891 resultados para Artificial arteries


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Aim: In the current climate of medical education, there is an ever-increasing demand for and emphasis on simulation as both a teaching and training tool. The objective of our study was to compare the realism and practicality of a number of artificial blood products that could be used for high-fidelity simulation. Method: A literature and internet search was performed and 15 artificial blood products were identified from a variety of sources. One product was excluded due to its potential toxicity risks. Five observers, blinded to the products, performed two assessments on each product using an evaluation tool with 14 predefined criteria including color, consistency, clotting, and staining potential to manikin skin and clothing. Each criterion was rated using a five-point Likert scale. The products were left for 24 hours, both refrigerated and at room temperature, and then reassessed. Statistical analysis was performed to identify the most suitable products, and both inter- and intra-rater variability were examined. Results: Three products scored consistently well with all five assessors, with one product in particular scoring well in almost every criterion. This highest-rated product had a mean rating of 3.6 of 5.0 (95% posterior Interval 3.4-3.7). Inter-rater variability was minor with average ratings varying from 3.0 to 3.4 between the highest and lowest scorer. Intrarater variability was negligible with good agreement between first and second rating as per weighted kappa scores (K = 0.67). Conclusion: The most realistic and practical form of artificial blood identified was a commercial product called KD151 Flowing Blood Syrup. It was found to be not only realistic in appearance but practical in terms of storage and stain removal.

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The common brown leafhopper, Orosius orientalis (Matsumura) (Homoptera: Cicadellidae), previously described as Orosius argentatus (Evans), is an important vector of several viruses and phytoplasmas worldwide. In Australia, phytoplasmas vectored by O. orientalis cause a range of economically important diseases, including legume little leaf (Hutton & Grylls, 1956), tomato big bud (Osmelak, 1986), lucerne witches broom (Helson, 1951), potato purple top wilt (Harding & Teakle, 1985), and Australian lucerne yellows (Pilkington et al., 2004). Orosius orientalis also transmits Tobacco yellow dwarf virus (TYDV; genus Mastrevirus, family Geminiviridae) to beans, causing bean summer death disease (Ballantyne, 1968), and to tobacco, causing tobacco yellow dwarf disease (Hill, 1937, 1941). TYDV has only been recorded in Australia to date. Both diseases result in significant production and quality losses (Ballantyne, 1968; Thomas, 1979; Moran & Rodoni, 1999). Although direct damage caused by leafhopper feeding has been observed, it is relatively minor compared to the losses resulting from disease (P Tr E bicki, unpubl.).

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A simple and sensitive spectrophotometric method for the simultaneous determination of acesulfame-K, sodium cyclamate and saccharin sodium sweeteners in foodstuff samples has been researched and developed. This analytical method relies on the different kinetic rates of the analytes in their oxidative reaction with KMnO4 to produce the green manganate product in an alkaline solution. As the kinetic rates of acesulfame-K, sodium cyclamate and saccharin sodium were similar and their kinetic data seriously overlapped, chemometrics methods, such as partial least squares (PLS), principal component regression (PCR) and classical least squares (CLS), were applied to resolve the kinetic data. The results showed that the PLS prediction model performed somewhat better. The proposed method was then applied for the determination of the three sweeteners in foodstuff samples, and the results compared well with those obtained by the reference HPLC method.

