Towards the design and implementation of aspect-oriented programming for spreadsheets

A spreadsheet usually starts as a simple and singleuser software artifact, but, as frequent as in other software systems, quickly evolves into a complex system developed by many actors. Often, different users work on different aspects of the same spreadsheet: while a secretary may be only involved in adding plain data to the spreadsheet, an accountant may define new business rules, while an engineer may need to adapt the spreadsheet content so it can be used by other software systems.Unfortunately,spreadsheetsystemsdonotoffermodular mechanisms, and as a consequence, some of the previous tasks may be defined by adding intrusive “code” to the spreadsheet. In this paper we go through the design and implementation of an aspect-oriented language for spreadsheets so that users can work on different aspects of a spreadsheet in a modular way. For example, aspects can be defined in order to introduce new business rules to an existing spreadsheet, or to manipulate the spreadsheet data to be ported to another system. Aspects are defined as aspect-oriented program specifications that are dynamically woven into the underlying spreadsheet by an aspect weaver. In this aspect-oriented style of spreadsheet development, differentusers develop,orreuse,aspects withoutaddingintrusive code to the original spreadsheet. Such code is added/executed by the spreadsheet weaving mechanism proposed in this paper.

Metaphorisms in programming

This paper introduces the metaphorism pattern of relational specification and addresses how specification following this pattern can be refined into recursive programs. Metaphorisms express input-output relationships which preserve relevant information while at the same time some intended optimization takes place. Text processing, sorting, representation changers, etc., are examples of metaphorisms. The kind of metaphorism refinement proposed in this paper is a strategy known as change of virtual data structure. It gives sufficient conditions for such implementations to be calculated using relation algebra and illustrates the strategy with the derivation of quicksort as example.

Stochastic effects and uncertainties in assessing electromagnetic interactions with control systems

Electromagnetic compatibility, lightning, crosstalk surge voltages, Monte Carlo simulation, accident initiator

stochastic method for automated matching of horizons across a fault in 3D seismic data

Seismic analysis, horizon matching, fault tracking, marked point process,stochastic annealing

Macroinvertebrates under stochastic hydrological disturbance in Cerrado streams of Central Brazil

In the Cerrado vegetation, where the seasonal is well defined, rainfall has an important role in controlling the flow of streams and consequently on the structure of macroinvertebrates community. Despite the effects of rainfall associated with seasonality are well studied, little is known about the effects of stochastic rains on the community. In the present study we evaluated the structure and faunal composition of four first-order streams in Central Brazil during the dry season in two years, with and without stochastic rains. Community sampling was done by colonization of boards of high density polyethylene (HDPE), removed after one month submerged in streams. Analysis of Variance (ANOVA) performed indicated no difference in rarefied richness between the two periods, different from numeric density of organisms that was higher in the period without disturbance; moreover, the Detrended Correspondence Analysis (DCA) revealed differences in faunal composition between the two periods. Our results indicate that stochastic rainfall is an important factor in structuring the macroinvertebrates community in studied region.

Linear stochastic differential algebraic equations with constant coefficients

We consider linear stochastic differential-algebraic equations with constant coefficients and additive white noise. Due to the nature of this class of equations, the solution must be defined as a generalised process (in the sense of Dawson and Fernique). We provide sufficient conditions for the law of the variables of the solution process to be absolutely continuous with respect to Lebesgue measure.

The optimal behaviour of firms facing stochastic costs

This paper aims at assessing the optimal behavior of a firm facing stochastic costs of production. In an imperfectly competitive setting, we evaluate to what extent a firm may decide to locate part of its production in other markets different from which it is actually settled. This decision is taken in a stochastic environment. Portfolio theory is used to derive the optimal solution for the intertemporal profit maximization problem. In such a framework, splitting production between different locations may be optimal when a firm is able to charge different prices in the different local markets.

