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.

Characterization of fungal soil communities by F-RISA and arbuscular mycorrhizal fungi from Araucaria angustifolia forest soils after replanting and wildfire disturbances

The Fungal Ribosomal Intergenic Spacer Analysis (F-RISA) was used to characterize soil fungal communities from three ecosystems of Araucaria angustifolia from Brazil: a native forest and two replanted forest ecosystems, one of them with a past history of wildfire. The arbuscular mycorrhizal fungi (AMF) infection was evaluated in Araucaria roots of 18-month-old axenic plants previously inoculated with soils collected from those areas in a greenhouse experiment. The principal component analysis of F-RISA profiles showed different soil fungal community between the three studied areas. Sixty three percent of F-RISA fragments amplified in the soil and the substrate samples presented lengths between 500 and 700 bp. The number of Operational Taxonomic Units (OTUs) was 34 for soil and 38 for substrate, however, more fragments were detected in soil (214) than in substrate (163). An in silico F-RISA analysis to compare our data with ITS1-5.8S-ITS2 sequences from NCBI database showed the presence of Ascomycota, Basidiomycota and Glomeromycota among the soil and substrate fungal communities. AMF infection was higher in plants inoculated with soil from the native forest and the replanted forest with wildfire, both presenting similar chemical characteristics but with different disturbance levels. These results indicate that soil chemical composition may influence the soil fungal community structures rather than the anthropogenic or fire disturbances.

Spatial heterogeneity of leaf wetness duration in apple trees and its influence on performance of a warning system for sooty blotch and flyspeck

To determine the effect of sensor placement on the performance of a disease-warning system for sooty blotch and flyspeck (SBFS), we measured leaf wetness duration (LWD) at 12 canopy positions in apple trees, then simulated operation of the disease-warning system using LWD measurements from different parts of the canopy. LWD sensors were placed in four trees within one Iowa orchard during two growing seasons, and in one tree in each of four orchards during a single growing season. The LWD measurements revealed substantial heterogeneity among sensor locations. In all data sets, the upper, eastern portion of the canopy had the longest mean daily LWD, and was the first site to form dew and the last to dry. The lower, western portion of the canopy averaged about 3 It less LWD per day than the top of the canopy, and was the last zone where dew formed and the first to dry off. On about 25% of nights when dew occurred in the top of the canopy, no dew formed in the lower, western canopy. Intracanopy variability of LWD was more pronounced when dew was the sole source of wetness than on days when rainfall occurred. Daily LWD in the upper, eastern portion of the canopy was slightly less than reference measurements made at a 0.7-m height over turfgrass located near the orchard. When LWD measurements from several canopy positions were input to the SBFS warning system, timing of occurrence of a fungicide-spray threshold varied by as much as 30 days among canopy positions. Under Iowa conditions, placement of an LWD sensor at an unobstructed site over turfgrass was a fairly accurate surrogate for the wettest part of the canopy. Therefore, such an extra-canopy LWD sensor might be substituted for a within-canopy sensor to enhance operational reliability of the SBFS warning system.

Genetic population data of 12 STR loci of the PowerPlex (R) Y system in the state of Sao Paulo population (Southeast of Brazil)

Allele frequency distributions and population data for 12 Y-chromosomal short tandem repeats (STRs) included in the PowerPlex (R) Y Systems (Promega) were obtained for a sample of 200 healthy unrelated males living in S (a) over tildeo Paulo State (Southeast of Brazil). A total of 192 haplotypes were identified, of which 184 were unique and 8 were found in 2 individuals. The average gene diversity of the 12 Y-STR was 0.6746 and the haplotype diversity was 0.9996. Pairwise analysis confirmed that our population is more similar with the Italy, North Portugal and Spain, being more distant of the Japan. (c) 2007 Elsevier Ireland Ltd. All rights reserved.

