948 resultados para extraction and separation techniques
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An approach for knowledge extraction from the information arriving to the knowledge base input and also new knowledge distribution over knowledge subsets already present in the knowledge base is developed. It is also necessary to realize the knowledge transform into parameters (data) of the model for the following decision-making on the given subset. It is assumed to realize the decision-making with the fuzzy sets’ apparatus.
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Petri Nets are a formal, graphical and executable modeling technique for the specification and analysis of concurrent and distributed systems and have been widely applied in computer science and many other engineering disciplines. Low level Petri nets are simple and useful for modeling control flows but not powerful enough to define data and system functionality. High level Petri nets (HLPNs) have been developed to support data and functionality definitions, such as using complex structured data as tokens and algebraic expressions as transition formulas. Compared to low level Petri nets, HLPNs result in compact system models that are easier to be understood. Therefore, HLPNs are more useful in modeling complex systems. ^ There are two issues in using HLPNs—modeling and analysis. Modeling concerns the abstracting and representing the systems under consideration using HLPNs, and analysis deals with effective ways study the behaviors and properties of the resulting HLPN models. In this dissertation, several modeling and analysis techniques for HLPNs are studied, which are integrated into a framework that is supported by a tool. ^ For modeling, this framework integrates two formal languages: a type of HLPNs called Predicate Transition Net (PrT Net) is used to model a system's behavior and a first-order linear time temporal logic (FOLTL) to specify the system's properties. The main contribution of this dissertation with regard to modeling is to develop a software tool to support the formal modeling capabilities in this framework. ^ For analysis, this framework combines three complementary techniques, simulation, explicit state model checking and bounded model checking (BMC). Simulation is a straightforward and speedy method, but only covers some execution paths in a HLPN model. Explicit state model checking covers all the execution paths but suffers from the state explosion problem. BMC is a tradeoff as it provides a certain level of coverage while more efficient than explicit state model checking. The main contribution of this dissertation with regard to analysis is adapting BMC to analyze HLPN models and integrating the three complementary analysis techniques in a software tool to support the formal analysis capabilities in this framework. ^ The SAMTools developed for this framework in this dissertation integrates three tools: PIPE+ for HLPNs behavioral modeling and simulation, SAMAT for hierarchical structural modeling and property specification, and PIPE+Verifier for behavioral verification.^
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Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.
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The use of styrene maleic acid (SMA) co-polymers to extract and purify transmembrane proteins, whilst retaining their native bilayer environment, overcomes many of the disadvantages associated with conventional detergent based procedures. This approach has huge potential for the future of membrane protein structural and functional studies. In this investigation we have systematically tested a range of commercially available SMA polymers, varying in both the ratio of styrene to maleic acid and in total size, for the ability to extract, purify and stabilise transmembrane proteins. Three different membrane proteins (BmrA, LeuT and ZipA) which vary in size and shape were used. Our results show that several polymers can be used to extract membrane proteins comparably to conventional detergents. A styrene:maleic acid ratio of either 2:1 or 3:1, combined with a relatively small average molecular weight (7.5-10 kDa) is optimal for membrane extraction, and this appears to be independent of the protein size, shape or expression system. A subset of polymers were taken forward for purification, functional and stability tests. Following a one-step affinity purification SMA 2000 was found to be the best choice for yield, purity and function. However the other polymers offer subtle differences in size and sensitivity to divalent cations that may be useful for a variety of downstream applications.
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Cancer comprises a collection of diseases, all of which begin with abnormal tissue growth from various stimuli, including (but not limited to): heredity, genetic mutation, exposure to harmful substances, radiation as well as poor dieting and lack of exercise. The early detection of cancer is vital to providing life-saving, therapeutic intervention. However, current methods for detection (e.g., tissue biopsy, endoscopy and medical imaging) often suffer from low patient compliance and an elevated risk of complications in elderly patients. As such, many are looking to “liquid biopsies” for clues into presence and status of cancer due to its minimal invasiveness and ability to provide rich information about the native tumor. In such liquid biopsies, peripheral blood is drawn from patients and is screened for key biomarkers, chiefly circulating tumor cells (CTCs). Capturing, enumerating and analyzing the genetic and metabolomic characteristics of these CTCs may hold the key for guiding doctors to better understand the source of cancer at an earlier stage for more efficacious disease management.
