Modelling the potential distribution of the invasive tomato red spider mite, Tetranychus evansi (Acari: Tetranychidae)

Predicting the potential geographical distribution of a species is particularly important for pests with strong invasive abilities. Tetranychus evansi Baker & Pritchard, possibly native to South America, is a spider mite pest of solanaceous crops. This mite is considered an invasive species in Africa and Europe. A CLIMEX model was developed to predict its global distribution. The model results fitted the known records of T. evansi except for some records in dry locations. Dryness as well as excess moisture stresses play important roles in limiting the spread of the mite in the tropics. In North America and Eurasia its potential distribution appears to be essentially limited by cold stress. Detailed potential distribution maps are provided for T. evansi in the Mediterranean Basin and in Japan. These two regions correspond to climatic borders for the species. Mite establishment in these areas can be explained by their relatively mild winters. The Mediterranean region is also the main area where tomato is grown in open fields in Europe and where the pest represents a threat. According to the model, the whole Mediterranean region has the potential to be extensively colonized by the mite. Wide expansion of the mite to new areas in Africa is also predicted. Agricultural issues highlighted by the modelled distribution of the pest are discussed.

Determining the season of death from the family composition of insects infesting carrion

Determining the season of death by means of the composition of the families of insects infesting carrion is rarely attempted in forensic studies and has never been statistically modelled. For this reason, a baseline-category logit model is proposed for predicting the season of death as a function of whether the area where the carcass was exposed is sunlit or shaded and of the relative abundance of particular families of carrion insects (Calliphoridae, Fanniidae, Sarcophagidae, and Formicidae). The field study was conducted using rodent carcasses (20-252 g) in an urban forest in southeastern Brazil. Four carcasses (2 in a sunlit and 2 in a shaded area) were placed simultaneously at the study site, twice during each season from August 2003 through June 2004. The feasibility of the model, measured in terms of overall accuracy, is 64 +/- 14%. It is likely the proposed model will assist forensic teams in predicting the season of death in tropical ecosystems, without the need of identifying the species of specimens or the remains of carrion insects.

Simulation of irrigated Thanzania grass growth based on photothermal units, nitrogen fertilization and water availability

Simulation of irrigated Thanzania grass growth based on photothermal units, nitrogen fertilization and water availability. The mathematical model to predict the forage yield using photothennal units was utilized with success in Elephant grass, Thanzania and Brachiaria niziziensis in the absence of water stress and nitrogen stress. The aim of this study was to propose models to estimate the forage yield of Thanzania grass under different irrigation (25, 50,75, 100 e 125% of ETc) and nitrogen level in various regions of Brazil. As such, models were developed to estimate the dry matter production of Panicum maximum Jacq. frass cv Thanzania in different irrigation and nitrogen levels, using photothermal units. The models were adjusted to doses of 0, 30, 60, 110 and 270 kg of N ha(-1), doses were divided in applications after each evaluation, with a rest cycle of 35 days. The adjusted model presented good performance in predicting dry matter production of Thanzania grass, with r(2) = 0.9999. The results made it possible to verify that the proposed model can be used to predict forage production in different regions of Brazil. It can be estimated, with good precision. The production of Thanzania grass dry matter can be accurately estimated in specific places (in function of latitude and time of year), with the maximum and minimum temperature values.

Spatio-temporal modeling of agricultural yield data with an application to pricing crop insurance contracts

This article presents a statistical model of agricultural yield data based on a set of hierarchical Bayesian models that allows joint modeling of temporal and spatial autocorrelation. This method captures a comprehensive range of the various uncertainties involved in predicting crop insurance premium rates as opposed to the more traditional ad hoc, two-stage methods that are typically based on independent estimation and prediction. A panel data set of county-average yield data was analyzed for 290 counties in the State of Parana (Brazil) for the period of 1990 through 2002. Posterior predictive criteria are used to evaluate different model specifications. This article provides substantial improvements in the statistical and actuarial methods often applied to the calculation of insurance premium rates. These improvements are especially relevant to situations where data are limited.

Quantification of chlorpheniramine maleate enantiomers by ultraviolet spectroscopy and chemometric methods

Chlorpheniramine maleate (CLOR) enantiomers were quantified by ultraviolet spectroscopy and partial least squares regression. The CLOR enantiomers were prepared as inclusion complexes with beta-cyclodextrin and 1-butanol with mole fractions in the range from 50 to 100%. For the multivariate calibration the outliers were detected and excluded and variable selection was performed by interval partial least squares and a genetic algorithm. Figures of merit showed results for accuracy of 3.63 and 2.83% (S)-CLOR for root mean square errors of calibration and prediction, respectively. The ellipse confidence region included the point for the intercept and the slope of 1 and 0, respectively. Precision and analytical sensitivity were 0.57 and 0.50% (S)-CLOR, respectively. The sensitivity, selectivity, adjustment, and signal-to-noise ratio were also determined. The model was validated by a paired t test with the results obtained by high-performance liquid chromatography proposed by the European pharmacopoeia and circular dichroism spectroscopy. The results showed there was no significant difference between the methods at the 95% confidence level, indicating that the proposed method can be used as an alternative to standard procedures for chiral analysis.

