977 resultados para NMR-diffusion
Resumo:
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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Spectroscopic studies of complex clinical fluids have led to the application of a more holistic approach to their chemical analysis becoming more popular and widely employed. The efficient and effective interpretation of multidimensional spectroscopic data relies on many chemometric techniques and one such group of tools is represented by so-called correlation analysis methods. Typical of these techniques are two-dimensional correlation analysis and statistical total correlation spectroscopy (STOCSY). Whilst the former has largely been applied to optical spectroscopic analysis, STOCSY was developed and has been applied almost exclusively to NMR metabonomic studies. Using a 1H NMR study of human blood plasma, from subjects recovering from exhaustive exercise trials, the basic concepts and applications of these techniques are examined. Typical information from their application to NMR-based metabonomics is presented and their value in aiding interpretation of NMR data obtained from biological systems is illustrated. Major energy metabolites are identified in the NMR spectra and the dynamics of their appearance and removal from plasma during exercise recovery are illustrated and discussed. The complementary nature of two-dimensional correlation analysis and statistical total correlation spectroscopy are highlighted.
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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.
Resumo:
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.
Resumo:
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.
Resumo:
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.
Resumo:
The numerical solution in one space dimension of advection--reaction--diffusion systems with nonlinear source terms may invoke a high computational cost when the presently available methods are used. Numerous examples of finite volume schemes with high order spatial discretisations together with various techniques for the approximation of the advection term can be found in the literature. Almost all such techniques result in a nonlinear system of equations as a consequence of the finite volume discretisation especially when there are nonlinear source terms in the associated partial differential equation models. This work introduces a new technique that avoids having such nonlinear systems of equations generated by the spatial discretisation process when nonlinear source terms in the model equations can be expanded in positive powers of the dependent function of interest. The basis of this method is a new linearisation technique for the temporal integration of the nonlinear source terms as a supplementation of a more typical finite volume method. The resulting linear system of equations is shown to be both accurate and significantly faster than methods that necessitate the use of solvers for nonlinear system of equations.
Resumo:
This article describes the first steps toward comprehensive characterization of molecular transport within scaffolds for tissue engineering. The scaffolds were fabricated using a novel melt electrospinning technique capable of constructing 3D lattices of layered polymer fibers with well - defined internal microarchitectures. The general morphology and structure order was then determined using T 2 - weighted magnetic resonance imaging and X - ray microcomputed tomography. Diffusion tensor microimaging was used to measure the time - dependent diffusivity and diffusion anisotropy within the scaffolds. The measured diffusion tensors were anisotropic and consistent with the cross - hatched geometry of the scaffolds: diffusion was least restricted in the direction perpendicular to the fiber layers. The results demonstrate that the cross - hatched scaffold structure preferentially promotes molecular transport vertically through the layers ( z - axis), with more restricted diffusion in the directions of the fiber layers ( x – y plane). Diffusivity in the x – y plane was observed to be invariant to the fiber thickness. The characteristic pore size of the fiber scaffolds can be probed by sampling the diffusion tensor at multiple diffusion times. Prospective application of diffusion tensor imaging for the real - time monitoring of tissue maturation and nutrient transport pathways within tissue engineering scaffolds is discussed.
Resumo:
Growth kinetics of carbon nanofibers in a hydrocarbon plasma is studied. In addition to gas-phase and surface processes common to chemical vapor deposition, the model includes (unique to plasma-exposed catalyst surfaces) ion-induced dissociation of hydrocarbons, interaction of adsorbed species with incoming hydrogen atoms, and dissociation of hydrocarbon ions. It is shown that at low, nanodevice-friendly process temperatures the nanofibers grow via surface diffusion of carbon adatoms produced on the catalyst particle via ion-induced dissociation of a hydrocarbon precursor. These results explain a lower activation energy of nanofiber growth in a plasma and can be used for the synthesis of other nanoassemblies. © 2007 American Institute of Physics.
Resumo:
A model for electronegative plasmas containing charged dust or colloidal grains was used. Numerical solutions based on the model demonstrate how a low-pressure diffusion equilibrium of the complex electronegative plasma system is dynamically sustained through plasma particle sources.