The isolation of CTCs from whole blood, however, remains a significant challenge due to their (i) low abundance, (ii) lack of a universal surface marker and (iii) epithelial-mesenchymal transition that down-regulates common surface markers (e.g., EpCAM), reducing their likelihood of detection via positive selection assays. These factors potentiate the need for an improved cell isolation strategy that can collect CTCs via both positive and negative selection modalities as to avoid the reliance on a single marker, or set of markers, for more accurate enumeration and diagnosis.
The technologies proposed herein offer a unique set of strategies to focus, sort and template cells in three independent microfluidic modules. The first module exploits ultrasonic standing waves and a class of elastomeric particles for the rapid and discriminate sequestration of cells. This type of cell handling holds promise not only in sorting, but also in the isolation of soluble markers from biofluids. The second module contains components to focus (i.e., arrange) cells via forces from acoustic standing waves and separate cells in a high throughput fashion via free-flow magnetophoresis. The third module uses a printed array of micromagnets to capture magnetically labeled cells into well-defined compartments, enabling on-chip staining and single cell analysis. These technologies can operate in standalone formats, or can be adapted to operate with established analytical technologies, such as flow cytometry. A key advantage of these innovations is their ability to process erythrocyte-lysed blood in a rapid (and thus high throughput) fashion. They can process fluids at a variety of concentrations and flow rates, target cells with various immunophenotypes and sort cells via positive (and potentially negative) selection. These technologies are chip-based, fabricated using standard clean room equipment, towards a disposable clinical tool. With further optimization in design and performance, these technologies might aid in the early detection, and potentially treatment, of cancer and various other physical ailments.
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Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.
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Petri Nets are a formal, graphical and executable modeling technique for the specification and analysis of concurrent and distributed systems and have been widely applied in computer science and many other engineering disciplines. Low level Petri nets are simple and useful for modeling control flows but not powerful enough to define data and system functionality. High level Petri nets (HLPNs) have been developed to support data and functionality definitions, such as using complex structured data as tokens and algebraic expressions as transition formulas. Compared to low level Petri nets, HLPNs result in compact system models that are easier to be understood. Therefore, HLPNs are more useful in modeling complex systems. There are two issues in using HLPNs - modeling and analysis. Modeling concerns the abstracting and representing the systems under consideration using HLPNs, and analysis deals with effective ways study the behaviors and properties of the resulting HLPN models. In this dissertation, several modeling and analysis techniques for HLPNs are studied, which are integrated into a framework that is supported by a tool. For modeling, this framework integrates two formal languages: a type of HLPNs called Predicate Transition Net (PrT Net) is used to model a system's behavior and a first-order linear time temporal logic (FOLTL) to specify the system's properties. The main contribution of this dissertation with regard to modeling is to develop a software tool to support the formal modeling capabilities in this framework. For analysis, this framework combines three complementary techniques, simulation, explicit state model checking and bounded model checking (BMC). Simulation is a straightforward and speedy method, but only covers some execution paths in a HLPN model. Explicit state model checking covers all the execution paths but suffers from the state explosion problem. BMC is a tradeoff as it provides a certain level of coverage while more efficient than explicit state model checking. The main contribution of this dissertation with regard to analysis is adapting BMC to analyze HLPN models and integrating the three complementary analysis techniques in a software tool to support the formal analysis capabilities in this framework. The SAMTools developed for this framework in this dissertation integrates three tools: PIPE+ for HLPNs behavioral modeling and simulation, SAMAT for hierarchical structural modeling and property specification, and PIPE+Verifier for behavioral verification.
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Phosphorus is an essential nutrient for life. In the ocean, phosphorus burial regulates marine primary production**1, 2. Phosphorus is removed from the ocean by sedimentation of organic matter, and the subsequent conversion of organic phosphorus to phosphate minerals such as apatite, and ultimately phosphorite deposits**3, 4. Bacteria are thought to mediate these processes**5, but the mechanism of sequestration has remained unclear. Here, we present results from laboratory incubations in which we labelled organic-rich sediments from the Benguela upwelling system, Namibia, with a 33P-radiotracer, and tracked the fate of the phosphorus. We show that under both anoxic and oxic conditions, large sulphide-oxidizing bacteria accumulate 33P in their cells, and catalyse the nearly instantaneous conversion of phosphate to apatite. Apatite formation was greatest under anoxic conditions. Nutrient analyses of Namibian upwelling waters and sediments suggest that the rate of phosphate-to-apatite conversion beneath anoxic bottom waters exceeds the rate of phosphorus release during organic matter mineralization in the upper sediment layers. We suggest that bacterial apatite formation is a significant phosphorus sink under anoxic bottom-water conditions. Expanding oxygen minimum zones are projected in simulations of future climate change**6, potentially increasing sequestration of marine phosphate, and restricting marine productivity.