The 2008 update of the Aspergillus nidulans genome annotation: A community effort

The identification and annotation of protein-coding genes is one of the primary goals of whole-genome sequencing projects, and the accuracy of predicting the primary protein products of gene expression is vital to the interpretation of the available data and the design of downstream functional applications. Nevertheless, the comprehensive annotation of eukaryotic genomes remains a considerable challenge. Many genomes submitted to public databases, including those of major model organisms, contain significant numbers of wrong and incomplete gene predictions. We present a community-based reannotation of the Aspergillus nidulans genome with the primary goal of increasing the number and quality of protein functional assignments through the careful review of experts in the field of fungal biology. (C) 2009 Elsevier Inc. All rights reserved.

Determination of coalescence kernels for high-shear granulation using DEM simulations

Discrete element method (DEM) modeling is used in parallel with a model for coalescence of deformable surface wet granules. This produces a method capable of predicting both collision rates and coalescence efficiencies for use in derivation of an overall coalescence kernel. These coalescence kernels can then be used in computationally efficient meso-scale models such as population balance equation (PBE) models. A soft-sphere DEM model using periodic boundary conditions and a unique boxing scheme was utilized to simulate particle flow inside a high-shear mixer. Analysis of the simulation results provided collision frequency, aggregation frequency, kinetic energy, coalescence efficiency and compaction rates for the granulation process. This information can be used to bridge the gap in multi-scale modeling of granulation processes between the micro-scale DEM/coalescence modeling approach and a meso-scale PBE modeling approach.

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.

Special issue on advances in data mining and its applications

Data mining is the process to identify valid, implicit, previously unknown, potentially useful and understandable information from large databases. It is an important step in the process of knowledge discovery in databases, (Olaru & Wehenkel, 1999). In a data mining process, input data can be structured, seme-structured, or unstructured. Data can be in text, categorical or numerical values. One of the important characteristics of data mining is its ability to deal data with large volume, distributed, time variant, noisy, and high dimensionality. A large number of data mining algorithms have been developed for different applications. For example, association rules mining can be useful for market basket problems, clustering algorithms can be used to discover trends in unsupervised learning problems, classification algorithms can be applied in decision-making problems, and sequential and time series mining algorithms can be used in predicting events, fault detection, and other supervised learning problems (Vapnik, 1999). Classification is among the most important tasks in the data mining, particularly for data mining applications into engineering fields. Together with regression, classification is mainly for predictive modelling. So far, there have been a number of classification algorithms in practice. According to (Sebastiani, 2002), the main classification algorithms can be categorized as: decision tree and rule based approach such as C4.5 (Quinlan, 1996); probability methods such as Bayesian classifier (Lewis, 1998); on-line methods such as Winnow (Littlestone, 1988) and CVFDT (Hulten 2001), neural networks methods (Rumelhart, Hinton & Wiliams, 1986); example-based methods such as k-nearest neighbors (Duda & Hart, 1973), and SVM (Cortes & Vapnik, 1995). Other important techniques for classification tasks include Associative Classification (Liu et al, 1998) and Ensemble Classification (Tumer, 1996).

A framework for electricity price spike analysis with advanced data mining methods

There are many techniques for electricity market price forecasting. However, most of them are designed for expected price analysis rather than price spike forecasting. An effective method of predicting the occurrence of spikes has not yet been observed in the literature so far. In this paper, a data mining based approach is presented to give a reliable forecast of the occurrence of price spikes. Combined with the spike value prediction techniques developed by the same authors, the proposed approach aims at providing a comprehensive tool for price spike forecasting. In this paper, feature selection techniques are firstly described to identify the attributes relevant to the occurrence of spikes. A simple introduction to the classification techniques is given for completeness. Two algorithms: support vector machine and probability classifier are chosen to be the spike occurrence predictors and are discussed in details. Realistic market data are used to test the proposed model with promising results.

Two dimensional computational fluid dynamic models for waste stabilisation ponds

Traditional waste stabilisation pond (WSP) models encounter problems predicting pond performance because they cannot account for the influence of pond features, such as inlet structure or pond geometry, on fluid hydrodynamics. In this study, two dimensional (2-D) computational fluid dynamics (CFD) models were compared to experimental residence time distributions (RTD) from literature. In one of the-three geometries simulated, the 2-D CFD model successfully predicted the experimental RTD. However, flow patterns in the other two geometries were not well described due to the difficulty of representing the three dimensional (3-D) experimental inlet in the 2-D CFD model, and the sensitivity of the model results to the assumptions used to characterise the inlet. Neither a velocity similarity nor geometric similarity approach to inlet representation in 2-D gave results correlating with experimental data. However. it was shown that 2-D CFD models were not affected by changes in values of model parameters which are difficult to predict, particularly the turbulent inlet conditions. This work suggests that 2-D CFD models cannot be used a priori to give an adequate description of the hydrodynamic patterns in WSP. (C) 1998 Elsevier Science Ltd. All rights reserved.

