988 resultados para Strong Stability


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This paper gives a review of recent progress in the design of numerical methods for computing the trajectories (sample paths) of solutions to stochastic differential equations. We give a brief survey of the area focusing on a number of application areas where approximations to strong solutions are important, with a particular focus on computational biology applications, and give the necessary analytical tools for understanding some of the important concepts associated with stochastic processes. We present the stochastic Taylor series expansion as the fundamental mechanism for constructing effective numerical methods, give general results that relate local and global order of convergence and mention the Magnus expansion as a mechanism for designing methods that preserve the underlying structure of the problem. We also present various classes of explicit and implicit methods for strong solutions, based on the underlying structure of the problem. Finally, we discuss implementation issues relating to maintaining the Brownian path, efficient simulation of stochastic integrals and variable-step-size implementations based on various types of control.

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The pioneering work of Runge and Kutta a hundred years ago has ultimately led to suites of sophisticated numerical methods suitable for solving complex systems of deterministic ordinary differential equations. However, in many modelling situations, the appropriate representation is a stochastic differential equation and here numerical methods are much less sophisticated. In this paper a very general class of stochastic Runge-Kutta methods is presented and much more efficient classes of explicit methods than previous extant methods are constructed. In particular, a method of strong order 2 with a deterministic component based on the classical Runge-Kutta method is constructed and some numerical results are presented to demonstrate the efficacy of this approach.

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Stochastic differential equations (SDEs) arise fi om physical systems where the parameters describing the system can only be estimated or are subject to noise. There has been much work done recently on developing numerical methods for solving SDEs. This paper will focus on stability issues and variable stepsize implementation techniques for numerically solving SDEs effectively.

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Background: The 30-item USDI is a self-report measure that assesses depressive symptoms among university students. It consists of three correlated three factors: Lethargy, Cognitive-Emotional and Academic motivation. The current research used confirmatory factor analysis to asses construct validity and determine whether the original factor structure would be replicated in a different sample. Psychometric properties were also examined. Method: Participants were 1148 students (mean age 22.84 years, SD = 6.85) across all faculties from a large Australian metropolitan university. Students completed a questionnaire comprising of the USDI, the Depression Anxiety Stress Scale (DASS) and Life Satisfaction Scale (LSS). Results: The three correlated factor model was shown to be an acceptable fit to the data, indicating sound construct validity. Internal consistency of the scale was also demonstrated to be sound, with high Cronbach Alpha values. Temporal stability of the scale was also shown to be strong through test-retest analysis. Finally, concurrent and discriminant validity was examined with correlations between the USDI and DASS subscales as well as the LSS, with sound results contributing to further support the construct validity of the scale. Cut-off points were also developed to aid total score interpretation. Limitations: Response rates are unclear. In addition, the representativeness of the sample could be improved potentially through targeted recruitment (i.e. reviewing the online sample statistics during data collection, examining the representativeness trends and addressing particular faculties within the university that were underrepresented). Conclusions: The USDI provides a valid and reliable method of assessing depressive symptoms found among university students.

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In recent years considerable attention has been paid to the numerical solution of stochastic ordinary differential equations (SODEs), as SODEs are often more appropriate than their deterministic counterparts in many modelling situations. However, unlike the deterministic case numerical methods for SODEs are considerably less sophisticated due to the difficulty in representing the (possibly large number of) random variable approximations to the stochastic integrals. Although Burrage and Burrage [High strong order explicit Runge-Kutta methods for stochastic ordinary differential equations, Applied Numerical Mathematics 22 (1996) 81-101] were able to construct strong local order 1.5 stochastic Runge-Kutta methods for certain cases, it is known that all extant stochastic Runge-Kutta methods suffer an order reduction down to strong order 0.5 if there is non-commutativity between the functions associated with the multiple Wiener processes. This order reduction down to that of the Euler-Maruyama method imposes severe difficulties in obtaining meaningful solutions in a reasonable time frame and this paper attempts to circumvent these difficulties by some new techniques. An additional difficulty in solving SODEs arises even in the Linear case since it is not possible to write the solution analytically in terms of matrix exponentials unless there is a commutativity property between the functions associated with the multiple Wiener processes. Thus in this present paper first the work of Magnus [On the exponential solution of differential equations for a linear operator, Communications on Pure and Applied Mathematics 7 (1954) 649-673] (applied to deterministic non-commutative Linear problems) will be applied to non-commutative linear SODEs and methods of strong order 1.5 for arbitrary, linear, non-commutative SODE systems will be constructed - hence giving an accurate approximation to the general linear problem. Secondly, for general nonlinear non-commutative systems with an arbitrary number (d) of Wiener processes it is shown that strong local order I Runge-Kutta methods with d + 1 stages can be constructed by evaluated a set of Lie brackets as well as the standard function evaluations. A method is then constructed which can be efficiently implemented in a parallel environment for this arbitrary number of Wiener processes. Finally some numerical results are presented which illustrate the efficacy of these approaches. (C) 1999 Elsevier Science B.V. All rights reserved.

