Thèses : « Stochastic cycle »

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He, Enuo. « Stochastic modelling of the cell cycle ». Thesis, University of Oxford, 2012. http://ora.ox.ac.uk/objects/uuid:04185cde-85af-4e24-8d06-94b865771cf1.

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Precise regulation of cell cycle events by the Cdk-control network is essential for cell proliferation and the perpetuation of life. The unidirectionality of cell cycle progression is governed by several critical irreversible transitions: the G1-to-S transition, the G2-to-M transition, and the M-to-G1 transition. Recent experimental and theoretical evidence has pulled into question the consensus view that irreversible protein degradation causes the irreversibility of those transitions. A new view has started to emerge, which explains the irreversibility of cell cycle transitions as a consequence of systems-level feedback rather than of proteolysis. This thesis applies mathematical modelling approaches to test this proposal for the Mto- G1 transition, which consists of two consecutive irreversible substeps: the metaphase-to-anaphase transition, and mitotic exit. The main objectives of the present work were: (i) to develop deterministic models to identify the essential molecular feedback loops and to examine their roles in the irreversibility of the M-to-G1 transition; (ii) to present a straightforward and reliable workflow to translate deterministic models of reaction networks into stochastic models; (iii) to explore the effects of noise on the cell cycle transitions using stochastic models, and to compare the deterministic and the stochastic approaches. In the first part of this thesis, I constructed a simplified deterministic model of the metaphase-to-anaphase transition, which is mainly regulated by the spindle assembly checkpoint (the SAC). Based on the essential feedback loops causing the bistability of the transition, this deterministic model provides explanations for three open questions regarding the SAC: Why is the SAC not reactivated when the kinetochore tension decreases to zero at anaphase onset? How can a single unattached kinetochore keep the SAC active? How is the synchronized and abrupt destruction of cohesin triggered? This deterministic model was then translated into a stochastic model of the SAC by treating the kinetochore microtubule attachment at prometaphase as a noisy process. The stochastic model was analyzed and simulation results were compared to the experimental data, with the aim of explaining the mitotic timing regulation by the SAC. Our model works remarkably well in qualitatively explaining experimental key findings and also makes testable predictions for different cell lines with very different number of chromosomes. The noise generated from the chemical interactions was found to only perturb the transit timing of the mitotic events, but not their ultimate outcomes: all cells eventually undergo anaphase, however, the time required to satisfy the SAC differs between cells due to stochastic effects. In the second part of the thesis, stochastic models of mitotic exit were created for two model organisms, budding yeast and mammalian cells. I analyzed the role of noise in mitotic exit at both the single-cell and the population level. Stochastic time series simulations of the models are able to explain the phenomenon of reversible mitotic exit, which is observed under specific experimental conditions in both model organisms. In spite of the fact that the detailed molecular networks of mitotic exit are very different in budding yeast and mammalian cells, their dynamic properties are similar. Importantly, bistability of the transitions is successfully captured also in the stochastic models. This work strongly supports the hypothesis that uni-directional cell cycle progression is a consequence of systems-level feedback in the cell cycle control system. Systems-level feedback creates alternative steady states, which allows cells to accomplish irreversible transitions, such as the M-to-G1 transition studied here. We demonstrate that stochastic models can serve as powerful tools to capture and study the heterogeneity of dynamical features among individual cells. In this way, stochastic simulations not only complement the deterministic approach, but also help to obtain a better understanding of mechanistic aspects. We argue that the effects of noise and the potential needs for stochastic simulations should not be overlooked in studying dynamic features of biological systems.

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Posadas, Sergio. « Stochastic simulation of a Commander's decision cycle (SSIM CODE) ». Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2001. http://handle.dtic.mil/100.2/ADA392113.

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Thesis (M.S. in Operations Research) Naval Postgraduate School, June 2001.
Thesis advisor(s): Paulo, Eugene P. ; Olson, Allen S. "June 2001." Includes bibliographical references (p. 111-115). Also available in print.

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VanDoorne, Rick. « Stochastic rail life cycle cost maintenance modeling using Monte Carlo simulation ». Diss., University of Pretoria, 2017. http://hdl.handle.net/2263/61343.

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The objective of this study was to quantify and determine trends in the uncertainty in the life cycle cost (LCC) associated with the maintenance and renewal (M&R) of the rail of a railway track under a fixed set of input parameters and conditions. Rail maintenance models were identified in the literature which use the mean or expected value of the input distributions to determine a corresponding mean or expected LCC. Although these models display important trends with regard to input parameters such as inspection intervals, they provide no means to quantify the uncertainty related to maintenance and renewal decisions. Thus, a numerical model was developed and programmed using MATLAB which allows the quantification of the uncertainty in the LCC estimated for a given set of conditions. The model uses Monte Carlo simulation to determine the LCC associated with the installation, maintenance and renewal of the rail. The model incorporates imperfect inspections, a hazard function for rail fatigue defects modelled using the Weibull probability distribution and a P-F interval for rail fatigue defects modelled using an exponential probability distribution. The model also allows the modelling of maintenance as either perfect or minimal maintenance as well as the use of either flash butt or alumino-thermic welds to conduct the maintenance. This allowed the development of a method to assess which weld type to use to minimise the minimum attainable mean LCC. The developed model was validated against a similar stochastic rail maintenance model from the literature. However, the model from the literature considers only the expected LCC and does not show any uncertainty related thereto. The novelty in this study therefore lies in the fact that the LCC uncertainty can be quantified in the form of a probability distribution at any given renewal tonnage for a given set of conditions. It was found that the distribution of the LCC at a given renewal tonnage followed a lognormal probability distribution. The standard deviation of the lognormal distributions fitted using the method of maximum likelihood was used as a metric to quantify the uncertainty related to the life cycle cost at a given renewal tonnage. The LCC uncertainty was found to increase with an increase in inspection interval length. Furthermore, the uncertainty was also found to increase with a respective increase in renewal tonnage. For varying inspection interval lengths it was found that the uncertainty of combined maintenance costs (planned plus unplanned maintenance costs) tended more strongly towards the uncertainty in the planned maintenance costs for smaller inspection intervals and more strongly towards the uncertainty in unplanned maintenance costs for larger inspection intervals. A critical cost ratio was found of flash butt weld cost to alumino-thermic weld cost at which the minimum attainable mean LCC was equal. It is more economical to use flash butt welding for maintenance if the cost of flash butt welding maintenance produces a cost ratio lower than the critical cost ratio. The developed model could allow railway operators to assess the risk associated with renewal of the rail at varying renewal tonnages for given conditions such as inspection interval lengths, detectability of rail fatigue defects and the arrival rate of rail fatigue defects.
Dissertation (MEng)--University of Pretoria, 2017.
Civil Engineering
MEng
Unrestricted

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McNally, Richard J. Q. « Stochastic modelling of the reproductive cycle in cows and related estimation problems ». Thesis, University of Reading, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.252896.

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Cheaitou, Ali. « Stochastic models for production-Inventory planning : application to short life-cycle products ». Châtenay-Malabry, Ecole centrale de Paris, 2008. http://www.theses.fr/2008ECAP1066.

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Dans le domaine du « Supply Chain Management » la source principale d’incertitude est la demande future. L’impact de l’incertitude de lademande sur les performances de la « Supply Chain » est important: par exemple, le taux mondial de rupture de stock, dans l’industrie dedistribution était en 2007 de 8. 3%. De l’autre côté, le taux mondial de produits invendus, dans la grande distribution, était en 2003 de 1%. Ces deux types de coûts, qui sont dus essentiellement à l’incertitude de la demande, représentent des pertes significatives pour lesdifférents acteurs de la « Supply Chain ». Dans cette thèse, on s’intéresse au développement de modèles mathématiques de planification de production et de gestion de stock, quiprennent en compte ce phénomène d’incertitude sur la demande, essentiellement pour de produits à court cycle de vie. On proposeplusieurs modèles de planification de production, à petit horizon de planification, qui prennent en compte les différents aspects de notreproblématique, telles que la remise à jour des prévisions de la demande et les options de retour « Payback » des produits. On souligne,dans ces modèles, un aspect important qui prend de l’ampleur à cause de la mondialisation, et qui est lié à la différence entre les coûtsde production des différents fournisseurs. . On propose à la fin de la thèse, un modèle généralisé qui pourrait être appliqué à des produitsà long cycle de vie, et qui exploite quelques résultats obtenus pour les produits à court cycle de vie. Tous ces modèles sont résolusanalytiquement ou bien numériquement en utilisant la programmation dynamique stochastique
In the Supply Chain Management domain, the main source of randomness is the future demand. The influence of this demand variabilityon the performance of the Supply Chain is very important: for example, in 2007 the global inventory shortage rate in the retail industrywere around 8. 3%. On the other hand, in 2003 the global Unsaleable products cost around 1% in the grocery industry. These two types ofcosts, which are mainly caused by the uncertainty of the future demand, represent important lost for the whole Supply Chain actors. This Ph. D. Dissertation aims at developing mathematical production planning and inventory management models, which take intoconsideration the randomness of the future demand in order to reduce its economic negative impact, essentially for short life cycleproducts. We provide many planning models that consider the main issues of the planning problems, such as the production capacities,the information updating processes, the supply contracts and the advanced capacity reservation in a total costs minimization context. Weconsider in these models some aspects that are not considered in the literature, such as the “Payback” or the return options. Weemphasize also on an important issue that characterize the globalization of the industry, which may be resumed in the difference betweenthe procurement costs of the different suppliers. This issue is considered in the most chapters presenting models for short life cycleproducts and in the last chapter it is generalized to a long life cycle products setting. All the presented models are solved eitheranalytically or numerically using the dynamic stochastic programming

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Chen, Minghan. « Stochastic Modeling and Simulation of Multiscale Biochemical Systems ». Diss., Virginia Tech, 2019. http://hdl.handle.net/10919/90898.

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Numerous challenges arise in modeling and simulation as biochemical networks are discovered with increasing complexities and unknown mechanisms. With the improvement in experimental techniques, biologists are able to quantify genes and proteins and their dynamics in a single cell, which calls for quantitative stochastic models for gene and protein networks at cellular levels that match well with the data and account for cellular noise. This dissertation studies a stochastic spatiotemporal model of the Caulobacter crescentus cell cycle. A two-dimensional model based on a Turing mechanism is investigated to illustrate the bipolar localization of the protein PopZ. However, stochastic simulations are often impeded by expensive computational cost for large and complex biochemical networks. The hybrid stochastic simulation algorithm is a combination of differential equations for traditional deterministic models and Gillespie's algorithm (SSA) for stochastic models. The hybrid method can significantly improve the efficiency of stochastic simulations for biochemical networks with multiscale features, which contain both species populations and reaction rates with widely varying magnitude. The populations of some reactant species might be driven negative if they are involved in both deterministic and stochastic systems. This dissertation investigates the negativity problem of the hybrid method, proposes several remedies, and tests them with several models including a realistic biological system. As a key factor that affects the quality of biological models, parameter estimation in stochastic models is challenging because the amount of empirical data must be large enough to obtain statistically valid parameter estimates. To optimize system parameters, a quasi-Newton algorithm for stochastic optimization (QNSTOP) was studied and applied to a stochastic budding yeast cell cycle model by matching multivariate probability distributions between simulated results and empirical data. Furthermore, to reduce model complexity, this dissertation simplifies the fundamental cooperative binding mechanism by a stochastic Hill equation model with optimized system parameters. Considering that many parameter vectors generate similar system dynamics and results, this dissertation proposes a general α-β-γ rule to return an acceptable parameter region of the stochastic Hill equation based on QNSTOP. Different objective functions are explored targeting different features of the empirical data.
Doctor of Philosophy
Modeling and simulation of biochemical networks faces numerous challenges as biochemical networks are discovered with increased complexity and unknown mechanisms. With improvement in experimental techniques, biologists are able to quantify genes and proteins and their dynamics in a single cell, which calls for quantitative stochastic models, or numerical models based on probability distributions, for gene and protein networks at cellular levels that match well with the data and account for randomness. This dissertation studies a stochastic model in space and time of a bacterium’s life cycle— Caulobacter. A two-dimensional model based on a natural pattern mechanism is investigated to illustrate the changes in space and time of a key protein population. However, stochastic simulations are often complicated by the expensive computational cost for large and sophisticated biochemical networks. The hybrid stochastic simulation algorithm is a combination of traditional deterministic models, or analytical models with a single output for a given input, and stochastic models. The hybrid method can significantly improve the efficiency of stochastic simulations for biochemical networks that contain both species populations and reaction rates with widely varying magnitude. The populations of some species may become negative in the simulation under some circumstances. This dissertation investigates negative population estimates from the hybrid method, proposes several remedies, and tests them with several cases including a realistic biological system. As a key factor that affects the quality of biological models, parameter estimation in stochastic models is challenging because the amount of observed data must be large enough to obtain valid results. To optimize system parameters, the quasi-Newton algorithm for stochastic optimization (QNSTOP) was studied and applied to a stochastic (budding) yeast life cycle model by matching different distributions between simulated results and observed data. Furthermore, to reduce model complexity, this dissertation simplifies the fundamental molecular binding mechanism by the stochastic Hill equation model with optimized system parameters. Considering that many parameter vectors generate similar system dynamics and results, this dissertation proposes a general α-β-γ rule to return an acceptable parameter region of the stochastic Hill equation based on QNSTOP. Different optimization strategies are explored targeting different features of the observed data.

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Davis, Neil Nathaniel. « Dynamic and Stochastic Modeling of Various Components of the Hydrological Cycle for East Africa ». NCSU, 2007. http://www.lib.ncsu.edu/theses/available/etd-05032007-094125/.

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This research has investigated the ability to model precipitation over East Africa using the RegCM regional climate model, and the ability of a stochastic model to predict Lake Victoria lake level one season in advance. The stochastic model was built using precipitation, sea surface temperatures and temperature, and provides detail about the steps used to develop the model. Precipitation modeling was carried out using RegCM and several convective schemes were compared to determine which performed best for East Africa. Additionally the microphysical scheme SUBEX was investigated thoroughly and several tuning parameter changes were made. Finally the precipitation from RegCM was split into 9 rainfall classifications which were then studied to determine how the regional climate model performed for representing rainfall events in the model, in terms of duration, intensity, and overall structure between all the event types.

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Kotze, Kevin Lawrence. « The South African business cycle and the application of dynamic stochastic general equilibrium models ». Thesis, Stellenbosch : Stellenbosch University, 2014. http://hdl.handle.net/10019.1/96055.

