Testing extreme value copulas to estimate the quantile

Testing weather or not data belongs could been generated by a family of extreme value copulas is difficult. We generalize a test and we prove that it can be applied whatever the alternative hypothesis. We also study the effect of using different extreme value copulas in the context of risk estimation. To measure the risk we use a quantile. Our results have motivated by a bivariate sample of losses from a real database of auto insurance claims. Methods are implemented in R.

Assessing inter-rater reliability when the raters are fixed: two concepts and two estimates.

Intraclass correlation (ICC) is an established tool to assess inter-rater reliability. In a seminal paper published in 1979, Shrout and Fleiss considered three statistical models for inter-rater reliability data with a balanced design. In their first two models, an infinite population of raters was considered, whereas in their third model, the raters in the sample were considered to be the whole population of raters. In the present paper, we show that the two distinct estimates of ICC developed for the first two models can both be applied to the third model and we discuss their different interpretations in this context.

Optimizing Pavement Base, Subbase, and Subgrade Layers for Cost and Performance of Local Roads, TR-640

This report is one of two products for this project with the other being a design guide. This report describes test results and comparative analysis from 16 different portland cement concrete (PCC) pavement sites on local city and county roads in Iowa. At each site the surface conditions of the pavement (i.e., crack survey) and foundation layer strength, stiffness, and hydraulic conductivity properties were documented. The field test results were used to calculate in situ parameters used in pavement design per SUDAS and AASHTO (1993) design methodologies. Overall, the results of this study demonstrate how in situ and lab testing can be used to assess the support conditions and design values for pavement foundation layers and how the measurements compare to the assumed design values. The measurements show that in Iowa, a wide range of pavement conditions and foundation layer support values exist. The calculated design input values for the test sites (modulus of subgrade reaction, coefficient of drainage, and loss of support) were found to be different than typically assumed. This finding was true for the full range of materials tested. The findings of this study support the recommendation to incorporate field testing as part of the process to field verify pavement design values and to consider the foundation as a design element in the pavement system. Recommendations are provided in the form of a simple matrix for alternative foundation treatment options if the existing foundation materials do not meet the design intent. The PCI prediction model developed from multi-variate analysis in this study demonstrated a link between pavement foundation conditions and PCI. The model analysis shows that by measuring properties of the pavement foundation, the engineer will be able to predict long term performance with higher reliability than by considering age alone. This prediction can be used as motivation to then control the engineering properties of the pavement foundation for new or re-constructed PCC pavements to achieve some desired level of performance (i.e., PCI) with time.

Testing the competitive exclusion principle using various niche parameters in a native (Natrix maura) and an introduced (N. tessellata) colubrid

Despite the increase of animal and plant introductions worldwide and the strong augmentation of the reptile trade, few invasive snake populations have been studied. Dice snakes (Natrix tessellata) were introduced to the shores of Lake Geneva (Switzerland) in the early 1920s, and are now well established. This region of introduction was previously inhabited by Viperine snakes (N. maura). Ever since these two species have been under monitoring (which began in 1996) the Viperine snake population has shown drastic decline. We examine here the possibility of trophic competition by analysing diet composition, prey size and trophic niche overlap. Spatial distribution is also assessed in order to address the question of spatial competitive exclusion. We found very similar diets, and thus a high trophic niche overlap, indicating no partitioning of the trophic resource. No arguments in favour of spatial competitive exclusion were found. Our study suggests that trophic competition may occur between the two natricines and that it may give an explanation for the drastic decline of the Viperine snake in this area. Other pathways potentially playing a role in the exclusion of the Viperine snake are discussed.

A statistical procedure for testing social reciprocity at group, dyadic and individual levels

This paper examines statistical analysis of social reciprocity, that is, the balance between addressing and receiving behaviour in social interactions. Specifically, it focuses on the measurement of social reciprocity by means of directionality and skew-symmetry statistics at different levels. Two statistics have been used as overall measures of social reciprocity at group level: the directional consistency and the skew-symmetry statistics. Furthermore, the skew-symmetry statistic allows social researchers to obtain complementary information at dyadic and individual levels. However, having computed these measures, social researchers may be interested in testing statistical hypotheses regarding social reciprocity. For this reason, it has been developed a statistical procedure, based on Monte Carlo sampling, in order to allow social researchers to describe groups and make statistical decisions.