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Biotribology, the study of lubrication, wear and friction within the body, has become a topic of high importance in recent times as we continue to encounter debilitating diseases and trauma that destroy function of the joints. A highly successful surgical procedure to replace the joint with an artificial equivalent alleviates dysfunction and pain. However, the wear of the bearing surfaces in prosthetic joints is a significant clinical problem and more patients are surviving longer than the life expectancy of the joint replacement. Revision surgery is associated with increased morbidity and mortality and has a far less successful outcome than primary joint replacement. As such, it is essential to ensure that everything possible is done to limit the rate of revision surgery. Past experience indicates that the survival rate of the implant will be influenced by many parameters, of primary importance, the material properties of the implant, the composition of the synovial fluid and the method of lubrication. In prosthetic joints, effective boundary lubrication is known to take place. The interaction of the boundary lubricant and the bearing material is of utmost importance. The identity of the vital active ingredient within synovial fluid (SF) to which we owe the near frictionless performance of our articulating joints has been the quest of researchers for many years. Once identified, tribo tests can determine what materials and more importantly what surfaces this fraction of SF can function most optimally with. Surface-Active Phospholipids (SAPL) have been implicated as the body’s natural load bearing lubricant. Studies in this thesis are the first to fully characterise the adsorbed SAPL detected on the surface of retrieved prostheses and the first to verify the presence of SAPL on knee prostheses. Rinsings from the bearing surfaces of both hip and knee prostheses removed from revision operations were analysed using High Performance Liquid Chromatography (HPLC) to determine the presence and profile of SAPL. Several common prosthetic materials along with a novel biomaterial were investigated to determine their tribological interaction with various SAPLs. A pin-on-flat tribometer was used to make comparative friction measurements between the various tribo-pairs. A novel material, Pyrolytic Carbon (PyC) was screened as a potential candidate as a load bearing prosthetic material. Friction measurements were also performed on explanted prostheses. SAPL was detected on all retrieved implant bearing surfaces. As a result of the study eight different species of phosphatidylcholines were identified. The relative concentrations of each species were also determined indicating that the unsaturated species are dominant. Initial tribo tests employed a saturated phosphatidylcholine (SPC) and the subsequent tests adopted the addition of the newly identified major constituents of SAPL, unsaturated phosphatidylcholine (USPC), as the test lubricant. All tribo tests showed a dramatic reduction in friction when synthetic SAPL was used as the lubricant under boundary lubrication conditions. Some tribopairs showed more of an affinity to SAPL than others. PyC performed superior to the other prosthetic materials. Friction measurements with explanted prostheses verified the presence and performance of SAPL. SAPL, in particular phosphatidylcholine, plays an essential role in the lubrication of prosthetic joints. Of particular interest was the ability of SAPLs to reduce friction and ultimately wear of the bearing materials. The identification and knowledge of the lubricating constituents of SF is invaluable for not only the future development of artificial joints but also in developing effective cures for several disease processes where lubrication may play a role. The tribological interaction of the various tribo-pairs and SAPL is extremely favourable in the context of reducing friction at the bearing interface. PyC is highly recommended as a future candidate material for use in load bearing prosthetic joints considering its impressive tribological performance.

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The selection criteria for contractor pre-qualification are characterized by the co-existence of both quantitative and qualitative data. The qualitative data is non-linear, uncertain and imprecise. An ideal decision support system for contractor pre-qualification should have the ability of handling both quantitative and qualitative data, and of mapping the complicated nonlinear relationship of the selection criteria, such that rational and consistent decisions can be made. In this research paper, an artificial neural network model was developed to assist public clients identifying suitable contractors for tendering. The pre-qualification criteria (variables) were identified for the model. One hundred and twelve real pre-qualification cases were collected from civil engineering projects in Hong Kong, and eighty-eight hypothetical pre-qualification cases were also generated according to the “If-then” rules used by professionals in the pre-qualification process. The results of the analysis totally comply with current practice (public developers in Hong Kong). Each pre-qualification case consisted of input ratings for candidate contractors’ attributes and their corresponding pre-qualification decisions. The training of the neural network model was accomplished by using the developed program, in which a conjugate gradient descent algorithm was incorporated for improving the learning performance of the network. Cross-validation was applied to estimate the generalization errors based on the “re-sampling” of training pairs. The case studies show that the artificial neural network model is suitable for mapping the complicated nonlinear relationship between contractors’ attributes and their corresponding pre-qualification (disqualification) decisions. The artificial neural network model can be concluded as an ideal alternative for performing the contractor pre-qualification task.

