253 resultados para VARIABLE DIFFUSION


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This paper assesses the capacity to provide semipermeability of the synthetic layer of surface-active phospholipids created to replace the depleted surface amorphous layer of articular cartilage. The surfaces of articular cartilage specimens in normal, delipidized, and relipidized conditions following incubation in dipalmitoyl-phosphatidylcholine and palmitoyl-oleoyl-phosphatidylcholine components of the joint lipid mixture were characterized nanoscopically with the atomic force microscope and also imaged as deuterium oxide (D2O) diffused transiently through these surfaces in a magnetic resonance imaging enclosure. The MR images were then used to determine the apparent diffusion coefficients in a purpose-built MATLAB®-based algorithm. Our results revealed that all surfaces were permeable to D2O, but that there was a significant difference in the semipermeability of the surfaces under the different conditions, relative to the apparent diffusion coefficients. Based on the results and observations, it can be concluded that the synthetic lipid that is deposited to replace the depleted SAL of articular cartilage is capable of inducing some level of semipermeability.

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Research indicates that empathy, a quality regarded as fundamentally important to nursing practice, is a teachable skill. Because empathic nurse-patient relationships are particularly important in the care of the terminally ill, this has direct relevance to the professional development of palliative care nurses. This article discusses the place of empathy as a criterion variable in the evaluation of a professional development program for palliative care nurses introduced at the Centre for Mental Health Nursing Research at Queensland University of Technology, Brisbane, Australia. A modified version of the Staff-Patient Interaction Response Scale (SPIRS) was used as a pre- and postintervention measure to assess the expressed empathy of the participating nurses. The modifications to SPIR and its coding system to make it suitable for palliative care nursing, and the mechanisms for improving and evaluating the reliability of this instrument will be discussed. The full description of this particular modification of SPIRS for palliative care research is provided as an example of how this instrument could be used in projects for which nurses undertake the difficult task of providing compassionate care to the terminally ill.

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The first objective of this project is to develop new efficient numerical methods and supporting error and convergence analysis for solving fractional partial differential equations to study anomalous diffusion in biological tissue such as the human brain. The second objective is to develop a new efficient fractional differential-based approach for texture enhancement in image processing. The results of the thesis highlight that the fractional order analysis captured important features of nuclear magnetic resonance (NMR) relaxation and can be used to improve the quality of medical imaging.

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Airborne particles have been shown to be associated with a wide range of adverse health effects, which has led to a recent increase in medical research to gain better insight into their health effects. However, accurate evaluation of the exposure-dose-response relationship is highly dependent on the ability to track actual exposure levels of people to airborne particles. This is quite a complex task, particularly in relation to submicrometer and ultrafine particles, which can vary quite significantly in terms of particle surface area and number concentrations. Therefore, suitable monitors that can be worn for measuring personal exposure to these particles are needed. This paper presents an evaluation of the metrological performance of six diffusion charger sensors, NanoTracer (Philips Aerasense) monitors, when measuring particle number and surface area concentrations, as well as particle number distribution mean when compared to reference instruments. Tests in the laboratory (by generating monodisperse and polydisperse aerosols) and in the field (using natural ambient particles) were designed to evaluate the response of these devices under both steady-state and dynamics conditions. Results showed that the NanoTracers performed well when measuring steady state aerosols, however they strongly underestimated actual concentrations during dynamic response testing. The field experiments also showed that, when the majority of the particles were smaller than 20 nm, which occurs during particle formation events in the atmosphere, the NanoTracer underestimated number concentration quite significantly. Even though the NanoTracer can be used for personal monitoring of exposure to ultrafine particles, it also has limitations which need to be considered in order to provide meaningful results.

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This study was undertaken to examine the influence that a set of Professional Development (PD) initiatives had on faculty use of Moodle, a well known Course Management System. The context of the study was a private language university just outside Tokyo, Japan. Specifically, it aimed to identify the way in which the PD initiatives adhered to professional development best practice criteria; how faculty members perceived the PD initiatives; what impact the PD initiatives had on faculty use of Moodle; and other variables that may have influenced faculty in their use of Moodle. The study utilised a mixed methods approach. Participants in the study were 42 teachers who worked at the university in the academic year 2008/9. The online survey consisted of 115 items, factored into 10 constructs. Data was collected through an online survey, semi-structured face-to-face interviews, post-workshop surveys, and a collection of textual artefacts. The quantitative data were analysed in SPSS, using descriptive statistics, Spearman's Rank Order correlation tests and a Kruskal-Wallis means test. The qualitative data was used to develop and expand findings and ideas. The results indicated that the PD initiatives adhered closely to criteria posited in technology-related professional development best practice criteria. Further, results from the online survey, post workshop surveys, and follow up face-to-face interviews indicated that while the PD initiatives that were implemented were positively perceived by faculty, they did not have the anticipated impact on Moodle use among faculty. Further results indicated that other variables, such as perceptions of Moodle, and institutional issues, had a considerable influence on Moodle use. The findings of the study further strengthened the idea that the five variables Everett Rogers lists in his Diffusion of Innovations model, including perceived attributes of an innovation; type of innovation decision; communication channels; nature of the social system; extent of change agents' promotion efforts, most influence the adoption of an innovation. However, the results also indicated that some of the variables in Rogers' DOI seem to have more of an influence than others, particularly the perceived attributes of an innovation variable. In addition, the findings of the study could serve to inform universities that have Course Management Systems (CMS), such as Moodle, about how to utilise them most efficiently and effectively. The findings could also help to inform universities about how to help faculty members acquire the skills necessary to incorporate CMSs into curricula and teaching practice. A limitation of this study was the use of a non-randomised sample, which could appear to have limited the generalisations of the findings to this particular Japanese context.

