Bayesian predictive modeling and comparison of oil samples

Statistical comparison of oil samples is an integral part of oil spill identification, which deals with the process of linking an oil spill with its source of origin. In current practice, a frequentist hypothesis test is often used to evaluate evidence in support of a match between a spill and a source sample. As frequentist tests are only able to evaluate evidence against a hypothesis but not in support of it, we argue that this leads to unsound statistical reasoning. Moreover, currently only verbal conclusions on a very coarse scale can be made about the match between two samples, whereas a finer quantitative assessment would often be preferred. To address these issues, we propose a Bayesian predictive approach for evaluating the similarity between the chemical compositions of two oil samples. We derive the underlying statistical model from some basic assumptions on modeling assays in analytical chemistry, and to further facilitate and improve numerical evaluations, we develop analytical expressions for the key elements of Bayesian inference for this model. The approach is illustrated with both simulated and real data and is shown to have appealing properties in comparison with both standard frequentist and Bayesian approaches

Spatially explicit structural equation modeling

Structural equation modeling (SEM) is a powerful statistical approach for the testing of networks of direct and indirect theoretical causal relationships in complex data sets with intercorrelated dependent and independent variables. SEM is commonly applied in ecology, but the spatial information commonly found in ecological data remains difficult to model in a SEM framework. Here we propose a simple method for spatially explicit SEM (SE-SEM) based on the analysis of variance/covariance matrices calculated across a range of lag distances. This method provides readily interpretable plots of the change in path coefficients across scale and can be implemented using any standard SEM software package. We demonstrate the application of this method using three studies examining the relationships between environmental factors, plant community structure, nitrogen fixation, and plant competition. By design, these data sets had a spatial component, but were previously analyzed using standard SEM models. Using these data sets, we demonstrate the application of SE-SEM to regularly spaced, irregularly spaced, and ad hoc spatial sampling designs and discuss the increased inferential capability of this approach compared with standard SEM. We provide an R package, sesem, to easily implement spatial structural equation modeling.

Towards development of a rapid and effective non-destructive testing strategy to identify brominated flame retardants in the plastics of consumer products

Polybrominated diphenyl ethers (PBDEs) are a class of brominated flame retardants (BFRs) once extensively used in the plastics of a wide range of consumer products. The listing of certain congeners that are constituents of commercial PBDE mixtures (including c-octaBDE) in the Stockholm Convention and tightening regulation of many other BFRs in recent years have created the need for a rapid and effective method of identifying BFR-containing plastics. A three-tiered testing strategy comparing results from non-destructive testing (X-ray fluorescence (XRF)) (n = 1714), a surface wipe test (n = 137) and destructive chemical analysis (n = 48) was undertaken to systematically identify BFRs in a wide range of consumer products. XRF rapidly identified bromine in 92% of products later confirmed to contain BFRs. Surface wipes of products identified tetrabromobisphenol A (TBBPA), c-octaBDE congeners and BDE-209 with relatively high accuracy (> 75%) when confirmed by destructive chemical analysis. A relationship between the amounts of BFRs detected in surface wipes and subsequent destructive testing shows promise in predicting not only the types of BFRs present but also estimating the concentrations present. Information about the types of products that may contain persistent BFRs will assist regulators in implementing policies to further reduce the occurrence of these chemicals in consumer products.

ISPCAN child abuse screening tool children's version (ICAST-C): Instrument development and multi-national pilot testing

Objective To develop a child victimization survey among a diverse group of child protection experts and examine the performance of the instrument through a set of international pilot studies. Methods The initial draft of the instrument was developed after input from scientists and practitioners representing 40 countries. Volunteers from the larger group of scientists participating in the Delphi review of the ICAST P and R reviewed the ICAST C by email in 2 rounds resulting in a final instrument. The ICAST C was then translated and back translated into six languages and field tested in four countries using a convenience sample of 571 children 12–17 years of age selected from schools and classrooms to which the investigators had easy access. Results The final ICAST C Home has 38 items and the ICAST C Institution has 44 items. These items serve as screeners and positive endorsements are followed by queries for frequency and perpetrator. Half of respondents were boys (49%). Endorsement for various forms of victimization ranged from 0 to 51%. Many children report violence exposure (51%), physical victimization (55%), psychological victimization (66%), sexual victimization (18%), and neglect in their homes (37%) in the last year. High rates of physical victimization (57%), psychological victimization (59%), and sexual victimization (22%) were also reported in schools in the last year. Internal consistency was moderate to high (alpha between .685 and .855) and missing data low (less than 1.5% for all but one item). Conclusions In pilot testing, the ICAST C identifies high rates of child victimization in all domains. Rates of missing data are low, and internal consistency is moderate to high. Pilot testing demonstrated the feasibility of using child self-report as one strategy to assess child victimization. Practice implications The ICAST C is a multi-national, multi-lingual, consensus-based survey instrument. It is available in six languages for international research to estimate child victimization. Assessing the prevalence of child victimization is critical in understanding the scope of the problem, setting national and local priorities, and garnering support for program and policy development aimed at child protection.

