Test of the fluctuation theorem for stochastic entropy production in a nonequilibrium steady state

We derive a simple closed analytical expression for the total entropy production along a single stochastic trajectory of a Brownian particle diffusing on a periodic potential under an external constant force. By numerical simulations we compute the probability distribution functions of the entropy and satisfactorily test many of the predictions based on Seiferts integral fluctuation theorem. The results presented for this simple model clearly illustrate the practical features and implications derived from such a result of nonequilibrium statistical mechanics.

Reproducibility of twitch mouth pressure, sniff nasal inspiratory pressure, and maximal inspiratory pressure.

Twitch mouth pressure (Pmo,tw) during magnetic phrenic nerve stimulation and sniff nasal inspiratory pressure (SNIP) were recently proposed as alternative noninvasive methods for assessing inspiratory muscle strength. This study aimed to compare their reproducibility with maximal inspiratory pressure (MIP) in normal subjects. Ten healthy subjects were studied at functional residual capacity in semirecumbent position. Cervical magnetic phrenic nerve stimulation was performed during gentle expiration against an occlusion incorporating a small leak. Constancy of stimulation was controlled by recording diaphragmatic electromyogram. Within and between-session reproducibility of pressure were studied for Pmo,tw, SNIP, and MIP. The subjects were studied during a session of 10 manoeuvres repeated after 1 day and 1 month. The mean values were 16 cmH2O for Pmo,tw, 118 cmH2O for SNIP, and 115 cmH2O for MIP. For the three tests, the within subject variation was small in relation to between-subject variation, with the intraclass correlation coefficient ranging 0.79-0.90 for Pmo,tw, 0.85-0.92 for SNIP, and 0.88-0.92 for MIP. At 1 day interval, the coefficient of repeatability (2 SD of differences) was 3.6 cmH2O for Pmo,tw, 32 cmH2O for SNIP and 28 cmH2O for MIP. At 1 month interval, the coefficient of repeatability was 5.8 cmH2O for Pmo,tw, 23 cmH2O for SNIP and 21 cmH2O for MIP. We conclude that the within session reproducibility of the new tests twitch mouth pressure and sniff nasal inspiratory pressure is sufficient to be clinically useful. For sniff nasal inspiratory pressure, the between session reproducibility established after 1 day was maintained after 1 month. For twitch mouth pressure, the between session reproducibility declined slightly after 1 month. These characteristics should be considered when using these methods to follow an individual patient over time.