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PURPOSE To compare diffusion-weighted functional magnetic resonance imaging (DfMRI), a novel alternative to the blood oxygenation level-dependent (BOLD) contrast, in a functional MRI experiment. MATERIALS AND METHODS Nine participants viewed contrast reversing (7.5 Hz) black-and-white checkerboard stimuli using block and event-related paradigms. DfMRI (b = 1800 mm/s2 ) and BOLD sequences were acquired. Four parameters describing the observed signal were assessed: percent signal change, spatial extent of the activation, the Euclidean distance between peak voxel locations, and the time-to-peak of the best fitting impulse response for different paradigms and sequences. RESULTS The BOLD conditions showed a higher percent signal change relative to DfMRI; however, event-related DfMRI showed the strongest group activation (t = 21.23, P < 0.0005). Activation was more diffuse and spatially closer to the BOLD response for DfMRI when the block design was used. DfMRIevent showed the shortest TTP (4.4 +/- 0.88 sec). CONCLUSION The hemodynamic contribution to DfMRI may increase with the use of block designs.
Resumo:
Articular cartilage (AC), an avascular connective tissue lining articulating surfaces of the long bones, comprises extracellular biopolymers. In functionally compromised states such as osteoarthritis, thinned or lost AC causes reduced mobility and increased health-care costs. Understanding of the characteristics responsible for the load bearing efficiency of AC and the factors leading to its degradation are incomplete. DTI shows the structural alignment of collagen in AC [1] and T2 relaxation measurements suggest that the average director of reorientational motion of water molecules depends on the degree of alignment of collagen in AC [2]. Information on the nature of the chemical interactions involved in functional AC is lacking. The need for AC structural integrity makes solid state NMR an ideal tool to study this tissue. We examined the contribution of water in different functional ‘compartments’ using 1H-MAS, 13C-MAS and 13C-CPMAS NMR of bovine patellar cartilage incubated in D2O. 1H-MAS spectra signal intensity was reduced due to H/D exchange without a measureable redistribution of relative signal intensity. Chemical shift anisotropy was estimated by lineshape analysis of multiple peaks in the 1H-MAS spinning sidebands. These asymmetrical sidebands suggested the presence of multiple water species in AC. Therefore, water was added in small aliquots to D2O saturated AC and the influence of H2O and D2O on organic components was studied with 13C-MAS-NMR and 13C-CPMAS-NMR. Signal intensity in 13C-MAS spectra showed no change in relative signal intensity throughout the spectrum. In 13C-CPMAS spectra, displacement of water by D2O resulted in a loss of signal in the aliphatic region due to a reduction in proton availability for cross-polarization. These results complement dehydration studies of cartilage using osmotic manipulation [3] and demonstrate components of cartilage that are in contact with mobile water.
Resumo:
Articular cartilage (AC), an avascular connective tissue lining articulating surfaces of the long bones, comprises extracellular biopolymers. In functionally compromised states such as osteoarthritis, thinned or lost AC causes reduced mobility and increased health-care costs. Understanding of the characteristics responsible for the load bearing efficiency of AC and the factors leading to its degradation are incomplete. DTI shows the structural alignment of collagen in AC [1] and T2 relaxation measurements suggest that the average director of reorientational motion of water molecules depends on the degree of alignment of collagen in AC [2]. Information on the nature of the chemical interactions involved in functional AC is lacking. The need for AC structural integrity makes solid state NMR an ideal tool to study this tissue. We examined the contribution of water in different functional ‘compartments’ using 1H-MAS, 13C-MAS and 13C-CPMAS NMR of bovine patellar cartilage incubated in D2O. 1H-MAS spectra signal intensity was reduced due to H/D exchange without a measureable redistribution of relative signal intensity. Chemical shift anisotropy was estimated by lineshape analysis of multiple peaks in the 1H-MAS spinning sidebands. These asymmetrical sidebands suggested the presence of multiple water species in AC. Therefore, water was added in small aliquots to D2O saturated AC and the influence of H2O and D2O on organic components was studied with 13C-MAS-NMR and 13C-CPMAS-NMR. Signal intensity in 13C-MAS spectra showed no change in relative signal intensity throughout the spectrum. In 13C-CPMAS spectra, displacement of water by D2O resulted in a loss of signal in the aliphatic region due to a reduction in proton availability for cross-polarization. These results complement dehydration studies of cartilage using osmotic manipulation [3] and demonstrate components of cartilage that are in contact with mobile water.
Resumo:
A discrete agent-based model on a periodic lattice of arbitrary dimension is considered. Agents move to nearest-neighbor sites by a motility mechanism accounting for general interactions, which may include volume exclusion. The partial differential equation describing the average occupancy of the agent population is derived systematically. A diffusion equation arises for all types of interactions and is nonlinear except for the simplest interactions. In addition, multiple species of interacting subpopulations give rise to an advection-diffusion equation for each subpopulation. This work extends and generalizes previous specific results, providing a construction method for determining the transport coefficients in terms of a single conditional transition probability, which depends on the occupancy of sites in an influence region. These coefficients characterize the diffusion of agents in a crowded environment in biological and physical processes.