Statistical literacy social media project for the masses

This article examines a social media assignment used to teach and practice statistical literacy with over 400 students each semester in large-lecture traditional, fully online, and flipped sections of an introductory-level statistics course. Following the social media assignment, students completed a survey on how they approached the assignment. Drawing from the authors’ experiences with the project and the survey results, this article offers recommendations for developing social media assignments in large courses that focus on the interplay between the social media tool and the implications of assignment prompts.

Design and flight testing of an integrated solar powered UAV and WSN for greenhouse gas monitoring emissions in agricultural farms

There is an increased interest in measuring the amount of greenhouse gases produced by farming practices . This paper describes an integrated solar powered Unmanned Air Vehicles (UAV) and Wireless Sensor Network (WSN) gas sensing system for greenhouse gas emissions in agricultural lands. The system uses a generic gas sensing system for CH4 and CO2 concentrations using metal oxide (MoX) and non-dispersive infrared sensors, and a new solar cell encapsulation method to power the unmanned aerial system (UAS)as well as a data management platform to store, analyze and share the information with operators and external users. The system was successfully field tested at ground and low altitudes, collecting, storing and transmitting data in real time to a central node for analysis and 3D mapping. The system can be used in a wide range of outdoor applications at a relatively low operational cost. In particular, agricultural environments are increasingly subject to emissions mitigation policies. Accurate measurements of CH4 and CO2 with its temporal and spatial variability can provide farm managers key information to plan agricultural practices. A video of the bench and flight test performed can be seen in the following link: https://www.youtube.com/watch?v=Bwas7stYIxQ

The v-MFG test: Investigating maternal, offspring and maternal-fetal genetic incompatibility effects on disease and viability

The MFG test is a family-based association test that detects genetic effects contributing to disease in offspring, including offspring allelic effects, maternal allelic effects and MFG incompatibility effects. Like many other family-based association tests, it assumes that the offspring survival and the offspring-parent genotypes are conditionally independent provided the offspring is affected. However, when the putative disease-increasing locus can affect another competing phenotype, for example, offspring viability, the conditional independence assumption fails and these tests could lead to incorrect conclusions regarding the role of the gene in disease. We propose the v-MFG test to adjust for the genetic effects on one phenotype, e.g., viability, when testing the effects of that locus on another phenotype, e.g., disease. Using genotype data from nuclear families containing parents and at least one affected offspring, the v-MFG test models the distribution of family genotypes conditional on offspring phenotypes. It simultaneously estimates genetic effects on two phenotypes, viability and disease. Simulations show that the v-MFG test produces accurate genetic effect estimates on disease as well as on viability under several different scenarios. It generates accurate type-I error rates and provides adequate power with moderate sample sizes to detect genetic effects on disease risk when viability is reduced. We demonstrate the v-MFG test with HLA-DRB1 data from study participants with rheumatoid arthritis (RA) and their parents, we show that the v-MFG test successfully detects an MFG incompatibility effect on RA while simultaneously adjusting for a possible viability loss.

