Solvability of an Infinite System of Singular Integral Equations

2000 Mathematics Subject Classification: 45G15, 26A33, 32A55, 46E15.

α-Mellin Transform and One of Its Applications

MSC 2010: 35R11, 44A10, 44A20, 26A33, 33C45

Nonstandard Finite Difference Schemes with Application to Finance: Option Pricing

2000 Mathematics Subject Classification: 65M06, 65M12.

Low Volatility Options and Numerical Diffusion of Finite Difference Schemes

2000 Mathematics Subject Classification: 65M06, 65M12.

Interaction of Kelvin waves and nonlocality of energy transfer in superfluids

We argue that the physics of interacting Kelvin Waves (KWs) is highly nontrivial and cannot be understood on the basis of pure dimensional reasoning. A consistent theory of KW turbulence in superfluids should be based upon explicit knowledge of their interactions. To achieve this, we present a detailed calculation and comprehensive analysis of the interaction coefficients for KW turbuelence, thereby, resolving previous mistakes stemming from unaccounted contributions. As a first application of this analysis, we derive a local nonlinear (partial differential) equation. This equation is much simpler for analysis and numerical simulations of KWs than the Biot-Savart equation, and in contrast to the completely integrable local induction approximation (in which the energy exchange between KWs is absent), describes the nonlinear dynamics of KWs. Second, we show that the previously suggested Kozik-Svistunov energy spectrum for KWs, which has often been used in the analysis of experimental and numerical data in superfluid turbulence, is irrelevant, because it is based upon an erroneous assumption of the locality of the energy transfer through scales. Moreover, we demonstrate the weak nonlocality of the inverse cascade spectrum with a constant particle-number flux and find resulting logarithmic corrections to this spectrum.

Dinamikus optimalizálás és a Leontief-modell (Dynamic optimization and the Leontief model)

A tanulmány a variációszámítás gazdasági alkalmazásaiból ismertet hármat. Mindhárom alkalmazás a Leontief-modellen alapszik. Az optimális pályák vizsgálata után arra keressük a választ, hogy az Euler–Lagrange-differenciálegyenlet rendszerrel kapott megoldások valóban optimális megoldásai-e a modelleknek. Arra a következtetésre jut a tanulmány, hogy csak pótlólagos közgazdasági feltételek bevezetésével határozhatók meg az optimális megoldások. Ugyanakkor a megfogalmazott feltételek segítségével az ismertetett modellek egy általánosabb keretbe illeszthetők. A tanulmány végső eredménye az, hogy mind a három modell optimális megoldása a Neumann-sugárnak felel meg. /===/ The study presents three economic applications of variation calculations. All three rely on the Leontief model. After examination of the optimal courses, an answer is sought to whether the solutions to the Euler–Lagrange differential equation system are really opti-mal solutions to the models. The study concludes that the optimal solutions can only be determined by introducing additional economic conditions. At the same time, the models presented can be fitted into a general framework with the help of the conditions outlined. The final conclusion of the study is that the optimal solution of all three models fits into the Neumann band.

Derivatív pénzügyi termékek árdinamikája és az új típusú kamatlábmodellek (Interest rate models and the price processes of financial derivatives)

Ennek a cikknek az a célja, hogy áttekintést adjon annak a folyamatnak néhány főbb állomásáról, amit Black, Scholes és Merton opcióárazásról írt cikkei indítottak el a 70-es évek elején, és ami egyszerre forradalmasította a fejlett nyugati pénzügyi piacokat és a pénzügyi elméletet. / === / This review article compares the development of financial theory within and outside Hungary in the last three decades starting with the Black-Scholes revolution. Problems like the term structure of interest rate volatilities which is in the focus of many research internationally has not received the proper attention among the Hungarian economists. The article gives an overview of no-arbitrage pricing, the partial differential equation approach and the related numerical techniques, like the lattice methods in pricing financial derivatives. The relevant concepts of the martingal approach are overviewed. There is a special focus on the HJM framework of the interest rate development. The idea that the volatility and the correlation can be traded is a new horizon to the Hungarian capital market.