Estimation of jump-diffusion processes via empirical characteristic functions

Preface The starting point for this work and eventually the subject of the whole thesis was the question: how to estimate parameters of the affine stochastic volatility jump-diffusion models. These models are very important for contingent claim pricing. Their major advantage, availability T of analytical solutions for characteristic functions, made them the models of choice for many theoretical constructions and practical applications. At the same time, estimation of parameters of stochastic volatility jump-diffusion models is not a straightforward task. The problem is coming from the variance process, which is non-observable. There are several estimation methodologies that deal with estimation problems of latent variables. One appeared to be particularly interesting. It proposes the estimator that in contrast to the other methods requires neither discretization nor simulation of the process: the Continuous Empirical Characteristic function estimator (EGF) based on the unconditional characteristic function. However, the procedure was derived only for the stochastic volatility models without jumps. Thus, it has become the subject of my research. This thesis consists of three parts. Each one is written as independent and self contained article. At the same time, questions that are answered by the second and third parts of this Work arise naturally from the issues investigated and results obtained in the first one. The first chapter is the theoretical foundation of the thesis. It proposes an estimation procedure for the stochastic volatility models with jumps both in the asset price and variance processes. The estimation procedure is based on the joint unconditional characteristic function for the stochastic process. The major analytical result of this part as well as of the whole thesis is the closed form expression for the joint unconditional characteristic function for the stochastic volatility jump-diffusion models. The empirical part of the chapter suggests that besides a stochastic volatility, jumps both in the mean and the volatility equation are relevant for modelling returns of the S&P500 index, which has been chosen as a general representative of the stock asset class. Hence, the next question is: what jump process to use to model returns of the S&P500. The decision about the jump process in the framework of the affine jump- diffusion models boils down to defining the intensity of the compound Poisson process, a constant or some function of state variables, and to choosing the distribution of the jump size. While the jump in the variance process is usually assumed to be exponential, there are at least three distributions of the jump size which are currently used for the asset log-prices: normal, exponential and double exponential. The second part of this thesis shows that normal jumps in the asset log-returns should be used if we are to model S&P500 index by a stochastic volatility jump-diffusion model. This is a surprising result. Exponential distribution has fatter tails and for this reason either exponential or double exponential jump size was expected to provide the best it of the stochastic volatility jump-diffusion models to the data. The idea of testing the efficiency of the Continuous ECF estimator on the simulated data has already appeared when the first estimation results of the first chapter were obtained. In the absence of a benchmark or any ground for comparison it is unreasonable to be sure that our parameter estimates and the true parameters of the models coincide. The conclusion of the second chapter provides one more reason to do that kind of test. Thus, the third part of this thesis concentrates on the estimation of parameters of stochastic volatility jump- diffusion models on the basis of the asset price time-series simulated from various "true" parameter sets. The goal is to show that the Continuous ECF estimator based on the joint unconditional characteristic function is capable of finding the true parameters. And, the third chapter proves that our estimator indeed has the ability to do so. Once it is clear that the Continuous ECF estimator based on the unconditional characteristic function is working, the next question does not wait to appear. The question is whether the computation effort can be reduced without affecting the efficiency of the estimator, or whether the efficiency of the estimator can be improved without dramatically increasing the computational burden. The efficiency of the Continuous ECF estimator depends on the number of dimensions of the joint unconditional characteristic function which is used for its construction. Theoretically, the more dimensions there are, the more efficient is the estimation procedure. In practice, however, this relationship is not so straightforward due to the increasing computational difficulties. The second chapter, for example, in addition to the choice of the jump process, discusses the possibility of using the marginal, i.e. one-dimensional, unconditional characteristic function in the estimation instead of the joint, bi-dimensional, unconditional characteristic function. As result, the preference for one or the other depends on the model to be estimated. Thus, the computational effort can be reduced in some cases without affecting the efficiency of the estimator. The improvement of the estimator s efficiency by increasing its dimensionality faces more difficulties. The third chapter of this thesis, in addition to what was discussed above, compares the performance of the estimators with bi- and three-dimensional unconditional characteristic functions on the simulated data. It shows that the theoretical efficiency of the Continuous ECF estimator based on the three-dimensional unconditional characteristic function is not attainable in practice, at least for the moment, due to the limitations on the computer power and optimization toolboxes available to the general public. Thus, the Continuous ECF estimator based on the joint, bi-dimensional, unconditional characteristic function has all the reasons to exist and to be used for the estimation of parameters of the stochastic volatility jump-diffusion models.

Round robin test: wear of nine dental restorative materials in six different wear simulators - supplement to the round robin test of 2005.

OBJECTIVE: The purpose of the present study was to submit the same materials that were tested in the round robin wear test of 2002/2003 to the Alabama wear method. METHODS: Nine restorative materials, seven composites (belleGlass, Chromasit, Estenia, Heliomolar, SureFil, Targis, Tetric Ceram) an amalgam (Amalcap) and a ceramic (IPS Empress) have been submitted to the Alabama wear method for localized and generalized wear. The test centre did not know which brand they were testing. Both volumetric and vertical loss had been determined with an optical sensor. After completion of the wear test, the raw data were sent to IVOCLAR for further analysis. The statistical analysis of the data included logarithmic transformation of the data, the calculation of relative ranks of each material within each test centre, measures of agreement between methods, the discrimination power and coefficient of variation of each method as well as measures of the consistency and global performance for each material. RESULTS: Relative ranks of the materials varied tremendously between the test centres. When all materials were taken into account and the test methods compared with each other, only ACTA agreed reasonably well with two other methods, i.e. OHSU and ZURICH. On the other hand, MUNICH did not agree with the other methods at all. The ZURICH method showed the lowest discrimination power, ACTA, IVOCLAR and ALABAMA localized the highest. Material-wise, the best global performance was achieved by the leucite reinforced ceramic material Empress, which was clearly ahead of belleGlass, SureFil and Estenia. In contrast, Heliomolar, Tetric Ceram and especially Chromasit demonstrated a poor global performance. The best consistency was achieved by SureFil, Tetric Ceram and Chromasit, whereas the consistency of Amalcap and Heliomolar was poor. When comparing the laboratory data with clinical data, a significant agreement was found for the IVOCLAR and ALABAMA generalized wear method. SIGNIFICANCE: As the different wear simulator settings measure different wear mechanisms, it seems reasonable to combine at least two different wear settings to assess the wear resistance of a new material.