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Thesis (PhD)--Stellenbosch University, 2014.
ENGLISH ABSTRACT: This dissertation considers the use of Dynamic Stochastic General Equilibrium (DSGE) models for the analysis of South African macroeconomic business cycle phenomena. It includes four separate, but interrelated parts, which follow a logical sequence. The rst part motivates the use of these models before establishing the theoretical foundations for these models. The theoretical foundations are accompanied by detailed derivations that are used to construct a model for a small open economy. The second part considers the properties of South African macroeconomic data that may be used to estimate the parameters in these models. It includes a discussion of the variables that may be included in such a model, as well as various methods that may be used to extract the business cycle. Thereafter, the sample size for the dataset is established, after investigating for possible structural breaks in the rst two moments of the data, using various univariate and multivariate techniques. The nal chapter of this part contains an investigation into the measures of core in ation, whereby a comparison of trimmed means, dynamic factor models and various wavelet decompositions are applied to data for South Africa. The third part considers the application of the dataset that was identi ed in part two, in a DSGE model that incorporates features that are typical of small open economies. It includes a discussion that relates to the role of the exchange rate in these models, which is found to contain key information. In addition, this part also includes a optimal policy investigation, which considers the reaction function of central bank. The nal part of this thesis considers more recent advances that have been applied to DSGE models for the South African economy. It includes an example of a nonlinear model that is estimated with the aid of a particle lter, which is then used for forecasting purposes. The forecasting results of both linear and nonlinear versions of the model are then compared with the results from various Vector Autoregression (VAR) and Bayesian VAR models.
AFRIKAANSE OPSOMMING: Hierdie proefskrif oorweeg die gebruik van Dinamiese Stogastiese Algemene Ewewig (Engels: Dynamic Stochastic General Equilibrium (DSGE)) modelle vir die analise van besigheidsiklus gebeure in die Suid Afrikaanse makroekonomie. Dit bestaan uit vier aparte dog onderling verwante dele wat in « logiese ontwikkeling vorm. Die eerste deel motiveer die gebruik van dié modelle en daarna word die teoretiese onderbou van die modelle daargestel. Die teoretiese onderbou word aangevul met gedetaileerde stappe van die a eiding van die verhoudings wat gebruik word om « model vir « klein oop ekonomie saam te stel. Die tweede deel oorweeg die eienskappe van Suid Afrikaanse makroekonomiese data wat relevant is vir « ekonometriese model in hierdie konteks. Dit sluit « bespreking in van die veranderlikes wat vir so « model gebruik kan word, asook « bespreking van die verskeie metodes wat gebruik kan word om die besigheidsiklus uit die data te identi seer. Die steekproefgrootte van die data word dan vasgestel, ná die moontlikheid van strukturele onderbrekings van tendens in die eerste en tweede momente van die data ondersoek is met behulp van verskeie enkel en meervoudige-veranderlike tegnieke. Die laaste hoofstuk van dié deel is « studie van verskeie maatstawwe van kern in asie (core in ation), waar « vergelyking getref word tussen die resultate van die volgende metodes toegepas op Suid Afrikaanse data: afgesnede gemiddeldes (trimmed means), dinamiese faktor modelle en verskeie golfvormige onderverdelings (wavelet decompositions). Die derde deel gebruik die datastel, wat in deel twee ontwikkel is, in die passing van « DSGE model wat die tipiese eienskappe van « klein oop ekonomie inkorporeer. Dit sluit « bespreking in van die rol van die wisselkoers in hierdie tipe modelle, en daar word empiries bevind dat die wisselkoers belangrike inligting bevat. Hierdie deel sluit ook « ondersoek in van optimale beleid in terme van die reaksie funksie van die sentrale bank. Die laaste deel van die proefskrif bestudeer die resultate van onlangse ontwikkellinge in DSGE modelle wat toegepas word op die Suid Afrikaanse ekonomie. Dit sluit « voorbeeld van « nie-liniêre model wat met behulp van « partikel lter (particle lter) geskat word en gebruik word vir vooruitskattings. Die vooruitskattings uit beide die liniêre en nie-liniêre modelle word dan vergelyk met dié verkry uit verskeie Vektor

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Boone, Laurence. « An assessment of trend extraction techniques : application to time series decomposition of business cycle and endogenous technical progress ». Thesis, London Business School (University of London), 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.295884.

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Fonseca, Julia Fernandes Araújo da. « Aggregate uncertainty, disappointment aversion and the business cycle ». reponame:Repositório Institucional do FGV, 2013. http://hdl.handle.net/10438/10940.

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We investigate the eff ect of aggregate uncertainty shocks on real variables. More speci fically, we introduce a shock in the volatility of productivity in an RBC model with long-run volatility risk and preferences that exhibit generalised disappointment aversion. We find that, when combined with a negative productivity shock, a volatility shock leads to further decline in real variables, such as output, consumption, hours worked and investment. For instance, out of the 2% decrease in output as a result of both shocks, we attribute 0.25% to the e ffect of an increase in volatility. We also fi nd that this e ffect is the same as the one obtained in a model with Epstein-Zin- Weil preferences, but higher than that of a model with expected utility. Moreover, GDA preferences yield superior asset pricing results, when compared to both Epstein-Zin-Weil preferences and expected utility.

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Brown, Jeffrey R. (Jeffrey Robert) 1968. « Retirement income, bequests, and insurance : implications of mortality risk in a stochastic life cycle model ». Thesis, Massachusetts Institute of Technology, 1999. http://hdl.handle.net/1721.1/9515.

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Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Economics, c1999.
Includes bibliographical references.
This thesis is composed of four studies on the role of annuities and life insurance in the portfolios of elderly households. It has long been known in the economics literature that annuities should be of substantial value in the portfolios of retired individuals. However, outside of private pension plans. the purchase of private annuity contracts is relatively rare. This paper explores the issues associated with this "Annuity Puzzle" using the framework of a life cycle model of consumption, extended to account for mortality uncertainty. Chapter 1 empirically examines household decisions about whether or not to annuitize balances 111 defined contribution pension plans upon retirement. This study calculates a utility based measure of annuity valuation for households nearing retirement, and allows for variation across households to result from variation in mortality rates, risk aversion. marital status, and the presence of pre-existing annuities such as Social Security. It finds that a one percentage point increase in the calculated gain from annuitization is associated with a one percentage point increase in the ex ante probability of annuitizing one's retirement resources. It also finds that the presence of bequest motives has no effect on the disposition of definer.'. contribution plan assets. The finding that bequest motives do not affect marginal annuity decisions is in contrast to some of the previous literature. In particular, previous research has argued that a significant fraction of the elderly are over-annuitized by Social Security, as evidenced by their decision to held life insurance. Chapter 2 re-examines this finding using new and better data on the age 70+ population, and finds little support for the existence of strong bequest motives. One important source of variation in the decision of whether or not to annuitizc is marital status. Chapter 3 explores the demand for joint-life annuity products among marrind couples, and finds that couples should value annuitization less than single individuals. This is because couples have Opportunities to share risk between them, and as such, marriage is a partial substitute for perfect annuity markets. This may help to explain the relative scarcity of private annuity contracts in the U.S. Chapter 4 extends the analysis of annuities to account for inflation risk. It explores the relative value of real versus nominal annuities, and also explores the gains to purchasing annuities that arc linked to an underlying portfolio of risky assets.
by Jeffrey R. Brown.
Ph.D.

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Klowss, Jonah J. « A stochastic mathematical model of 4D tumour speroids with real-time flourescent cell cycle labelling ». Thesis, Queensland University of Technology, 2022. https://eprints.qut.edu.au/232769/1/Jonah_Klowss_Thesis.pdf.

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Tumour spheroid experiments have been used to study the growth of tumours and inform treatment methods for the last 50 years. In this thesis, a novel individual-based mathematical model of tumour spheroid experiments with cell-cycle labelling is developed to study how tumour spheroids with human melanoma cells evolve under laboratory conditions. Qualitative and quantitative analyses demonstrate that mathematical model data compare well with experimental results, and quantitative information about nutrient availability in the spheroid, which is difficult to measure experimentally, is made accessible.

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Rabitsch, Katrin, et Christian Schoder. « Buffer stock savings in a New-Keynesian business cycle model ». WU Vienna University of Economics and Business, 2016. http://epub.wu.ac.at/5158/1/wp231.pdf.

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We introduce the tractable buffer stock savings setup of Carroll (2009 NBER Working Paper) into an otherwise conventional New-Keynesian dynamic stochastic general equilibrium model with financial frictions. The introduction of a precautionary saving motive arising from an uninsurable risk of permanent income loss, affects the model's properties in a number of interesting ways: it produces a more hump-shaped reaction of consumption in response to both supply (technology) and demand (monetary) shocks, and more pronounced reactions in response to demand shocks. Adoption of the buffer stock savings setup thus offers a more microfounded way, compared to, e.g., habit preferences in consumption, to introduce Keynesian features into the model, serving as a device to curbing excessive consumption smoothing, and to attributing a higher role to demand driven fluctuations. We also discuss steady state effects, determinacy properties as well as other practical issues. (authors' abstract)
Series: Department of Economics Working Paper Series

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Pihnastyi, O. M., et V. D. Khodusov. « Stochastic equation of the technological process ». Thesis, Igor Sikorsky Kyiv Polytechnic Institute, 2018. http://repository.kpi.kharkov.ua/handle/KhPI-Press/39059.

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This document presents the construction of a stochastic equation for the process of manufacturing products on a production line. We base our research on the synchronized production line. The minimum size of the inter-operational storage is determined, at which the continuous production is possible. The stochastic equation of the production process is written in canonical form. The definition of the diffusion coefficient for the time of processing of subjects of labour.

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Kirkham, Richard John. « A stochastic whole life cycle cost model for a National Health Service acute care hospital building ». Thesis, University of Liverpool, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.250243.

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Besbes, Khaoula. « Supply chain design with product life cycle considerations ». Thesis, Artois, 2013. http://www.theses.fr/2013ARTO0209/document.

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Notre travail de recherche traite la problématique de la conception d’une chaîne logistique multi-niveaux tout en tenant compte du cycle de vie du produit. Par cycle de vie du produit, nous voulons dire la succession des quatre phases de commercialisation que traverse un produit à travers le temps, à savoir : l’introduction, la croissance, la maturité et le déclin. L’objectif est de mette en place un modèle mathématique qui soit fondé sur une analyse approfondie des différents acteurs de la chaîne, selon la phase du cycle de vie du produit.Trois principaux modèles ont été développés dans cette thèse. Chacun fait l’objet d’un chapitre à part entière.Le premier modèle développé vise à concevoir une chaîne logistique de coût minimum, tout en prenant en considération l’efficacité des différents acteurs potentiels calculée selon plusieurs critères (coût, qualité, innovation, qualité du service, délais de livraisons, …), ainsi que sa variation au cours du cycle de vie du produit. Un deuxième modèle a été mis en place pour la conception d’une chaîne logistique durable, tout en prenant en considération le cycle de vie du produit. Dans ce modèle, trois objectifs différents ont été pris en compte à la fois, à savoir, un objectif économique, un objectif environnemental et un objectif social. Dans les deux premiers modèles, nous avons supposé que le produit aura un cycle de vie classique. Cependant, dans la réalité, ceci n’est pas toujours le cas. En effet, quelques produits connaissent des cycles de vie très atypiques et donc très éloignés de la courbe d’un cycle de vie théorique. Pour ce faire, un troisième modèle stochastique a été proposé pour la conception d’une chaîne logistique robuste, tenant compte des différents scénarios du cycle de vie du produit
Our research addresses the problem of designing a multi-level supply chain, while taking into consideration the product life cycle. By product life cycle, we mean the succession of the four marketing stages that a product goes through since its introduction to the market and until it will be removed from. All products have a life cycle which can be classified into four discrete stages: introduction, growth, maturity and decline.Depending on the product life cycle phases, and based on a thorough analysis of the different supply chain potential actors, this study aims to establish mathematical models to design an efficient supply chain network. Three main models have been developed in this thesis. The first proposed model aims to design a product-driven supply chain with a minimal total cost, taking into consideration the evaluation of the different potential actors effectiveness, according to several criteria (cost, quality, innovation, quality service, timely delivery, ...).A second model was developed to design of a sustainable supply chain network, taking into account the product life cycle. In this model, three different objectives at the time were considered, namely, an economic objective, an environmental objective and a social objective.In the two previous models, we have assumed that the product has a classical life cycle. However, in the reality this is not always the case. Indeed, some products have very atypical life cycles, whose curves are very different from the classical one. To tackle this problem, in the third part of this thesis, we propose a stochastic model to design a robust supply chain network, taking into account the different product life cycle scenarios

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Wang, Shuo. « Analysis and Application of Haseltine and Rawlings's Hybrid Stochastic Simulation Algorithm ». Diss., Virginia Tech, 2016. http://hdl.handle.net/10919/82717.

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Stochastic effects in cellular systems are usually modeled and simulated with Gillespie's stochastic simulation algorithm (SSA), which follows the same theoretical derivation as the chemical master equation (CME), but the low efficiency of SSA limits its application to large chemical networks. To improve efficiency of stochastic simulations, Haseltine and Rawlings proposed a hybrid of ODE and SSA algorithm, which combines ordinary differential equations (ODEs) for traditional deterministic models and SSA for stochastic models. In this dissertation, accuracy analysis, efficient implementation strategies, and application of of Haseltine and Rawlings's hybrid method (HR) to a budding yeast cell cycle model are discussed. Accuracy of the hybrid method HR is studied based on a linear chain reaction system, motivated from the modeling practice used for the budding yeast cell cycle control mechanism. Mathematical analysis and numerical results both show that the hybrid method HR is accurate if either numbers of molecules of reactants in fast reactions are above certain thresholds, or rate constants of fast reactions are much larger than rate constants of slow reactions. Our analysis also shows that the hybrid method HR allows for a much greater region in system parameter space than those for the slow scale SSA (ssSSA) and the stochastic quasi steady state assumption (SQSSA) method. Implementation of the hybrid method HR requires a stiff ODE solver for numerical integration and an efficient event-handling strategy for slow reaction firings. In this dissertation, an event-handling strategy is developed based on inverse interpolation. Performances of five wildly used stiff ODE solvers are measured in three numerical experiments. Furthermore, inspired by the strategy of the hybrid method HR, a hybrid of ODE and SSA stochastic models for the budding yeast cell cycle is developed, based on a deterministic model in the literature. Simulation results of this hybrid model match very well with biological experimental data, and this model is the first to do so with these recently available experimental data. This study demonstrates that the hybrid method HR has great potential for stochastic modeling and simulation of large biochemical networks.
Ph. D.

