949 resultados para Optimal vaccine distribution
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The formation of an internal barrier to the diffusion of small molecules in the lens during middle age is hypothesized to be a key event in the development of age-related nuclear (ARN) cataract. Changes in membrane lipids with age may be responsible. In this study, we investigated the effect of age on the distribution of sphingomyelins, the most abundant lens phospholipids. Human lens sections were initially analyzed by MALDI mass spectrometry imaging. A distinct annular distribution of the dihydrosphingomyelin, DHSM (d18:0/16:0), in the barrier region was observed in 64- and 70-year-old lenses but not in a 23-year-old lens. An increase in the dihydroceramide, DHCer (d18:0/16:0), in the lens nucleus was also observed in the older lenses. These findings were supported by ESI mass spectrometry analysis of lipid extracts from lenses dissected into outer, barrier, and nuclear regions. A subsequent analysis of 18 lenses ages 20-72 years revealed that sphingomyelin levels increased with age in the barrier region until reaching a plateau at approximately 40 years of age. Such changes in lipid composition will have a significant impact on the physical properties of the fiber cell membranes and may be associated with the formation of a barrier.-Deeley, J. M., J. A. Hankin, M. G. Friedrich, R. C. Murphy, R. J. W. Truscott, T. W. Mitchell, and S. J. Blanksby. Sphingolipid distribution changes with age in the human lens. J. Lipid Res. 2010. 51: 2753-2760.
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Background Few cancers pose greater challenges than head and neck (H&N) cancer. Residual effects following treatment include body image changes, pain, fatigue and difficulties with appetite, swallowing and speech. Depression is a common comorbidity. There is limited evidence about ways to assist patients to achieve optimal adjustment after completion of treatment. In this study, we aim to examine the effectiveness and feasibility of a model of survivorship care to improve the quality of life of patients who have completed treatment for H&N cancer. Methods This is a preliminary study in which 120 patients will be recruited. A prospective randomised controlled trial of the H&N Cancer Survivor Self-management Care Plan (HNCP) involving pre- and post-intervention assessments will be used. Consecutive patients who have completed a defined treatment protocol for H&N cancer will be recruited from two large cancer services and randomly allocated to one of three study arms: (1) usual care, (2) information in the form of a written resource or (3) the HNCP delivered by an oncology nurse who has participated in manual-based training and skill development in patient self-management support. The trained nurses will meet patients in a face-to-face interview lasting up to 60 minutes to develop an individualised HNCP, based on principles of chronic disease self-management. Participants will be assessed at baseline, 3 and 6 months. The primary outcome measure is quality of life. The secondary outcome measures include mood, self-efficacy and health-care utilisation. The feasibility of implementing this intervention in routine clinical care will be assessed through semistructured interviews with participating nurses, managers and administrators. Interviews with patients who received the HNCP will explore their perceptions of the HNCP, including factors that assisted them in achieving behavioural change. Discussion In this study, we aim to improve the quality of life of a patient population with unique needs by means of a tailored self-management care plan developed upon completion of treatment. Delivery of the intervention by trained oncology nurses is likely to be acceptable to patients and, if successful, will be a model of care that can be implemented for diverse patient populations.
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This project was an innovative approach in developing smart coordination of available energy resources to improve the integration level of PV in distribution network. Voltage and loading issues are considered as the main concerns for future electricity grid which need to be avoided using such resources. A distributed control structure was proposed for the resources in distribution network to avoid noted power quality issues.
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The cotton strip assay (CSA) is an established technique for measuring soil microbial activity. The technique involves burying cotton strips and measuring their tensile strength after a certain time. This gives a measure of the rotting rate, R, of the cotton strips. R is then a measure of soil microbial activity. This paper examines properties of the technique and indicates how the assay can be optimised. Humidity conditioning of the cotton strips before measuring their tensile strength reduced the within and between day variance and enabled the distribution of the tensile strength measurements to approximate normality. The test data came from a three-way factorial experiment (two soils, two temperatures, three moisture levels). The cotton strips were buried in the soil for intervals of time ranging up to 6 weeks. This enabled the rate of loss of cotton tensile strength with time to be studied under a range of conditions. An inverse cubic model accounted for greater than 90% of the total variation within each treatment combination. This offers support for summarising the decomposition process by a single parameter R. The approximate variance of the decomposition rate was estimated from a function incorporating the variance of tensile strength and the differential of the function for the rate of decomposition, R, with respect to tensile strength. This variance function has a minimum when the measured strength is approximately 2/3 that of the original strength. The estimates of R are almost unbiased and relatively robust against the cotton strips being left in the soil for more or less than the optimal time. We conclude that the rotting rate X should be measured using the inverse cubic equation, and that the cotton strips should be left in the soil until their strength has been reduced to about 2/3.
