Hurricanes and climate in the Caribbean during the past 3700 years BP

International audienceA multiproxy analysis of lacustrine sediments cored in Grand-Case Pond at Saint-Martin, north of the Lesser Antilles archipelago, reveals three distinct climatic periods for the last 3700 years. From 3700 to ~2500 yr cal. BP and from 1150 yr cal. BP to the present, carbonate mud deposition occurred in connection with pond lowstands. These periods were also punctuated by severe drought events, marked by gypsum laminae, and hurricane landfalls, leading to marine sand inputs into the pond. The intermediate time interval, from 2500 to 1150 yr cal. BP, is typified by black organic mud deposition, suggesting that hypoxic to anoxic conditions prevailed at the pond bottom. These were probably linked with a perennial pond highstand and reflect more uniform and wetter climatic conditions than today. The carbon isotopic composition of the ostracod Perissocytheridea bisulcata shows that the lowest δ13C values are recorded during the hypoxic periods, as a consequence of bacterial recycling of isotopically depleted organic matter. Such a climatic history agrees closely with that documented from other records in the Caribbean area, such as the Cariaco Basin, central coast of Belize or Barbados. By constrast, discrepancies seem to emerge from the comparison between hurricane activity recorded at Saint-Martin on the one hand and Vieques (Puerto Rico) on the other hand. We explain this apparent contradiction by a balance between two distinct storm paths in response to latitudinal shifts of the Intertropical Convergence Zone (ITCZ). Stronger storm activity over the Gulf coast and the inner Caribbean Sea is favoured by a southern position of the ITCZ in connection with dry climatic conditions. Plausible links with the North Atlantic Oscillation (NAO) are also suggested

How To Perform Meaningful Estimates of Genetic Effects

Although the genotype-phenotype map plays a central role both in Quantitative and Evolutionary Genetics, the formalization of a completely general and satisfactory model of genetic effects, particularly accounting for epistasis, remains a theoretical challenge. Here, we use a two-locus genetic system in simulated populations with epistasis to show the convenience of using a recently developed model, NOIA, to perform estimates of genetic effects and the decomposition of the genetic variance that are orthogonal even under deviations from the Hardy-Weinberg proportions. We develop the theory for how to use this model in interval mapping of quantitative trait loci using Halley-Knott regressions, and we analyze a real data set to illustrate the advantage of using this approach in practice. In this example, we show that departures from the Hardy-Weinberg proportions that are expected by sampling alone substantially alter the orthogonal estimates of genetic effects when other statistical models, like F2 or G2A, are used instead of NOIA. Finally, for the first time from real data, we provide estimates of functional genetic effects as sets of effects of natural allele substitutions in a particular genotype, which enriches the debate on the interpretation of genetic effects as implemented both in functional and in statistical models. We also discuss further implementations leading to a completely general genotype-phenotype map

An early warning method for agricultural products price spike based on artificial neural networks prediction

In general, the agricultural producing sector is affected by the diversity in supply, mostly from small companies, in addition to the rigidity of the demand, the territorial dispersion, the seasonality or the generation of employment related to the rural environment. These characteristics differentiate the agricultural sector from other economic sectors. On the other hand, the volatility of prices payed by producers, the high cost of raw materials, and the instability of both domestic and international markets are factors which have eroded the competitiveness and profitability of the agricultural sector. Because of the advance in technology, applications have been developed based on Artificial Neural Networks (ANN) which have helped the development of sales forecast on consumer products, improving the accuracy of traditional forecasting systems. This research uses the RNA to develop an early warning system for facing the increase in agricultural products, considering macro and micro economic variables and factors related to the seasons of the year

Variable selection for large p small n regression models with incomplete data: Mapping QTL with epistases

<p>Abstract</p> <p>Background</p> <p>Identifying quantitative trait loci (QTL) for both additive and epistatic effects raises the statistical issue of selecting variables from a large number of candidates using a small number of observations. Missing trait and/or marker values prevent one from directly applying the classical model selection criteria such as Akaike's information criterion (AIC) and Bayesian information criterion (BIC).</p> <p>Results</p> <p>We propose a two-step Bayesian variable selection method which deals with the sparse parameter space and the small sample size issues. The regression coefficient priors are flexible enough to incorporate the characteristic of "large <it>p </it>small <it>n</it>" data. Specifically, sparseness and possible asymmetry of the significant coefficients are dealt with by developing a Gibbs sampling algorithm to stochastically search through low-dimensional subspaces for significant variables. The superior performance of the approach is demonstrated via simulation study. We also applied it to real QTL mapping datasets.</p> <p>Conclusion</p> <p>The two-step procedure coupled with Bayesian classification offers flexibility in modeling "large p small n" data, especially for the sparse and asymmetric parameter space. This approach can be extended to other settings characterized by high dimension and low sample size.</p