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Quinn, Katie J. (Katie Julia). « Characterizing cell-cycle as a global regulator of stochastic transcription and noisy gene expression in S. cerevisiae ». Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/91062.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Chemical Engineering, 2014.
Cataloged from PDF version of thesis.
Includes bibliographical references.
Even in the same environment, genetically identical cells can exhibit remarkable variability, or noise, in gene expression. This expression noise impacts the function of gene regulatory networks, depending on its origins. Hence, a prerequisite for understanding or designing gene regulatory networks is characterizing the origins and statistics of the noise. Variability has been largely attributed to the inherently stochastic nature of transcription. Expression statistics from multiple organisms are consistent with an influential model of "bursty" expression, where promoters are generally inactive but infrequently produce multiple mRNA. But fluctuations in the cell environment can also contribute, leaving the origins of noise unclear. We sought to determine the origins of noise in gene expression from the synthetic tetO promoter in S cerevisiae. We use single-molecule mRNA FISH to quantify nuclear and cytoplasmic mRNA in a population expression distribution, and models of stochastic mRNA production and degradation to infer underlying transcriptional dynamics. Rather than transcriptional bursting, we find that noise is driven by large differences in transcriptional activity between the G1 and S/G2/M stage of the cell cycle. Furthermore, we quantitatively characterize these dynamics of transcription by measuring expression in cells arrested at the G1/S and G2/M transition. Promoters activate in S/G2 with probability determined by activator level. mRNA statistics from an active promoter with a single operator are Poisson; expression with multiple operators is more variable. Promoters appear to inactivate at the M/G1 transition, with lower activator levels leading to increased probability of inactivation. Thus below a certain activator threshold, all cells are inactive in G1.mRNA processing and export introduces further variability. Similar analysis of the native, chromatin-regulated PHO5 promoter yields the same results. Hence cell-cycle driven transcription dynamics may be prevalent among regulated yeast genes. The timing of S/G2 activation suggests DNA replication and chromatin maturation may be linked to repressed transcription. Cell-cycle-linked fluctuations in expression are likely to affect gene behavior in regulatory networks. This thesis advocates the importance of cellular context in gene regulation and reveals a novel role of cell-cycle as a driver of eukaryotic transcription, advancing our understanding of stochastic transcription and noise in gene expression.
by Katie J. Quinn.
Ph. D.

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Carr, Michael John. « Estimating parameters of a stochastic cell invasion model with Fluorescent cell cycle labelling using approximate Bayesian computation ». Thesis, Queensland University of Technology, 2021. https://eprints.qut.edu.au/226946/1/Michael_Carr_Thesis.pdf.

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Understanding the underlying mechanisms of melanoma cell behaviour is crucial to developing better drug treatment methods. In this thesis, we use advanced mathematical modelling and statistical inference techniques to obtain, for the first time, accurate estimates of the rates at which cells multiply and spread at multiple stages of the cell cycle. The mathematical model is fitted to data that uses fluorescent cell cycle labelling technology to visualise different phases of the cell cycle in real time. The accurately calibrated mathematical model enables a deeper understanding of cell behaviour and has potential for more precisely assessing treatment efficacy.

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Hagan, Michael A. « LIFE CYCLE ASSESSMENT OF BIOMASS HARVESTING FOR ON-FARM BIOFUEL PRODUCTION ». UKnowledge, 2015. http://uknowledge.uky.edu/bae_etds/31.

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Understanding the energy input and emissions resulting from the development of biofuels is important to quantify the overall benefit of the biofuel. As part of the On-Farm Biomass Processing project, a life cycle assessment (LCA) was conducted on the process to harvest and transport agricultural crop residues ready for processing into biofuel. A Microsoft Excel model was developed that inventories the entire life cycle of the process, including incorporation of stochastic analysis within the model. The LCA results of the agricultural equipment manufacture are presented, along with the results of each step of the process, including fertilizer addition, single pass harvest, double pass harvest, and transport from the field to processing facility. Various methods of analyzing co-products are also presented for the single pass harvesting step, in which comparisons between market based, mass based and process-purpose based allocation methods are reviewed. The process-purpose based method of fuel consumption difference between combine operation in conventional harvest versus single pass harvest is determined to be the most realistic of the process. A detailed comparison of the energy and emission differences between single pass and double pass harvesting is given, along with the total LCA results of harvesting and transporting the biomass.

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Ahmadian, Mansooreh. « Hybrid Modeling and Simulation of Stochastic Effects on Biochemical Regulatory Networks ». Diss., Virginia Tech, 2020. http://hdl.handle.net/10919/99481.

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A complex network of genes and proteins governs the robust progression through cell cycles in the presence of inevitable noise. Stochastic modeling is viewed as a key paradigm to study the effects of intrinsic and extrinsic noise on the dynamics of biochemical networks. A detailed quantitative description of such complex and multiscale networks via stochastic modeling poses several challenges. First, stochastic models generally require extensive computations, particularly when applied to large networks. Second, the accuracy of stochastic models is highly dependent on the quality of the parameter estimation based on experimental observations. The goal of this dissertation is to address these problems by developing new efficient methods for modeling and simulation of stochastic effects in biochemical systems. Particularly, a hybrid stochastic model is developed to represent a detailed molecular mechanism of cell cycle control in budding yeast cells. In a single multiscale model, the proposed hybrid approach combines the advantages of two regimes: 1) the computational efficiency of a deterministic approach, and 2) the accuracy of stochastic simulations. The results show that this hybrid stochastic model achieves high computational efficiency while generating simulation results that match very well with published experimental measurements. Furthermore, a new hierarchical deep classification (HDC) algorithm is developed to address the parameter estimation problem in a monomolecular system. The HDC algorithm adopts a neural network that, via multiple hierarchical search steps, finds reasonably accurate ranges for the model parameters. To train the neural network in the presence of experimental data scarcity, the proposed method leverages the domain knowledge from stochastic simulations to generate labeled training data. The results show that the proposed HDC algorithm yields accurate ranges for the model parameters and highlight the potentials of model-free learning for parameter estimation in stochastic modeling of complex biochemical networks.
Doctor of Philosophy
Cell cycle is a process in which a growing cell replicates its DNA and divides into two cells. Progression through the cell cycle is regulated by complex interactions between networks of genes, transcripts, and proteins. These interactions inside the confined volume of a cell are subject to inherent noise. To provide a quantitative description of the cell cycle, several deterministic and stochastic models have been developed. However, deterministic models cannot capture the intrinsic noise. In addition, stochastic modeling poses the following challenges. First, stochastic models generally require extensive computations, particularly when applied to large networks. Second, the accuracy of stochastic models is highly dependent on the accuracy of the estimated model parameters. The goal of this dissertation is to address these challenges by developing new efficient methods for modeling and simulation of stochastic effects in biochemical networks. The results show that the proposed hybrid model that combines stochastic and deterministic modeling approaches can achieve high computational efficiency while generating accurate simulation results. Moreover, a new machine learning-based method is developed to address the parameter estimation problem in biochemical systems. The results show that the proposed method yields accurate ranges for the model parameters and highlight the potentials of model-free learning for parameter estimation in stochastic modeling of complex biochemical networks.

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Dessalles, Renaud. « Stochastic models for protein production : the impact of autoregulation, cell cycle and protein production interactions on gene expression ». Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLX005/document.

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Le mécanisme de production des protéines, qui monopolise la majorité des ressources d'une bactérie, est hautement stochastique: chaque réaction biochimique qui y participe est due à des collisions aléatoires entre molécules, potentiellement présentes en petites quantités. La bonne compréhension de l'expression génétique nécessite donc de recourir à des modèles stochastiques qui sont à même de caractériser les différentes origines de la variabilité dans la production ainsi que les dispositifs biologiques permettant éventuellement de la contrôler.Dans ce contexte, nous avons analysé la variabilité d'une protéine produite avec un mécanisme d'autorégulation négatif: c'est-à-dire dans le cas où la protéine est un répresseur pour son propre gène. Le but est de clarifier l'effet de l'autorégulation sur la variance du nombre de protéines exprimées. Pour une même production moyenne de protéine, nous avons cherché à comparer la variance à l'équilibre d'une protéine produite avec le mécanisme d'autorégulation et celle produite en « boucle ouverte ». En étudiant un modèle limite, avec une mise à l'échelle (scaling), nous avons pu faire une telle comparaison de manière analytique. Il apparaît que l'autorégulation réduit effectivement la variance, mais cela reste néanmoins limité : un résultat asymptotique montre que la variance ne pourra pas être réduite de plus de 50%. L'effet sur la variance à l'équilibre étant modéré, nous avons cherché un autre effet possible de l'autorégulation: nous avons observé que la vitesse de convergence à l'équilibre est plus rapide dans le cadre d'un modèle avec autorégulation.Les modèles classiques de production des protéines considèrent un volume constant, sans phénomènes de division ou de réplication du gène, avec des ARN-polymérases et les ribosomes en concentrations constantes. Pourtant, les variation au cours du cycle de chacune de ces quantités a été proposée dans la littérature comme participant à la variabilité des protéines. Nous proposons une série de modèles de complexité croissante qui vise à aboutir à une représentation réaliste de l'expression génétique. Dans un modèle avec un volume suivant le cycle cellulaire, nous intégrons successivement le mécanisme de production des protéines (transcription et traduction), la répartition aléatoire des composés à la division et la réplication du gène. Le dernier modèle intègre enfin l'ensemble des gènes de la cellule et considère leurs interactions dans la production des différentes protéines à travers un partage commun des ARN-polymérases et des ribosomes, présents en quantités limitées. Pour les modèles où cela était possible, la moyenne et la variance de la concentration de chacune des protéines ont été déterminées analytiquement en ayant eu recours au formalisme des Processus Ponctuels de Poisson Marqués. Pour les cas plus complexes, nous avons estimé la variance au moyen de simulations stochastiques. Il apparaît que, dans l'ensemble des mécanismes étudiés, la source principale de la variabilité provient du mécanisme de production des protéines lui-même (bruit dit « intrinsèque »). Ensuite, parmi les autres aspects « extrinsèques », seule la répartition aléatoire des composés semble avoir potentiellement un effet significatif sur la variance; les autres ne montrent qu'un effet limité sur la concentration des protéines. Ces résultats ont été confrontés à certaines mesures expérimentales, et montrent un décalage encore inexpliqué entre la prédiction théorique et les données biologiques, ce qui appelle à de nouvelles hypothèses quant aux possibles sources de variabilité.En conclusion, les processus étudiés ont permis une meilleure compréhension des phénomènes biologiques en explorant certaines hypothèses difficilement testables expérimentalement. Des modèles étudiés, nous avons pu dégager théoriquement certaines tendances, montrant que la modélisation stochastique est un outil important pour la bonne compréhension des mécanismes d'expression génétique
The mechanism of protein production, to which is dedicated the majority of resources of the bacteria, is highly stochastic: every biochemical reaction that is involved in this process is due to random collisions between molecules, potentially present in low quantities. The good understanding of gene expression requires therefore to resort to stochastic models that are able to characterise the different origins of protein production variability as well as the biological devices that potentially control it.In this context, we have analysed the variability of a protein produced with a negative autoregulation mechanism: i.e. in the case where the protein is a repressor of its own gene. The goal is to clarify the effect of this feedback on the variance of the number of produced proteins. With the same average protein production, we sought to compare the equilibrium variance of a protein produced with the autoregulation mechanism and the one produced in “open loop”. By studying the model under a scaling regime, we have been able to perform such comparison analytically. It appears that the autoregulation indeed reduces the variance; but it is nonetheless limited: an asymptotic result shows that the variance won't be reduced by more than 50%. The effect on the variance being moderate, we have searched for another possible effect for autoregulation: it havs been observed that the convergence to equilibrium is quicker in the case of a model with autoregulation.Classical models of protein production usually consider a constant volume, without any division or gene replication and with constant concentrations of RNA-polymerases and ribosomes. Yet, it has been suggested in the literature that the variations of these quantities during the cell cycle may participate to protein variability. We propose a series of models of increasing complexity that aims to reach a realistic representation of gene expression. In a model with a changing volume that follows the cell cycle, we integrate successively the protein production mechanism (transcription and translation), the random segregation of compounds at division, and the gene replication. The last model integrates then all the genes of the cell and takes into account their interactions in the productions of different proteins through a common sharing of RNA-polymerases and ribosomes, available in limited quantities. For the models for which it was possible, the mean and the variance of the concentration of each proteins have been analytically determined using the Marked Poisson Point Processes. In the more complex cases, we have estimated the variance using computational simulations. It appears that, among all the studied mechanisms, the main source of variability comes from the protein production mechanism itself (referred as “intrinsic noise”). Then, among the other “extrinsic” aspects, only the random segregation of compounds at division seems to have potentially a significant impact on the variance; the other aspects show only a limited effect on protein concentration. These results have been confronted to some experimental measures, and show a still unexplained decay between the theoretical predictions and the biological data; it instigates the formulations of new hypotheses for other possible sources of variability.To conclude, the processes studied have allowed a better understanding of biological phenomena by exploring some hypotheses that are difficult to test experimentally. In the studied models, we have been able to indicate theoretically some trends; hence showing that the stochastic modelling is an important tool for a good understanding of gene expression mechanisms

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Ahn, Tae-Hyuk. « Computational Techniques for the Analysis of Large Scale Biological Systems ». Diss., Virginia Tech, 2012. http://hdl.handle.net/10919/77162.