Development of Preliminary Load and Resistance Factor Design of Drilled Shafts in Iowa, RB03-012, 2014

The Federal Highway Administration (FHWA) mandated utilizing the Load and Resistance Factor Design (LRFD) approach for all new bridges initiated in the United States after October 1, 2007. To achieve part of this goal, a database for Drilled Shaft Foundation Testing (DSHAFT) was developed and reported on by Garder, Ng, Sritharan, and Roling in 2012. DSHAFT is aimed at assimilating high-quality drilled shaft test data from Iowa and the surrounding regions. DSHAFT is currently housed on a project website (http://srg.cce.iastate.edu/dshaft) and contains data for 41 drilled shaft tests. The objective of this research was to utilize the DSHAFT database and develop a regional LRFD procedure for drilled shafts in Iowa with preliminary resistance factors using a probability-based reliability theory. This was done by examining current design and construction practices used by the Iowa Department of Transportation (DOT) as well as recommendations given in the American Association of State Highway and Transportation Officials (AASHTO) LRFD Bridge Design Specifications and the FHWA drilled shaft guidelines. Various analytical methods were used to estimate side resistance and end bearing of drilled shafts in clay, sand, intermediate geomaterial (IGM), and rock. Since most of the load test results obtained from O-cell do not pass the 1-in. top displacement criterion used by the Iowa DOT and the 5% of shaft diameter for top displacement criterion recommended by AASHTO, three improved procedures are proposed to generate and extend equivalent top load-displacement curves that enable the quantification of measured resistances corresponding to the displacement criteria. Using the estimated and measured resistances, regional resistance factors were calibrated following the AASHTO LRFD framework and adjusted to resolve any anomalies observed among the factors. To illustrate the potential and successful use of drilled shafts in Iowa, the design procedures of drilled shaft foundations were demonstrated and the advantages of drilled shafts over driven piles were addressed in two case studies.

Testing a large-scale forestry scenario model by means of successive inventories on a forest property

Abstract

Isothermal microcalorimetry for antifungal susceptibility testing of Mucorales, Fusarium spp., and Scedosporium spp.

We evaluated isothermal microcalorimetry for real-time susceptibility testing of non-Aspergillus molds. MIC and minimal effective concentration (MEC) values of Mucorales (n = 4), Fusarium spp. (n = 4), and Scedosporium spp. (n = 4) were determined by microbroth dilution according to the Clinical Laboratory Standard Institute M38-A2 guidelines. Heat production of molds was measured at 37 °C in Sabouraud dextrose broth inoculated with 2.5 × 10(4) spores/mL in the presence of amphotericin B, voriconazole, posaconazole, caspofungin, and anidulafungin. As determined by microcalorimetry, amphotericin B was the most active agent against Mucorales (MHIC 0.06-0.125 μg/mL) and Fusarium spp. (MHIC 1-4 μg/mL), whereas voriconazole was the most active agent against Scedosporium spp. (MHIC 0.25 to 8 μg/mL). The percentage of agreement (within one 2-fold dilution) between the MHIC and MIC (or MEC) was 67%, 92%, 75%, and 83% for amphotericin B, voriconazole, posaconazole, and caspofungin, respectively. Microcalorimetry provides additional information on timing of antifungal activity, enabling further investigation of drug-mold and drug-drug interaction, and optimization of antifungal treatment.

Influence of multiple injections of human chorionic gonadotropin (hCG) on urine and serum endogenous steroids concentrations.

Since it is established that human chorionic gonadotropin (hCG) affects testosterone production and release in the human body, the use of this hormone as a performance enhancing drug has been prohibited by the World Anti-Doping Agency. Nowadays, the only validated biomarker of a hCG doping is its direct quantification in urine. However, this specific parameter is subjected to large inter-individual variability and its determination is directly dependent on the reliability of hCG immunoassays used. In order to counteract these weaknesses, new biomarkers need to be evidenced. To address this issue, a pilot clinical study was performed on 10 volunteers submitted to 3 subsequent hCG injections. Blood and urine samples were collected during two weeks in order to follow the physiological effects on related compounds such as the steroid profile or hormones involved in the hypothalamo-pituitary axis. The hCG pharmacokinetic observed in all subjects was, as expected, prone to important inter-individual variations. Using ROC plots, level of testosterone and testosterone on luteinizing hormone ratio in both blood and urine were found to be the most relevant biomarker of a hCG abuse, regardless of inter-individual variations. In conclusion, this study showed the crucial importance of reliable quantification methods to assess low differences in hormonal patterns. In regard to these results and to anti-doping requirements and constraints, blood together with urine matrix should be included in the anti-doping testing program. Together with a longitudinal follow-up approach it could constitute a new strategy to detect a hCG abuse, applicable to further forms of steroid or other forbidden drug manipulation.

