STOCHASTIC QUANTIZATION OF FERMIONIC THEORIES - RENORMALIZATION OF THE MASSIVE THIRRING MODEL

Using the Langevin approach for stochastic processes, we study the renormalizability of the massive Thirring model. At finite fictitious time, we prove the absence of induced quadrilinear counterterms by verifying the cancellation of the divergencies of graphs with four external lines. This implies that the vanishing of the renormalization group beta function already occurs at finite times.

Cooperative RNA Polymerase Molecules Behavior on a Stochastic Sequence-Dependent Model for Transcription Elongation

The transcription process is crucial to life and the enzyme RNA polymerase (RNAP) is the major component of the transcription machinery. The development of single-molecule techniques, such as magnetic and optical tweezers, atomic-force microscopy and single-molecule fluorescence, increased our understanding of the transcription process and complements traditional biochemical studies. Based on these studies, theoretical models have been proposed to explain and predict the kinetics of the RNAP during the polymerization, highlighting the results achieved by models based on the thermodynamic stability of the transcription elongation complex. However, experiments showed that if more than one RNAP initiates from the same promoter, the transcription behavior slightly changes and new phenomenona are observed. We proposed and implemented a theoretical model that considers collisions between RNAPs and predicts their cooperative behavior during multi-round transcription generalizing the Bai et al. stochastic sequence-dependent model. In our approach, collisions between elongating enzymes modify their transcription rate values. We performed the simulations in Mathematica® and compared the results of the single and the multiple-molecule transcription with experimental results and other theoretical models. Our multi-round approach can recover several expected behaviors, showing that the transcription process for the studied sequences can be accelerated up to 48% when collisions are allowed: the dwell times on pause sites are reduced as well as the distance that the RNAPs backtracked from backtracking sites. © 2013 Costa et al.

Hybrid nanocomposites containing carboxymethylcellulose and silver nanoparticles

Silver nanoparticles have high temperature stability and low volatility, and at the nanoscale are known to be an effective antifungal and antimicrobial agent. The present investigation involves the synthesis of silver nanoparticle/carboxymethylcellulose nanocomposites. The nanoparticles synthesised in this study had sizes in the range of 100 and 40 nm. The nanocomposites formed by a combination of metallic nanoparticles and carboxymethylcellulose were characterised by contact angle measurements, solubility tests, thermal and mechanical analyses, and morphological images. Improvements in the hydrophobic properties were observed with inclusion of the nanoparticles in the nanocomposites, with the best results occurring after the addition of 40 nm nanoparticles in a carboxymethylcellulose matrix. The silver nanoparticles tend to occupy the empty spaces in the pores of the carboxymethylcellulose matrix, inducing the collapse of these pores and thereby improving the tensile and barrier properties of the film. Copyright © 2013 American Scientific Publishers All rights reserved.

Consequences of plant population size for pollinator visitation and plant reproductive success

Habitat loss and fragmentation have a prominent role in determining the size of plant populations, and can affect plant-pollinator interactions. It is hypothesized that in small plant populations the ability to set seeds can be reduced due to limited pollination services, since individuals in small populations can receive less quantity or quality of visits. In this study, I investigated the effect of population size on plant reproductive success and insect visitation in 8 populations of two common species in the island of Lesvos, Greece (Mediterranean Sea), Echium plantagineum and Ballota acetabulosa, and of a rare perennial shrub endemic to north-central Italy, Ononis masquillierii. All the three species depended on insect pollinators for sexual reproduction. For each species, pollen limitation was present in all or nearly all populations, but the relationship between pollen limitation and population size was only present in Ononis masquillierii. However, in Echium plantagineum, significant relationships between both open-pollinated and handcrossed-pollinated seed sets and population size were found, being small populations comparatively less productive than large ones. Additionally, for this species, livestock grazing intensity was greater for small populations and for sparse patches, and had a negative influence on productivity of the remnant plants. Both Echium plantagineum and Ballota acetabulosa attracted a great number of insects, representing a wide spectrum of pollinators, thereby can be considered as generalist species. For Ballota acetabulosa, the most important pollinators were megachilid female bees, and insect diversity didn’t decrease with decreasing plant population size. By contrast, Ononis masquillierii plants generally received few visits, with flowers specialized on small bees (Lasioglossum spp.), representing the most important insect guild. In Echium plantagineum and Ballota acetabulosa, plants in small and large populations received the same amount of visits per flower, and no differences in the number of intraplant visited flowers were detected. On the contrary, large Ononis populations supported higher amounts of pollinators than small ones. At patch level, high Echium flower density was associated with more and higher quality pollinators. My results indicate that small populations were not subject to reduced pollination services than large ones in Echium plantagineum and Ballota acetabulosa, and suggest that grazing and resource limitation could have a major impact on population fitness in Echium plantagineum. The absence of any size effects in these two species can be explained in the light of their high local abundance, wide habitat specificity, and ability to compete with other co-flowering species for pollinators. By contrast, size represents a key characteristic for both pollination and reproduction in Ononis masquillierii populations, as an increase in size could mitigate the negative effects coming from the disadvantageous reproductive traits of the species. Finally, the widespread occurrence of pollen limitation in the three species may be the result of 1) an ongoing weakening or disruption of plantpollinator interactions derived from ecological perturbations, 2) an adaptive equilibrium in response to stochastic processes, and 3) the presence of unfavourable reproductive traits (for Ononis masquillierii).