Less Risk, More Effort : Demand Risk Allocation in Incomplete Contracts

This article investigates the allocation of demand risk within an incomplete contract framework. We consider an incomplete contractual relationship between a public authority and a private provider (i.e. a public-private partnership), in which the latter invests in non-verifiable cost-reducing efforts and the former invests in non-verifiable adaptation efforts to respond to changing consumer demand over time. We show that the party that bears the demand risk has fewer hold-up opportunities and that this leads the other contracting party to make more effort. Thus, in our model, bearing less risk can lead to more effort, which we describe as a new example of âeuro~counter-incentivesâeuro?. We further show that when the benefits of adaptation are important, it is socially preferable to design a contract in which the demand risk remains with the private provider, whereas when the benefits of cost-reducing efforts are important, it is socially preferable to place the demand risk on the public authority. We then apply these results to explain two well-known case studies.

A quantitative test of Hamilton's rule for the evolution of altruism.

The evolution of altruism is a fundamental and enduring puzzle in biology. In a seminal paper Hamilton showed that altruism can be selected for when rb - c > 0, where c is the fitness cost to the altruist, b is the fitness benefit to the beneficiary, and r is their genetic relatedness. While many studies have provided qualitative support for Hamilton's rule, quantitative tests have not yet been possible due to the difficulty of quantifying the costs and benefits of helping acts. Here we use a simulated system of foraging robots to experimentally manipulate the costs and benefits of helping and determine the conditions under which altruism evolves. By conducting experimental evolution over hundreds of generations of selection in populations with different c/b ratios, we show that Hamilton's rule always accurately predicts the minimum relatedness necessary for altruism to evolve. This high accuracy is remarkable given the presence of pleiotropic and epistatic effects as well as mutations with strong effects on behavior and fitness (effects not directly taken into account in Hamilton's original 1964 rule). In addition to providing the first quantitative test of Hamilton's rule in a system with a complex mapping between genotype and phenotype, these experiments demonstrate the wide applicability of kin selection theory.

Development of LRFD Procedures for Bridge Pile Foundations in Iowa Final Report, June 2010

For well over 100 years, the Working Stress Design (WSD) approach has been the traditional basis for geotechnical design with regard to settlements or failure conditions. However, considerable effort has been put forth over the past couple of decades in relation to the adoption of the Load and Resistance Factor Design (LRFD) approach into geotechnical design. With the goal of producing engineered designs with consistent levels of reliability, the Federal Highway Administration (FHWA) issued a policy memorandum on June 28, 2000, requiring all new bridges initiated after October 1, 2007, to be designed according to the LRFD approach. Likewise, regionally calibrated LRFD resistance factors were permitted by the American Association of State Highway and Transportation Officials (AASHTO) to improve the economy of bridge foundation elements. Thus, projects TR-573, TR-583 and TR-584 were undertaken by a research team at Iowa State University’s Bridge Engineering Center with the goal of developing resistance factors for pile design using available pile static load test data. To accomplish this goal, the available data were first analyzed for reliability and then placed in a newly designed relational database management system termed PIle LOad Tests (PILOT), to which this first volume of the final report for project TR-573 is dedicated. PILOT is an amalgamated, electronic source of information consisting of both static and dynamic data for pile load tests conducted in the State of Iowa. The database, which includes historical data on pile load tests dating back to 1966, is intended for use in the establishment of LRFD resistance factors for design and construction control of driven pile foundations in Iowa. Although a considerable amount of geotechnical and pile load test data is available in literature as well as in various State Department of Transportation files, PILOT is one of the first regional databases to be exclusively used in the development of LRFD resistance factors for the design and construction control of driven pile foundations. Currently providing an electronically organized assimilation of geotechnical and pile load test data for 274 piles of various types (e.g., steel H-shaped, timber, pipe, Monotube, and concrete), PILOT (http://srg.cce.iastate.edu/lrfd/) is on par with such familiar national databases used in the calibration of LRFD resistance factors for pile foundations as the FHWA’s Deep Foundation Load Test Database. By narrowing geographical boundaries while maintaining a high number of pile load tests, PILOT exemplifies a model for effective regional LRFD calibration procedures.