPE (low density polyethylene) film coating, 13 µm PVC (Polyvinyl chloride), and non-coated sample (13 °C control treatment). Physicochemical analyses were performed twice a week. A statistical design was completely randomized with 8 repetitions for each treatment plus the control treatment. The results were submitted to variance analysis, and the averages compared by the Tukey test at 5% probability. Among the quality parameters analyzed, more significant differences were observed for weight loss, texture, and peel moisture content. The results showed that the maximum storage period for mangosteen at 25 °C is two weeks; while storage at13 °C can guarantee the conservation of this fruit for 25 days. Therefore, the treatment at 13 °C/90-95% RH without the use of coatings and films was more effective and economical.

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The advancement of science and technology makes it clear that no single perspective is any longer sufficient to describe the true nature of any phenomenon. That is why the interdisciplinary research is gaining more attention overtime. An excellent example of this type of research is natural computing which stands on the borderline between biology and computer science. The contribution of research done in natural computing is twofold: on one hand, it sheds light into how nature works and how it processes information and, on the other hand, it provides some guidelines on how to design bio-inspired technologies. The first direction in this thesis focuses on a nature-inspired process called gene assembly in ciliates. The second one studies reaction systems, as a modeling framework with its rationale built upon the biochemical interactions happening within a cell. The process of gene assembly in ciliates has attracted a lot of attention as a research topic in the past 15 years. Two main modelling frameworks have been initially proposed in the end of 1990s to capture ciliates’ gene assembly process, namely the intermolecular model and the intramolecular model. They were followed by other model proposals such as templatebased assembly and DNA rearrangement pathways recombination models. In this thesis we are interested in a variation of the intramolecular model called simple gene assembly model, which focuses on the simplest possible folds in the assembly process. We propose a new framework called directed overlap-inclusion (DOI) graphs to overcome the limitations that previously introduced models faced in capturing all the combinatorial details of the simple gene assembly process. We investigate a number of combinatorial properties of these graphs, including a necessary property in terms of forbidden induced subgraphs. We also introduce DOI graph-based rewriting rules that capture all the operations of the simple gene assembly model and prove that they are equivalent to the string-based formalization of the model. Reaction systems (RS) is another nature-inspired modeling framework that is studied in this thesis. Reaction systems’ rationale is based upon two main regulation mechanisms, facilitation and inhibition, which control the interactions between biochemical reactions. Reaction systems is a complementary modeling framework to traditional quantitative frameworks, focusing on explicit cause-effect relationships between reactions. The explicit formulation of facilitation and inhibition mechanisms behind reactions, as well as the focus on interactions between reactions (rather than dynamics of concentrations) makes their applicability potentially wide and useful beyond biological case studies. In this thesis, we construct a reaction system model corresponding to the heat shock response mechanism based on a novel concept of dominance graph that captures the competition on resources in the ODE model. We also introduce for RS various concepts inspired by biology, e.g., mass conservation, steady state, periodicity, etc., to do model checking of the reaction systems based models. We prove that the complexity of the decision problems related to these properties varies from P to NP- and coNP-complete to PSPACE-complete. We further focus on the mass conservation relation in an RS and introduce the conservation dependency graph to capture the relation between the species and also propose an algorithm to list the conserved sets of a given reaction system.

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Global warming is one of the most alarming problems of this century. Initial scepticism concerning its validity is currently dwarfed by the intensification of extreme weather events whilst the gradual arising level of anthropogenic CO2 is pointed out as its main driver. Most of the greenhouse gas (GHG) emissions come from large point sources (heat and power production and industrial processes) and the continued use of fossil fuels requires quick and effective measures to meet the world’s energy demand whilst (at least) stabilizing CO2 atmospheric levels. The framework known as Carbon Capture and Storage (CCS) – or Carbon Capture Utilization and Storage (CCUS) – comprises a portfolio of technologies applicable to large‐scale GHG sources for preventing CO2 from entering the atmosphere. Amongst them, CO2 capture and mineralisation (CCM) presents the highest potential for CO2 sequestration as the predicted carbon storage capacity (as mineral carbonates) far exceeds the estimated levels of the worldwide identified fossil fuel reserves. The work presented in this thesis aims at taking a step forward to the deployment of an energy/cost effective process for simultaneous capture and storage of CO2 in the form of thermodynamically stable and environmentally friendly solid carbonates. R&D work on the process considered here began in 2007 at Åbo Akademi University in Finland. It involves the processing of magnesium silicate minerals with recyclable ammonium salts for extraction of magnesium at ambient pressure and 400‐440⁰C, followed by aqueous precipitation of magnesium in the form of hydroxide, Mg(OH)2, and finally Mg(OH)2 carbonation in a pressurised fluidized bed reactor at ~510⁰C and ~20 bar PCO2 to produce high purity MgCO3. Rock material taken from the Hitura nickel mine, Finland, and serpentinite collected from Bragança, Portugal, were tested for magnesium extraction with both ammonium sulphate and bisulphate (AS and ABS) for determination of optimal operation parameters, primarily: reaction time, reactor type and presence of moisture. Typical efficiencies range from 50 to 80% of magnesium extraction at 350‐450⁰C. In general ABS performs better than AS showing comparable efficiencies at lower temperature and reaction times. The best experimental results so far obtained include 80% magnesium extraction with ABS at 450⁰C in a laboratory scale rotary kiln and 70% Mg(OH)2 carbonation in the PFB at 500⁰C, 20 bar CO2 pressure for 15 minutes. The extraction reaction with ammonium salts is not at all selective towards magnesium. Other elements like iron, nickel, chromium, copper, etc., are also co‐extracted. Their separation, recovery and valorisation are addressed as well and found to be of great importance. The assessment of the exergetic performance of the process was carried out using Aspen Plus® software and pinch analysis technology. The choice of fluxing agent and its recovery method have a decisive sway in the performance of the process: AS is recovered by crystallisation and in general the whole process requires more exergy (2.48–5.09 GJ/tCO2sequestered) than ABS (2.48–4.47 GJ/tCO2sequestered) when ABS is recovered by thermal decomposition. However, the corrosive nature of molten ABS and operational problems inherent to thermal regeneration of ABS prohibit this route. Regeneration of ABS through addition of H2SO4 to AS (followed by crystallisation) results in an overall negative exergy balance (mainly at the expense of low grade heat) but will flood the system with sulphates. Although the ÅA route is still energy intensive, its performance is comparable to conventional CO2 capture methods using alkanolamine solvents. An energy‐neutral process is dependent on the availability and quality of nearby waste heat and economic viability might be achieved with: magnesium extraction and carbonation levels ≥ 90%, the processing of CO2‐containing flue gases (eliminating the expensive capture step) and production of marketable products.