Lokális energiamódszer kicsi rendben gerjesztett Liénard-egyenletekre (Local energy method for little order forced equations)

Az x''+f(x) x'+g(x) = 0 alakú Liénard-típusú differenciálegyenlet központi szerepet játszik az üzleti ciklusok Káldor-Kalecki-féle [3,4] és Goodwin-féle [2] modelljeiben, sőt egy a munkanélküliség és vállalkozás-ösztönzések ciklikus változásait leíró újabb modellben [1] is. De ugyanez a nemlineáris egyenlettípus a gerjesztett ingák és elektromos rezgőkörök elméletét is felöleli [5]. Az ezzel kapcsolatos irodalom nagyrészt a határciklusok létezését vizsgálja (pl. [5]), pedig az alapvető stabilitási kérdések jóval áttekinthetőbb módon kezelhetők, s a kapott eredmények közvetve a határciklusok létezésének feltételeit is sokkal jobban be tudják határolni. Jelen dolgozatban az egyváltozós analízis hatékony nyelvezetével olyan egyszerűen megfogalmazható eredményekhez jutunk, amelyek képesek kitágítani az üzleti és más közgazdasági ciklusok modelljeinek kereteit, illetve pl. az [1]-beli modellhez újabb szemléltető speciális eseteket is nyerünk. ____ The Liénard type differential equation of the form x00 + f(x) ¢ x0 + g(x) = 0 has a central role in business cycle models by Káldor [3], Kalecki [4] and Goodwin [2], moreover in a new model describing the cyclical behavior of unemployment and entrepreneurship [1]. The same type of nonlinear equation explains the features of forced pendulums and electric circuits [5]. The related literature discusses mainly the existence of limit cycles, although the fundamental stability questions of this topic can be managed much more easily. The achieved results also outline the conditions for the existence of limit cycles. In this work, by the effective language of real valued analysis, we obtain easy-formulated results which may broaden the frames of economic and business cycle models, moreover we may gain new illustrative particular cases for e.g., [1].

Theoretical Investigation of Intra- and Inter-cellular Spatiotemporal Calcium Patterns in Microcirculation

Microcirculatory vessels are lined by endothelial cells (ECs) which are surrounded by a single or multiple layer of smooth muscle cells (SMCs). Spontaneous and agonist induced spatiotemporal calcium (Ca2+) events are generated in ECs and SMCs, and regulated by complex bi-directional signaling between the two layers which ultimately determines the vessel tone. The contractile state of microcirculatory vessels is an important factor in the determination of vascular resistance, blood flow and blood pressure. This dissertation presents theoretical insights into some of the important and currently unresolved phenomena in microvascular tone regulation. Compartmental and continuum models of isolated EC and SMC, coupled EC-SMC and a multi-cellular vessel segment with deterministic and stochastic descriptions of the cellular components were developed, and the intra- and inter-cellular spatiotemporal Ca2+ mobilization was examined. Coupled EC-SMC model simulations captured the experimentally observed localized subcellular EC Ca2+ events arising from the opening of EC transient receptor vanilloid 4 (TRPV4) channels and inositol triphosphate receptors (IP3Rs). These localized EC Ca2+ events result in endothelium-derived hyperpolarization (EDH) and Nitric Oxide (NO) production which transmit to the adjacent SMCs to ultimately result in vasodilation. The model examined the effect of heterogeneous distribution of cellular components and channel gating kinetics in determination of the amplitude and spread of the Ca2+ events. The simulations suggested the necessity of co-localization of certain cellular components for modulation of EDH and NO responses. Isolated EC and SMC models captured intracellular Ca2+ wave like activity and predicted the necessity of non-uniform distribution of cellular components for the generation of Ca2+ waves. The simulations also suggested the role of membrane potential dynamics in regulating Ca2+ wave velocity. The multi-cellular vessel segment model examined the underlying mechanisms for the intercellular synchronization of spontaneous oscillatory Ca2+ waves in individual SMC. From local subcellular events to integrated macro-scale behavior at the vessel level, the developed multi-scale models captured basic features of vascular Ca2+ signaling and provide insights for their physiological relevance. The models provide a theoretical framework for assisting investigations on the regulation of vascular tone in health and disease.

