ECONOMICAL OCCUPATION OF AGRICULTURAL AREA OF PIRACICABA (SAO PAULO STATE, BRAZIL), INCLUDING RISK THROUGH LINEAR PROGRAMMING

The economic occupation of an area of 500 ha for Piracicaba was studied with the irrigated cultures of maize, tomato, sugarcane and beans, having used models of deterministic linear programming and linear programming including risk for the Target-Motad model, where two situations had been analyzed. In the deterministic model the area was the restrictive factor and the water was not restrictive for none of the tested situations. For the first situation the gotten maximum income was of R$ 1,883,372.87 and for the second situation it was of R$ 1,821,772.40. In the model including risk a producer that accepts risk can in the first situation get the maximum income of R$ 1,883,372. 87 with a minimum risk of R$ 350 year(-1), and in the second situation R$ 1,821,772.40 with a minimum risk of R$ 40 year(-1). Already a producer averse to the risk can get in the first situation a maximum income of R$ 1,775,974.81 with null risk and for the second situation R$ 1.707.706, 26 with null risk, both without water restriction. These results stand out the importance of the inclusion of the risk in supplying alternative occupations to the producer, allowing to a producer taking of decision considered the risk aversion and the pretension of income.

Geographic variation and positive selection on M7 lysin, an acrosomal sperm protein in mussels (Mytilus spp.)

Successful fertilization in free-spawning marine organisms depends on the interactions between genes expressed on the surfaces of eggs and sperm. Positive selection frequently characterizes the molecular evolution of such genes, raising the possibility that some common deterministic process drives the evolution of gamete recognition genes and may even be important for understanding the evolution of prezygotic isolation and speciation in the marine realm. One hypothesis is that gamete recognition genes are subject to selection for prezygotic isolation, namely reinforcement. In a previous study, positive selection on the gene coding for the acrosomal sperm protein M7 lysin was demonstrated among allopatric populations of mussels in the Mytilus edulis species group (M. edulis, M. galloprovincialis, and M. trossulus). Here, we expand sampling to include M7 lysin haplotypes from populations where mussel species are sympatric and hybridize to determine whether there is a pattern of reproductive character displacement, which would be consistent with reinforcement driving selection on this gene. We do not detect a strong pattern of reproductive character displacement; there are no unique haplotypes in sympatry nor is there consistently greater population structure in comparisons involving sympatric populations. One distinct group of haplotypes, however, is strongly affected by natural selection and this group of haplotypes is found within M. galloprovincialis populations throughout the Northern Hemisphere concurrent with haplotypes common to M. galloprovincialis and M. edulis. We suggest that balancing selection, perhaps resulting from sexual conflicts between sperm and eggs, maintains old allelic diversity within M. galloprovincialis.

Cytoplasmic incompatibility in Drosophila populations: influence of assortative mating on symbiont distribution

Cytoplasmic incompatibility is known to occur between strains of both Drosophila simulans and D. melanogaster. Incompatibility is associated with the infection of Drosophila with microorganismal endosymbionts. This paper reports survey work conducted on strains of D. simulans and D. melanogaster from diverse geographical locations finding that infected populations are relatively rare and scattered in their distribution. The distribution of infected populations of D. simulans appears to be at odds with deterministic models predicting the rapid spread of the infection through uninfected populations. Examination of isofemale lines from four localities in California where populations appear to be polymorphic for the infection failed to find evidence for consistent assortative mating preferences between infected and uninfected populations that may explain the basis for the observed polymorphism.

Modeling ex vivo hematopoiesis using chemical engineering metaphors

Ex vivo hematopoiesis is increasingly used for clinical applications. Models of ex vivo hematopoiesis are required to better understand the complex dynamics and to optimize hematopoietic culture processes. A general mathematical modeling framework is developed which uses traditional chemical engineering metaphors to describe the complex hematopoietic dynamics. Tanks and tubular reactors are used to describe the (pseudo-) stochastic and deterministic elements of hematopoiesis, respectively. Cells at any point in the differentiation process can belong to either an immobilized, inert phase (quiescent cells) or a mobile, active phase (cycling cells). The model describes five processes: (1) flow (differentiation), (2) autocatalytic formation (growth),(3) degradation (death), (4) phase transition from immobilized to mobile phase (quiescent to cycling transition), and (5) phase transition from mobile to immobilized phase (cycling to quiescent transition). The modeling framework is illustrated with an example concerning the effect of TGF-beta 1 on erythropoiesis. (C) 1998 Published by Elsevier Science Ltd. All rights reserved.