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Additive manufacturing (shortened as AM), or more commonly 3D printing, consists of wide variety of different modern manufacturing technologies. AM is based on direct printing of a digital 3D model to a final product which is fabricated adding material layer by layer. This is from where term additive manufacturing has its origin. It is not only material what is added, but it is also value, properties etc. which are added. AM enables production of different and even better products compared to conventional manufacturing technologies. An estimation of potential of additive manufacturing can be gathered by considering the potential of laser cutting, which is one of the most widely used modern manufacturing technologies. This technique has been used over 40 years, and whole market around this technology is at the moment c. four billion euros and yearly growth is around 10 %. One factor affecting this success of laser cutting is that laser cutting enables radical improvements to products made of flat sheet. AM and 3D printing will do the same for three dimensional parts. Laser devices, which are at the moment used in 3D printing, are globally at the moment only around 1% of all laser devices used in any fabrication technology, so even with a cautious estimate the potential growth of at least 100 % is coming in next few years. Role of education is very important, when this kind of modern technology is industrially implemented. When both generation entering to work life and also generation who has been a while in work life understands new technology, its potential and limitations, this is the point when also product design can be rethought Potential of product design is driving force for wide use of additive manufacturing and 3D printing. Utilization of additive manufacturing and 3D printing is also opportunity for Finland and Finnish industry. This technology can save Finnish manufacturing industry. This technique has stron potential, as Finland has traditionally strong industrial know-how and good ICT knowledge.

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Grapevine winter hardiness is a key factor in vineyard success in many cool climate wine regions. Winter hardiness may be governed by a myriad of factors in addition to extreme weather conditions – e.g. soil factors (texture, chemical composition, moisture, drainage), vine water status, and yield– that are unique to each site. It was hypothesized that winter hardiness would be influenced by certain terroir factors , specifically that vines with low water status [more negative leaf water potential (leaf ψ)] would be more winter hardy than vines with high water status (more positive leaf ψ). Twelve different vineyard blocks (six each of Riesling and Cabernet franc) throughout the Niagara Region in Ontario, Canada were chosen. Data were collected during the growing season (soil moisture, leaf ψ), at harvest (yield components, berry composition), and during the winter (bud LT50, bud survival). Interpolation and mapping of the variables was completed using ArcGIS 10.1 (ESRI, Redlands, CA) and statistical analyses (Pearson’s correlation, principal component analysis, multilinear regression) were performed using XLSTAT. Clear spatial trends were observed in each vineyard for soil moisture, leaf ψ, yield components, berry composition, and LT50. Both leaf ψ and berry weight could predict the LT50 value, with strong positive correlations being observed between LT50 and leaf ψ values in eight of the 12 vineyard blocks. In addition, vineyards in different appellations showed many similarities (Niagara Lakeshore, Lincoln Lakeshore, Four Mile Creek, Beamsville Bench). These results suggest that there is a spatial component to winter injury, as with other aspects of terroir, in the Niagara region.

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Vineyards vary over space and time, making geomatics technologies ideally suited to study terroir. This study applied geomatics technologies - GPS, remote sensing and GIS - to characterize the spatial variability at Stratus Vineyards in the Niagara Region. The concept of spatial terroir was used to visualize, monitor and analyze the spatial and temporal variability of variables that influence grape quality. Spatial interpolation and spatial autocorrelation were used to measure the pattern demonstrated by soil moisture, leaf water potential, vine vigour, soil composition and grape composition on two Cabernet Franc blocks and one Chardonnay block. All variables demonstrated some spatial variability within and between the vineyard block and over time. Soil moisture exhibited the most significant spatial clustering and was temporally stable. Geomatics technologies provided valuable spatial information related to the natural spatial variability at Stratus Vineyards and can be used to inform and influence vineyard management decisions.