An efficient algorithm to perform multiple testing in epistasis screening

Background: Research in epistasis or gene-gene interaction detection for human complex traits has grown over the last few years. It has been marked by promising methodological developments, improved translation efforts of statistical epistasis to biological epistasis and attempts to integrate different omics information sources into the epistasis screening to enhance power. The quest for gene-gene interactions poses severe multiple-testing problems. In this context, the maxT algorithm is one technique to control the false-positive rate. However, the memory needed by this algorithm rises linearly with the amount of hypothesis tests. Gene-gene interaction studies will require a memory proportional to the squared number of SNPs. A genome-wide epistasis search would therefore require terabytes of memory. Hence, cache problems are likely to occur, increasing the computation time. In this work we present a new version of maxT, requiring an amount of memory independent from the number of genetic effects to be investigated. This algorithm was implemented in C++ in our epistasis screening software MBMDR-3.0.3. We evaluate the new implementation in terms of memory efficiency and speed using simulated data. The software is illustrated on real-life data for Crohn’s disease. Results: In the case of a binary (affected/unaffected) trait, the parallel workflow of MBMDR-3.0.3 analyzes all gene-gene interactions with a dataset of 100,000 SNPs typed on 1000 individuals within 4 days and 9 hours, using 999 permutations of the trait to assess statistical significance, on a cluster composed of 10 blades, containing each four Quad-Core AMD Opteron(tm) Processor 2352 2.1 GHz. In the case of a continuous trait, a similar run takes 9 days. Our program found 14 SNP-SNP interactions with a multiple-testing corrected p-value of less than 0.05 on real-life Crohn’s disease (CD) data. Conclusions: Our software is the first implementation of the MB-MDR methodology able to solve large-scale SNP-SNP interactions problems within a few days, without using much memory, while adequately controlling the type I error rates. A new implementation to reach genome-wide epistasis screening is under construction. In the context of Crohn’s disease, MBMDR-3.0.3 could identify epistasis involving regions that are well known in the field and could be explained from a biological point of view. This demonstrates the power of our software to find relevant phenotype-genotype higher-order associations.

Assessment of Nondestructive Testing Technologies for Quality Control/Quality Assurance of Asphalt Mixtures, TR-653, 2015

Asphalt pavements suffer various failures due to insufficient quality within their design lives. The American Association of State Highway and Transportation Officials (AASHTO) Mechanistic-Empirical Pavement Design Guide (MEPDG) has been proposed to improve pavement quality through quantitative performance prediction. Evaluation of the actual performance (quality) of pavements requires in situ nondestructive testing (NDT) techniques that can accurately measure the most critical, objective, and sensitive properties of pavement systems. The purpose of this study is to assess existing as well as promising new NDT technologies for quality control/quality assurance (QC/QA) of asphalt mixtures. Specifically, this study examined field measurements of density via the PaveTracker electromagnetic gage, shear-wave velocity via surface-wave testing methods, and dynamic stiffness via the Humboldt GeoGauge for five representative paving projects covering a range of mixes and traffic loads. The in situ tests were compared against laboratory measurements of core density and dynamic modulus. The in situ PaveTracker density had a low correlation with laboratory density and was not sensitive to variations in temperature or asphalt mix type. The in situ shear-wave velocity measured by surface-wave methods was most sensitive to variations in temperature and asphalt mix type. The in situ density and in situ shear-wave velocity were combined to calculate an in situ dynamic modulus, which is a performance-based quality measurement. The in situ GeoGauge stiffness measured on hot asphalt mixtures several hours after paving had a high correlation with the in situ dynamic modulus and the laboratory density, whereas the stiffness measurement of asphalt mixtures cooled with dry ice or at ambient temperature one or more days after paving had a very low correlation with the other measurements. To transform the in situ moduli from surface-wave testing into quantitative quality measurements, a QC/QA procedure was developed to first correct the in situ moduli measured at different field temperatures to the moduli at a common reference temperature based on master curves from laboratory dynamic modulus tests. The corrected in situ moduli can then be compared against the design moduli for an assessment of the actual pavement performance. A preliminary study of microelectromechanical systems- (MEMS)-based sensors for QC/QA and health monitoring of asphalt pavements was also performed.

Testing the effects of genetic crossing distance on embryo survival within a metapopulation of brown trout (Salmo trutta)

Predicting progeny performance from parental genetic divergence can potentially enhance the efficiency of supportive breeding programmes and facilitate risk assessment. Yet, experimental testing of the effects of breeding distance on offspring performance remains rare, especially in wild populations of vertebrates. Recent studies have demonstrated that embryos of salmonid fish are sensitive indicators of additive genetic variance for viability traits. We therefore used gametes of wild brown trout (Salmo trutta) from five genetically distinct populations of a river catchment in Switzerland, and used a full factorial design to produce over 2,000 embryos in 100 different crosses with varying genetic distances (FST range 0.005-0.035). Customized egg capsules allowed recording the survival of individual embryos until hatching under natural field conditions. Our breeding design enabled us to evaluate the role of the environment, of genetic and nongenetic parental contributions, and of interactions between these factors, on embryo viability. We found that embryo survival was strongly affected by maternal environmental (i.e. non-genetic) effects and by the microenvironment, i.e. by the location within the gravel. However, embryo survival was not predicted by population divergence, parental allelic dissimilarity, or heterozygosity, neither in the field nor under laboratory conditions. Our findings suggest that the genetic effects of inter-population hybridization within a genetically differentiated meta-population can be minor in comparison to environmental effects.