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Background Sexually-transmitted pathogens often have severe reproductive health implications if treatment is delayed or absent, especially in females. The complex processes of disease progression, namely replication and ascension of the infection through the genital tract, span both extracellular and intracellular physiological scales, and in females can vary over the distinct phases of the menstrual cycle. The complexity of these processes, coupled with the common impossibility of obtaining comprehensive and sequential clinical data from individual human patients, makes mathematical and computational modelling valuable tools in developing our understanding of the infection, with a view to identifying new interventions. While many within-host models of sexually-transmitted infections (STIs) are available in existing literature, these models are difficult to deploy in clinical/experimental settings since simulations often require complex computational approaches. Results We present STI-GMaS (Sexually-Transmitted Infections – Graphical Modelling and Simulation), an environment for simulation of STI models, with a view to stimulating the uptake of these models within the laboratory or clinic. The software currently focuses upon the representative case-study of Chlamydia trachomatis, the most common sexually-transmitted bacterial pathogen of humans. Here, we demonstrate the use of a hybrid PDE–cellular automata model for simulation of a hypothetical Chlamydia vaccination, demonstrating the effect of a vaccine-induced antibody in preventing the infection from ascending to above the cervix. This example illustrates the ease with which existing models can be adapted to describe new studies, and its careful parameterisation within STI-GMaS facilitates future tuning to experimental data as they arise. Conclusions STI-GMaS represents the first software designed explicitly for in-silico simulation of STI models by non-theoreticians, thus presenting a novel route to bridging the gap between computational and clinical/experimental disciplines. With the propensity for model reuse and extension, there is much scope within STI-GMaS to allow clinical and experimental studies to inform model inputs and drive future model development. Many of the modelling paradigms and software design principles deployed to date transfer readily to other STIs, both bacterial and viral; forthcoming releases of STI-GMaS will extend the software to incorporate a more diverse range of infections.
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This thesis investigates the impacts of variable speed limit on motorway speed variation and headway distribution. Initiative techniques of traffic flow categorisation study contribute in analysing the effects of variable speed limit on various traffic states. The project focuses on the speed harmonisation impacts within and across lanes as well as the uniformity of headway spread in the application of variable speed limit.
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Uniform DNA distribution in tumors is a prerequisite step for high transfection efficiency in solid tumors. To improve the transfection efficiency of electrically assisted gene delivery to solid tumors in vivo, we explored how tumor histological properties affected transfection efficiency. In four different tumor types (B16F1, EAT, SA-1 and LPB), proteoglycan and collagen content was morphometrically analyzed, and cell size and cell density were determined in paraffin-embedded tumor sections under a transmission microscope. To demonstrate the influence of the histological properties of solid tumors on electrically assisted gene delivery, the correlation between histological properties and transfection efficiency with regard to the time interval between DNA injection and electroporation was determined. Our data demonstrate that soft tumors with larger spherical cells, low proteoglycan and collagen content, and low cell density are more effectively transfected (B16F1 and EAT) than rigid tumors with high proteoglycan and collagen content, small spindle-shaped cells and high cell density (LPB and SA-1). Furthermore, an optimal time interval for increased transfection exists only in soft tumors, this being in the range of 5-15 min. Therefore, knowledge about the histology of tumors is important in planning electrogene therapy with respect to the time interval between DNA injection and electroporation.
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The effect of an ordered array of nanocones on a conducting substrate immersed in the plasma on the transport of the plasma ions is investigated. The real conical shape of the cones is rigorously incorporated into the model. The movement of 10^5 CH3+ ions in the plasma sheath modified by the nanocone array is simulated. The ions are driven by the electric fields produced by the sheath and the nanostructures. The surface charge density and the total charge on the nanotips with different aspect ratios are computed. The ion transport simulation provides important characteristics of the displacement and velocity of the ions. The relative ion distribution along the lateral surfaces of the carbon nanotips is computed as well. It is shown that a rigorous account of the realistic nanostructure shape leads to very different distribution of the ion fluxes on the nanostructured surfaces compared to the previously reported works. The ion flux distribution is a critical factor in the nucleation process on the substrate and determines the nanostructure growth patterns.
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The effect of a magnetic field of two magnetic coils on the ion current density distribution in the setup for low-temperature plasma deposition is investigated. The substrate of 400 mm diameter is placed at a distance of 325 mm from the plasma duct exit, with the two magnetic coils mounted symmetrically under the substrate at a distance of 140 mm relative to the substrate centre. A planar probe is used to measure the ion current density distribution along the plasma flux cross-sections at distances of 150, 230, and 325 mm from the plasma duct exit. It is shown that the magnetic field strongly affects the ion current density distribution. Transparent plastic films are used to investigate qualitatively the ion density distribution profiles and the effect of the magnetic field. A theoretical model is developed to describe the interaction of the ion fluxes with the negative space charge regions associated with the magnetic trapping of the plasmaelectrons. Theoretical results are compared with the experimental measurements, and a reasonable agreement is demonstrated.
