Local and global error models to improve uncertainty quantification

In groundwater applications, Monte Carlo methods are employed to model the uncertainty on geological parameters. However, their brute-force application becomes computationally prohibitive for highly detailed geological descriptions, complex physical processes, and a large number of realizations. The Distance Kernel Method (DKM) overcomes this issue by clustering the realizations in a multidimensional space based on the flow responses obtained by means of an approximate (computationally cheaper) model; then, the uncertainty is estimated from the exact responses that are computed only for one representative realization per cluster (the medoid). Usually, DKM is employed to decrease the size of the sample of realizations that are considered to estimate the uncertainty. We propose to use the information from the approximate responses for uncertainty quantification. The subset of exact solutions provided by DKM is then employed to construct an error model and correct the potential bias of the approximate model. Two error models are devised that both employ the difference between approximate and exact medoid solutions, but differ in the way medoid errors are interpolated to correct the whole set of realizations. The Local Error Model rests upon the clustering defined by DKM and can be seen as a natural way to account for intra-cluster variability; the Global Error Model employs a linear interpolation of all medoid errors regardless of the cluster to which the single realization belongs. These error models are evaluated for an idealized pollution problem in which the uncertainty of the breakthrough curve needs to be estimated. For this numerical test case, we demonstrate that the error models improve the uncertainty quantification provided by the DKM algorithm and are effective in correcting the bias of the estimate computed solely from the MsFV results. The framework presented here is not specific to the methods considered and can be applied to other combinations of approximate models and techniques to select a subset of realizations

SPATIAL UNCERTAINTY OF NUTRIENT LOSS BY EROSION IN SUGARCANE HARVESTING SCENARIOS

The assessment of spatial uncertainty in the prediction of nutrient losses by erosion associated with landscape models is an important tool for soil conservation planning. The purpose of this study was to evaluate the spatial and local uncertainty in predicting depletion rates of soil nutrients (P, K, Ca, and Mg) by soil erosion from green and burnt sugarcane harvesting scenarios, using sequential Gaussian simulation (SGS). A regular grid with equidistant intervals of 50 m (626 points) was established in the 200-ha study area, in Tabapuã, São Paulo, Brazil. The rate of soil depletion (SD) was calculated from the relation between the nutrient concentration in the sediments and the chemical properties in the original soil for all grid points. The data were subjected to descriptive statistical and geostatistical analysis. The mean SD rate for all nutrients was higher in the slash-and-burn than the green cane harvest scenario (Student’s t-test, p<0.05). In both scenarios, nutrient loss followed the order: Ca>Mg>K>P. The SD rate was highest in areas with greater slope. Lower uncertainties were associated to the areas with higher SD and steeper slopes. Spatial uncertainties were highest for areas of transition between concave and convex landforms.

Validation of a Low-Cost Human Papillomavirus Genotyping Assay Based on PGMY PCR and Reverse Blotting Hybridization with Reusable Membranes.

The genotyping of human papillomaviruses (HPV) is essential for the surveillance of HPV vaccines. We describe and validate a low-cost PGMY-based PCR assay (PGMY-CHUV) for the genotyping of 31 HPV by reverse blotting hybridization (RBH). Genotype-specific detection limits were 50 to 500 genome equivalents per reaction. RBH was 100% specific and 98.61% sensitive using DNA sequencing as the gold standard (n = 1,024 samples). PGMY-CHUV was compared to the validated and commercially available linear array (Roche) on 200 samples. Both assays identified the same positive (n = 182) and negative samples (n = 18). Seventy-six percent of the positives were fully concordant after restricting the comparison to the 28 genotypes shared by both assays. At the genotypic level, agreement was 83% (285/344 genotype-sample combinations; κ of 0.987 for single infections and 0.853 for multiple infections). Fifty-seven of the 59 discordant cases were associated with multiple infections and with the weakest genotypes within each sample (P < 0.0001). PGMY-CHUV was significantly more sensitive for HPV56 (P = 0.0026) and could unambiguously identify HPV52 in mixed infections. PGMY-CHUV was reproducible on repeat testing (n = 275 samples; 392 genotype-sample combinations; κ of 0.933) involving different reagents lots and different technicians. Discordant results (n = 47) were significantly associated with the weakest genotypes in samples with multiple infections (P < 0.0001). Successful participation in proficiency testing also supported the robustness of this assay. The PGMY-CHUV reagent costs were estimated at $2.40 per sample using the least expensive yet proficient genotyping algorithm that also included quality control. This assay may be used in low-resource laboratories that have sufficient manpower and PCR expertise.

Identification and validation of copy number variants using SNP genotyping arrays from a large clinical cohort.