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The mean action time is the mean of a probability density function that can be interpreted as a critical time, which is a finite estimate of the time taken for the transient solution of a reaction-diffusion equation to effectively reach steady state. For high-variance distributions, the mean action time under-approximates the critical time since it neglects to account for the spread about the mean. We can improve our estimate of the critical time by calculating the higher moments of the probability density function, called the moments of action, which provide additional information regarding the spread about the mean. Existing methods for calculating the nth moment of action require the solution of n nonhomogeneous boundary value problems which can be difficult and tedious to solve exactly. Here we present a simplified approach using Laplace transforms which allows us to calculate the nth moment of action without solving this family of boundary value problems and also without solving for the transient solution of the underlying reaction-diffusion problem. We demonstrate the generality of our method by calculating exact expressions for the moments of action for three problems from the biophysics literature. While the first problem we consider can be solved using existing methods, the second problem, which is readily solved using our approach, is intractable using previous techniques. The third problem illustrates how the Laplace transform approach can be used to study coupled linear reaction-diffusion equations.

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Monte Carlo simulations were used to investigate the relationship between the morphological characteristics and the diffusion tensor (DT) of partially aligned networks of cylindrical fibres. The orientation distributions of the fibres in each network were approximately uniform within a cone of a given semi-angle (θ0). This semi-angle was used to control the degree of alignment of the fibres. The networks studied ranged from perfectly aligned (θ0 = 0) to completely disordered (θ0 = 90°). Our results are qualitatively consistent with previous numerical models in the overall behaviour of the DT. However, we report a non-linear relationship between the fractional anisotropy (FA) of the DT and collagen volume fraction, which is different to the findings from previous work. We discuss our results in the context of diffusion tensor imaging of articular cartilage. We also demonstrate how appropriate diffusion models have the potential to enable quantitative interpretation of the experimentally measured diffusion-tensor FA in terms of collagen fibre alignment distributions.

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We investigate the physical origins of etching observed during Ti diffusion. The relationship between observed etch depth and water vapor content in the annealing environment is quantified. The dynamics of the etching process are also identified. It is discovered that water vapor content is essential for etching and that there is a characteristic delay before etching is observed. From these observations we can conclude that the process is electrochemical in nature with ionic defects diffusing into the Ti strip from the lithium niobate and these defects catalyzing the dissociation of water into reactive ions.

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This study addresses the research question: ‘What are the diffusion determinants for extreme weather-proofing technology in the Australian built environment?’ In order to effectively identify diffusion determinants, a synthesis of literature in both technical and management fields was conducted from a system-wide perspective. Review results where then interpreted through an innovation system framework, drawn from innovation systems literature, in order to map the current state of extreme weather-proofing technology diffusion in the Australian built environment industry. Drivers and obstacles to optimal diffusion are presented. Results show the important role to be played by Australian governments in facilitating improved weather proofing technology diffusion. This applies to governments in their various roles, but particularly as regulators, clients/owners and investors in research & development and education. In the role as regulators, findings suggest Australian governments should be encouraging the application of innovative finance options and positive end-user incentives to promote the uptake of weather proofing technology. Additionally, in their role as clients/owners, diffusion can be improved by adjusting building and infrastructure specifications to encourage designers and constructors to incorporate extreme weather proofing technology in new and redeveloped built assets. Finally, results suggest greater investment is required in research and development and improved knowledge sharing across the construction supply chain to further mitigate risks associated with greater incidences of extreme weather events.

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In order to establish the influence of the drying air characteristics on the drying performance and fluidization quality of bovine intestine for pet food, several drying tests have been carried out in a laboratory scale heat pump assisted fluid bed dryer. Bovine intestine samples were heat pump fluidized bed dried at atmospheric pressure and at temperatures below and above the materials freezing points, equipped with a continuous monitoring system. The investigation of the drying characteristics have been conducted in the temperature range −10 to 25 ◦C and the airflow in the range 1.5–2.5 m/s. Some experiments were conducted as single temperature drying experiments and others as two stage drying experiments employing two temperatures. An Arrhenius-type equation was used to interpret the influence of the drying air temperature on the effective diffusivity, calculated with the method of slopes in terms of energy activation, and this was found to be sensitive to the temperature. The effective diffusion coefficient of moisture transfer was determined by the Fickian method using uni-dimensional moisture movement in both moisture, removal by evaporation and combined sublimation and evaporation. Correlations expressing the effective moisture diffusivity and drying temperature are reported. Bovine particles were characterized according to the Geldart classification and the minimum fluidization velocity was calculated using the Ergun Equation and generalized equation for all drying conditions at the beginning and end of the trials. Walli’s model was used to categorize stability of the fluidization at the beginning and end of the dryingv for each trial. The determined Walli’s values were positive at the beginning and end of all trials indicating stable fluidization at the beginning and end for each drying condition.