Stochastic dominance and absolute risk aversion

In this paper we propose the infimum of the Arrow-Pratt index of absolute risk aversion as a measure of global risk aversion of a utility function. We then show that, for any given arbitrary pair of distributions, there exists a threshold level of global risk aversion such that all increasing concave utility functions with at least as much global risk aversion would rank the two distributions in the same way. Furthermore, this threshold level is sharp in the sense that, for any lower level of global risk aversion, we can find two utility functions in this class yielding opposite preference relations for the two distributions.

Generalized backward doubly stochastic differential equations and SPDEs with nonlinear Neumann boundary conditions

In this paper, a new class of generalized backward doubly stochastic differential equations is investigated. This class involves an integral with respect to an adapted continuous increasing process. A probabilistic representation for viscosity solutions of semi-linear stochastic partial differential equations with a Neumann boundary condition is given.

Reflected Backward Stochastic Differential Equation with Jumps and RCLL Obstacle

In this paper we study one-dimensional reflected backward stochastic differential equation when the noise is driven by a Brownian motion and an independent Poisson point process when the solution is forced to stay above a right continuous left-hand limited obstacle. We prove existence and uniqueness of the solution by using a penalization method combined with a monotonic limit theorem.

Improving the risk concept: a revision of Arrow-Pratt theory in the context of controlled dynamic stochastic environments

In the literature on risk, one generally assume that uncertainty is uniformly distributed over the entire working horizon, when the absolute risk-aversion index is negative and constant. From this perspective, the risk is totally exogenous, and thus independent of endogenous risks. The classic procedure is "myopic" with regard to potential changes in the future behavior of the agent due to inherent random fluctuations of the system. The agent's attitude to risk is rigid. Although often criticized, the most widely used hypothesis for the analysis of economic behavior is risk-neutrality. This borderline case must be envisaged with prudence in a dynamic stochastic context. The traditional measures of risk-aversion are generally too weak for making comparisons between risky situations, given the dynamic �complexity of the environment. This can be highlighted in concrete problems in finance and insurance, context for which the Arrow-Pratt measures (in the small) give ambiguous.

Improving the effort concept: a revision of the traditional approach in the context of controlled Dynamic Stochastic Environments

The objective of this paper is to re-evaluate the attitude to effort of a risk-averse decision-maker in an evolving environment. In the classic analysis, the space of efforts is generally discretized. More realistic, this new approach emploies a continuum of effort levels. The presence of multiple possible efforts and performance levels provides a better basis for explaining real economic phenomena. The traditional approach (see, Laffont, J. J. & Tirole, J., 1993, Salanie, B., 1997, Laffont, J.J. and Martimort, D, 2002, among others) does not take into account the potential effect of the system dynamics on the agent's behavior to effort over time. In the context of a Principal-agent relationship, not only the incentives of the Principal can determine the private agent to allocate a good effort, but also the evolution of the dynamic system. The incentives can be ineffective when the environment does not incite the agent to invest a good effort. This explains why, some effici

A class of stochastic games with infinitely many interacting agents related to Glauber dynamics on random graphs

We introduce and study a class of infinite-horizon nonzero-sum non-cooperative stochastic games with infinitely many interacting agents using ideas of statistical mechanics. First we show, in the general case of asymmetric interactions, the existence of a strategy that allows any player to eliminate losses after a finite random time. In the special case of symmetric interactions, we also prove that, as time goes to infinity, the game converges to a Nash equilibrium. Moreover, assuming that all agents adopt the same strategy, using arguments related to those leading to perfect simulation algorithms, spatial mixing and ergodicity are proved. In turn, ergodicity allows us to prove “fixation”, i.e. that players will adopt a constant strategy after a finite time. The resulting dynamics is related to zerotemperature Glauber dynamics on random graphs of possibly infinite volume.

Strong solutions for stochastic porous media equations with jumps

We prove global well-posedness in the strong sense for stochastic generalized porous media equations driven by locally square integrable martingales with stationary independent increments.