A method for setting the size of plant conservation target areas

Realistic time frames in which management decisions are made often preclude the completion of the detailed analyses necessary for conservation planning. Under these circumstances, efficient alternatives may assist in approximating the results of more thorough studies that require extensive resources and time. We outline a set of concepts and formulas that may be used in lieu of detailed population viability analyses and habitat modeling exercises to estimate the protected areas required to provide desirable conservation outcomes for a suite of threatened plant species. We used expert judgment of parameters and assessment of a population size that results in a specified quasiextinction risk based on simple dynamic models The area required to support a population of this size is adjusted to take into account deterministic and stochastic human influences, including small-scale disturbance deterministic trends such as habitat loss, and changes in population density through processes such as predation and competition. We set targets for different disturbance regimes and geographic regions. We applied our methods to Banksia cuneata, Boronia keysii, and Parsonsia dorrigoensis, resulting in target areas for conservation of 1102, 733, and 1084 ha, respectively. These results provide guidance on target areas and priorities for conservation strategies.

Stochastic structure and individual-tree growth models

The majority of past and current individual-tree growth modelling methodologies have failed to characterise and incorporate structured stochastic components. Rather, they have relied on deterministic predictions or have added an unstructured random component to predictions. In particular, spatial stochastic structure has been neglected, despite being present in most applications of individual-tree growth models. Spatial stochastic structure (also called spatial dependence or spatial autocorrelation) eventuates when spatial influences such as competition and micro-site effects are not fully captured in models. Temporal stochastic structure (also called temporal dependence or temporal autocorrelation) eventuates when a sequence of measurements is taken on an individual-tree over time, and variables explaining temporal variation in these measurements are not included in the model. Nested stochastic structure eventuates when measurements are combined across sampling units and differences among the sampling units are not fully captured in the model. This review examines spatial, temporal, and nested stochastic structure and instances where each has been characterised in the forest biometry and statistical literature. Methodologies for incorporating stochastic structure in growth model estimation and prediction are described. Benefits from incorporation of stochastic structure include valid statistical inference, improved estimation efficiency, and more realistic and theoretically sound predictions. It is proposed in this review that individual-tree modelling methodologies need to characterise and include structured stochasticity. Possibilities for future research are discussed. (C) 2001 Elsevier Science B.V. All rights reserved.

Extrinsic versus intrinsic factors in the decline and extinction of Australian marsupials

Recent attempts to explain the susceptibility of vertebrates to declines worldwide have largely focused on intrinsic factors such as body size, reproductive potential, ecological specialization, geographical range and phylogenetic longevity. Here, we use a database of 145 Australian marsupial species to test the effects of both intrinsic and extrinsic factors in a multivariate comparative approach. We model five intrinsic (body size, habitat specialization, diet, reproductive rate and range size) and four extrinsic (climate and range overlap with introduced foxes, sheep and rabbits) factors. We use quantitative measures of geographical range contraction as indices of decline. We also develop a new modelling approach of phylogenetically independent contrasts combined with imputation of missing values to deal simultaneously with phylogenetic structuring and missing data. One extrinsic variable-geographical range overlap with sheep-was the only consistent predictor of declines. Habitat specialization was independently but less consistently associated with declines. This suggests that extrinsic factors largely determine interspecific variation in extinction risk among Australian marsupials, and that the intrinsic factors that are consistently associated with extinction risk in other vertebrates are less important in this group. We conclude that recent anthropogenic changes have been profound enough to affect species on a continent-wide scale, regardless of their intrinsic biology.

A note on the multiple partners assignment game

In the assignment game of Shapley and Shubik [Shapley, L.S., Shubik, M., 1972. The assignment game. I. The core, International journal of Game Theory 1, 11-130] agents are allowed to form one partnership at most. That paper proves that, in the context of firms and workers, given two stable payoffs for the firms there is a stable payoff which gives each firm the larger of the two amounts and also one which gives each of them the smaller amount. Analogous result applies to the workers. Sotomayor [Sotomayor, M., 1992. The multiple partners game. In: Majumdar, M. (Ed.), Dynamics and Equilibrium: Essays in Honor to D. Gale. Mcmillian, pp. 322-336] extends this analysis to the case where both types of agents may form more than one partnership and an agent`s payoff is multi-dimensional. Instead, this note concentrates in the total payoff of the agents. It is then proved the rather unexpected result that again the maximum of any pair of stable payoffs for the firms is stable but the minimum need not be, even if we restrict the multiplicity of partnerships to one of the sides. (C) 2009 Elsevier B.V. All rights reserved.

Price dispersion and price indexes

The traditional theory of price index numbers is based on the law of one price. But in the real world, we frequently observe the existence of an equilibrium price dispersion instead of one price of equilibrium. This article discusses the effects of price dispersion on two price indexes: the cost of living index and the consumer price index. With price dispersion and consumer searching for the lowest price, these indexes cannot be interpreted as deterministic indicators, but as stochastic indicators, and they can be biased if price dispersion is not taken into account. A measure for the bias of the consumer price index is proposed and the article ends with an estimation of the bias based on data obtained from the consumer price index calculated for the city of Sao Paulo, Brazil, from January 1988 through December 2004. The period analysed is very interesting, because it exhibits different inflationary environments: high levels and high volatility of the rates of inflation with great price dispersion until July 1994 and low and relatively stable rates of inflation with prices less dispersed after August 1994.