Análise do fluxo d’água na barragem Engenheiro Armando Ribeiro Gonçalves - Açu/RN

The solution of partial differential equation of seepage problems is difficult to find analytically, especially for situations that involve great complexity. To overcome this problem, software based on finite differences and finite elements are usually used. This work presents the use of a finite element software, the GEO5, to solve the seepage problem at a dam of very complex section, the dam Eng. Armando Ribeiro Gonçalves, which at the end of its construction suffered rupture of the upstream slope at the central dam and then went through a process of reconstruction and auscultation. The analyses were performed for the operating condition of the reservoir, with an established flow. A numerical model was developed based on the level readings of the reservoir water and their piezometric readings as a proposal for the evaluation and future behavior prediction of the dam on established flow conditions. The use of constitutive models with the aid of computer systems is reflected in a way to predict future risk situations so they can be prevented

Effects of seasonally varying temperature and salinity on the dynamics of sea lice (Lepeophtheirus salmonis)

Sea lice (Lepeophtheirus salmonis) are an economically significant parasite in salmonid aquaculture. They exhibit temperature-dependent development rates and salinity-dependent mortality, which can greatly impact sea lice population dynamics, but no deterministic models have incorporated these seasonal variables. To understand how seasonality affects sea lice population dynamics, I derive a delay differential equation model with temperature and salinity dependence. I find that peak reproductive output in Newfoundland and British Columbia differs by four months. A sensitivity analysis shows sea lice abundance is most sensitive to variation in mean annual water temperature and salinity, whereas it is lease sensitive to infection rate. Additionally, I investigate the effects of production cycle timing on sea lice management and find that optimal production cycle start times are between the 281st and 337th days of the year in Newfoundland. I also demonstrate that adjusting follow-up treatment timing in response to temperature can improve treatment regimes. My results suggest that effective sea lice management requires consideration of local temperature and salinity patterns.

Essays on Job Search and Labor Market Dynamics

This dissertation consists of three separate essays on job search and labor market dynamics. In the first essay, “The Impact of Labor Market Conditions on Job Creation: Evidence from Firm Level Data”, I study how much changes in labor market conditions reduce employment fluctuations over the business cycle. Changes in labor market conditions make hiring more expensive during expansions and cheaper during recessions, creating counter-cyclical incentives for job creation. I estimate firm level elasticities of labor demand with respect to changes in labor market conditions, considering two margins: changes in labor market tightness and changes in wages. Using employer-employee matched data from Brazil, I find that all firms are more sensitive to changes in wages rather than labor market tightness, and there is substantial heterogeneity in labor demand elasticity across regions. Based on these results, I demonstrate that changes in labor market conditions reduce the variance of employment growth over the business cycle by 20% in a median region, and this effect is equally driven by changes along each margin. Moreover, I show that the magnitude of the effect of labor market conditions on employment growth can be significantly affected by economic policy. In particular, I document that the rapid growth of the national minimum wages in Brazil in 1997-2010 amplified the impact of the change in labor market conditions during local expansions and diminished this impact during local recessions.

In the second essay, “A Framework for Estimating Persistence of Local Labor

Demand Shocks”, I propose a decomposition which allows me to study the persistence of local labor demand shocks. Persistence of labor demand shocks varies across industries, and the incidence of shocks in a region depends on the regional industrial composition. As a result, less diverse regions are more likely to experience deeper shocks, but not necessarily more long lasting shocks. Building on this idea, I propose a decomposition of local labor demand shocks into idiosyncratic location shocks and nationwide industry shocks and estimate the variance and the persistence of these shocks using the Quarterly Census of Employment and Wages (QCEW) in 1990-2013.

In the third essay, “Conditional Choice Probability Estimation of Continuous- Time Job Search Models”, co-authored with Peter Arcidiacono and Arnaud Maurel, we propose a novel, computationally feasible method of estimating non-stationary job search models. Non-stationary job search models arise in many applications, where policy change can be anticipated by the workers. The most prominent example of such policy is the expiration of unemployment benefits. However, estimating these models still poses a considerable computational challenge, because of the need to solve a differential equation numerically at each step of the optimization routine. We overcome this challenge by adopting conditional choice probability methods, widely used in dynamic discrete choice literature, to job search models and show how the hazard rate out of unemployment and the distribution of the accepted wages, which can be estimated in many datasets, can be used to infer the value of unemployment. We demonstrate how to apply our method by analyzing the effect of the unemployment benefit expiration on duration of unemployment using the data from the Survey of Income and Program Participation (SIPP) in 1996-2007.