HLA-DR/DQ haplotype in rheumatoid arthritis: Novel allelic associations in UK Caucasians

Objective. To elucidate the relative importance of the HLA-DR and HLA-DQ loci in conferring genetic predisposition to rheumatoid arthritis (RA). Methods. HLA-DRB1 and HLA-DQB1 alleles were typed in a set of 685 patients with RA using sequence-specific polymerase chain reaction. Allele and phenotype frequencies were compared with those in 2 large sets of historical, ethnically matched healthy controls, using the relative predispositional effect method. Results. Positive association was confirmed with the shared epitope positive HLA-DRB1 alleles associated with RA in Caucasians. A significant susceptibility effect was observed with HLA-DRB1*09, described in other ethnically diverse populations but not in Caucasians. A significant underrepresentation of the HLA-DRB1*0103 variant was noted among the RA cases, supporting the proposed protective role of the DERAA motif at residues 70-74 of the DRβ molecule. No HLA-DRB1 independent association of the HLA-DQB1 alleles, implicated in predisposing to RA, was evident. Conclusion. These data corroborate the shared epitope hypothesis of susceptibility to RA and provide strong evidence for the DRB1 locus as the primary RA susceptibility factor in the HLA region.

Initial prototype testing of Ray's Night Out: A new mobile app targeting risky drinking in young people

Background Risky single occasion drinking (RSOD; 4 or more drinks in <6 h) more than doubles the risk of injury in young people (15 - 25 years). The potential role of smartphone apps in reducing RSOD in young people is yet to be explored. Objective: To describe the initial prototype testing of ‘Ray's Night Out’, a new iPhone app targeting RSOD in young people. Method Quantitative and qualitative methods were used to evaluate the quality, perceived utility, and acceptability of the app among nine young people (19e23 years). Results Participants reported Ray's Night Out had good to excellent levels of functionality and visual appeal, acceptable to good levels of entertainment, interest and information, and acceptable levels of customization and interactivity. Young people thought the app had high levels of youth appeal, would prompt users to think about their alcohol use limits, but was unlikely to motivate a change in alcohol use in its current form. Qualitative data provided several suggestions for improving the app. Conclusion Following revision, Ray's Night Out could provide an effective intervention for RSOD in non help-seeking young people. A randomized controlled trial is currently underway to test the final prototype of the app.

Statistical modelling and power analysis for detecting trends in total suspended sediment loads

The export of sediments from coastal catchments can have detrimental impacts on estuaries and near shore reef ecosystems such as the Great Barrier Reef. Catchment management approaches aimed at reducing sediment loads require monitoring to evaluate their effectiveness in reducing loads over time. However, load estimation is not a trivial task due to the complex behaviour of constituents in natural streams, the variability of water flows and often a limited amount of data. Regression is commonly used for load estimation and provides a fundamental tool for trend estimation by standardising the other time specific covariates such as flow. This study investigates whether load estimates and resultant power to detect trends can be enhanced by (i) modelling the error structure so that temporal correlation can be better quantified, (ii) making use of predictive variables, and (iii) by identifying an efficient and feasible sampling strategy that may be used to reduce sampling error. To achieve this, we propose a new regression model that includes an innovative compounding errors model structure and uses two additional predictive variables (average discounted flow and turbidity). By combining this modelling approach with a new, regularly optimised, sampling strategy, which adds uniformity to the event sampling strategy, the predictive power was increased to 90%. Using the enhanced regression model proposed here, it was possible to detect a trend of 20% over 20 years. This result is in stark contrast to previous conclusions presented in the literature. (C) 2014 Elsevier B.V. All rights reserved.

Sediment concentration prediction and statistical evaluation for annual load estimation

We consider the development of statistical models for prediction of constituent concentration of riverine pollutants, which is a key step in load estimation from frequent flow rate data and less frequently collected concentration data. We consider how to capture the impacts of past flow patterns via the average discounted flow (ADF) which discounts the past flux based on the time lapsed - more recent fluxes are given more weight. However, the effectiveness of ADF depends critically on the choice of the discount factor which reflects the unknown environmental cumulating process of the concentration compounds. We propose to choose the discount factor by maximizing the adjusted R-2 values or the Nash-Sutcliffe model efficiency coefficient. The R2 values are also adjusted to take account of the number of parameters in the model fit. The resulting optimal discount factor can be interpreted as a measure of constituent exhaustion rate during flood events. To evaluate the performance of the proposed regression estimators, we examine two different sampling scenarios by resampling fortnightly and opportunistically from two real daily datasets, which come from two United States Geological Survey (USGS) gaging stations located in Des Plaines River and Illinois River basin. The generalized rating-curve approach produces biased estimates of the total sediment loads by -30% to 83%, whereas the new approaches produce relatively much lower biases, ranging from -24% to 35%. This substantial improvement in the estimates of the total load is due to the fact that predictability of concentration is greatly improved by the additional predictors.

