617 resultados para stochastic growth
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In this paper, we introduce the Stochastic Adams-Bashforth (SAB) and Stochastic Adams-Moulton (SAM) methods as an extension of the tau-leaping framework to past information. Using the theta-trapezoidal tau-leap method of weak order two as a starting procedure, we show that the k-step SAB method with k >= 3 is order three in the mean and correlation, while a predictor-corrector implementation of the SAM method is weak order three in the mean but only order one in the correlation. These convergence results have been derived analytically for linear problems and successfully tested numerically for both linear and non-linear systems. A series of additional examples have been implemented in order to demonstrate the efficacy of this approach.
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The rapid increase in migration into host countries and the growth of immigrant-owned business enterprises has revitalized research on ethnic business. Does micro (individual)-level social capital, or meso (group)-level location within the ethnic enclave lead to immigrant business growth? Or do you need both? We analyze quantitative data collected from 110 Chinese restaurants in Australia, a major host country. At the micro level we find that coethnic (same ethnic group) networks are critical to the growth of an immigrant entrepreneur's business, particularly in the early years. But non-coethnic (different ethnic group) social capital only has a positive impact on business growth for immigrant businesses outside the ethnic enclave. Our findings are relevant, not only to host-country policymakers, but also for future immigrant business owners and ethnic community leaders trying to better understand how to promote healthy communities and sustainable economic growth.
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Stochastic (or random) processes are inherent to numerous fields of human endeavour including engineering, science, and business and finance. This thesis presents multiple novel methods for quickly detecting and estimating uncertainties in several important classes of stochastic processes. The significance of these novel methods is demonstrated by employing them to detect aircraft manoeuvres in video signals in the important application of autonomous mid-air collision avoidance.
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Background Biochemical systems with relatively low numbers of components must be simulated stochastically in order to capture their inherent noise. Although there has recently been considerable work on discrete stochastic solvers, there is still a need for numerical methods that are both fast and accurate. The Bulirsch-Stoer method is an established method for solving ordinary differential equations that possesses both of these qualities. Results In this paper, we present the Stochastic Bulirsch-Stoer method, a new numerical method for simulating discrete chemical reaction systems, inspired by its deterministic counterpart. It is able to achieve an excellent efficiency due to the fact that it is based on an approach with high deterministic order, allowing for larger stepsizes and leading to fast simulations. We compare it to the Euler τ-leap, as well as two more recent τ-leap methods, on a number of example problems, and find that as well as being very accurate, our method is the most robust, in terms of efficiency, of all the methods considered in this paper. The problems it is most suited for are those with increased populations that would be too slow to simulate using Gillespie’s stochastic simulation algorithm. For such problems, it is likely to achieve higher weak order in the moments. Conclusions The Stochastic Bulirsch-Stoer method is a novel stochastic solver that can be used for fast and accurate simulations. Crucially, compared to other similar methods, it better retains its high accuracy when the timesteps are increased. Thus the Stochastic Bulirsch-Stoer method is both computationally efficient and robust. These are key properties for any stochastic numerical method, as they must typically run many thousands of simulations.
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Since we still know very little about stem cells in their natural environment, it is useful to explore their dynamics through modelling and simulation, as well as experimentally. Most models of stem cell systems are based on deterministic differential equations that ignore the natural heterogeneity of stem cell populations. This is not appropriate at the level of individual cells and niches, when randomness is more likely to affect dynamics. In this paper, we introduce a fast stochastic method for simulating a metapopulation of stem cell niche lineages, that is, many sub-populations that together form a heterogeneous metapopulation, over time. By selecting the common limiting timestep, our method ensures that the entire metapopulation is simulated synchronously. This is important, as it allows us to introduce interactions between separate niche lineages, which would otherwise be impossible. We expand our method to enable the coupling of many lineages into niche groups, where differentiated cells are pooled within each niche group. Using this method, we explore the dynamics of the haematopoietic system from a demand control system perspective. We find that coupling together niche lineages allows the organism to regulate blood cell numbers as closely as possible to the homeostatic optimum. Furthermore, coupled lineages respond better than uncoupled ones to random perturbations, here the loss of some myeloid cells. This could imply that it is advantageous for an organism to connect together its niche lineages into groups. Our results suggest that a potential fruitful empirical direction will be to understand how stem cell descendants communicate with the niche and how cancer may arise as a result of a failure of such communication.