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An accelerated pace of discovery in biological sciences is made possible by a new generation of computational biology and bioinformatics tools. In this dissertation we develop novel computational, analytical, and high performance simulation techniques for biological problems, with applications to the yeast cell division cycle, and to the RNA-Sequencing of the yellow fever mosquito. Cell cycle system evolves stochastic effects when there are a small number of molecules react each other. Consequently, the stochastic effects of the cell cycle are important, and the evolution of cells is best described statistically. Stochastic simulation algorithm (SSA), the standard stochastic method for chemical kinetics, is often slow because it accounts for every individual reaction event. This work develops a stochastic version of a deterministic cell cycle model, in order to capture the stochastic aspects of the evolution of the budding yeast wild-type and mutant strain cells. In order to efficiently run large ensembles to compute statistics of cell evolution, the dissertation investigates parallel simulation strategies, and presents a new probabilistic framework to analyze the performance of dynamic load balancing algorithms. This work also proposes new accelerated stochastic simulation algorithms based on a fully implicit approach and on stochastic Taylor expansions. Next Generation RNA-Sequencing, a high-throughput technology to sequence cDNA in order to get information about a sample's RNA content, is becoming an efficient genomic approach to uncover new genes and to study gene expression and alternative splicing. This dissertation develops efficient algorithms and strategies to find new genes in Aedes aegypti, which is the most important vector of dengue fever and yellow fever. We report the discovery of a large number of new gene transcripts, and the identification and characterization of genes that showed male-biased expression profiles. This basic information may open important avenues to control mosquito borne infectious diseases.
Ph. D.

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Schlichting, Julia Katharina. « Modeling synchronization effects in the yeast cell cycle ». Doctoral thesis, Humboldt-Universität zu Berlin, 2019. http://dx.doi.org/10.18452/19835.

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Saccharomyces cerevisiae ist ein bekanntester Modellorganismen in der Systembiologie, der häufig zur Untersuchung des mitotischen Zellzyklus eukaryotischer Zellen verwendet wird. Des Zellzyklus wird durch Cycline, Cyclin-abhängige Kinasen (CDK) und CDK-Inhibitoren (CKI) reguliert. Der wichtigste Kontrollpunkt innerhalb des Zellzyklus reguliert den Übergang von der G1 in die S Phase und wird START genannt. Im dieser Arbeit verwenden wir einen stochastischen Modellierungsansatz, um die Auswirkungen verschiedener Synchronisationsmethoden auf den Zellzyklus zu untersuchen. Um Modellparameter zu schätzen, kombinieren wir Phasen aufgelöste mRNA-Verteilungen unsynchronisierter Einzelzellen und Protein-Zeitreihen synchronisierter Zellpopulationen. Somit können wir mRNA-Dynamiken für ausgewählte Synchronisationsmethoden vorhersagen. In einem zweistufigen Optimierungsansatz unterscheiden wir zwischen mRNA- und Protein-Ebene. Die Parameterschätzung basiert auf der Maximum-Likelihood-Methode. Die Phasen aufgelösten mRNA-Verteilungen wurden mithilfe der smFISH-Technik für SIC1, CLN2 und CLB5 gemessen. Die Protein-Zeitreihen wurden mithilfe von Western Blots für entsprechenden Proteine gemessen. Die gemessenen Moleküle sind die Hauptregulatoren des G1-S Phasenübergangs, welche die Komponenten unseres Zellzyklusmodells darstellen. Durch die erfolgreiche Integration von qualitativ unterschiedlichen Datentypen in der Parameterschätzung konnten wir eine systematische Analyse von Synchronisationseffekten auf den Zellzyklus durchführen. Der zeitlicher Ablauf des Zellzyklus ist dabei maßgeblich beeinflusst. Die stärksten zeitlichen Veränderungen weist die Synchronisation mit alpha-Faktor auf. Elutrierte Zellen sind den unsynchronisierten Zellen trotz verlängerter G1 Phase am ähnlichsten. Wir zeigen in dieser Arbeit, dass synchronisierte Zellpopulationen unzureichend sind, um Rückschlüsse auf den Zellzyklus unsynchronisierter Zellen zu ziehen.
cell cycle, G1/S transition, stochastic modeling, parameter estimation, smFISH, singel cells, Western blotting, cell populations Saccharomyces cerevisiae is a famous model organism in systems biology to study the mitotic cell cycle in eukaryotic cells. The cell cycle is a highly controlled process which is regulated by cyclins, cycline-dependent kinases (CDK) and cyclin-dependent kinase inhibitors (CKI). The main kinase involved in cell cycle regulation is Cdc28. START is the most important check point and controls the G1 to S phase transition. At this point, cells decide if they enter a new cell division cycle or not. In this study, we analyze influences of different synchronization methods on the cell cycle and differences between unsynchronized and synchronized cells by using a stochastic modeling approach. We combine phase-resolved mRNA distributions of unsynchronized single cells and protein time courses of synchronized cell populations to estimate model parameters and to predict synchronization specific mRNA dynamics. Parameter estimation is based on a maximum likelihood approach and performed in a 2-step-optimization in which we differentiate between mRNA and protein level. We measured phase-resolved mRNA distributions of mRNA species SIC1, CLN2 and CLB5 by smFISH and protein time courses of protein species Sic1, Cln2 and Clb5 by Western blotting. These molecules are key regulators of the G1 to S phase transition and represent components of our cell cycle model. By integrating qualitatively different data types in parameter estimation, we come up with a systematic analysis of synchronization effects on the cell cycle. Cell cycle timing is mainly responsible for differences between unsynchronized and synchronized cells and is mostly affected in alpha-factor synchronized cells. Ignoring the prolongation of the G1 phase, elutriated cells are most similar to unsynchronized cells. We show that synchronized cell populations are insufficient to derive general cell cycle behavior of unsynchronized cells.

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Jaster, Nicole. « Ratchet models of molecular motors ». Phd thesis, Universität Potsdam, 2003. http://opus.kobv.de/ubp/volltexte/2005/90/.

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Transportvorgänge in und von Zellen sind von herausragender Bedeutung für das Überleben des Organismus. Muskeln müssen sich kontrahieren können, Chromosomen während der Mitose an entgegengesetzte Enden der Zelle bewegt und Organellen, das sind von Membranen umschlossene Kompartimente, entlang molekularer Schienen transportiert werden.
Molekulare Motoren sind Proteine, deren Hauptaufgabe es ist, andere Moleküle zu bewegen. Dazu wandeln sie die bei der ATP-Hydrolyse freiwerdende chemische Energie in mechanische Arbeit um. Die Motoren des Zellskeletts gehören zu den drei Superfamilien Myosin, Kinesin und Dynein. Ihre Schienen sind Filamente des Zellskeletts, Actin und die Microtubuli.
In dieser Arbeit werden stochastische Modelle untersucht, welche dazu dienen, die Fortbewegung dieser linearen molekularen Motoren zu beschreiben. Die Skala, auf der wir die Bewegung betrachten, reicht von einzelnen Schritten eines Motorproteins bis in den Bereich der gerichteten Bewegung entlang eines Filaments. Ein Einzelschritt überbrückt je nach Protein etwa 10 nm und wird in ungefähr 10 ms zurückgelegt. Unsere Modelle umfassen M Zustände oder Konformationen, die der Motor annehmen kann, während er sich entlang einer eindimensionalen Schiene bewegt. An K Orten dieser Schiene sind Übergänge zwischen den Zuständen möglich. Die Geschwindigkeit des Proteins lässt sich in Abhängigkeit von den vertikalen Übergangsraten zwischen den einzelnen Zuständen analytisch bestimmen. Wir berechnen diese Geschwindigkeit für Systeme mit bis zu vier Zuständen und Orten und können weiterhin eine Reihe von Regeln ableiten, die uns einschätzen helfen, wie sich ein beliebiges vorgegebenes System verhalten wird.
Darüber hinaus betrachten wir entkoppelte Subsysteme, also einen oder mehrere Zustände, die keine Verbindung zum übrigen System haben. Mit einer bestimmten Wahrscheinlichkeit kann ein Motor einen Zyklus von Konformationen durchlaufen, mit einer anderen Wahrscheinlichkeit einen davon unabhängigen anderen.
Aktive Elemente werden in realen Transportvorgängen durch Motorproteine nicht auf die Übergänge zwischen den Zuständen beschränkt sein. In verzerrten Netzwerken oder ausgehend von der diskreten Mastergleichung des Systems können auch horizontale Raten spezifiziert werden und müssen weiterhin nicht mehr die Bedingungen der detaillierten Balance erfüllen. Damit ergeben sich eindeutige, komplette Pfade durch das jeweilige Netzwerk und Regeln für die Abhängigkeit des Gesamtstroms von allen Raten des Systems. Außerdem betrachten wir die zeitliche Entwicklung für vorgegebene Anfangsverteilungen.
Bei Enzymreaktionen gibt es die Idee des Hauptpfades, dem diese bevorzugt folgen. Wir bestimmen optimale Pfade und den maximalen Fluss durch vorgegebene Netzwerke.
Um darüber hinaus die Geschwindigkeit des Motors in Abhängigkeit von seinem Treibstoff ATP angeben zu können, betrachten wir mögliche Reaktionskinetiken, die den Zusammenhang zwischen den unbalancierten Übergangsraten und der ATP-Konzentration bestimmen. Je nach Typ der Reaktionskinetik und Anzahl unbalancierter Raten ergeben sich qualitativ unterschiedliche Verläufe der Geschwindigkeitskurven in Abhängigkeit von der ATP-Konzentration.
Die molekularen Wechselwirkungspotentiale, die der Motor entlang seiner Schiene erfährt, sind unbekannt.Wir vergleichen unterschiedliche einfache Potentiale und die Auswirkungen auf die Transportkoeffizienten, die sich durch die Lokalisation der vertikalen Übergänge im Netzwerkmodell im Vergleich zu anderen Ansätzen ergeben.
Transport processes in and of cells are of major importance for the survival of the organism. Muscles have to be able to contract, chromosomes have to be moved to opposing ends of the cell during mitosis, and organelles, which are compartments enclosed by membranes, have to be transported along molecular tracks.
Molecular motors are proteins whose main task is moving other molecules.For that purpose they transform the chemical energy released in the hydrolysis of ATP into mechanical work. The motors of the cytoskeleton belong to the three super families myosin, kinesin and dynein. Their tracks are filaments of the cytoskeleton, namely actin and the microtubuli.
Here, we examine stochastic models which are used for describing the movements of these linear molecular motors. The scale of the movements comprises the regime of single steps of a motor protein up to the directed walk along a filament. A single step bridges around 10 nm, depending on the protein, and takes about 10 ms, if there is enough ATP available. Our models comprise M states or conformations the motor can attain during its movement along a one-dimensional track. At K locations along the track transitions between the states are possible. The velocity of the protein depending on the transition rates between the single states can be determined analytically. We calculate this velocity for systems of up to four states and locations and are able to derive a number of rules which are helpful in estimating the behaviour of an arbitrary given system.
Beyond that we have a look at decoupled subsystems, i.e., one or a couple of states which have no connection to the remaining system. With a certain probability a motor undergoes a cycle of conformational changes, with another probability an independent other cycle.
Active elements in real transport processes by molecular motors will not be limited to the transitions between the states. In distorted networks or starting from the discrete Master equation of the system, it is possible to specify horizontal rates, too, which furthermore no longer have to fulfill the conditions of detailed balance. Doing so, we obtain unique, complete paths through the respective network and rules for the dependence of the total current on all the rates of the system. Besides, we view the time evolutions for given initial distributions.
In enzymatic reactions there is the idea of a main pathway these reactions follow preferably. We determine optimal paths and the maximal flow for given networks.
In order to specify the dependence of the motor's velocity on its fuel ATP, we have a look at possible reaction kinetics determining the connection between unbalanced transitions rates and ATP-concentration. Depending on the type of reaction kinetics and the number of unbalanced rates, we obtain qualitatively different curves connecting the velocity to the ATP-concentration.
The molecular interaction potentials the motor experiences on its way along its track are unknown. We compare different simple potentials and the effects the localization of the vertical rates in the network model has on the transport coefficients in comparison to other models.

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Mrad, Houda. « Business cycle fluctuations and monetary policy in emerging economies ». Thesis, Aix-Marseille, 2018. http://www.theses.fr/2018AIXM0187.

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Dans cette thèse nous examinons différents aspects des fluctuations dans les économies émergentes. Premièrement, afin d’établir les régularités empiriques de ces pays nous examinons le contexte économique des pays du Moyen Orient et d’Afrique du Nord. Ensuite, nous estimons un modèle des cycles réels pour essayer de reproduire les faits stylisés de ces pays, mais aussi pour évaluer la performance de ces modèles néoclassiques augmentés de deux types de chocs de productivité transitoire et permanent. Ceci fait l’objet du chapitre 2 dont le résultat est en faveur de l'hypothèse "Le cycle c'est la tendance" . Le deuxième aspect porte sur l’importance des frictions financières, il est traité dans le troisième chapitre qui introduit des chocs financiers au modèle de croissance stochastique. Nous identifions le rôle des frictions financières dans l’économie tunisienne comme étant un amplificateur de l’effet des chocs de productivité. Le quatrième chapitre porte sur l'analyse de la politique monétaire. Premièrement, nous examinons le régime de ciblage d’inflation où nos résultats empiriques supportent une implémentation de la stricte version du ciblage d’inflation avec une fonction de réaction basée sur des prévisions de l'inflation. Deuxièmement, nous exploitant les règles monétaires optimales en présence de la rigidité d l'information dans le cadre d’un modèle stochastique d’équilibre général (DSGE). Nos résultats, révèlent que les chocs du taux de marge de la force de travail jouent un rôle important dans les fluctuations de l’économie tunisienne, la règle de Taylor produit un taux satisfaisant de bien être, alors que les règles qui ciblent le niveau de prix ne sont pas efficaces
This thesis investigates different aspects of the fluctuations in emerging economies. First, it examines the MENA countries’ context to establish the empirical regularities. Then, to replicate the MENA countries’ business cycle patterns observed in the annual data, we estimate a standard real business cycle (RBC) model to assess the performance of the neoclassical model with transitory and permanent shocks. This is the purpose of chapter 2 which results support the assumption "The cycle is the trend". The second aspect refers to the importance of financial frictions and is addressed in the third chapter which adds new financial shocks to the stochastic growth model. We determine the role of financial frictions in the Tunisian economy not as the source of business cycle fluctuations but as an amplifier of the effects of total factor of productivity shocks.The fourth chapter analyzes monetary policy in emerging economies. Firstly, we examine the inflation targeting regime under the lens of a New Keynesian forward-looking model. We also, estimate a Taylor rule and some other alternatives in order to determine which rule to adopt within this framework. Empirical results support the implementation of a strict inflation targeting regime, with an inflation forecast based rule as a reaction function. Secondly, we explore the optimal monetary policy rules using a New Keynesian DSGE model. In particular we assume that information stickiness as the only type of rigidity in the model. We find that Whereas, Taylor rule in its original version provides substantial welfare gains, price-level targeting regime was suboptimal

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Tino, Clayton P. « Wind models and stochastic programming algorithms for en route trajectory prediction and control ». Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/50242.