BACKGROUND: Genotypes obtained with commercial SNP arrays have been extensively used in many large case-control or population-based cohorts for SNP-based genome-wide association studies for a multitude of traits. Yet, these genotypes capture only a small fraction of the variance of the studied traits. Genomic structural variants (GSV) such as Copy Number Variation (CNV) may account for part of the missing heritability, but their comprehensive detection requires either next-generation arrays or sequencing. Sophisticated algorithms that infer CNVs by combining the intensities from SNP-probes for the two alleles can already be used to extract a partial view of such GSV from existing data sets. RESULTS: Here we present several advances to facilitate the latter approach. First, we introduce a novel CNV detection method based on a Gaussian Mixture Model. Second, we propose a new algorithm, PCA merge, for combining copy-number profiles from many individuals into consensus regions. We applied both our new methods as well as existing ones to data from 5612 individuals from the CoLaus study who were genotyped on Affymetrix 500K arrays. We developed a number of procedures in order to evaluate the performance of the different methods. This includes comparison with previously published CNVs as well as using a replication sample of 239 individuals, genotyped with Illumina 550K arrays. We also established a new evaluation procedure that employs the fact that related individuals are expected to share their CNVs more frequently than randomly selected individuals. The ability to detect both rare and common CNVs provides a valuable resource that will facilitate association studies exploring potential phenotypic associations with CNVs. CONCLUSION: Our new methodologies for CNV detection and their evaluation will help in extracting additional information from the large amount of SNP-genotyping data on various cohorts and use this to explore structural variants and their impact on complex traits.

Improved multiple-locus variable-number tandem-repeat assay for Staphylococcus aureus genotyping, providing a highly informative technique together with strong phylogenetic value.

We describe an improved multiple-locus variable-number tandem-repeat (VNTR) analysis (MLVA) scheme for genotyping Staphylococcus aureus. We compare its performance to those of multilocus sequence typing (MLST) and spa typing in a survey of 309 strains. This collection includes 87 epidemic methicillin-resistant S. aureus (MRSA) strains of the Harmony collection, 75 clinical strains representing the major MLST clonal complexes (CCs) (50 methicillin-sensitive S. aureus [MSSA] and 25 MRSA), 135 nasal carriage strains (133 MSSA and 2 MRSA), and 13 published S. aureus genome sequences. The results show excellent concordance between the techniques' results and demonstrate that the discriminatory power of MLVA is higher than those of both MLST and spa typing. Two hundred forty-two genotypes are discriminated with 14 VNTR loci (diversity index, 0.9965; 95% confidence interval, 0.9947 to 0.9984). Using a cutoff value of 45%, 21 clusters are observed, corresponding to the CCs previously defined by MLST. The variability of the different tandem repeats allows epidemiological studies, as well as follow-up of the evolution of CCs and the identification of potential ancestors. The 14 loci can conveniently be analyzed in two steps, based upon a first-line simplified assay comprising a subset of 10 loci (panel 1) and a second subset of 4 loci (panel 2) that provides higher resolution when needed. In conclusion, the MLVA scheme proposed here, in combination with available on-line genotyping databases (including http://mlva.u-psud.fr/), multiplexing, and automatic sizing, can provide a basis for almost-real-time large-scale population monitoring of S. aureus.

Quantifying Uncertainty in Real Time Performance Measurement for Highway Winter Maintenance Operations – Phase 2, RB03-013, 2014

Winter weather in Iowa is often unpredictable and can have an adverse impact on traffic flow. The Iowa Department of Transportation (Iowa DOT) attempts to lessen the impact of winter weather events on traffic speeds with various proactive maintenance operations. In order to assess the performance of these maintenance operations, it would be beneficial to develop a model for expected speed reduction based on weather variables and normal maintenance schedules. Such a model would allow the Iowa DOT to identify situations in which speed reductions were much greater than or less than would be expected for a given set of storm conditions, and make modifications to improve efficiency and effectiveness. The objective of this work was to predict speed changes relative to baseline speed under normal conditions, based on nominal maintenance schedules and winter weather covariates (snow type, temperature, and wind speed), as measured by roadside weather stations. This allows for an assessment of the impact of winter weather covariates on traffic speed changes, and estimation of the effect of regular maintenance passes. The researchers chose events from Adair County, Iowa and fit a linear model incorporating the covariates mentioned previously. A Bayesian analysis was conducted to estimate the values of the parameters of this model. Specifically, the analysis produces a distribution for the parameter value that represents the impact of maintenance on traffic speeds. The effect of maintenance is not a constant, but rather a value that the researchers have some uncertainty about and this distribution represents what they know about the effects of maintenance. Similarly, examinations of the distributions for the effects of winter weather covariates are possible. Plots of observed and expected traffic speed changes allow a visual assessment of the model fit. Future work involves expanding this model to incorporate many events at multiple locations. This would allow for assessment of the impact of winter weather maintenance across various situations, and eventually identify locations and times in which maintenance could be improved.