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In Burrage and Burrage [1] it was shown that by introducing a very general formulation for stochastic Runge-Kutta methods, the previous strong order barrier of order one could be broken without having to use higher derivative terms. In particular, methods of strong order 1.5 were developed in which a Stratonovich integral of order one and one of order two were present in the formulation. In this present paper, general order results are proven about the maximum attainable strong order of these stochastic Runge-Kutta methods (SRKs) in terms of the order of the Stratonovich integrals appearing in the Runge-Kutta formulation. In particular, it will be shown that if an s-stage SRK contains Stratonovich integrals up to order p then the strong order of the SRK cannot exceed min{(p + 1)/2, (s - 1)/2), p greater than or equal to 2, s greater than or equal to 3 or 1 if p = 1.

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Wing length is a key character for essential behaviours related to bird flight such as migration and foraging. In the present study, we initiate the search for the genes underlying wing length in birds by studying a long-distance migrant, the great reed warbler (Acrocephalus arundinaceus). In this species wing length is an evolutionary interesting trait with pronounced latitudinal gradient and sex-specific selection regimes in local populations. We performed a quantitative trait locus (QTL) scan for wing length in great reed warblers using phenotypic, genotypic, pedigree and linkage map data from our long-term study population in Sweden. We applied the linkage analysis mapping method implemented in GRIDQTL (a new web-based software) and detected a genome-wide significant QTL for wing length on chromosome 2, to our knowledge, the first detected QTL in wild birds. The QTL extended over 25 cM and accounted for a substantial part (37%) of the phenotypic variance of the trait. A genome scan for tarsus length (a bodysize-related trait) did not show any signal, implying that the wing-length QTL on chromosome 2 was not associated with body size. Our results provide a first important step into understanding the genetic architecture of avian wing length, and give opportunities to study the evolutionary dynamics of wing length at the locus level. This journal is© 2010 The Royal Society.

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The drawdown of reservoirs can significantly affect the stability of upstream slopes of earth dams. This is due to the removal of the balancing hydraulic forces acting on the dams and the undrained condition within the upstream slope soils. In such scenarios, the stability of the slopes can be influenced by a range of factors including drawdown rates, slope inclination and soil properties. This paper investigates the effects of drawdown rate, saturated hydraulic conductivity and unsaturated shear strength of dam materials on the stability of the upstream slope of an earth dam. In this study, the analysis of pore-water pressure changes within the upstream slope during reservoir drawdown was coupled with the slope stability analysis using the general limit equilibrium method. The results of the analysis suggested that a decrease in the reservoir water level caused the stability of the upstream slope to decrease. The dam embankment constructed with highly permeable soil was found to be more stable during drawdown scenarios, compared to others. Further, lower drawdown rates resulted in a higher safety factor for the upstream slope. Also, the safety factor of the slope calculated using saturated shear strength properties of the dam materials was slightly higher than that calculated using unsaturated shear strength properties. In general, for all the scenarios analysed, the lowest safety factor was found to be at the reservoir water level of about 2/3 of drawdown regime.

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As a novel sensitive element and due to its advantages of immunity to electrical interference, distributed measurement, etc., fiber Bragg grating (FBG) has been researched widely. To realize the substitution of high accurate electronic temperature sensors, high sensitive FBG temperature sensors can be made by taking advantage of its characters of being sensitive to both temperature and strain. Although there are reports about high sensitive FBG temperature sensors, however, few about their stability have been done. We manufactured a high sensitive FBG temperature sensor, and put it together with an average FBG temperature sensor and an electronic crystal temperature sensor into a stainless steel container filled by water to observe the room temperature change. By comparing their results in two weeks, we have found out that: although the high sensitive FBG temperature sensor is in much better agreement with the electronic crystal sensor than the average FBG sensor is, it has occurred some small drifts. Because the drifts appeared in the process of further pulling the FBG, it might be a result of the slip of the FBG fixing points. This contributes some good experiences to the application of FBG in high accuracy temperature measurement.

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Sedimentary palygorskite (SP) and hydrothermal palygorskite (HP) were characterized by XRF, TG/DSC, andXRD. The total iron and dissociative iron in palygorskite were detected using spectrophotometry. The results showed that about 3.57 wt% of Fe2O3 was detected in SP in contrast with 0.4 wt% in HP. SP was a Fe-substituted palygorskite, and HP was an Al-rich palygorskite. The occurrence of Fe substitution in SP resulted in two mass loss steps of coordinated water and resulted in a larger d spacing. The SP showed greater thermal stability than the HP. It was proposed the change of (200) diffraction peak and (240) diffraction peak reflect changes of tetrahedral and octahedral structures in palygorskite.