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There is a need for a fuel-optimal required time of arrival (RTA) mode for aircraft flight management systems capable of enabling controlled time of arrival functionality in the presence of wind speed forecast uncertainty. A computationally tractable two-stage stochastic algorithm utilizing a data-driven, location-specific forecast uncertainty model to generate forecast uncertainty scenarios is proposed as a solution. Three years of Aircraft Communications Addressing and Reporting Systems (ACARS) wind speed reports are used in conjunction with corresponding wind speed forecasts from the Rapid Update Cycle (RUC) forecast product to construct an inhomogeneous Markov model quantifying forecast uncertainty characteristics along specific route through the national airspace system. The forecast uncertainty modeling methodology addresses previously unanswered questions regarding the regional uncertainty characteristics of the RUC model, and realizations of the model demonstrate a clear tendency of the RUC product to be positively biased along routes following the normal contours of the jet stream. A two-stage stochastic algorithm is then developed to calculate the fuel optimal stage one cruise speed given a required time of arrival at a destination waypoint and wind forecast uncertainty scenarios generated using the inhomogeneous Markov model. The algorithm utilizes a quadratic approximation of aircraft fuel flow rate as a function of cruising Mach number to quickly search for the fuel-minimum stage one cruise speed while keeping computational footprint small and ensuring RTA adherence. Compared to standard approaches to the problem utilizing large scale linear programming approximations, the algorithm performs significantly better from a computational complexity standpoint, providing solutions in fractional power time while maintaining computational tractability in on-board systems.

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Zhu, Shaoming. « Multiscale analysis of protein functions and stochastic modelling of gene transcriptional regulatory networks ». Thesis, Queensland University of Technology, 2010. https://eprints.qut.edu.au/41693/1/Shaoming_Zhu_Thesis.pdf.

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Genomic and proteomic analyses have attracted a great deal of interests in biological research in recent years. Many methods have been applied to discover useful information contained in the enormous databases of genomic sequences and amino acid sequences. The results of these investigations inspire further research in biological fields in return. These biological sequences, which may be considered as multiscale sequences, have some specific features which need further efforts to characterise using more refined methods. This project aims to study some of these biological challenges with multiscale analysis methods and stochastic modelling approach. The first part of the thesis aims to cluster some unknown proteins, and classify their families as well as their structural classes. A development in proteomic analysis is concerned with the determination of protein functions. The first step in this development is to classify proteins and predict their families. This motives us to study some unknown proteins from specific families, and to cluster them into families and structural classes. We select a large number of proteins from the same families or superfamilies, and link them to simulate some unknown large proteins from these families. We use multifractal analysis and the wavelet method to capture the characteristics of these linked proteins. The simulation results show that the method is valid for the classification of large proteins. The second part of the thesis aims to explore the relationship of proteins based on a layered comparison with their components. Many methods are based on homology of proteins because the resemblance at the protein sequence level normally indicates the similarity of functions and structures. However, some proteins may have similar functions with low sequential identity. We consider protein sequences at detail level to investigate the problem of comparison of proteins. The comparison is based on the empirical mode decomposition (EMD), and protein sequences are detected with the intrinsic mode functions. A measure of similarity is introduced with a new cross-correlation formula. The similarity results show that the EMD is useful for detection of functional relationships of proteins. The third part of the thesis aims to investigate the transcriptional regulatory network of yeast cell cycle via stochastic differential equations. As the investigation of genome-wide gene expressions has become a focus in genomic analysis, researchers have tried to understand the mechanisms of the yeast genome for many years. How cells control gene expressions still needs further investigation. We use a stochastic differential equation to model the expression profile of a target gene. We modify the model with a Gaussian membership function. For each target gene, a transcriptional rate is obtained, and the estimated transcriptional rate is also calculated with the information from five possible transcriptional regulators. Some regulators of these target genes are verified with the related references. With these results, we construct a transcriptional regulatory network for the genes from the yeast Saccharomyces cerevisiae. The construction of transcriptional regulatory network is useful for detecting more mechanisms of the yeast cell cycle.

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He, Junkai. « Effective models and methods for stochastic disassembly line problems ». Thesis, université Paris-Saclay, 2020. http://www.theses.fr/2020UPASE009.

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L'étude du désassemblage des produits en fin de vie (EOL) sous incertitude est un sujet de recherche important en raison de ses avantages en termes de réduction de déchets, d'économie de ressources non-renouvelables et de protection de l'environnement. Les travaux existants sur les lignes de désassemblage supposent que l'information incertaine peut être estimée par des lois de probabilité ou par des fonctions et se focalisent seulement sur des problèmes stochastiques d'équilibrage de ces lignes. Cependant, il n'est pas toujours possible d'obtenir l'information incertaine complète dû à un manque de données historiques ou d'un volume excessif de données. De plus, le problème intégré des lignes de désassemblage a rarement été abordé. Dans cette thèse, quatre nouveaux problèmes stochastiques des lignes de désassemblage avec seulement à disposition l'information incertaine partielle sont investigués. L'objectif est de proposer des modèles et des méthodes efficaces pour ces problèmes. Les principaux travaux apportés par cette thèse sont les suivants :Premièrement, un nouveau problème stochastique d'équilibrage des lignes de désassemblage (SDLBP) est étudié dans le but de minimiser le coût des lignes avec les durées incertaines d'exécution des tâches, en ne tenant compte que de la moyenne, de l'écart-type et de la borne supérieure du taux de changement. Un modèle avec chance-contrainte est d'abord établi, qui est par la suite transformé approximativement en un modèle distribution-free basé sur l'analyse des propriétés. Ensuite, une heuristique est développée pour résoudre le modèle transformé. Des résultats expérimentaux montrent que le modèle distribution-free peut résoudre efficacement ce SDLBP avec de l'information incertaine partielle.Dans la plupart des travaux existants, le temps de cycle qui représente le temps d'achèvement maximal des postes de travail est prédéterminé. Cependant, le coût des lignes de désassemblage et le temps de cycle sont deux critères de performance contradictoires et s'impactent mutuellement. Un nouveau SDLBP bi-objectif est investi pour minimiser le coût des lignes et le temps de cycle, où seule l'information partielle des durées des tâches est requise. Un modèle bi-objectif distribution-free est construit et une méthode ε-contrainte améliorée est conçue. Des expériences montrent que la méthode ε-contrainte proposée peut réduire de plus de 90% le nombre d'itérations par rapport à la méthode ε-contrainte classique.Ces lignes pourraient générer des pollutions pendant le processus de désassemblage des produits EOL, néanmoins ce facteur n'a pas été considéré dans les précédents travaux. Nous nous intéressons à un nouveau SDLBP vert afin de minimiser le coût des lignes et la pollution, dans lequel des postes de travail avec des prix d'achat différents peuvent générer des quantités différentes de pollution. Un nouveau modèle bi-objectif est formulé et une méthode ε-contrainte spécifique au problème est proposée. Des résultats expérimentaux révèlent qu'un choix approprié des postes de travail peut effectivement réduire la pollution d'une ligne de désassemblage.L'optimisation intégrée d'équilibrage et de planification des lignes de désassemblage, qui n'a pas été étudiée auparavant, pourrait améliorer l'efficacité du système de désassemblage et réduire ses dépenses. Un problème stochastique intégré d'équilibrage et de planification des lignes de désassemblage (ISDLBPP) est adressé pour minimiser le coût global du système, où les ratios d'obtention des composantes et leur demande sont supposés être incertains. Une programmation stochastique à deux étapes est construite et des inégalités valides sont proposées pour réduire l'espace de recherche. Puis, des méthodes sample average approximation (SAA) et L-shaped sont proposées pour ce problème. Des expériences montrent que le temps de calcul moyen de la méthode L-shaped est seulement de 60% de celui de la méthode SAA, avec une qualité de solution comparable
Studying the disassembly of End-of-Life (EOL) products under uncertainty is becoming a hot research topic due to its benefits in reducing waste, saving non-renewable resources, and protecting the environment. Existing disassembly line works assume that stochastic information can be estimated as probability distributions or functions and most of them focus on stochastic disassembly line balancing problems. However, it is not always possible to obtain complete stochastic information due to a lack of historical data or excessive data volume, and the integrated disassembly line problem has been rarely addressed. In this thesis, four novel stochastic disassembly line problems with only partial stochastic information are investigated. The purpose is to propose effective models and solution methods for the considered problems. The main works of this thesis are:Firstly, a new stochastic disassembly line balancing problem (SDLBP) is studied to minimize the disassembly line cost under stochastic task processing times, given only the mean, standard deviation, and change-rate upper bound. For the problem, a chance-constrained model is first formulated, which is further approximately transformed into a distribution-free model by property analysis. Then, a fast heuristic is devised to solve the transformed model. Experimental results demonstrate that the distribution-free model can effectively solve the SDLBP with only partial stochastic information.In most existing literature, the cycle time that represents the maximum completion time among workstations is given. However, the disassembly line cost and cycle time are two conflicting performance criteria and impact mutually. In this thesis, a new bi-objective distribution-free SDLBP is studied to minimize the disassembly line cost and cycle time, where partial information of task processing times is required. For the problem, a bi-objective distribution-free model is constructed, and an improved ε-constraint method is designed. Numerical experiments show that the proposed method can reduce more than 90% computation rounds, compared with the basic ε-constraint method.Disassembly lines may generate pollution during separating EOL products, but this factor has not been considered in the previous SDLBP works. In this thesis, we study a new green-oriented distribution-free SDLBP to minimize the disassembly line cost and pollution emission simultaneously, in which workstations with different purchase prices can have different amounts of pollution emissions. For the problem, a new bi-objective model is formulated and a problem-specific ε-constraint method is devised. Experimental results show that selecting appropriately workstations can effectively reduce the pollution emission of a disassembly line. Besides, some managerial insights are discussed.The integrated optimization of disassembly line balancing and planning may enhance the efficiency of the disassembly system and reduce its expenses, which has not been studied before. In this thesis, an integrated stochastic disassembly line balancing and planning problem (ISDLBPP) is addressed to minimize the overall system cost, where component demands and component yield ratios are assumed to be uncertain. For the problem, a two-stage stochastic programming model is established and valid inequalities are devised to reduce the search space. Then, the sample average approximation (SAA) method and the L-shaped method are applied to solve the model. Numerical experiments show that the L-shaped method can save more than 60% computation time than the SAA method, without sacrificing solution quality

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Huang, Shih-Yun. « Real investment and dividend policy in a dynamic stochastic general equilibrium (DSGE) model : corporate finance at an aggregate level through DSGE models ». Thesis, University of Bradford, 2010. http://hdl.handle.net/10454/5440.

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In this thesis, I take a theoretical dynamic stochastic general equilibrium (DSGE) approach to investigate optimal aggregate dividend policy. I make the following contribution: 1. I extend the standard DSGE model to incorporate a residual dividend policy, external financing and default and find that simulated optimal aggregate payouts are much more volatile than the observed data when other variables are close to the values observed in the data. 2. I examine the sensitivity of optimal aggregate dividend policy to the level of the representative agent's habit motive. My results show that, when the habit motive gets stronger, the volatility of optimal aggregate payouts increases while the volatility of aggregate consumption decreases. This is consistent with the hypothesis that investors use cash payouts from well diversified portfolios to help smooth consumption. 3. I demonstrate that the variability of optimal aggregate payouts is sensitive to capital adjustment costs. My simulated results show that costly frictions from changing the capital base of the firm cause optimal aggregate dividends and real investments to be smooth and share prices to be volatile. This finding is consistent with prior empirical observations. 4. I run simulations that support the hypothesis that optimal aggregate dividend policy is similar when the representative firm is risk averse to when it has capital adjustment costs. In both cases, optimal aggregate dividends volatility is very low. 5. In all calibrated DSGE models, apart from case 4, optimal aggregate payouts are found to be countercyclical. This supports the hypothesis that corporations prefer to hold more free cash flows for potential investment opportunities instead of paying dividends when the economy is booming, but is inconsistent with observed data. Keywords: Dynamic Stochastic General Equilibrium (DSGE), real business cycle, utility function, habits, dividends.

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Amoussouvi, Aouefa. « Transcriptional timing and noise of yeast cell cycle regulators ». Doctoral thesis, Humboldt-Universität zu Berlin, 2020. http://dx.doi.org/10.18452/21398.