Uncertainty, electoral incentives and political myopia

We study the determinants of political myopia in a rational model of electoral accountability where the key elements are informational frictions and uncertainty. We build aframework where political ability is ex-ante unknown and policy choices are not perfectlyobservable. On the one hand, elections improve accountability and allow to keep well-performing incumbents. On the other, politicians invest too little in costly policies withfuture returns in an attempt to signal high ability and increase their reelection probability.Contrary to the conventional wisdom, uncertainty reduces political myopia and may, undersome conditions, increase social welfare. We use the model to study how political rewardscan be set so as to maximise social welfare and the desirability of imposing a one-term limitto governments. The predictions of our theory are consistent with a number of stylised factsand with a new empirical observation documented in this paper: aggregate uncertainty, measured by economic volatility, is associated to better fiscal discipline in a panel of 20 OECDcountries.

Alternative genotyping method for the single nucleotide polymorphism A2959G (AF159246) of the bovine CAST gene

The objective of this work was to genotype the single nucleotide polymorphism (SNP) A2959G (AF159246) of bovine CAST gene by PCR-RFLP technique, and to report its use for the first time. For this, 147 Bos indicus and Bos taurus x Bos indicus animals were genotyped. The accuracy of the method was confirmed through the direct sequencing of PCR products of nine individuals. The lowest frequency of the meat tenderness favorable allele (A) in Bos indicus was confirmed. The use of PCR-RFLP for the genotyping of the bovine CAST gene SNP was shown to be robust and inexpensive, which will greatly facilitate its analysis by laboratories with basic structure.

Endosperm genotyping as a strategy to differentiate the allele source in maize heterozygous progeny

The objective of this work was to distinguish the parental source of alleles in heterozygous progeny using semiquantitative polymerase chain reaction (PCR) in maize endosperm. Endosperms derived from direct and reciprocal single-cross hybrids between maize inbred lines L3 and L1113-01 were genotyped by semiquantitative PCR methodology (SQ-PCR) using fluorescent microsatellite primers. The amplification products were evaluated by the ratios of fluorescence intensity (RFI), calculated between the peaks corresponding to the alleles derived from each parental line. Based on the statistically significant contrast between RFI mean values of direct and reciprocal single-cross hybrids, it was possible to distinguish the number of alleles received from each parental line and, ultimately, to determine the origin of the alleles of each cross. Thus, endosperm genotyping using SQ-PCR is a promising strategy to map QTL in maize outbred populations.

When physician-expressed uncertainty leads to patient dissatisfaction: a gender study.

CONTEXT: Communication guidelines often advise physicians to disclose to their patients medical uncertainty regarding the diagnosis, origin of the problem, and treatment. However, the effect of the expression of such uncertainty on patient outcomes (e.g. satisfaction) has produced conflicting results in the literature that indicate either no effect or a negative effect. The differences in the results of past studies may be explained by the fact that potential gender effects on the link between physician-expressed uncertainty and patient outcomes have not been investigated systematically. OBJECTIVES: On the basis of previous research documenting indications that patients may judge female physicians by more severe criteria than they do male physicians, and that men are more prejudiced than women towards women, we predicted that physician-expressed uncertainty would have more of a negative impact on patient satisfaction when the physician in question was female rather than male, and especially when the patient was a man. METHODS: We conducted two studies with complementary designs. Study 1 was a randomised controlled trial conducted in a simulated setting (120 analogue patients Analogue patients are healthy participants asked to put themselves in the shoes of real medical patients by imagining being the patients of physicians shown on videos); Study 2 was a field study conducted in real medical interviews (36 physicians, 69 patients). In Study 1, participants were presented with vignettes that varied in terms of the physician's gender and physician-expressed uncertainty (high versus low). In Study 2, physicians were filmed during real medical consultations and the level of uncertainty they expressed was coded by an independent rater according to the videos. In both studies, patient satisfaction was assessed using a questionnaire. RESULTS: The results confirmed that expressed uncertainty was negatively related to patient satisfaction only when the physician was a woman (Studies 1 and 2) and when the patient was a man (Study 2). CONCLUSIONS: We believe that patients have the right to be fully informed of any medical uncertainties. If our results are confirmed in further research, the question of import will refer not to whether female physicians should communicate uncertainty, but to how they should communicate it. For instance, if it proves true that uncertainty negatively impacts on (male) patients' satisfaction, female physicians might want to counterbalance this impact by emphasizing other communication skills.