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Chromium oxyhydroxide nanomaterials with narrow size-distribution were synthesised through a simple hydrothermal method. Experimental conditions, such as reaction duration and pH values of the precipitation process and hydrothermal treatment played important roles in determining the nature of the final product chromium oxyhydroxide nanomaterials. The effect of these synthesis parameters were studied with the assistance of X-ray diffraction, scanning electron microscopy, X-ray photoelectron spectroscopy and thermogravimetric analyses. This research has developed a controllable synthesis of Chromium oxyhydroxide nanomaterials from Chromium oxide colloids.

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We have characterized anapaite Ca2Fe2+(PO4)2·4(H2O), a rare Ca and Fe phosphate, using a combination of electron microscopy and vibrational spectroscopy. The mineral occurs in soils and lacustrine sediments and is usually related to the diagenetic process in phosphorous rich sediments. The phosphate anion is characterized by its Raman spectrum with an intense sharp band at 943 cm-1, attributed to the ν1 PO4 3- symmetric stretching mode. Three bands at 992, 1039 and 1071 cm-1 are attributed to ν3 PO4 3-antisymmetric stretching modes. The infrared spectrum of anapaite shows complexity with a series of overlapping bands. Water in the structure of anapaite is observed by OH stretching vibrations at 2777, 3022 and 3176 cm-1 (Raman) and 2744, 3014 and 3096 cm-1 (infrared). The position of these bands provides evidence for the strong hydrogen bonding of water in the anapaite structure and contributes to the stability of the mineral.

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Triangle-shaped nanohole, nanodot, and lattice antidot structures in hexagonal boron-nitride (h-BN) monolayer sheets are characterized with density functional theory calculations utilizing the local spin density approximation. We find that such structures may exhibit very large magnetic moments and associated spin splitting. N-terminated nanodots and antidots show strong spin anisotropy around the Fermi level, that is, half-metallicity. While B-terminated nanodots are shown to lack magnetism due to edge reconstruction, B-terminated nanoholes can retain magnetic character due to the enhanced structural stability of the surrounding two-dimensional matrix. In spite of significant lattice contraction due to the presence of multiple holes, antidot super lattices are predicted to be stable, exhibiting amplified magnetism as well as greatly enhanced half-metallicity. Collectively, the results indicate new opportunities for designing h-BNbased nanoscale devices with potential applications in the areas of spintronics, light emission, and photocatalysis.

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Anisotropic damage distribution and evolution have a profound effect on borehole stress concentrations. Damage evolution is an irreversible process that is not adequately described within classical equilibrium thermodynamics. Therefore, we propose a constitutive model, based on non-equilibrium thermodynamics, that accounts for anisotropic damage distribution, anisotropic damage threshold and anisotropic damage evolution. We implemented this constitutive model numerically, using the finite element method, to calculate stress–strain curves and borehole stresses. The resulting stress–strain curves are distinctively different from linear elastic-brittle and linear elastic-ideal plastic constitutive models and realistically model experimental responses of brittle rocks. We show that the onset of damage evolution leads to an inhomogeneous redistribution of material properties and stresses along the borehole wall. The classical linear elastic-brittle approach to borehole stability analysis systematically overestimates the stress concentrations on the borehole wall, because dissipative strain-softening is underestimated. The proposed damage mechanics approach explicitly models dissipative behaviour and leads to non-conservative mud window estimations. Furthermore, anisotropic rocks with preferential planes of failure, like shales, can be addressed with our model.

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The double-stranded conformation of cellular DNA is a central aspect of DNA stabilisation and protection. The helix preserves the genetic code against chemical and enzymatic degradation, metabolic activation, and formation of secondary structures. However, there are various instances where single-stranded DNA is exposed, such as during replication or transcription, in the synthesis of chromosome ends, and following DNA damage. In these instances, single-stranded DNA binding proteins are essential for the sequestration and processing of single-stranded DNA. In order to bind single-stranded DNA, these proteins utilise a characteristic and evolutionary conserved single-stranded DNA-binding domain, the oligonucleotide/oligosaccharide-binding (OB)-fold. In the current review we discuss a subset of these proteins involved in the direct maintenance of genomic stability, an important cellular process in the conservation of cellular viability and prevention of malignant transformation. We discuss the central roles of single-stranded DNA binding proteins from the OB-fold domain family in DNA replication, the restart of stalled replication forks, DNA damage repair, cell cycle-checkpoint activation, and telomere maintenance.