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Die Genexpression ist ein stochastischer Prozess, dessen strenge Regulation einen ungestörten Zellzyklusverlauf ermöglicht. Jeglicher Stress löst eine Neuprogrammierung der Expression und somit einen Stillstand des Zellzyklus aus. Um ein besseres Verständnis des eukaryotischen Zellzyklus zu erlangen, wurde in dieser Arbeit die Fluoreszenzmikroskopie einzelner Zellen (S.cerevisiae) mit stochastischer Modellierung der Hauptregulatorgene des G1/S-Übergangs (SIC1, CLN2, CLB5) kombiniert. Mithilfe des MS2-CP-Systems wurden mRNA-Level von SIC1 in lebenden Zellen bestimmt und verschiedene Transportwege von SIC1-mRNA visualisiert. RNA-FISH in Kombination mit genetischen und morphologischen Markierungen ermöglichte es, die absolute Quantifizierung von SIC1-, CLN2- und CLB5-mRNA in allen Zyklusphasen vorzunehmen. Die Auswirkung von Osmostress, in Hinblick auf eine transkriptionale Verzerrung, wurde untersucht. Basierend auf den experimentellen-Daten wurde ein stochastisches Model entwickelt, dass die Expression von SIC1, CLN2 und CLB5 mRNA und Proteinlevel in Abhängigkeit von Osmostress über den gesamten Zellzyklus hinweg abbildet. Die Modellierung ermöglichte eine in silico Synchronisation und somit die Extraktion kinetischer Parameter. Die Expression der beobachteten Gene wurde im Verlauf des Zellzyklus nicht ein- und ausgeschaltet, stattdessen kam es zu Phasen hoher oder niedriger Expression. Niedriger SIC1 Expression gewährleistete niedriger Sic1 Protein Verzerrung und robustes G1/S Timing. CLN2 und CLB5 zeigten ein maximales Expressionslevel in G1 und auch eine erhöhte Expression in der späten Mitose. Osmostress induzierte einen langanhaltenden Effekt auf die Transkription und die Dauer der Zellzyklusphasen. Der hier vorgestellte Ansatz ermöglichte quantitative Einblicke in die Genexpression und zeitliche Koordination des Zellzyklus von S.cerevisiae. Einige der hier beobachteten Regulationsmechanismen könnten allgemeine Gültigkeit im eukaryotischen Zellzyklus besitzen.
Gene expression is a stochastic process and its appropriate regulation is critical for cell cycle progression. Cellular stress response requires expression reprogramming and cell cycle arrest. Time-resolved quantitative methods on single cells are needed to understand eukaryotic cell cycle in context of noisy gene expression and external perturbations. We applied single-cell fluorescence microscopy and stochastic modeling to SIC1, CLN2 and CLB5, the main G1/S regulators in S. cerevisiae. Using MS2-CP system we estimated SIC1 mRNA levels and visualized different types of transport for SIC1 mRNA particles in living cells. With RNA-FISH combined to genetic and morphological markers we monitored absolute numbers of mRNA and transcriptional noise over cell cycle phases with and without osmostress. Stochastic modeling enabled in silico synchronization, the extraction of kinetic parameters as well as expanded the static mRNA data into time courses for mRNAs, proteins and their noise. Based on our experimental data we developed a stochastic model of G1/S timing centered on SIC1 and a second one for the entire cell cycle involving SIC1, CLN2 and CLB5 and the response to osmostress. All three genes exhibited basal expression throughout cell cycle enlightening that transcription is not divided in on and off but rather in high and low phases. A low SIC1 transcript level ensured a low protein noise and a robust timing of the G1/S transition. CLN2 and CLB5 showed main expression peaks in G1 as well as an expression upshift in late mitosis. Osmostress induced different periods of transcriptional inhibition for CLN2 and CLB5 and long-term impact on cell cycle phase duration. Our approach disclosed detailed quantitative insights into gene expression and cell cycle timing, not available from bulk experiments. Importantly some regulation mechanisms specific to SIC1, CLN2 and CLB5 might be generalized to other genes as well as to other organisms.

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Fujiwara, Ippei. « Three essays on dynamic general equilibrium models ». Thesis, University of Oxford, 2009. http://ora.ox.ac.uk/objects/uuid:b963d031-cd68-4bee-91b7-4541e5d600d2.

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This thesis aims at contributing to the existing studies in the dynamic stochastic general equilibrium model, particularly in the new Keynesian models, on three aspects. It consists of three chapters. Chapter 2 is on “Dynamic new Keynesian Life-Cycle Model.” Chapter 3 is on “Re-thinking Price Stability in an Economy with Endogenous Firm Entry: Real Imperfections under Product Variety.” Chapter 4 is on “Growth Expectation.” Abstracts of each Chapter are as follows. In Chapter 2, we first construct a dynamic new Keynesian model that incorporates life-cycle behavior a la Gertler (1999), in order to study whether structural shocks to the economy have asymmetric effects on heterogeneous agents, namely workers and retirees. We also examine whether considerations of life-cycle and demographic structure alter the dynamic properties of the monetary business cycle model, specifically the degree of amplification in impulse responses. According to our simulation results, shocks indeed have asymmetric impacts on different households and the demographic structure does alter the size of responses against shocks by changing the trade-off between substitution and income effects. In Chapter 3, we re-think price stability in an economy with endogenous firm entry under possible distortions. We first demonstrate that endogenous entry causes real imperfections. Reflecting fluctuations in the number of varieties, the gap between the natural and the efficient level of output is no longer constant and variant to shocks. As a result, the central bank faces a trade-off between stabilizing inflation and welfare-relevant output gap. Then, we show that this results in the non-zero optimal rate of inflation. We further check whether welfare can be enhanced by targeting welfare-based inflation instead of cross-sectional average inflation contrary to the previous findings. Simulations even with such distortions as unknown natural interest rate or no fiscal remedy for efficient non-stochastic steady states, however, support cross-sectional average inflation targeting although there may exist some small gains by referring also to welfare-based inflation rates. Incomplete stabilization may enhance welfare in an economy when agents cannot internalize the externality on the love for variety. Chapter 4 is about the difficulty in producing reasonable business cycles for the expectation shock about higher future technology. For a long time, changes in expectations about the future have been thought to be significant sources of economic fluctuations, as argued by Pigou (1926). Although creating such an expectation-driven cycle (the Pigou cycle) in equilibrium business cycle models was considered to be a difficult challenge, as pointed out by Barro and King (1984), recently, several researchers have succeeded in producing the Pigou cycle by balancing the tension between the wealth effect and the substitution effect stemming from the higher expected future productivity. Seminal research by Christiano et al. (2007a) explains the “stock market boom-bust cycles,” characterized by increases in consumption, labor inputs, investment and the stock prices relating to high expected future technology levels, by introducing investment growth adjustment costs, habit formation in consumption, sticky prices and an inflation-targeting central bank. We, however, show that such a cycle is difficult to generate based on “growth expectation,” which reflect expectations of higher productivity growth rates. Thus, Barro and King’s (1984) prediction still applies.

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Saad, Lara. « Optimisation du coût du cycle de vie des structures en béton armé ». Thesis, Clermont-Ferrand 2, 2016. http://www.theses.fr/2016CLF22692/document.

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Les structures de génie civil, en particulier les ponts en béton armé, doivent être conçues et gérées pour assurer les besoins de transport et de communication dans la société. Il est indispensable de garantir un fonctionnement convenable et sécuritaire de ces structures, puisque les défaillances peuvent conduire à des perturbations du transport, des pertes catastrophiques de concessions et des pertes de vies humaines, avec des impacts économiques, sociétaux et environnementaux graves, à court et à long termes. Les gestionnaires entreprennent diverses activités pour maintenir la performance et le fonctionnement adéquat à long terme, tout en satisfaisant les contraintes financières et sécuritaires. Idéalement, ils peuvent recourir à des techniques d'optimisation pour établir les compromis entre la réduction du coût du cycle de vie (LCC) et la maximisation de la durée de vie. Cela nécessite le développement de l’analyse du cycle de vie, de l’analyse de fiabilité et de l'optimisation structurale.Les approches actuelles pour la conception et la gestion des structures s’appuyant sur l’analyse du coût de cycle de vie, montrent les besoins suivants : (1) une approche intégrée et systématique pour modéliser de façon cohérente les processus de dégradation, les charges de trafic, le vieillissement et les conséquences directes et indirectes de la défaillance, (2) une considération complète des dépendances économiques, structurales et stochastiques entre les différents éléments de l’ouvrage, (3) une approche permettant de modéliser efficacement un système structural formé de plusieurs éléments interdépendants, (4) une évaluation des conséquences de la dégradation et de la redistribution des charges entre les éléments en tenant compte de la redondance du système et de la configuration de l’ouvrage, (5) une méthode d'optimisation de la conception et de la maintenance qui préserve l’exigence de fiabilité tout en considérant la robustesse de la décision. L'objectif global de cette thèse est de fournir des procédures améliorées qui peuvent être appliquées à la conception et à la gestion fiabilistes et robustes des ouvrages en béton armé, en réduisant les coûts supportés par les gestionnaires et les utilisateurs, tout en tenant compte des dépendances entre les éléments. Dans la première partie de cette thèse, une synthèse bibliographique concernant les procédures de la conception et de la maintenance basée sur des calculs fiabilistes est présentée, et les différents composants du LCC sont développés. Ensuite, une approche est proposée pour la conception des ouvrages en tenant compte du coût aux usagers et en intégrant dans la fonction du coût de cycle de vie. Le modèle couplé corrosion-fatigue est aussi considéré dans l’optimisation de la conception. La planification de la maintenance des ouvrages est ensuite développée, en considérant les différents types d'interaction entre les éléments, en particulier les dépendances économiques, structurales et stochastiques. Ce modèle utilise l'analyse de l'arbre de défaillance et les probabilités conditionnelles pour tenir compte des dépendances dans la planification de la maintenance. Les conséquences de la dégradation et de la redistribution des charges sont prises en compte dans l'approche proposée. Par ailleurs, une méthode pratique de calcul de la fiabilité d'un système formé de plusieurs composantes interdépendantes est proposée, à travers un facteur de redondance calculé par la modélisation mécanique. Enfin, une nouvelle procédure d'optimisation est proposée, permettant de tenir compte des incertitudes dans le système et la capacité structurale de s'adapter aux variabilités intrinsèques. La procédure proposée tient compte des incertitudes et de la variabilité dans une formulation cohérente, validée au moyen des applications numériques. (...)
Civil engineering structures, particularly reinforced concrete bridges, should be designed and managed to ensure the society needs. It is crucial to assure that these structures function properly and safely as damage during the service life can lead to transport disturbance, catastrophic loss of property, causalities, as well as severe economic, social, and environmental impacts, in addition to long term consequences. Decision-makers adopt various activities to maintain adequate long-term performance and functionality while satisfying financial constraints. Ideally, they may employ optimization techniques to identify the trade-offs between minimizing the life-cycle cost (LCC) and maximizing the expected service life. This requires the development of three challenging chores: life cycle analysis, reliability analysis and structural optimization. The current approaches for the design and management of structures through a Life-cycle cost analysis (LCCA) highlight the following needs: (1) an integrated and systematic approach to model coherently the deterioration processes, the increasing traffic loads, the aging and the direct and indirect consequences of failure, (2) a mutual consideration of economic, structural and stochastic dependencies between the elements of a structural system, (3) an adequate approach for the deterioration dependencies and load redistribution between the elements, (4) an improvement of system reliability computation as a function of the structural redundancy and configuration that can take into account the dependencies between the elements, (5) a consideration of design and maintenance optimization procedures that focus coherently on the robustness of the management decision and on the satisfaction of reliability requirements.The overall objective of this study is to provide improved LCCA and procedures that can be applied to select optimal and robust design and maintenance decisions regarding new and existing reinforced concrete structures, by minimizing both manager and user costs, while providing the required safety along the structure lifetime, taking into account the most severe degradation processes and the dependencies between structural elements. In the first part of this thesis, a literature review concerning the current probabilistic design and maintenance procedures is presented, and the LCC components are discussed. Then, a new approach is developed to evaluate the user delay costs on a reinforced concrete bridge structure, based on direct and indirect costs related to degradation and failure, and to integrate it to the life cycle cost function, in order to allow for probabilistic design. In addition,the coupled corrosion-fatigue model is considered in the design optimization. Afterward, a structural maintenance planning approach is developed to consider the three types of interactions, namely economic, structural and stochastic dependencies. The proposed model uses fault tree analysis and conditional probabilities to reflect the dependencies in the maintenance planning. The consequences of degradation are evaluated and a method is proposed to account for the load redistribution. Moreover, a practical formulation for quantifying the reliability of a system formed of interrelated components is proposed, by the mean of a redundancy factor that can be computed by finite element analysis. Finally, a new optimization procedure is proposed, by taking into account the uncertainties in the analysis, and the structural ability to adapt to variability, unforeseen actions or deterioration mechanisms. The proposed procedure takes account of uncertainties andvariability in one consistent formulation, which is shown through numerical applications. (...)

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SALMAN, RAMIZ. « Identification of common economic cycles using optimal multivariate filters ». Doctoral thesis, Università degli Studi di Milano-Bicocca, 2022. http://hdl.handle.net/10281/394321.

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This thesis includes two essays that are focused on developing multivariate filter approaches to be used for extracting common cyclical components where the common components can be used as an estimator of a business cycle. The first chapter aims to develop an optimal multivariate filter in order to extract common cyclical components of macroeconomic indicators. The filter allows macroeconomic series to be modeled as a phase shifted version of a coinciding business cycle (BC) while keeping other time series components such as the stochastic trend and idiosyncratic shocks intact (i.e. they are individually specified for each series). Earlier studies of Rünstler (2004), Valle e Azevedo et al. (2006) have applied phase shift in the form of a delay parameter when specifying lead-lag cycles. However, the lead-lag relationship is defined by rotating the baseline cycle which leads to loss of information. This deficiency is especially important if one considers working in continuous time. Therefore, this paper improves on the former technique by allowing a more flexible phase shift mechanism on the original BC. This in turn should lead to more realistic estimates and filters considering that the underlying data is generated through a continuous time framework. The study starts by presenting a structure for bi-variate time series system and then extends to model to incorporate a structure for three time series and beyond. Kalman filter and smoothing recursions are applied to compute the smoothed cycle estimates and to construct the likelihood function. Using simulated data, we test both model specifications by carrying out a grid search of the initial delay parameter to see the likelihood behavior as the parameter moves into fractional neighborhoods. Afterwards, applying the methodology to a set of EU countries and macroeconomic indicators; the study aims to shed light to the presence of cyclical heterogeneity at country level economic activity for major EU member states. A second empirical study provides analysis on how the model can be implemented for assigning a lead/lag ordering to three main economic indicators of a single country. The second chapter implements a multivariate non-parametric filtering approach; the Vertical Multivariate Singular Spectrum Analysis (V-MSSA) of Hassani and Mahmoudvand (2013) and Golyandina et al. (2013). to be applied for identifying a common economic cycle indicator. The methodology is a data-driven procedure that can decompose a time series into many sub components. By exploiting this ability of the SSA, the paper aims to first extract cyclical components based on frequency characteristics and then follow by choosing only common cyclical component pairs with-in the business cycle frequency spectrum. These components will then be aggregated for constructing an EU region wide Business cycle indicator. The chapter outlines each steps of the algorithm that will eventually identify the SSA filter to act as a band-pass filter. The study then proceeds with simulation based data where the common cycle can be controlled and extracted a priori as a benchmark to the SSA-based filter estimates. The study follows with an empirical analysis similar to the framework set in Valle e Azevedo et al. (2006) with the aim to identify a Euro region business cycle indicator. The SSA based filter estimate is compared with Euro region economic activity indicators; the EuroCoin and the quarterly GDP growth rate of the EU area. Our results presents evidence of a successful alternative for tracing the cyclical position of the EU economy from a much smaller data set. Moreover, the constructed indicator also could serve as an unobserved proxy for a monthly growth cycle. A further analysis is also conducted to reveal whether the SSA based approach can be considered as an alternative to parametric filtering methods by providing results of common cycle extraction using Unobserved component model alternatives.
This thesis includes two essays that are focused on developing multivariate filter approaches to be used for extracting common cyclical components where the common components can be used as an estimator of a business cycle. The first chapter aims to develop an optimal multivariate filter in order to extract common cyclical components of macroeconomic indicators. The filter allows macroeconomic series to be modeled as a phase shifted version of a coinciding business cycle (BC) while keeping other time series components such as the stochastic trend and idiosyncratic shocks intact (i.e. they are individually specified for each series). Earlier studies of Rünstler (2004), Valle e Azevedo et al. (2006) have applied phase shift in the form of a delay parameter when specifying lead-lag cycles. However, the lead-lag relationship is defined by rotating the baseline cycle which leads to loss of information. This deficiency is especially important if one considers working in continuous time. Therefore, this paper improves on the former technique by allowing a more flexible phase shift mechanism on the original BC. This in turn should lead to more realistic estimates and filters considering that the underlying data is generated through a continuous time framework. The study starts by presenting a structure for bi-variate time series system and then extends to model to incorporate a structure for three time series and beyond. Kalman filter and smoothing recursions are applied to compute the smoothed cycle estimates and to construct the likelihood function. Using simulated data, we test both model specifications by carrying out a grid search of the initial delay parameter to see the likelihood behavior as the parameter moves into fractional neighborhoods. Afterwards, applying the methodology to a set of EU countries and macroeconomic indicators; the study aims to shed light to the presence of cyclical heterogeneity at country level economic activity for major EU member states. A second empirical study provides analysis on how the model can be implemented for assigning a lead/lag ordering to three main economic indicators of a single country. The second chapter implements a multivariate non-parametric filtering approach; the Vertical Multivariate Singular Spectrum Analysis (V-MSSA) of Hassani and Mahmoudvand (2013) and Golyandina et al. (2013). to be applied for identifying a common economic cycle indicator. The methodology is a data-driven procedure that can decompose a time series into many sub components. By exploiting this ability of the SSA, the paper aims to first extract cyclical components based on frequency characteristics and then follow by choosing only common cyclical component pairs with-in the business cycle frequency spectrum. These components will then be aggregated for constructing an EU region wide Business cycle indicator. The chapter outlines each steps of the algorithm that will eventually identify the SSA filter to act as a band-pass filter. The study then proceeds with simulation based data where the common cycle can be controlled and extracted a priori as a benchmark to the SSA-based filter estimates. The study follows with an empirical analysis similar to the framework set in Valle e Azevedo et al. (2006) with the aim to identify a Euro region business cycle indicator. The SSA based filter estimate is compared with Euro region economic activity indicators; the EuroCoin and the quarterly GDP growth rate of the EU area. Our results presents evidence of a successful alternative for tracing the cyclical position of the EU economy from a much smaller data set. Moreover, the constructed indicator also could serve as an unobserved proxy for a monthly growth cycle. A further analysis is also conducted to reveal whether the SSA based approach can be considered as an alternative to parametric filtering methods by providing results of common cycle extraction using Unobserved component model alternatives.