Stochastic foundations of dynamic trade and labor market models

This dissertation consists of three self-contained papers that are related to two main topics. In particular, the first and third studies focus on labor market modeling, whereas the second essay presents a dynamic international trade setup.rnrnIn Chapter "Expenses on Labor Market Reforms during Transitional Dynamics", we investigate the arising costs of a potential labor market reform from a government point of view. To analyze various effects of unemployment benefits system changes, this chapter develops a dynamic model with heterogeneous employed and unemployed workers.rn rnIn Chapter "Endogenous Markup Distributions", we study how markup distributions adjust when a closed economy opens up. In order to perform this analysis, we first present a closed-economy general-equilibrium industry dynamics model, where firms enter and exit markets, and then extend our analysis to the open-economy case.rn rnIn Chapter "Unemployment in the OECD - Pure Chance or Institutions?", we examine effects of aggregate shocks on the distribution of the unemployment rates in OECD member countries.rn rnIn all three chapters we model systems that behave randomly and operate on stochastic processes. We therefore exploit stochastic calculus that establishes clear methodological links between the chapters.

Self-dual continuous processes

The important application of semi-static hedging in financial markets naturally leads to the notion of conditionally quasi self-dual processes which is, for continuous semimartingales, related to conditional symmetry properties of both their ordinary as well as their stochastic logarithms. We provide a structure result for continuous conditionally quasi self-dual processes. Our main result is to give a characterization of continuous Ocone martingales via a strong version of self-duality.

Hybrid stochastic simulations of intracellular reaction-diffusion systems.

With the observation that stochasticity is important in biological systems, chemical kinetics have begun to receive wider interest. While the use of Monte Carlo discrete event simulations most accurately capture the variability of molecular species, they become computationally costly for complex reaction-diffusion systems with large populations of molecules. On the other hand, continuous time models are computationally efficient but they fail to capture any variability in the molecular species. In this study a hybrid stochastic approach is introduced for simulating reaction-diffusion systems. We developed an adaptive partitioning strategy in which processes with high frequency are simulated with deterministic rate-based equations, and those with low frequency using the exact stochastic algorithm of Gillespie. Therefore the stochastic behavior of cellular pathways is preserved while being able to apply it to large populations of molecules. We describe our method and demonstrate its accuracy and efficiency compared with the Gillespie algorithm for two different systems. First, a model of intracellular viral kinetics with two steady states and second, a compartmental model of the postsynaptic spine head for studying the dynamics of Ca+2 and NMDA receptors.

Deposition reactors for solar grade silicon: a comparative thermal analysis of a Siemens reactor and a fluidized bed reactor

Polysilicon production costs contribute approximately to 25-33% of the overall cost of the solar panels and a similar fraction of the total energy invested in their fabrication. Understanding the energy losses and the behaviour of process temperature is an essential requirement as one moves forward to design and build large scale polysilicon manufacturing plants. In this paper we present thermal models for two processes for poly production, viz., the Siemens process using trichlorosilane (TCS) as precursor and the fluid bed process using silane (monosilane, MS).We validate the models with some experimental measurements on prototype laboratory reactors relating the temperature profiles to product quality. A model sensitivity analysis is also performed, and the efects of some key parameters such as reactor wall emissivity, gas distributor temperature, etc., on temperature distribution and product quality are examined. The information presented in this paper is useful for further understanding of the strengths and weaknesses of both deposition technologies, and will help in optimal temperature profiling of these systems aiming at lowering production costs without compromising the solar cell quality.

Modeling stochastic gene expression: Implications for haploinsufficiency

There is increasing recognition that stochastic processes regulate highly predictable patterns of gene expression in developing organisms, but the implications of stochastic gene expression for understanding haploinsufficiency remain largely unexplored. We have used simulations of stochastic gene expression to illustrate that gene copy number and expression deactivation rates are important variables in achieving predictable outcomes. In gene expression systems with non-zero expression deactivation rates, diploid systems had a higher probability of uninterrupted gene expression than haploid systems and were more successful at maintaining gene product above a very low threshold. Systems with relatively rapid expression deactivation rates (unstable gene expression) had more predictable responses to a gradient of inducer than systems with slow or zero expression deactivation rates (stable gene expression), and diploid systems were more predictable than haploid, with or without dosage compensation. We suggest that null mutations of a single allele in a diploid organism could decrease the probability of gene expression and present the hypothesis that some haploinsufficiency syndromes might result from an increased susceptibility to stochastic delays of gene initiation or interruptions of gene expression.

Molecular stochastics : a study of direct production of stochastic sequences from transducers /

Vita.

A stochastic control system /

Bibliography: p. 12.

An empirical study of three stochastic approximation techniques applicable to sensitivity testing (U)

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Numerical methods for strong solutions of stochastic differential equations: an overview

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

Stochastic modelling and simulations for solute transport in porous media

A stochastic model for solute transport in aquifers is studied based on the concepts of stochastic velocity and stochastic diffusivity. By applying finite difference techniques to the spatial variables of the stochastic governing equation, a system of stiff stochastic ordinary differential equations is obtained. Both the semi-implicit Euler method and the balanced implicit method are used for solving this stochastic system. Based on the Karhunen-Loeve expansion, stochastic processes in time and space are calculated by means of a spatial correlation matrix. Four types of spatial correlation matrices are presented based on the hydraulic properties of physical parameters. Simulations with two types of correlation matrices are presented.