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We present a mini-review of the development and contemporary applications of diffusion-sensitive nuclear magnetic resonance (NMR) techniques in biomedical sciences. Molecular diffusion is a fundamental physical phenomenon present in all biological systems. Due to the connection between experimentally measured diffusion metrics and the microscopic environment sensed by the diffusing molecules, diffusion measurements can be used for characterisation of molecular size, molecular binding and association, and the morphology of biological tissues. The emergence of magnetic resonance was instrumental to the development of biomedical applications of diffusion. We discuss the fundamental physical principles of diffusion NMR spectroscopy and diffusion MR imaging. The emphasis is placed on conceptual understanding, historical evolution and practical applications rather than complex technical details. Mathematical description of diffusion is presented to the extent that it is required for the basic understanding of the concepts. We present a wide range of spectroscopic and imaging applications of diffusion magnetic resonance, including colloidal drug delivery vehicles; protein association; characterisation of cell morphology; neural fibre tractography; cardiac imaging; and the imaging of load-bearing connective tissues. This paper is intended as an accessible introduction into the exciting and growing field of diffusion magnetic resonance.

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The movement of molecules inside living cells is a fundamental feature of biological processes. The ability to both observe and analyse the details of molecular diffusion in vivo at the single-molecule and single-cell level can add significant insight into understanding molecular architectures of diffus- ing molecules and the nanoscale environment in which the molecules diffuse. The tool of choice for monitoring dynamic molecular localization in live cells is fluorescence microscopy, especially so combining total internal reflection fluorescence with the use of fluorescent protein (FP) reporters in offering exceptional imaging contrast for dynamic processes in the cell mem- brane under relatively physiological conditions compared with competing single-molecule techniques. There exist several different complex modes of diffusion, and discriminating these from each other is challenging at the mol- ecular level owing to underlying stochastic behaviour. Analysis is traditionally performed using mean square displacements of tracked particles; however, this generally requires more data points than is typical for single FP tracks owing to photophysical instability. Presented here is a novel approach allowing robust Bayesian ranking of diffusion processes to dis-criminate multiple complex modes probabilistically. It is a computational approach that biologists can use to understand single-molecule features in live cells.

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In the field of rolling element bearing diagnostics envelope analysis, and in particular the squared envelope spectrum, have gained in the last years a leading role among the different digital signal processing techniques. The original constraint of constant operating speed has been relaxed thanks to the combination of this technique with the computed order tracking, able to resample signals at constant angular increments. In this way, the field of application of squared envelope spectrum has been extended to cases in which small speed fluctuations occur, maintaining the effectiveness and efficiency that characterize this successful technique. However, the constraint on speed has to be removed completely, making envelope analysis suitable also for speed and load transients, to implement an algorithm valid for all the industrial application. In fact, in many applications, the coincidence of high bearing loads, and therefore high diagnostic capability, with acceleration-deceleration phases represents a further incentive in this direction. This paper is aimed at providing and testing a procedure for the application of envelope analysis to speed transients. The effect of load variation on the proposed technique will be also qualitatively addressed.

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Diagnostics of rolling element bearings involves a combination of different techniques of signal enhancing and analysis. The most common procedure presents a first step of order tracking and synchronous averaging, able to remove the undesired components, synchronous with the shaft harmonics, from the signal, and a final step of envelope analysis to obtain the squared envelope spectrum. This indicator has been studied thoroughly, and statistically based criteria have been obtained, in order to identify damaged bearings. The statistical thresholds are valid only if all the deterministic components in the signal have been removed. Unfortunately, in various industrial applications, characterized by heterogeneous vibration sources, the first step of synchronous averaging is not sufficient to eliminate completely the deterministic components and an additional step of pre-whitening is needed before the envelope analysis. Different techniques have been proposed in the past with this aim: The most widely spread are linear prediction filters and spectral kurtosis. Recently, a new technique for pre-whitening has been proposed, based on cepstral analysis: the so-called cepstrum pre-whitening. Owing to its low computational requirements and its simplicity, it seems a good candidate to perform the intermediate pre-whitening step in an automatic damage recognition algorithm. In this paper, the effectiveness of the new technique will be tested on the data measured on a full-scale industrial bearing test-rig, able to reproduce the harsh conditions of operation. A benchmark comparison with the traditional pre-whitening techniques will be made, as a final step for the verification of the potentiality of the cepstrum pre-whitening.