Abstract:
mortality of plutella xylostella (lepidoptera, plutellidae) by parasitoids in the province of santa fe, argentina. plutella xylostella (linnaeus, 1758) (lepidoptera, plutellidae) larvae cause severe economic damage on cabbage, brassica oleracea l. variety capitata (brassicaceae), in the horticultural fields in the province of santa fe, argentina. overuse of broad spectrum insecticides affects the action of natural enemies of this insect on cabbage. the objectives of this work were to identify the parasitoids of p. xylostella and to determine their influence on larva and pupa mortality. weekly collections of larvae and pupae were randomly conducted in cabbage crops during spring 2006 and 2007. the immature forms collected were classified according to their developmental stage: l1 and l2 (ls = small larvae), l3 (lm = medium larvae), l4 (ll = large larvae), pre-pupae and pupae (p). each individual was observed daily in the laboratory until the adult pest or parasitoid emergence. we identified parasitoids, the number of instar and the percentage of mortality of p. xylostella for each species of parasitoid. parasitoids recorded were: diadegma insulare (cresson, 1875) (hymenoptera, ichneumonidae), oomyzus sokolowskii (kurdjumov, 1912) (hymenoptera, eulophidae), cotesia plutellae (kurdjumov, 1912) (hymenoptera, braconidae) and an unidentified species of chalcididae (hymenoptera). besides parasitoids, an unidentified entomopathogenic fungus was also recorded in 2006 and 2007. in 2006, the most successful parasitoids were d. insulare and o. sokolowskii, while in 2007 only d. insulare exerted a satisfactory control and it attacked the early instars of the pest.

Abstract:
It has recently been observed that a stochastic (infinite degree of freedom) time series with a $1/f^\alpha$ power spectrum can exhibit a finite correlation dimension, even for arbitrarily large data sets. [A.R. Osborne and A.~Provenzale, {\sl Physica D} {\bf 35}, 357 (1989).] I will discuss the relevance of this observation to the practical estimation of dimension from a time series, and in particular I will argue that a good dimension algorithm need not be trapped by this anomalous fractal scaling. Further, I will analytically treat the case of gaussian \onefas noise, with explicit high and low frequency cutoffs, and derive the scaling of the correlation integral $C(N,r)$ in various regimes of the $(N,r)$ plane. Appears in: {\sl Phys. Lett. A} {\bf 155} (1991) 480--493.

Abstract:
A common first step in time series signal analysis involves digitally filtering the data to remove linear correlations. The residual data is spectrally white (it is ``bleached''), but in principle retains the nonlinear structure of the original time series. It is well known that simple linear autocorrelation can give rise to spurious results in algorithms for estimating nonlinear invariants, such as fractal dimension and Lyapunov exponents. In theory, bleached data avoids these pitfalls. But in practice, bleaching obscures the underlying deterministic structure of a low-dimensional chaotic process. This appears to be a property of the chaos itself, since nonchaotic data are not similarly affected. The adverse effects of bleaching are demonstrated in a series of numerical experiments on known chaotic data. Some theoretical aspects are also discussed.

Abstract:
We compare two theoretically distinct approaches to generating artificial (or ``surrogate'') data for testing hypotheses about a given data set. The first and more straightforward approach is to fit a single ``best'' model to the original data, and then to generate surrogate data sets that are ``typical realizations'' of that model. The second approach concentrates not on the model but directly on the original data; it attempts to constrain the surrogate data sets so that they exactly agree with the original data for a specified set of sample statistics. Examples of these two approaches are provided for two simple cases: a test for deviations from a gaussian distribution, and a test for serial dependence in a time series. Additionally, we consider tests for nonlinearity in time series based on a Fourier transform (FT) method and on more conventional autoregressive moving-average (ARMA) fits to the data. The comparative performance of hypothesis testing schemes based on these two approaches is found to depend on whether or not the discriminating statistic is pivotal. A statistic is ``pivotal'' if its distribution is the same for all processes consistent with the null hypothesis. The typical-realization method requires that the discriminating statistic satisfy this property. The constrained-realization approach, on the other hand, does not share this requirement, and can provide an accurate and powerful test without having to sacrifice flexibility in the choice of discriminating statistic.

Abstract:
We propose an extension to multivariate time series of the phase-randomized Fourier-transform algorithm for generating surrogate data. Such surrogate data sets must mimic not only the autocorrelations of each of the variables in the original data set, they must mimic the cross-correlations {\em between} all the variables as well. The method is applied both to a simulated example (the three components of the Lorenz equations) and to data from a multichannel electroencephalogram.

Abstract:
Extensions to various information theoretic quantities used for nonlinear time series analysis are discussed, as well as their relationship to the generalized correlation integral. It is shown that calculating redundancies from the correlation integral can be more accurate and more efficient than direct box counting methods. It is also demonstrated that many commonly used nonlinear statistics have information theory based analogues. Furthermore, the relationship between the correlation integral and information theoretic statistics allows us to define ``local'' versions of many information theory based statistics; including a local version of the Kolmogorov-Sinai entropy, which gives an estimate of the local predictability.

Abstract:
The statistical precision of a chord method for estimating fractal dimension from a correlation integral is derived. The optimal chord length is determined, and a comparison is made to other estimators. These calculations use the approximation that all pairwise distances between the points are statistically independent; the adequacy of this approximation is assessed numerically. The chord method provides a very quick and easy dimension estimate which is only slightly less precise than the optimal estimator. Keywords: correlation dimension, statistical error

Abstract:
A method is presented for estimating the background at a given location on a sky map by interpolating the estimated background from a set of concentric annuli which surround this location. If the background is nonuniform but smoothly varying, this method provides a more accurate (though less precise) estimate than can be obtained with a single annulus. Several applications of multi-annulus background estimation are discussed, including direct testing for point sources in the presence of a nonuniform background, the generation of "surrogate maps" for characterizing false alarm rates, and precise testing of the null hypothesis that the background is uniform.

Abstract:
By mid 2004, the Basel Committee on Banking Supervision (BCBS) is epected to launch its final recommendations on minimum capital requirements in the banking industry. Although there is the intention to arrive at capital charges which concur with economic intuition, the risk weight formulas proposed by the committee will lack an adequate treatment of concentration risks in credit portfolios. The question arises whether this problem can be solved without recourse to fully-fledged portfolio models. Since recent practical experience shows that the risk measure Conditional Value-at-Risk (CVaR) is particularly well suited for detecting concentrations, we develop the semi-asymptotic approach by Emmer and Tasche in the CVaR context and compare it with the capital charges recently suggested by the Basel Committee. Both approaches are based on the same Vasicek one-factor model.

Abstract:
a list of small mammals obtained in the region of comodoro rivadavia (gulf san jorge district, patagonia phytogeographic province) is here included. eighty caviomorfs, presumably microcavia australis were captured. we also identified 1 marsupial (lestodelphys halli) and 39 rodents: 19 graomys griseoflavus (2n=36, 37 and 38), 1 phyllotis xanthopygus (2n=38), 7 reithrodon auritus (2n=34) and 12 abrothrix olivaceus (2n=44). in the last species the diploid number of chromosome is different to previous reports (2n=52). this difference may be attributed to structural chromosomal polymorphism.