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The uniform growth of copper oxide nanowires on the top of copper plate has been investigated during the exposure to radiofrequency plasma discharge in respect to plasma properties and its localization. The copper samples of 10 mm radius and 1 mm in thickness were exposed to argon-oxygen plasma created at discharge power of 150 W. After 10 min, almost uniform growth of nanowires was achieved over large surface. There were significant distortions in nanowire length and shape near the edges. Based on the experimental results, we developed a theoretical model, which took into account a balance in heat released at the flow of the current to the nanowire and rejected from the nanowire. This model established a dependence of the maximal length of the nanowire at dependence on the plasma parameters, where the limiting factor for nanowire growth and distortions in distribution are ballistic effects of ions and their local fluxes. In contrast, the plasma heating by potential interactions of species has very little influence on the length and smaller deviations in flux are allowed for uniformity of growth
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The “third-generation” 3D graphene structures, T-junction graphene micro-wells (T-GMWs) are produced on cheap polycrystalline Cu foils in a single-step, low-temperature (270 °C), energy-efficient, and environment-friendly dry plasma-enabled process. T-GMWs comprise vertical graphene (VG) petal-like sheets that seemlessly integrate with each other and the underlying horizontal graphene sheets by forming T-junctions. The microwells have the pico-to-femto-liter storage capacity and precipitate compartmentalized PBS crystals. The T-GMW films are transferred from the Cu substrates, without damage to the both, in de-ionized or tap water, at room temperature, and without commonly used sacrificial materials or hazardous chemicals. The Cu substrates are then re-used to produce similar-quality T-GMWs after a simple plasma conditioning. The isolated T-GMW films are transferred to diverse substrates and devices and show remarkable recovery of their electrical, optical, and hazardous NO2 gas sensing properties upon repeated bending (down to 1 mm radius) and release of flexible trasparent display plastic substrates. The plasma-enabled mechanism of T-GMW isolation in water is proposed and supported by the Cu plasma surface modification analysis. Our GMWs are suitable for various optoelectronic, sesning, energy, and biomedical applications while the growth approach is potentially scalable for future pilot-scale industrial production.
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In order to simulate stiff biochemical reaction systems, an explicit exponential Euler scheme is derived for multidimensional, non-commutative stochastic differential equations with a semilinear drift term. The scheme is of strong order one half and A-stable in mean square. The combination with this and the projection method shows good performance in numerical experiments dealing with an alternative formulation of the chemical Langevin equation for a human ether a-go-go related gene ion channel mode
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We present an algorithm for multiarmed bandits that achieves almost optimal performance in both stochastic and adversarial regimes without prior knowledge about the nature of the environment. Our algorithm is based on augmentation of the EXP3 algorithm with a new control lever in the form of exploration parameters that are tailored individually for each arm. The algorithm simultaneously applies the “old” control lever, the learning rate, to control the regret in the adversarial regime and the new control lever to detect and exploit gaps between the arm losses. This secures problem-dependent “logarithmic” regret when gaps are present without compromising on the worst-case performance guarantee in the adversarial regime. We show that the algorithm can exploit both the usual expected gaps between the arm losses in the stochastic regime and deterministic gaps between the arm losses in the adversarial regime. The algorithm retains “logarithmic” regret guarantee in the stochastic regime even when some observations are contaminated by an adversary, as long as on average the contamination does not reduce the gap by more than a half. Our results for the stochastic regime are supported by experimental validation.
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BACKGROUND Many koala populations around Australia are in serious decline, with a substantial component of this decline in some Southeast Queensland populations attributed to the impact of Chlamydia. A Chlamydia vaccine for koalas is in development and has shown promise in early trials. This study contributes to implementation preparedness by simulating vaccination strategies designed to reverse population decline and by identifying which age and sex category it would be most effective to target. METHODS We used field data to inform the development and parameterisation of an individual-based stochastic simulation model of a koala population endemic with Chlamydia. The model took into account transmission, morbidity and mortality caused by Chlamydia infections. We calibrated the model to characteristics of typical Southeast Queensland koala populations. As there is uncertainty about the effectiveness of the vaccine in real-world settings, a variety of potential vaccine efficacies, half-lives and dosing schedules were simulated. RESULTS Assuming other threats remain constant, it is expected that current population declines could be reversed in around 5-6 years if female koalas aged 1-2 years are targeted, average vaccine protective efficacy is 75%, and vaccine coverage is around 10% per year. At lower vaccine efficacies the immunological effects of boosting become important: at 45% vaccine efficacy population decline is predicted to reverse in 6 years under optimistic boosting assumptions but in 9 years under pessimistic boosting assumptions. Terminating a successful vaccination programme at 5 years would lead to a rise in Chlamydia prevalence towards pre-vaccination levels. CONCLUSION For a range of vaccine efficacy levels it is projected that population decline due to endemic Chlamydia can be reversed under realistic dosing schedules, potentially in just 5 years. However, a vaccination programme might need to continue indefinitely in order to maintain Chlamydia prevalence at a sufficiently low level for population growth to continue.
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South Africa is an emerging and industrializing economy which is experiencing remarkable progress. We contend that amidst the developments in the economy, the role of energy, trade openness and financial development are critical. In this article, we revisit the pivotal role of these factors. We use the ARDL bounds [72], the Bayer and Hanck [11] cointegration techniques, and an extended Cobb–Douglas framework, to examine the long-run association with output per worker over the sample period 1971–2011. The results support long-run association between output per worker, capital per worker and the shift parameters. The short-run elasticity coefficients are as follows: energy (0.24), trade (0.07), financial development (−0.03). In the long-run, the elasticity coefficients are: trade openness (0.05), energy (0.29), and financial development (−0.04). In both the short-run and the long-run, we note the post-2000 period has a marginal positive effect on the economy. The Toda and Yamamoto [91] Granger causality results show that a unidirectional causality from capital stock and energy consumption to output; and from capital stock to trade openness; a bidirectional causality between trade openness and output; and absence (neutrality) of any causality between financial development and output thus indicating that these two variables evolve independent of each other.