Iron deficiency and frequency of HFE C282Y gene mutation in Brazilian blood donors

Limited data are available about iron deficiency (ID) in Brazilian blood donors. This study evaluated the frequencies of ID and iron-deficiency anaemia (IDA) separately and according to frequency of blood donations. The protective effect of the heterozygous genotype for HFE C282Y mutation against ID and IDA in female blood donors was also determined. Five hundred and eight blood donors were recruited at the Blood Bank of Santa Casa in Sao Paulo, Brazil. Haemoglobin and serum ferritin concentrations were measured. The genotype for HFE C282Y mutation was determined by polymerase chain reaction followed by restriction fragment length polymorphism analysis. The ID was found in 21 center dot 1% of the women and 2 center dot 6% of the men whereas the IDA was found in 6 center dot 8 and 0 center dot 3%, respectively. The ID was found in 11 center dot 9% of the women in group 1 (first-time blood donors) and the frequency increased to 38 center dot 9% in women of the group 3 (blood donors donating once or more times in the last 12 months). No ID was found in men from group 1; however the ID frequency increased to 0 center dot 9% in group 2 (who had donated blood before but not in the last 12 months) and 5 center dot 0% in group 3. In summary, the heterozygous genotype was not associated with reduction of ID or IDA frequencies in both genders, but in male blood donors it was associated with a trend to elevated ferritin levels (P = 0 center dot 060). ID is most frequent in Brazilian women but was also found in men of group 3.

Comparison of oxygen mass transfer coefficient in simple and extractive fermentation systems

Aeration and agitation are important variables to ensure effective oxygen transfer rate during aerobic bioprocesses: therefore, the knowledge of the volumetric mass transfer coefficient (k(L)a) is required. In view of selecting the optimum oxygen requirements for extractive fermentation in aqueous two-phase system (ATPS), the k(L)a values in a typical ATPS medium were compared in this work with those in distilled water and in a simple fermentation medium. in the absence of biomass. Aeration and agitation were selected as the independent variables using a 2(2) full factorial design. Both variables showed statistically significant effects on k(L)a, and the highest values of this parameter in both media for simple fermentation (241 s(-1)) and extractive fermentation with ATPS (70.3 s(-1)) were observed at the highest levels of aeration (5 vvm) and agitation (1200 rpm). The k(L)a values were then used to establish mathematical correlations of this response as a function of the process variables. The exponents of the power number (N(3)D(2)) and superficial gas velocity (V(s)) determined in distilled water (alpha = 0.39 and beta = 0.47, respectively) were in reasonable agreement with the ones reported in the literature for several aqueous systems and close to those determined for a simple fermentation medium (alpha=0.38 and beta=0.41). On the other hand, as expected by the increased viscosity in the presence of polyethylene glycol, their values were remarkably higher in a typical medium for extractive fermentation (alpha=0.50 and beta=1.0). A reasonable agreement was found between the experimental data of k(L)a for the three selected systems and the values predicted by the theoretical models, under a wide range of operational conditions. (C) 2009 Elsevier B.V. All rights reserved.

Brazilian Network of Food Data Systems and LATINFOODS Regional Technical Compilation Committee: Food composition activities (2006-2009)

The Brazilian Network of Food Data Systems (BRASILFOODS) has been keeping the Brazilian Food Composition Database-USP (TBCA-USP) (http://www.fcf.usp.br/tabela) since 1998. Besides the constant compilation, analysis and update work in the database, the network tries to innovate through the introduction of food information that may contribute to decrease the risk for non-transmissible chronic diseases, such as the profile of carbohydrates and flavonoids in foods. In 2008, data on carbohydrates, individually analyzed, of 112 foods, and 41 data related to the glycemic response produced by foods widely consumed in the country were included in the TBCA-USP. Data (773) about the different flavonoid subclasses of 197 Brazilian foods were compiled and the quality of each data was evaluated according to the USDAs data quality evaluation system. In 2007, BRASILFOODS/USP and INFOODS/FAO organized the 7th International Food Data Conference ""Food Composition and Biodiversity"". This conference was a unique opportunity for interaction between renowned researchers and participants from several countries and it allowed the discussion of aspects that may improve the food composition area. During the period, the LATINFOODS Regional Technical Compilation Committee and BRASILFOODS disseminated to Latin America the Form and Manual for Data Compilation, version 2009, ministered a Food Composition Data Compilation course and developed many activities related to data production and compilation. (C) 2010 Elsevier Inc. All rights reserved.