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Pihnastyi, O. M., G. K. Kozhevnikov et Tetiana Bondarenko. « The information controlling model transport system during transient conditions ». Thesis, Institute of Electrical and Electronics Engineers, Inc., USA, 2019. http://repository.kpi.kharkov.ua/handle/KhPI-Press/48796.

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This article is devoted to designing an information management system for the conveyor line of mining enterprises. The analytical design method for the transient mode of the stepped speed control system of the conveyor line was developed. The partial differential equation was used in constructing the conveyor line model. The description of the production system is fulfilled in the single step approximation. A decision was obtained which determines the state of the parameters of the production line for a technological position specified as a function of time. Has been determined the length of the transition period during which the initial condition for the distribution of labour objects along the conveyor affects the parameters of the state of the conveyor line. The method for calculating the current parameters of a conveyor line with the use of partial differential equations allows the design of control systems for production lines of conveyor type for transient modes. The originality of the results obtained is to improve the PDE-models of the conveyor-type production systems used to design highly efficient production control systems operating in transient modes.

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Al-Tamimi, Rami Salhab. « Continuous time disaggregation in hierarchical production planning ». [Tampa, Fla] : University of South Florida, 2006. http://purl.fcla.edu/usf/dc/et/SFE0001819.

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Sergi, Francesco. « De la révolution lucasienne aux modèles DSGE : réflexions sur les développements récents de la modélisation macroéconomique ». Thesis, Paris 1, 2017. http://www.theses.fr/2017PA01E059/document.

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Ce travail propose une mise en perspective des pratiques de modélisation macroéconomique,depuis les travaux de Robert E. Lucas dans les années 1970 jusqu’aux contributions actuelles de l’approche dite d’équilibre général dynamique stochastique (DSGE). Cette mise en perspective permet de caractériser l’essor des modèles DSGE comme un compromis entre conceptions antagonistes de la modélisation : d’une part, celle de l’approche des cycles réels (RBC) et, d’autre part, celle de la nouvelle économie keynésienne. Pour justifier cette opposition, ce travail propose une reconstruction épistémologique de l’histoire récente de la macroéconomie, à savoir une analyse des différents critères qui définissent la validité et la pertinence d’un modèle. L’hypothèse de travail est qu’on peut identifier, pour chaque pratique de modélisation,trois critères méthodologiques fondamentaux : la validité interne (l’adéquation des hypothèses d’un modèle aux concepts aux formalismes d’une théorie), la validité externe(l’adéquation des hypothèses et/ou des résultats d’un modèle au monde réel, et les procédés quantitatifs pour évaluer cette adéquation) et le critère de hiérarchie (la préférence pour la validité interne sur la validité externe, ou vice versa). Cette grille de lecture, inspirée de la littérature sur les modèles en philosophie des sciences, permet d’apporter quatre contributions originales à l’histoire de la macroéconomie récente. (1) Elle permet de concevoir l’essor des modèles DSGE sans faire appel à l’explication proposée par l’historiographie produite par les macroéconomistes eux-mêmes,à savoir l’existence d’un consensus et d’un progrès technique exogène. Contre cette vision de l’histoire en termes de progrès scientifique, nous mettons en avant les oppositions méthodologiques au sein de la macroéconomie et nous illustrons l’interdépendance entre activité théorique et développement des méthodes statistiques et économétriques. (2) La thèse s’attaque au cloisonnement entre histoire des théories macroéconomiques et histoire des méthodes quantitatives. Grâce à sa perspective méthodologique, ce travail permet d’opérer la jonction entre ces deux littératures et de développer les bases d’une vision globale des transformations récentes de la macroéconomie. (3) La relecture méthodologique de l’histoire de la modélisation permet de mettre en évidence comment la condition de validité externe a représenté le principal point de clivage entre différentes conceptions de la modélisation. La question de la validité externe apparaît par ailleurs intrinsèquement liée à la question de l’explication causale des phénomènes, sur laquelle repose largement la justification de la modélisation comme outil d’expertise des politiques économiques. (4) Ce travail aboutit à une caractérisation originale de l’approche DSGE : loin de constituer une «synthèse» ou un consensus, cette approche s’apparente à un compromis, fragilisé par l’antagonisme méthodologique entre ses parties prenantes
This dissertation provides a history of macroeconomic modeling practices from RobertE. Lucas’s works in the 1970s up to today’s dynamic stochastic general equilibrium (DSGE) approach. Working from a historical perspective, I suggest that the recent rise of DSGE models should be characterized as a compromise between opposing views of modeling methodology—on the one hand, the real business cycle (RBC) view, on the other hand, the new Keynesian view. In order to justify this claim, my work provides an epistemological reconstruction of the recent history of macroeconomics, building from ananalysis of the criteria defining the validity and the pertinence of a model. My assumption is that recent macroeconomic modeling practices can be described by three distinctive methodological criteria : the internal validity criterion (which establishes the consistency between models’ assumptions and concepts and formalisms of a theory), the external validity criterion (which establishes the consistency between the assumptions and results of a model and the real world, as well as the quantitative methods needed to assess such a consistency) and the hierarchization criterion (which establishes the preference for internal over external validity, or vice versa). This epistemological reconstruction draws primarily from the literature about models in the philosophy of science. My work aims to make four contributions to the history of recent macroeconomics. (1) To understand the rise of DSGE models without referring to the explanation providedby the macroeconomists themselves, who tend to think that macroeconomics evolved through theoretical consensus and exogenous technical progress. By distancing itself fromthis perspective, my work draws attention to the disruptive character of methodological controversies and to the interdependence between theoretical activity and the developmentof statistical and econometric methods. (2) To overcome the existing divide betweenthe history of macroeconomic theories and the history of quantitative methods. Throughits epistemological perspective, my work reconciles these two historiographies and specifiesthe basis for a comprehensive understanding of recent developments in macroeconomics.(3) To put the accent on the external validity condition as the main controversial issue separating different views of macro-modeling methodology. Furthermore, I illustrate how the debate about external validity is closely related to the problem of casual explanation and, finally, to the conditions for providing economic policy evaluation. (4) To characterize the DSGE approach: although DSGE models are often presented as a“synthesis”, or as a “consensus”, they are better described as a shaky compromise between two opposing methodological visions

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Magno, Alessandra Cristina Gomes. « Relação entre o volume da célula e dinâmica do ciclo celular em mamíferos ». Universidade Federal de Juiz de Fora (UFJF), 2016. https://repositorio.ufjf.br/jspui/handle/ufjf/4784.

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O objetivo principal deste trabalho é adicionar e analisar uma equação que repre senta o volume no modelo dinâmico do ciclo celular de mamíferos proposto por Gérard e Goldbeter (2011). A divisão celular ocorre quando o complexo ciclinaB/Cdk1(quínase dependente de ciclina) é totalmente degradado atingindo um valor mínimo. Neste ponto, a célula é divida em duas novas células ﬁlhas e cada uma irá conter a metade do conteúdo citoplasmático da célula mãe. As equações do modelo de base são válidas apenas se o volume celular, onde as reações ocorrem, é constante. Quando o volume celular não é constante, isto é, a taxa de variação do volume em relação ao tempo é explicitamente levada em consideração no modelo matemático, então as equações do modelo original não são mais válidas. Portanto, todas as equações foram modiﬁcadas a partir do princípio de conservação das massas para considerar um volume que varia ao longo do tempo. Por meio desta abordagem, o volume celular afeta todas as variáveis do modelo. Dois méto dos diferentes de simulação foram efetuados: determinista e estocástico. Na simulação estocástica, o volume afeta todos os parâmetros do modelo que possuem de alguma forma unidade molar, enquanto que no determinista, ele é incorporado nas equações diferen ciais. Na simulação determinista, as espécies bioquímicas podem estar em unidades de concentração, enquanto na simulação estocástica tais espécies devem ser convertidas para número de moléculas que são diretamente proporcional ao volume celular. Em um esforço para entender a inﬂuência da nova equação sobre o modelo uma análise de estabilidade foi feita. Isso esclarece como o novo parâmetro µ, fator de crescimento do volume celular, impacta na estabilidade do ciclo limite do modelo. Para encontrar a solução aproximada do modelo determinista, o método Runge Kutta de quarta ordem foi implementado. Já para o modelo estocástico, o método direto de Gillespie foi usado. Para concluir, um modelo mais preciso, em comparação ao modelo de base, foi desenvolvido ao levar em consideração a inﬂuência da taxa de variação do volume celular sobre o ciclo celular.
The main goal of this work is to add and analyse an equation that represents the volume in a dynamical model of the mammalian cell cycle proposed by Gérard and Gold beter (2011). The cell division occurs when the cyclinB/Cdk1 (cyclin-dependent kinase) complex is totally degraded and it reaches a minimum value. At this point, the cell is divided into two newborn daughter cells and each one will contain the half of the cyto plasmic content of the mother cell. The equations of our base model are valid only if the cell volume, where the reactions occur, is constant. Whether the cell volume is not constant, that is, the rate of change of its volume with respect to time is explicitly taken into account in the mathematical model, then the equations of the original model are no longer valid. Therefore, every equations were modiﬁed from the mass conservation prin ciple for considering a volume that changes with time. Through this approach, the cell volume aﬀects all model variables. Two diﬀerent dynamic simulation methods were ac complished: deterministic and stochastic. In the stochastic simulation, the volume aﬀects every model’s parameters which have molar unit, whereas in the deterministic one, it is incorporated into the diﬀerential equations. In deterministic simulation, the biochemical species may be in concentration units, while in stochastic simulation such species must be converted to number of molecules which are directly proportional to the cell volume. In an eﬀort to understand the inﬂuence of the new equation over the model an stability analysis was performed. This elucidates how the new parameter µ, cell volume growth factor, impacts the stability of the model’s limit cycle. In order to ﬁnd the approximated solution of the deterministic model, the fourth order Runge Kutta method was implemen ted. As for the stochastic model, the Gillespie’s Direct Method was used. In conclusion, a more precise model, in comparison to the base model, was created for the cell cycle as it now takes into consideration the rate of change of the cell volume.

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Wainwright, Martin J. (Martin James) 1973. « Stochastic processes on graphs with cycles : geometric and variational approaches ». Thesis, Massachusetts Institute of Technology, 2002. http://hdl.handle.net/1721.1/8371.

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Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2002.
Includes bibliographical references (leaves 259-271).
Stochastic processes defined on graphs arise in a tremendous variety of fields, including statistical physics, signal processing, computer vision, artificial intelligence, and information theory. The formalism of graphical models provides a useful language with which to formulate fundamental problems common to all of these fields, including estimation, model fitting, and sampling. For graphs without cycles, known as trees, all of these problems are relatively well-understood, and can be solved efficiently with algorithms whose complexity scales in a tractable manner with problem size. In contrast, these same problems present considerable challenges in general graphs with cycles. The focus of this thesis is the development and analysis of methods, both exact and approximate, for problems on graphs with cycles. Our contributions are in developing and analyzing techniques for estimation, as well as methods for computing upper and lower bounds on quantities of interest (e.g., marginal probabilities; partition functions). In order to do so, we make use of exponential representations of distributions, as well as insight from the associated information geometry and Legendre duality. Our results demonstrate the power of exponential representations for graphical models, as well as the utility of studying collections of modified problems defined on trees embedded within the original graph with cycles. The specific contributions of this thesis include the following. We develop a method for performing exact estimation of Gaussian processes on graphs with cycles by solving a sequence of modified problems on embedded spanning trees.
(cont.) We introduce the tree-based reparameterization framework for approximate estimation of discrete processes. This perspective leads to a number of theoretical results on belief propagation and related algorithms, including characterizations of their fixed points and the associated approximation error. Next we extend the notion of reparameterization to a much broader class of methods for approximate inference, including Kikuchi methods, and present results on their fixed points and accuracy. Finally, we develop and analyze a novel class of upper bounds on the log partition function based on convex combinations of distributions in the exponential domain. In the special case of combining tree-structured distributions, the associated dual function gives an interesting perspective on the Bethe free energy.
by Martn J. Wainwright.
Ph.D.