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Objectives: To describe longitudinal height, weight, and body mass index changes up to 15 years after childhood liver transplantation. Study design: Retrospective chart review of patients who underwent liver transplant from 1985-2004 was performed. Subjects were age <18 years at transplant, survived ≥5 years, with at least 2 recorded measurements, of which one was ≥5 years post-transplant. Measurements were recorded pre-transplant, 1, 5, 10, and 15 years later. Results: Height and weight data were available in 98 and 104 patients, respectively; 47% were age <2 years at transplant; 58% were Australian, and the rest were from Japan. Height recovery continued for at least 10 years to reach the 26th percentile (Z-score -0.67) 15 years after transplant. Australians had better growth recovery and attained 47th percentile (Z-score -0.06) at 15 years. Weight recovery was most marked in the first year and continued for 15 years even in well-nourished children. Growth impaired and malnourished children at transplant exhibited the best growth, but remained significantly shorter and lighter even 15 years later. No effect of sex or age at transplant was noted on height or weight recovery. Post-transplant factors significantly impact growth recovery and likely caused the dichotomous growth recovery between Australian and Japanese children; 9% (9/98) of patients were overweight on body mass index calculations at 10-15 years but none were obese. Conclusions: After liver transplant, children can expect ongoing height and weight recovery for at least 10-15 years. Growth impairment at transplant and post-transplant care significantly impact long-term growth recovery. Copyright © 2013 Mosby Inc. All rights reserved.
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Aim: This study aimed to document the growth patterns of a contemporary cohort of preterm infants born appropriate for gestational age (AGA). It was hypothesised that preterm AGA (PT-AGA) infants would display poorer growth than full-term AGA (FT-AGA) infants. Methods: Sixty-four PT-AGA infants and 64 FT-AGA infants were assessed at 0, 4, 8 and 12 months of corrected age (CA). Measurements of weight and length were recorded at each of the specified ages. Centers for Disease Control and Prevention growth data were used to calculate Z-scores for weight and length based on CA. Results: The mean length and weight Z-scores of PT-AGA infants were found to be significantly less than those of FT-AGA infants at term, 4, 8 and 12 months of CA (P < 0.001). The mean weight Z-score of PT-AGA infants was found to be less than their mean length Z-score at each time point, though the differences were not significant. Conclusions: The results of this study suggest that PT-AGA infants are likely to display poorer growth than FT-AGA infants until at least 1 year of CA. Long-term growth monitoring in this population is recommended. © 2008 The Authors.
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Peak bone mass achieved in adolescence is a determinant of bone mass in later life. In order to identify genetic variants affecting bone mineral density (BMD), we performed a genome-wide association study of BMD and related traits in 1518 children from the Avon Longitudinal Study of Parents and Children (ALSPAC). We compared results with a scan of 134 adults with high or low hip BMD. We identified associations with BMD in an area of chromosome 12 containing the Osterix (SP7) locus, a transcription factor responsible for regulating osteoblast differentiation (ALSPAC: P = 5.8 × 10-4; Australia: P = 3.7 × 10-4). This region has previously shown evidence of association with adult hip and lumbar spine BMD in an Icelandic population, as well as nominal association in a UK population. A meta-analysis of these existing studies revealed strong association between SNPs in the Osterix region and adult lumbar spine BMD (P = 9.9 × 10-11). In light of these findings, we genotyped a further 3692 individuals from ALSPAC who had whole body BMD and confirmed the association in children as well (P = 5.4 × 10-5). Moreover, all SNPs were related to height in ALSPAC children, but not weight or body mass index, and when height was included as a covariate in the regression equation, the association with total body BMD was attenuated. We conclude that genetic variants in the region of Osterix are associated with BMD in children and adults probably through primary effects on growth.
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As part of an anti-cancer natural product drug discovery program, we recently identified eusynstyelamide B (EB), which displayed cytotoxicity against MDA-MB-231 breast cancer cells (IC50 = 5 μM) and induced apoptosis. Here, we investigated the mechanism of action of EB in cancer cell lines of the prostate (LNCaP) and breast (MDA-MB-231). EB inhibited cell growth (IC50 = 5 μM) and induced a G2 cell cycle arrest, as shown by a significant increase in the G2/M cell population in the absence of elevated levels of the mitotic marker phospho-histone H3. In contrast to MDA-MB-231 cells, EB did not induce cell death in LNCaP cells when treated for up to 10 days. Transcript profiling and Ingenuity Pathway Analysis suggested that EB activated DNA damage pathways in LNCaP cells. Consistent with this, CHK2 phosphorylation was increased, p21CIP1/WAF1 was up-regulated and CDC2 expression strongly reduced by EB. Importantly, EB caused DNA double-strand breaks, yet did not directly interact with DNA. Analysis of topoisomerase II-mediated decatenation discovered that EB is a novel topoisomerase II poison.