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Cardiovascular diseases refer to the class of diseases that involve the heart or blood vessels (arteries and veins). Examples of medical devices for treating the cardiovascular diseases include ventricular assist devices (VADs), artificial heart valves and stents. Metallic biomaterials such as titanium and its alloy are commonly used for ventricular assist devices. However, titanium and its alloy show unacceptable thrombosis, which represents a major obstacle to be overcome. Polyurethane (PU) polymer has better blood compatibility and has been used widely in cardiovascular devices. Thus one aim of the project was to coat a PU polymer onto a titanium substrate by increasing the surface roughness, and surface functionality. Since the endothelium of a blood vessel has the most ideal non-thrombogenic properties, it was the target of this research project to grow an endothelial cell layer as a biological coating based on the tissue engineering strategy. However, seeding endothelial cells on the smooth PU coating surfaces is problematic due to the quick loss of seeded cells which do not adhere to the PU surface. Thus it was another aim of the project to create a porous PU top layer on the dense PU pre-layer-coated titanium substrate. The method of preparing the porous PU layer was based on the solvent casting/particulate leaching (SCPL) modified with centrifugation. Without the step of centrifugation, the distribution of the salt particles was not uniform within the polymer solution, and the degree of interconnection between the salt particles was not well controlled. Using the centrifugal treatment, the pore distribution became uniform and the pore interconnectivity was improved even at a high polymer solution concentration (20%) as the maximal salt weight was added in the polymer solution. The titanium surfaces were modified by alkli and heat treatment, followed by functionlisation using hydrogen peroxide. A silane coupling agent was coated before the application of the dense PU pre-layer and the porous PU top layer. The ability of the porous top layer to grow and retain the endothelial cells was also assessed through cell culture techniques. The bonding strengths of the PU coatings to the modified titanium substrates were measured and related to the surface morphologies. The outcome of the project is that it has laid a foundation to achieve the strategy of endothelialisation for the blood compatibility of medical devices. This thesis is divided into seven chapters. Chapter 2 describes the current state of the art in the field of surface modification in cardiovascular devices such as ventricular assist devices (VADs). It also analyses the pros and cons of the existing coatings, particularly in the context of this research. The surface coatings for VADs have evolved from early organic/ inorganic (passive) coatings, to bioactive coatings (e.g. biomolecules), and to cell-based coatings. Based on the commercial applications and the potential of the coatings, the relevant review is focused on the following six types of coatings: (1) titanium nitride (TiN) coatings, (2) diamond-like carbon (DLC) coatings, (3) 2-methacryloyloxyethyl phosphorylcholine (MPC) polymer coatings, (4) heparin coatings, (5) textured surfaces, and (6) endothelial cell lining. Chapter 3 reviews the polymer scaffolds and one relevant fabrication method. In tissue engineering, the function of a polymeric material is to provide a 3-dimensional architecture (scaffold) which is typically used to accommodate transplanted cells and to guide their growth and the regeneration of tissue. The success of these systems is dependent on the design of the tissue engineering scaffolds. Chapter 4 describes chemical surface treatments for titanium and titanium alloys to increase the bond strength to polymer by altering the substrate surface, for example, by increasing surface roughness or changing surface chemistry. The nature of the surface treatment prior to bonding is found to be a major factor controlling the bonding strength. By increasing surface roughness, an increase in surface area occurs, which allows the adhesive to flow in and around the irregularities on the surface to form a mechanical bond. Changing surface chemistry also results in the formation of a chemical bond. Chapter 5 shows that bond strengths between titanium and polyurethane could be significantly improved by surface treating the titanium prior to bonding. Alkaline heat treatment and H2O2 treatment were applied to change the surface roughness and the surface chemistry of titanium. Surface treatment increases the bond strength by altering the substrate surface in a number of ways, including increasing the surface roughness and changing the surface chemistry. Chapter 6 deals with the characterization of the polyurethane scaffolds, which were fabricated using an enhanced solvent casting/particulate (salt) leaching (SCPL) method developed for preparing three-dimensional porous scaffolds for cardiac tissue engineering. The enhanced method involves the combination of a conventional SCPL method and a step of centrifugation, with the centrifugation being employed to improve the pore uniformity and interconnectivity of the scaffolds. It is shown that the enhanced SCPL method and a collagen coating resulted in a spatially uniform distribution of cells throughout the collagen-coated PU scaffolds.In Chapter 7, the enhanced SCPL method is used to form porous features on the polyurethane-coated titanium substrate. The cavities anchored the endothelial cells to remain on the blood contacting surfaces. It is shown that the surface porosities created by the enhanced SCPL may be useful in forming a stable endothelial layer upon the blood contacting surface. Chapter 8 finally summarises the entire work performed on the fabrication and analysis of the polymer-Ti bonding, the enhanced SCPL method and the PU microporous surface on the metallic substrate. It then outlines the possibilities for future work and research in this area.