Migrating eprints.org data to a Fez repository

This document records the process of migrating eprints.org data to a Fez repository. Fez is a Web-based digital repository and workflow management system based on Fedora (http://www.fedora.info/). At the time of migration, the University of Queensland Library was using EPrints 2.2.1 [pepper] for its ePrintsUQ repository. Once we began to develop Fez, we did not upgrade to later versions of eprints.org software since we knew we would be migrating data from ePrintsUQ to the Fez-based UQ eSpace. Since this document records our experiences of migration from an earlier version of eprints.org, anyone seeking to migrate eprints.org data into a Fez repository might encounter some small differences. Moving UQ publication data from an eprints.org repository into a Fez repository (hereafter called UQ eSpace (http://espace.uq.edu.au/) was part of a plan to integrate metadata (and, in some cases, full texts) about all UQ research outputs, including theses, images, multimedia and datasets, in a single repository. This tied in with the plan to identify and capture the research output of a single institution, the main task of the eScholarshipUQ testbed for the Australian Partnership for Sustainable Repositories project (http://www.apsr.edu.au/). The migration could not occur at UQ until the functionality in Fez was at least equal to that of the existing ePrintsUQ repository. Accordingly, as Fez development occurred throughout 2006, a list of eprints.org functionality not currently supported in Fez was created so that programming of such development could be planned for and implemented.

A simple data logger for student-designed rocket experiments.

The final-year project for Mechanical & Space Engineering students at UQ often involves the design and flight testing of an experiment. This report describes the design and use of a simple data logger that should be suitable for collecting data from the students' flight experiments. The exercise here was taken as far as the construction of a prototype device that is suitable for ground-based testing, say, the static firing of a hybrid rocket motor.

Equational Reasoning as a Tool for Data Analysis

A combination of deductive reasoning, clustering, and inductive learning is given as an example of a hybrid system for exploratory data analysis. Visualization is replaced by a dialogue with the data.

Leadership Attributes and Cultural Values in Australia and New Zealand Compared: An Initial Report Based on GLOBE Data.

This paper reports a comparative study of Australian and New Zealand leadership attributes, based on the GLOBE (Global Leadership and Organizational Behavior Effectiveness) program. Responses from 344 Australian managers and 184 New Zealand managers in three industries were analyzed using exploratory and confirmatory factor analysis. Results supported some of the etic leadership dimensions identified in the GLOBE study, but also found some emic dimensions of leadership for each country. An interesting finding of the study was that the New Zealand data fitted the Australian model, but not vice versa, suggesting asymmetric perceptions of leadership in the two countries.

Selection bias in gene extraction on the basis of microarray gene-expression data

In the context of cancer diagnosis and treatment, we consider the problem of constructing an accurate prediction rule on the basis of a relatively small number of tumor tissue samples of known type containing the expression data on very many (possibly thousands) genes. Recently, results have been presented in the literature suggesting that it is possible to construct a prediction rule from only a few genes such that it has a negligible prediction error rate. However, in these results the test error or the leave-one-out cross-validated error is calculated without allowance for the selection bias. There is no allowance because the rule is either tested on tissue samples that were used in the first instance to select the genes being used in the rule or because the cross-validation of the rule is not external to the selection process; that is, gene selection is not performed in training the rule at each stage of the cross-validation process. We describe how in practice the selection bias can be assessed and corrected for by either performing a cross-validation or applying the bootstrap external to the selection process. We recommend using 10-fold rather than leave-one-out cross-validation, and concerning the bootstrap, we suggest using the so-called. 632+ bootstrap error estimate designed to handle overfitted prediction rules. Using two published data sets, we demonstrate that when correction is made for the selection bias, the cross-validated error is no longer zero for a subset of only a few genes.

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.

Using household survey data to inform policy decisions regarding the delivery of evidence-based parenting interventions.

Background: This study used household survey data on the prevalence of child, parent and family variables to establish potential targets for a population-level intervention to strengthen parenting skills in the community. The goals of the intervention include decreasing child conduct problems, increasing parental self-efficacy, use of positive parenting strategies, decreasing coercive parenting and increasing help-seeking, social support and participation in positive parenting programmes. Methods: A total of 4010 parents with a child under the age of 12 years completed a statewide telephone survey on parenting. Results: One in three parents reported that their child had a behavioural or emotional problem in the previous 6 months. Furthermore, 9% of children aged 2–12 years meet criteria for oppositional defiant disorder. Parents who reported their child's behaviour to be difficult were more likely to perceive parenting as a negative experience (i.e. demanding, stressful and depressing). Parents with greatest difficulties were mothers without partners and who had low levels of confidence in their parenting roles. About 20% of parents reported being stressed and 5% reported being depressed in the 2 weeks prior to the survey. Parents with personal adjustment problems had lower levels of parenting confidence and their child was more difficult to manage. Only one in four parents had participated in a parent education programme. Conclusions: Implications for the setting of population-level goals and targets for strengthening parenting skills are discussed.