On thermodynamics in the primary power conversion of oscillating water column wave energy converters

The paper presents an investigation to the thermodynamics of the air flow in the air chamber for the oscillating water column wave energy converters, in which the oscillating water surface in the water column pressurizes or de-pressurises the air in the chamber. To study the thermodynamics and the compressibility of the air in the chamber, a method is developed in this research: the power take-off is replaced with an accepted semi-empirical relationship between the air flow rate and the oscillating water column chamber pressure, and the thermodynamic process is simplified as an isentropic process. This facilitates the use of a direct expression for the work done on the power take-off by the flowing air and the generation of a single differential equation that defines the thermodynamic process occurring inside the air chamber. Solving the differential equation, the chamber pressure can be obtained if the interior water surface motion is known or the chamber volume (thus the interior water surface motion) if the chamber pressure is known. As a result, the effects of the air compressibility can be studied. Examples given in the paper have shown the compressibility, and its effects on the power losses for large oscillating water column devices.

Scaling limits of a model for selection at two scales

The dynamics of a population undergoing selection is a central topic in evolutionary biology. This question is particularly intriguing in the case where selective forces act in opposing directions at two population scales. For example, a fast-replicating virus strain outcompetes slower-replicating strains at the within-host scale. However, if the fast-replicating strain causes host morbidity and is less frequently transmitted, it can be outcompeted by slower-replicating strains at the between-host scale. Here we consider a stochastic ball-and-urn process which models this type of phenomenon. We prove the weak convergence of this process under two natural scalings. The first scaling leads to a deterministic nonlinear integro-partial differential equation on the interval $[0,1]$ with dependence on a single parameter, $\lambda$. We show that the fixed points of this differential equation are Beta distributions and that their stability depends on $\lambda$ and the behavior of the initial data around $1$. The second scaling leads to a measure-valued Fleming-Viot process, an infinite dimensional stochastic process that is frequently associated with a population genetics.

Petri Net Siphon Analysis and Network Centrality Measures for Identifying Combination Therapies in Signaling Pathways

Aberrant behavior of biological signaling pathways has been implicated in diseases such as cancers. Therapies have been developed to target proteins in these networks in the hope of curing the illness or bringing about remission. However, identifying targets for drug inhibition that exhibit good therapeutic index has proven to be challenging since signaling pathways have a large number of components and many interconnections such as feedback, crosstalk, and divergence. Unfortunately, some characteristics of these pathways such as redundancy, feedback, and drug resistance reduce the efficacy of single drug target therapy and necessitate the employment of more than one drug to target multiple nodes in the system. However, choosing multiple targets with high therapeutic index poses more challenges since the combinatorial search space could be huge. To cope with the complexity of these systems, computational tools such as ordinary differential equations have been used to successfully model some of these pathways. Regrettably, for building these models, experimentally-measured initial concentrations of the components and rates of reactions are needed which are difficult to obtain, and in very large networks, they may not be available at the moment. Fortunately, there exist other modeling tools, though not as powerful as ordinary differential equations, which do not need the rates and initial conditions to model signaling pathways. Petri net and graph theory are among these tools. In this thesis, we introduce a methodology based on Petri net siphon analysis and graph network centrality measures for identifying prospective targets for single and multiple drug therapies. In this methodology, first, potential targets are identified in the Petri net model of a signaling pathway using siphon analysis. Then, the graph-theoretic centrality measures are employed to prioritize the candidate targets. Also, an algorithm is developed to check whether the candidate targets are able to disable the intended outputs in the graph model of the system or not. We implement structural and dynamical models of ErbB1-Ras-MAPK pathways and use them to assess and evaluate this methodology. The identified drug-targets, single and multiple, correspond to clinically relevant drugs. Overall, the results suggest that this methodology, using siphons and centrality measures, shows promise in identifying and ranking drugs. Since this methodology only uses the structural information of the signaling pathways and does not need initial conditions and dynamical rates, it can be utilized in larger networks.