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One of the main aims in artificial intelligent system is to develop robust and efficient optimisation methods for Multi-Objective (MO) and Multidisciplinary Design (MDO) design problems. The paper investigates two different optimisation techniques for multi-objective design optimisation problems. The first optimisation method is a Non-Dominated Sorting Genetic Algorithm II (NSGA-II). The second method combines the concepts of Nash-equilibrium and Pareto optimality with Multi-Objective Evolutionary Algorithms (MOEAs) which is denoted as Hybrid-Game. Numerical results from the two approaches are compared in terms of the quality of model and computational expense. The benefit of using the distributed hybrid game methodology for multi-objective design problems is demonstrated.

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To date, studies have focused on the acquisition of alphabetic second languages (L2s) in alphabetic first language (L1) users, demonstrating significant transfer effects. The present study examined the process from a reverse perspective, comparing logographic (Mandarin-Chinese) and alphabetic (English) L1 users in the acquisition of an artificial logographic script, in order to determine whether similar language-specific advantageous transfer effects occurred. English monolinguals, English-French bilinguals and Chinese-English bilinguals learned a small set of symbols in an artificial logographic script and were subsequently tested on their ability to process this script in regard to three main perspectives: L2 reading, L2 working memory (WM), and inner processing strategies. In terms of L2 reading, a lexical decision task on the artificial symbols revealed markedly faster response times in the Chinese-English bilinguals, indicating a logographic transfer effect suggestive of a visual processing advantage. A syntactic decision task evaluated the degree to which the new language was mastered beyond the single word level. No L1-specific transfer effects were found for artificial language strings. In order to investigate visual processing of the artificial logographs further, a series of WM experiments were conducted. Artificial logographs were recalled under concurrent auditory and visuo-spatial suppression conditions to disrupt phonological and visual processing, respectively. No L1-specific transfer effects were found, indicating no visual processing advantage of the Chinese-English bilinguals. However, a bilingual processing advantage was found indicative of a superior ability to control executive functions. In terms of L1 WM, the Chinese-English bilinguals outperformed the alphabetic L1 users when processing L1 words, indicating a language experience-specific advantage. Questionnaire data on the cognitive strategies that were deployed during the acquisition and processing of the artificial logographic script revealed that the Chinese-English bilinguals rated their inner speech as lower than the alphabetic L1 users, suggesting that they were transferring their phonological processing skill set to the acquisition and use of an artificial script. Overall, evidence was found to indicate that language learners transfer specific L1 orthographic processing skills to L2 logographic processing. Additionally, evidence was also found indicating that a bilingual history enhances cognitive performance in L2.

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Artificial neural network (ANN) learning methods provide a robust and non-linear approach to approximating the target function for many classification, regression and clustering problems. ANNs have demonstrated good predictive performance in a wide variety of practical problems. However, there are strong arguments as to why ANNs are not sufficient for the general representation of knowledge. The arguments are the poor comprehensibility of the learned ANN, and the inability to represent explanation structures. The overall objective of this thesis is to address these issues by: (1) explanation of the decision process in ANNs in the form of symbolic rules (predicate rules with variables); and (2) provision of explanatory capability by mapping the general conceptual knowledge that is learned by the neural networks into a knowledge base to be used in a rule-based reasoning system. A multi-stage methodology GYAN is developed and evaluated for the task of extracting knowledge from the trained ANNs. The extracted knowledge is represented in the form of restricted first-order logic rules, and subsequently allows user interaction by interfacing with a knowledge based reasoner. The performance of GYAN is demonstrated using a number of real world and artificial data sets. The empirical results demonstrate that: (1) an equivalent symbolic interpretation is derived describing the overall behaviour of the ANN with high accuracy and fidelity, and (2) a concise explanation is given (in terms of rules, facts and predicates activated in a reasoning episode) as to why a particular instance is being classified into a certain category.