Statistical power calculation and sample size determination for environmental studies with data below detection limits

Power calculation and sample size determination are critical in designing environmental monitoring programs. The traditional approach based on comparing the mean values may become statistically inappropriate and even invalid when substantial proportions of the response values are below the detection limits or censored because strong distributional assumptions have to be made on the censored observations when implementing the traditional procedures. In this paper, we propose a quantile methodology that is robust to outliers and can also handle data with a substantial proportion of below-detection-limit observations without the need of imputing the censored values. As a demonstration, we applied the methods to a nutrient monitoring project, which is a part of the Perth Long-Term Ocean Outlet Monitoring Program. In this example, the sample size required by our quantile methodology is, in fact, smaller than that by the traditional t-test, illustrating the merit of our method.

Direct shear testing on unsaturated silty soils to investigate the effects of drying and wetting on shear strength parameters at low suction

A modified conventional direct shear device was used to measure unsaturated shear strength of two silty soils at low suction values (0 ~ 50 kPa) that were achieved by following drying and wetting paths of soil water characteristic curves (SWCCs). The results revealed that the internal friction angle of the soils was not significantly affected by either the suction or the drying wetting SWCCs. The apparent cohesion of soil increased with a decreasing rate as suction increased. Shear stress-shear displacement curves obtained from soil specimens subjected to the same net normal stress and different suction values showed a higher initial stiffness and a greater peak stress as suction increased. A soil in wetting exhibited slightly higher peak shear stress and more contractive volume change behavior than that of soil in drying at the same net normal stress and suction.

Domain Adaptation on the Statistical Manifold

In this paper, we tackle the problem of unsupervised domain adaptation for classification. In the unsupervised scenario where no labeled samples from the target domain are provided, a popular approach consists in transforming the data such that the source and target distributions be- come similar. To compare the two distributions, existing approaches make use of the Maximum Mean Discrepancy (MMD). However, this does not exploit the fact that prob- ability distributions lie on a Riemannian manifold. Here, we propose to make better use of the structure of this man- ifold and rely on the distance on the manifold to compare the source and target distributions. In this framework, we introduce a sample selection method and a subspace-based method for unsupervised domain adaptation, and show that both these manifold-based techniques outperform the cor- responding approaches based on the MMD. Furthermore, we show that our subspace-based approach yields state-of- the-art results on a standard object recognition benchmark.

Random Breath Testing Operation and Effectiveness in 1987

• In December 1986 funds were approved to double the intensity of random breath testing (RBT) and provide publicity support for police efforts. These changes were considered necessary to make RBT effective. • RBT methods were changed in the metropolitan area to enable block testing (pulling over a block of traffic rather than one or two cars), deployment of police to cut off escape routes, and testing by traffic patrols in all police subdivisions. Additional operators were trained for country RBT. • A publicity campaign was developed, aimed mainly at male drivers aged 18-50. The campaign consisted of the “cardsharp” television commercials, radio commercials, newspaper articles, posters and pamphlets. • Increased testing and the publicity campaigns were launched on 10 April 1987. • Police tests increased by 92.5% in May – December 1987, compared with the same period in the previous four years. • The detection rate for drinking drivers picked up by police who were cutting off escape routes was comparatively high, indicating that drivers were attempting to avoid RBT, and that this police method was effective at detecting these drivers. • A telephone survey indicated that drivers were aware of the messages of the publicity campaign. • The telephone survey also indicated that the target group had been exposed to high levels of RBT, as planned, and that fear of apprehension was the major factor deterring them from drink driving. • A roadside survey of driver blood alcohol concentrations (BACs) by the University of Adelaide’s Road Accident Research Unit (RARU) showed that, between 10p.m. and 3a.m., the proportion of drivers in Adelaide with a BAC greater than or equal to 0/08 decreased by 42%. • Drivers under 21 were identified as a possible problem area. • Fatalities in the twelve month period commencing May 1987 decreased by 18% in comparison with the previous twelve month period, and by 13% in comparison with the average of the previous two twelve month periods (commencing May 1985 and May 1986). There are indications that this trend is continuing. • It is concluded that the increase in RBT, plus publicity, was successful in achieving its aims of reductions in drink driving and accidents.