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Multiscale, multiphase numerical modeling is used to explain the mechanisms of effective control of chirality distributions of single-walled carbon nanotubes in direct plasma growth and suggest effective approaches to further improvement. The model includes an unprecedented combination of the plasma sheath, ion/radical transport, species creation/loss, plasma–surface interaction, heat transfer, surface/bulk diffusion, graphene layer nucleation, and bending/lift-off modules. It is shown that the constructive interplay between the plasma and the Gibbs–Thomson effect can lead to the effective nucleation and lift-off of small graphene layers on small metal catalyst nanoparticles. As a result, much thinner nanotubes with narrower chirality distributions can nucleate at much lower process temperatures and pressures compared to thermal CVD. This approach is validated by a host of experimental results, substantially reduces the amounts of energy and atomic matter required for the nanotube growth, and can be extended to other nanoscale structures and materials systems, thereby nearing the ultimate goal of energy- and matter-efficient nanotechnology.
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Large-scale (∼109 atoms) numerical simulations reveal that plasma-controlled dynamic delivery and redistribution of carbon atoms between the substrate and nanotube surfaces enable the growth of ultralong single walled carbon nanotubes (SWCNTs) and explain the common experimental observation of slower growth at advanced stages. It is shown that the plasma-based processes feature up to two orders of magnitude higher growth rates than equivalent neutral-gas systems and are better suited for the SWCNT synthesis at low nanodevice friendly temperatures. © 2008 American Institute of Physics.
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Using Monte Carlo simulation technique, we have calculated the distribution of ion current extracted from low-temperature plasmas and deposited onto the substrate covered with a nanotube array. We have shown that a free-standing carbon nanotube is enclosed in a circular bead of the ion current, whereas in square and hexagonal nanotube patterns, the ion current is mainly concentrated along the lines connecting the nearest nanotubes. In a very dense array (with the distance between nanotubes/nanotube-height ratio less than 0.05), the ions do not penetrate to the substrate surface and deposit on side surfaces of the nanotubes.
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The quick detection of an abrupt unknown change in the conditional distribution of a dependent stochastic process has numerous applications. In this paper, we pose a minimax robust quickest change detection problem for cases where there is uncertainty about the post-change conditional distribution. Our minimax robust formulation is based on the popular Lorden criteria of optimal quickest change detection. Under a condition on the set of possible post-change distributions, we show that the widely known cumulative sum (CUSUM) rule is asymptotically minimax robust under our Lorden minimax robust formulation as a false alarm constraint becomes more strict. We also establish general asymptotic bounds on the detection delay of misspecified CUSUM rules (i.e. CUSUM rules that are designed with post- change distributions that differ from those of the observed sequence). We exploit these bounds to compare the delay performance of asymptotically minimax robust, asymptotically optimal, and other misspecified CUSUM rules. In simulation examples, we illustrate that asymptotically minimax robust CUSUM rules can provide better detection delay performance at greatly reduced computation effort compared to competing generalised likelihood ratio procedures.
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A global, or averaged, model for complex low-pressure argon discharge plasmas containing dust grains is presented. The model consists of particle and power balance equations taking into account power loss on the dust grains and the discharge wall. The electron energy distribution is determined by a Boltzmann equation. The effects of the dust and the external conditions, such as the input power and neutral gas pressure, on the electron energy distribution, the electron temperature, the electron and ion number densities, and the dust charge are investigated. It is found that the dust subsystem can strongly affect the stationary state of the discharge by dynamically modifying the electron energy distribution, the electron temperature, the creation and loss of the plasma particles, as well as the power deposition. In particular, the power loss to the dust grains can take up a significant portion of the input power, often even exceeding the loss to the wall.
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Angular distribution of microscopic ion fluxes around nanotubes arranged into a dense ordered pattern on the surface of the substrate is studied by means of multiscale numerical simulation. The Monte Carlo technique was used to show that the ion current density is distributed nonuniformly around the carbon nanotubes arranged into a dense rectangular array. The nonuniformity factor of the ion current flux reaches 7 in dense (5× 1018 m-3) plasmas for a nanotube radius of 25 nm, and tends to 1 at plasma densities below 1× 1017 m-3. The results obtained suggest that the local density of carbon adatoms on the nanotube side surface, at areas facing the adjacent nanotubes of the pattern, can be high enough to lead to the additional wall formation and thus cause the single- to multiwall structural transition, and other as yet unexplained nanoscience phenomena.