A comparison of segmental and wrist-to-ankle methodologies of bioimpedance analysis

The common approach of bioelectrical impedance analysis to estimate body water uses a wrist-to-ankle methodology which, although not indicated by theory, has the advantage of ease of application particularly for clinical studies involving patients with debilitating diseases. A number of authors have suggested the use of a segmental protocol in which the impedances of the trunk and limbs are measured separately to provide a methodology more in keeping with basic theory. The segmental protocol hits not, however, been generally adopted, partly because of the increased complexity involved in its application, and partly because studies comparing the two methodologies have not clearly demonstrated a significant improvement from the segmental methodology. We have conducted a small pilot study involving ten subjects to investigate the efficacy of the two methodologies in a group of normal subjects. The study did not require the independent measure of body water, by for example isotope dilution, as the subjects were maintained in a state of constant hydration with only the distribution between limbs and trunk changing as a result of change in posture. The results demonstrate a significant difference between the two methodologies in predicting the expected constancy of body water in this study, with the segmental methodology indicating a mean percentage change in extracellular water of -2.2%; which was not significantly different from the expected null result, whereas the wrist-to-ankle methodology indicated a mean percentage change in extracellular water of -6.6%. This is significantly different from the null result, and from the value obtained from the segmental methodology (p = 0.006). Similar results were obtained using estimates of total body water from the two methodologies. (C) 1998 Elsevier Science Ltd. All rights reserved.

Mutational analysis of the cystathionine beta-synthase gene: A splicing mutation, two missense mutations and an insertion in patients with homocystinuria

RT-PCR and direct sequence analyses were used to define mutations in the cystathionine beta-synthase (CBS) gene in two unrelated male patients with vitamin B6 nonresponsive homocystinuria. Both patients were compound heterozygotes for CBS alleles containing point mutations. One patient had a maternally derived G-->A transition in the splice-donor site of intron 1, resulting in aberrant splicing of CBS mRNA. The other allele contained a missense mutation resulting in the previously reported E144K mutant CBS protein. The second patient had a maternally derived 4 bp insertion in exon 17, predicted to cause a CBS peptide of altered amino acid sequence. A 494G-->A transition was found in exon 4 of the other allele, predicting a C165Y substitution. Expression of recombinant CBS protein, containing the C165Y mutation, had no detectable catalytic activity. Each mutation was confirmed in genomic DNA. (C) 1998 Wiley-Liss, Inc.

Capillary coexistence and criticality in mesopores: Modification of the Kelvin theory

The classical model of capillary equilibrium in cylindrical pores is modified here by the introduction of molecular concepts and the solid fluid interaction potential. The new approach accurately predicts capillary coexistence and criticality, with results quantitatively matching those from density functional theory for nitrogen adsorption, while also predicting condensation pressures in agreement with reported experimental findings for MCM-41. The larger critical pore size for nitrogen adsorption in these materials, however, suggests a modification of the potential function parameters, evaluated here from data for hydroxylated silica.

Analysis and application of an equilibrium model for in vitro bioassay systems with three components: Receptor, hormone and hormone-binding-protein

A simple theoretical framework is presented for bioassay studies using three component in vitro systems. An equilibrium model is used to derive equations useful for predicting changes in biological response after addition of hormone-binding-protein or as a consequence of increased hormone affinity. Sets of possible solutions for receptor occupancy and binding protein occupancy are found for typical values of receptor and binding protein affinity constants. Unique equilibrium solutions are dictated by the initial condition of total hormone concentration. According to the occupancy theory of drug action, increasing the affinity of a hormone for its receptor will result in a proportional increase in biological potency. However, the three component model predicts that the magnitude of increase in biological potency will be a small fraction of the proportional increase in affinity. With typical initial conditions a two-fold increase in hormone affinity for its receptor is predicted to result in only a 33% increase in biological response. Under the same conditions an Ii-fold increase in hormone affinity for receptor would be needed to produce a two-fold increase in biological potency. Some currently used bioassay systems may be unrecognized three component systems and gross errors in biopotency estimates will result if the effect of binding protein is not calculated. An algorithm derived from the three component model is used to predict changes in biological response after addition of binding protein to in vitro systems. The algorithm is tested by application to a published data set from an experimental study in an in vitro system (Lim et al., 1990, Endocrinology 127, 1287-1291). Predicted changes show good agreement (within 8%) with experimental observations. (C) 1998 Academic Press Limited.