Loss of Ergodicity in the Transition from Annealed to Quenched Disorder in a Finite Kinetic Ising Model

We consider a kinetic Ising model which represents a generic agent-based model for various types of socio-economic systems. We study the case of a finite (and not necessarily large) number of agents N as well as the asymptotic case when the number of agents tends to infinity. The main ingredient are individual decision thresholds which are either fixed over time (corresponding to quenched disorder in the Ising model, leading to nonlinear deterministic dynamics which are generically non-ergodic) or which may change randomly over time (corresponding to annealed disorder, leading to ergodic dynamics). We address the question how increasing the strength of annealed disorder relative to quenched disorder drives the system from non-ergodic behavior to ergodicity. Mathematically rigorous analysis provides an explicit and detailed picture for arbitrary realizations of the quenched initial thresholds, revealing an intriguing ""jumpy"" transition from non-ergodicity with many absorbing sets to ergodicity. For large N we find a critical strength of annealed randomness, above which the system becomes asymptotically ergodic. Our theoretical results suggests how to drive a system from an undesired socio-economic equilibrium (e. g. high level of corruption) to a desirable one (low level of corruption).

A family of perfect hashing methods

Minimal perfect hash functions are used for memory efficient storage and fast retrieval of items from static sets. We present an infinite family of efficient and practical algorithms for generating order preserving minimal perfect hash functions. We show that almost all members of the family construct space and time optimal order preserving minimal perfect hash functions, and we identify the one with minimum constants. Members of the family generate a hash function in two steps. First a special kind of function into an r-graph is computed probabilistically. Then this function is refined deterministically to a minimal perfect hash function. We give strong theoretical evidence that the first step uses linear random time. The second step runs in linear deterministic time. The family not only has theoretical importance, but also offers the fastest known method for generating perfect hash functions.

Chance-lowering causes

Philosophers have long been fascinated by the connection between cause and effect: are 'causes' things we can experience, or are they concepts provided by our minds? The study of causation goes back to Aristotle, but resurged with David Hume and Immanuel Kant, and is now one of the most important topics in metaphysics. Most of the recent work done in this area has attempted to place causation in a deterministic, scientific, worldview. But what about the unpredictable and chancey world we actually live in: can one theory of causation cover all instances of cause and effect?Cause and Chance: Causation in an Indeterministic Worldis a collection of specially written papers by world-class metaphysicians. Its focus is the problem facing the 'reductionist' approach to causation: the attempt to cover all types of causation, deterministic and indeterministic, with one basic theory.

Implicit Taylor methods for stiff stochastic differential equations

In this paper we discuss implicit Taylor methods for stiff Ito stochastic differential equations. Based on the relationship between Ito stochastic integrals and backward stochastic integrals, we introduce three implicit Taylor methods: the implicit Euler-Taylor method with strong order 0.5, the implicit Milstein-Taylor method with strong order 1.0 and the implicit Taylor method with strong order 1.5. The mean-square stability properties of the implicit Euler-Taylor and Milstein-Taylor methods are much better than those of the corresponding semi-implicit Euler and Milstein methods and these two implicit methods can be used to solve stochastic differential equations which are stiff in both the deterministic and the stochastic components. Numerical results are reported to show the convergence properties and the stability properties of these three implicit Taylor methods. The stability analysis and numerical results show that the implicit Euler-Taylor and Milstein-Taylor methods are very promising methods for stiff stochastic differential equations.

Stiffly accurate Runge-Kutta methods for stiff stochastic differential equations

In this paper we discuss implicit methods based on stiffly accurate Runge-Kutta methods and splitting techniques for solving Stratonovich stochastic differential equations (SDEs). Two splitting techniques: the balanced splitting technique and the deterministic splitting technique, are used in this paper. We construct a two-stage implicit Runge-Kutta method with strong order 1.0 which is corrected twice and no update is needed. The stability properties and numerical results show that this approach is suitable for solving stiff SDEs. (C) 2001 Elsevier Science B.V. All rights reserved.

Fitting a mixture model to three-mode three-way data with missing information

When the data consist of certain attributes measured on the same set of items in different situations, they would be described as a three-mode three-way array. A mixture likelihood approach can be implemented to cluster the items (i.e., one of the modes) on the basis of both of the other modes simultaneously (i.e,, the attributes measured in different situations). In this paper, it is shown that this approach can be extended to handle three-mode three-way arrays where some of the data values are missing at random in the sense of Little and Rubin (1987). The methodology is illustrated by clustering the genotypes in a three-way soybean data set where various attributes were measured on genotypes grown in several environments.