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Lim, Dongwook. « A systematic approach to design for lifelong aircraft evolution ». Diss., Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/28280.

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Thesis (M. S.)--Aerospace Engineering, Georgia Institute of Technology, 2009.
Committee Chair: Mavris, Dimitri; Committee Member: Bishop, Carlee; Committee Member: Costello, Mark; Committee Member: Nam, Taewoo; Committee Member: Schrage, Daniel.

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Mustafayev, Elchin. « Policy interactions, uncertainty, and credit cycles in financial dynamic stochastic general equilibrium models ». Thesis, University of Nottingham, 2018. http://eprints.nottingham.ac.uk/53227/.

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This dissertation joins a vibrant conversation in macroeconomics about the role of financial frictions in business cycles spurred on by the recent financial crisis. Our proposed study contributes to this lively debate in a fundamental way by putting forward two DSGE models. Firstly, we consider a DSGE model which accounts for the financial sector and assumes a distorted steady state. Unlike in studies where the welfare effects of distinct policy bodies i.e. the central bank and the macroprudential institution are not tracked, in our proposed model we derive welfare-based loss functions that trace associated inefficiencies emerging from both nominal and financial distortions. Therefore, to the best of our knowledge, this model is the first to consider welfare-based mandates to the central bank and the macroprudential institution that targets related inefficiencies. In addition, a key innovation of this model is the use of such welfare-based mandate in a game-theoretical framework. Secondly, we introduce a DSGE model, which in addition to financial frictions, is augmented with stochastic volatility and nominal rigidities. This model is then used to assess the effectiveness of conventional, unconventional monetary policies and macroprudential policies in mitigating the effects of disturbances in the presence of risk shocks. To the best of our knowledge, this second model is the first to analyse the effectiveness of unconventional monetary policy and macroprudential policies with stochastic volatility. Furthermore, another key novelty of our research is the analysis of the interactions between three policy options, namely conventional, unconventional monetary and macroprudential policies.

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Oh, Jonghyeon. « Essays on Business Cycles and Dynamic Stochastic General Equilibrium Models with Heterogeneous Agents ». The Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1397790687.

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Sanja, Stanisavljev. « Развој стохастичког модела оптимизације времена трајања циклуса производње у малим и средњим предузећима ». Phd thesis, Univerzitet u Novom Sadu, Fakultet tehničkih nauka u Novom Sadu, 2017. https://www.cris.uns.ac.rs/record.jsf?recordId=104398&source=NDLTD&language=en.

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У докторској дисертацијиприказан је развој стохастичког модела оптимизације времена трајања циклуса производње у малим и средњим предузећима. Модел ће омогућити ефикасно праћење и анализу елемената врема циклуса производње у малим и средњим предузећима, у циљу оптимизације серијске производње и побољшања конкурентности у савременом пословању. Циљ је боље управљање производњом у малим и средљим предузећима као носиоцима привредног раста и развоја. Модел је примењен и експериментално доказан у три предузећа где је истраживање спроведено у периоду 2011-2014 године.
U doktorskoj disertacijiprikazan je razvoj stohastičkog modela optimizacije vremena trajanja ciklusa proizvodnje u malim i srednjim preduzećima. Model će omogućiti efikasno praćenje i analizu elemenata vrema ciklusa proizvodnje u malim i srednjim preduzećima, u cilju optimizacije serijske proizvodnje i poboljšanja konkurentnosti u savremenom poslovanju. Cilj je bolje upravljanje proizvodnjom u malim i sredljim preduzećima kao nosiocima privrednog rasta i razvoja. Model je primenjen i eksperimentalno dokazan u tri preduzeća gde je istraživanje sprovedeno u periodu 2011-2014 godine.
The Doctoral Dissertation presents the development of stochastic optimization model of production cycle time in small and medium size enterprises.The model will enable efficient tracking and analysis of production cycle time elements in small and medium size enterprises in order to optimize assenibly line production and to improve competitiveness in modern business.The aim is better production contol in small and medium size enterprisesas industial growth and development holders. The model was applied and proved experimentally in three enerprises where the research was caried out from 2011 to 2014.

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Zhang, Fang. « Essays on Rational Inattention and Business Cycles ». The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1338256275.

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Nookhwun, Nuwat. « An analysis of the relationship between monetary policy, business cycles and financial stability ». Thesis, University of Oxford, 2017. https://ora.ox.ac.uk/objects/uuid:d56b4883-1eee-4d26-9b12-554414791969.

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The thesis sheds light on key policy issues emerging from the recent Global Financial Crisis. The first chapter studies whether expansionary monetary policy contributes to bank risk-taking, in the case of Asia. I rely on panel data analysis covering 432 banks in 9 Asian countries over the year 2000-2011. The ratio of risky assets to total assets serves as a risk-taking indicator. The results support the existence of the bank risk-taking channel, which is more pronounced for banks listed on the stock market. I also report new findings with respect to how banks take more risk following monetary expansion. Importantly, evidence of excessive leverage is not found. The second chapter constructs a model for analyzing bank risk-taking. I embed firm heterogeneity, endogenous default risk and capital adequacy regulation into both RBC and NK DSGE models. A subset of the firms can partially default on their loans obligation but subject to non-pecuniary default penalty. With those financial frictions in place, I find that standard macroeconomic shocks can induce banks to engage in higher risk-taking. The chapter then explores the effectiveness of several macro-prudential tools in mitigating risk-taking. I find countercyclical capital buffers and risky to total asset ratio targeting to be effective. The third chapter emphasises the spillover effects of shocks originating in the housing and financial market on the real economy. I embed endogenous mortgage default into a New Keynesian model that features housing and the banking sector. The latter faces capital regulation. We study two key shocks, namely shocks to the variance of idiosyncratic housing shock and shocks to the penalty on capital regulation. Both are instrumental in causing a surge in mortgage default and loans risk premium, which constrains bank lending activity. The chapter later introduces three macroprudential measures to explore whether they improve economic stability and welfare.

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Dudu, Hasan. « Efficiency In Turkish Agriculture A Farm Household Level Analysis ». Master's thesis, METU, 2006. http://etd.lib.metu.edu.tr/upload/12606979/index.pdf.

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This thesis analyzes the efficiency structure of Turkish agriculture in farm household level by using various models of stochastic frontier analysis. A household level survey conducted in 2002 and 2004 is used in the analysis. Firstly, an efficient production frontier is estimated by a panel data models. By using these estimates, relative importance of production factors and their interaction with various farm specific factors are inspected. The parameters of production frontier show that agricultural production is crucially dependant on land and there is an excessive employment of labor in Turkish agriculture. Secondly, the efficiency scores are estimated at farm household level. The results are reported according to NUTS-II regional classification and many other farm specific characteristics. The western parts of the country are found to be relatively more efficient and there is a high deviation in mean efficiencies of different regions. There is an increase in mean efficiencies of all regions from 2002 to 2004. Besides, crop patterns, farm size, education level of household chief and irrigation are found to be effective on efficiency.

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Robin, Frédérique. « Modeling and analysis of cell population dynamics : application to the early development of ovarian follicles ». Thesis, Sorbonne université, 2019. http://www.theses.fr/2019SORUS344.

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Cette thèse vise à concevoir et analyser des modèles de dynamique des populations dédiés à la dynamique des cellules somatiques durant les premiers stades de la croissance du follicule ovarien. Les comportements des modèles sont analysés par des approches théoriques et numériques, et les valeurs des paramètres sont calibrées en proposant des stratégies de maximum de vraisemblance adaptées à notre jeu de données spécifique. Un modèle stochastique non linéaire, qui tient compte de la dynamique conjointe entre deux types cellulaires (précurseur et prolifératif), est dédié à l'activation de la croissance folliculaire. Une approche rigoureuse de projection par états finis est mise en œuvre pour caractériser l'état du système à l'extinction et calculer le temps d'extinction des cellules précurseurs. Un modèle linéaire multi-type structuré en âge, appliquée à la population de cellules prolifératives, est dédié à la croissance folliculaire précoce. Les différents types correspondent ici aux positions spatiales des cellules. Ce modèle est de type décomposable ; les transitions sont unidirectionnelles du premier vers le dernier type. Nous prouvons la convergence en temps long du modèle stochastique de Bellman-Harris et de l'équation de McKendrick-VonFoerster multi-types. Nous adaptons les résultats existants dans le cas où le théorème de Perron-Frobenius ne s'applique pas, et nous obtenons des formules analytiques explicites pour les moments asymptotiques des nombres de cellules et de la distribution stationnaire en âge. Nous étudions également le caractère bien posé du problème inverse associé au modèle déterministe
This thesis aims to design and analyze population dynamics models dedicated to the dynamics of somatic cells during the early stages of ovarian follicle growth. The model behaviors are analyzed through theoretical and numerical approaches, and the calibration of parameters is performed by proposing maximum likelihood strategies adapted to our specific dataset. A non-linear stochastic model, that accounts for the joint dynamics of two cell types (precursors and proliferative), is dedicated to the activation of follicular growth. In particular, we compute the extinction time of precursor cells. A rigorous finite state projection approach is implemented to characterize the system state at extinction. A linear multitype age-structured model for the proliferative cell population is dedicated to the early follicle growth. The different types correspond here to the spatial cell positions. This model is of decomposable kind; the transitions are unidirectional from the first to the last spatial type. We prove the long-term convergence for both the stochastic Bellman-Harris model and the multi-type McKendrick-VonFoerster equation. We adapt existing results in a context where the Perron-Frobenius theorem does not apply, and obtain explicit analytical formulas for the asymptotic moments of cell numbers and stable age distribution. We also study the well-posedness of the inverse problem associated with the deterministic model

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Lindgren, Georg. « Physical process effects on catchment-scale pollutant transport-attenuation, coastal loading and abatement efficiency ». Doctoral thesis, KTH, Mark- och vattenteknik, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3900.

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Pollutants follow various subsurface and surface water pathways from sources within a catchment to its outlet and may cause detrimental effects on downstream water quality and ecosystems. Along their different transport pathways through a catchment, pollutants may be attenuated subject to different physical and biogeochemical processes. In this thesis, physical process effects on such catchment-scale pollutant transport and attenuation, resulting coastal pollutant loading and its efficient abatement are investigated. For this purpose, pollutant transport-attenuation is modeled both generically using a Lagrangian Stochastic Advective-Reactive (LaSAR) approach and site specifically for the Swedish Norrström basin using the GIS-based dynamic nitrogen transport-attenuation model POLFLOW. Furthermore, the role of such modeling for catchment-scale pollutant abatement is also investigated by use of economic optimization modeling. Results indicate that appropriate characterization of catchment-scale solute transport and attenuation processes requires accurate quantification of the specific solute pathways from different sources in a catchment, through the subsurface and surface water systems of the catchment, to the catchment outlet. The various physical processes that act on solute transported along these pathways may be quantified appropriately by use of relevant solute travel time distributions for each water subsystem that the pathways cross through the catchment. Such distributions capture the physical solute travel time variability from source to catchment outlet and its effects on reactive pollutant transport. Results of this thesis show specifically that neglect of such physical solute travel time variability in large-scale models of nitrogen transport and attenuation in catchments may yield misleading model estimates of nitrogen attenuation rates. Results for nitrogen abatement optimization in catchments further indicate that inefficient solutions for coastal nitrogen load reduction may result from simplifying physical transport assumptions made in different catchment-scale nitrogen transport-attenuation models. Modeling of possible future nitrogen management scenarios show also that slow nitrogen transport and reversible mass transfer processes in the subsurface water systems of catchments may greatly delay and temporally redistribute coastal nitrogen load effects of inland nitrogen source abatement over decades or much longer. Achievement of the national Swedish environmental objective to reduce the anthropogenic coastal nitrogen loading by 30% may therefore require up to a 40% reduction of both point sources, for achieving a fast coastal load response, and diffuse sources, for maintaining the coastal load reduction also in the long term.
QC 20100908

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Sun, Qi. « Four essays in dynamic macroeconomics ». Thesis, St Andrews, 2010. http://hdl.handle.net/10023/941.

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Baptista, Alexandra Cristina Ferros dos Santos Nascimento. « Sistemas dinâmicos discretos em álgebras ». Doctoral thesis, Universidade de Évora, 2012. http://hdl.handle.net/10174/14751.

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Neste trabalho é feito o estudo de sistemas dinâmicos discretos em álgebras de matrizes. Este tema é explorado recorrendo a várias ferramentas da álgebra linear, com o objectivo de tirar partido da estrutura algébrica do espaço. É estudada a aplicação quadrática matricial, tomando uma matriz como parâmetro, aliando as propriedades algébricas à teoria das aplicações quadráticas escalares já existente, no caso real e complexo. São exploradas diversas características da dinâmica, tais como, a existência de ciclos comutativos e não-comutativos, a sua estabilidade, entre outras. São estudadas possíveis generalizações para o caso matricial das noções de conjunto de Mandelbrot e de conjunto de Julia. Os resultados atingidos são aplicados ao estudo da dinâmica da aplicação quadrática em diferentes álgebras hipercomplexas. É explorada a iteração quadrática no conjunto das matrizes estocásticas simétricas; as conclusões ilustram o comportamento do sistema dinâmico discreto definido no espaço das cadeias de Markov reversíveis; ABSTRACT: In this work we study discrete dynamical systems in matrix algebras. This subject is explored using different tools of linear algebra, in order to take advantage of the algebraic structure of the space. It is studied the iteration of a quadratic family in the algebra of real matrices, with a parameter matrix, combining the properties of the algebraic theory with the theory of the quadratic map in the real and complex cases. Several characteristics of the dynamics are explored, such as, the existence of commutative and non-commutative cycles, its stability, among others. Possible generalizations of the Mandelbrot set and Julia set are considered and studied. The results obtained are applied to the study of the quadratic dynamic in different hypercomplex algebras. Quadratic iteration is explored in the set of symmetric stochastic matrices; the findings illustrate the behavior of the discrete dynamical system on the space of reversible Markov chains.

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Thèses sur le sujet « Stochastic cycle »

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