Antitubercular therapy decreases nitric oxide production in HIV/TB coinfected patients

BACKGROUND: Nitric oxide (NO) production is increased among patients with human immunodeficiency virus (HIV) infection and also among those with tuberculosis (TB). In this study we sought to determine if there was increased NO production among patients with HIV/TB coinfection and the effect of four weeks chemotherapy on this level. METHODS: 19 patients with HIV/TB coinfection were studied. They were treated with standard four drug antitubercular therapy and sampled at baseline and four weeks. 20 patients with HIV infection, but no opportunistic infections, were disease controls and 20 individuals were healthy controls. Nitrite and citrulline, surrogate markers for NO, were measured spectrophotometrically. RESULTS: The mean age of HIV/TB patients was 28.4 ± 6.8 years and CD4 count was 116 ± 36.6/mm. Mean nitrite level among HIV/TB coinfected was 207.6 ± 48.8 nmol/ml. This was significantly higher than 99.7 ± 26.5 nmol/ml, the value for HIV infected without opportunistic infections and 46.4 ± 16.2 nmol/ml, the value for healthy controls (p value < 0.01). The level of HIV/TB coinfected NO in patients declined to 144.5 ± 34.4 nmol/ml at four weeks of therapy (p value < 0.05). Mean citrulline among HIV/TB coinfected was 1446.8 ± 468.8 nmol/ml. This was significantly higher than 880.8 ± 434.8 nmol/ml, the value for HIV infected without opportunistic infections and 486.6 ± 212.5 nmol/ml, the value for healthy controls (p value < 0.01). Levels of citrolline in HIV/TB infected declined to 1116.2 ± 388.6 nmol/ml at four weeks of therapy (p value < 0.05). CONCLUSIONS: NO production is elevated among patients with HIV infection, especially so among HIV/TB coinfected patients, but declines significantly following 4 weeks of antitubercular therapy

Energy Flow in the Hadronic Final State of Diffractive and Non-Diffractive Deep-Inelastic Scattering at HERA

An investigation of the hadronic final state in diffractive and non--diffractive deep--inelastic electron--proton scattering at HERA is presented, where diffractive data are selected experimentally by demanding a large gap in pseudo --rapidity around the proton remnant direction. The transverse energy flow in the hadronic final state is evaluated using a set of estimators which quantify topological properties. Using available Monte Carlo QCD calculations, it is demonstrated that the final state in diffractive DIS exhibits the features expected if the interaction is interpreted as the scattering of an electron off a current quark with associated effects of perturbative QCD. A model in which deep--inelastic diffraction is taken to be the exchange of a pomeron with partonic structure is found to reproduce the measurements well. Models for deep--inelastic $ep$ scattering, in which a sizeable diffractive contribution is present because of non--perturbative effects in the production of the hadronic final state, reproduce the general tendencies of the data but in all give a worse description.Comment: 22 pages, latex, 6 Figures appended as uuencoded fil

A Search for Selectrons and Squarks at HERA

Data from electron-proton collisions at a center-of-mass energy of 300 GeV are used for a search for selectrons and squarks within the framework of the minimal supersymmetric model. The decays of selectrons and squarks into the lightest supersymmetric particle lead to final states with an electron and hadrons accompanied by large missing energy and transverse momentum. No signal is found and new bounds on the existence of these particles are derived. At 95% confidence level the excluded region extends to 65 GeV for selectron and squark masses, and to 40 GeV for the mass of the lightest supersymmetric particle.Comment: 13 pages, latex, 6 Figure

Generalized linear model for interval mapping of quantitative trait loci

We developed a generalized linear model of QTL mapping for discrete traits in line crossing experiments. Parameter estimation was achieved using two different algorithms, a mixture model-based EM (expectation–maximization) algorithm and a GEE (generalized estimating equation) algorithm under a heterogeneous residual variance model. The methods were developed using ordinal data, binary data, binomial data and Poisson data as examples. Applications of the methods to simulated as well as real data are presented. The two different algorithms were compared in the data analyses. In most situations, the two algorithms were indistinguishable, but when large QTL are located in large marker intervals, the mixture model-based EM algorithm can fail to converge to the correct solutions. Both algorithms were coded in C++ and interfaced with SAS as a user-defined SAS procedure called PROC QTL