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Lithium is used in the cathode and electrolyte of rechargeable batteries in many portable electronics and electric vehicles, and is thus seen as a critical component of modern technology (Gruber et al., 2011). Electric vehicles are promoted as a way to reduce carbon emissions associated with the transportation sector, which accounts for 14.3% of anthropogenic greenhouse gas emissions (OECD International Transport Forum, 2010). However, the sustainability of lithium procurement will influence the overall environmental impact of this proposed “green” solution. It is estimated that 66% of the world’s lithium resource is contained in natural brines, 24% in pegmatites, and 8% in sedimentary rocks such as hectorite clays (Gruber et al., 2011). It has been shown that “[r]ecycling of lithium from Li-ion batteries may be a critical factor in balancing the supply of lithium with future demand” (Gruber et al., 2011). In an attempt to quantify energy and materials consumption associated with production of a unit of useful lithium compounds, industry reports and peer-reviewed scientific literature concerning lithium mining and lithium recycling were reviewed and compared. Other aspects of sustainability, such as waste or by-products produced in the production of a unit of useful lithium, were also explored. Thus, this paper will serve to further the evaluation of the comparative environmental consequences associated with lithium production via extraction versus recycling. Efficiencies must be made in both processes to maximize productivity while minimizing ecological harm.
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We study work extraction from the Dicke model achieved using simple unitary cyclic transformations keeping into account both a non optimal unitary protocol, and the energetic cost of creating the initial state. By analyzing the role of entanglement, we find that highly entangled states can be inefficient for energy storage when considering the energetic cost of creating the state. Such surprising result holds notwithstanding the fact that the criticality of the model at hand can sensibly improve the extraction of work. While showing the advantages of using a many-body system for work extraction, our results demonstrate that entanglement is not necessarily advantageous for energy storage purposes, when non optimal processes are considered. Our work shows the importance of better understanding the complex interconnections between non-equilibrium thermodynamics of quantum systems and correlations among their subparts.
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Economic losses resulting from disease development can be reduced by accurate and early detection of plant pathogens. Early detection can provide the grower with useful information on optimal crop rotation patterns, varietal selections, appropriate control measures, harvest date and post harvest handling. Classical methods for the isolation of pathogens are commonly used only after disease symptoms. This frequently results in a delay in application of control measures at potentially important periods in crop production. This paper describes the application of both antibody and DNA based systems to monitor infection risk of air and soil borne fungal pathogens and the use of this information with mathematical models describing risk of disease associated with environmental parameters.
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The exhibition was of sketches and a photograph from my PhD practice research. The practice-research was comprised of observing opera singers in rehearsal and sketching them as they moved. As well as records of body position, and to some degree dynamic flow, the exhibited sketches were regarded as kinaesthetic responses in and of themselves – responses to the environment of the rehearsal, in particular responding to the sounds of the orchestra. These sketches were, in part, generated through an embodiment of the music, which was occurring in the same moment as the singer was engaged in embodying the music. These sketches were then used as tools that therefore contained kinaesthetic information which could be unlocked through a process of Butoh derived embodiment techniques alongside reference to the sketched image. This ultimately allowed me to move from a spectatorial position to a performance maker position, bringing a sense of the operatic into the non-singing body, whether that was my own or the bodies of other performers. In this way, and combined with rigorous observation of the corporeal restrictions of singing operatically, choreographies were created that employed operatic ways of moving in non-singing bodies and the operatic was extracted from opera and employed in movement based practice. The aspect of the practice-research exhibited is the correspondence between sketched documentation of the singers in rehearsal and photographic documentation of the dancer (researcher) in performance.
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The study of ichthyio-plankton stages and its relations with the environment and other organisms is therefore crucial for a correct use of fishery resources. In this context, the extraction and the analysis of the content of the digestive tract, is a key method for the identification of the diet in early larval stages, the determination of the resources they rely on and possibly a comparison with the diet of other species. Additionally this approach could be useful in determination on occurrence of species competition. This technique is preceded by the analysis of morphometric data (Blackith & Reyment, 1971; Marcus, 1990), that is the acquisition of quantitative variables measured from the morphology of the object of study. They are linear distances, count, angles and ratios. The subsequent application of multivariate statistical methods, aims to quantify the changes in morphological measures between and within groups, relating them to the type and size of prey and evaluate if some changes appear in food choices along the larvae growth.