Functional error modeling for uncertainty quantification in hydrogeology

Approximate models (proxies) can be employed to reduce the computational costs of estimating uncertainty. The price to pay is that the approximations introduced by the proxy model can lead to a biased estimation. To avoid this problem and ensure a reliable uncertainty quantification, we propose to combine functional data analysis and machine learning to build error models that allow us to obtain an accurate prediction of the exact response without solving the exact model for all realizations. We build the relationship between proxy and exact model on a learning set of geostatistical realizations for which both exact and approximate solvers are run. Functional principal components analysis (FPCA) is used to investigate the variability in the two sets of curves and reduce the dimensionality of the problem while maximizing the retained information. Once obtained, the error model can be used to predict the exact response of any realization on the basis of the sole proxy response. This methodology is purpose-oriented as the error model is constructed directly for the quantity of interest, rather than for the state of the system. Also, the dimensionality reduction performed by FPCA allows a diagnostic of the quality of the error model to assess the informativeness of the learning set and the fidelity of the proxy to the exact model. The possibility of obtaining a prediction of the exact response for any newly generated realization suggests that the methodology can be effectively used beyond the context of uncertainty quantification, in particular for Bayesian inference and optimization.

3D morphometry using automated aortic segmentation in native MR angiography: an alternative to contrast enhanced MRA?

INTRODUCTION Native-MR angiography (N-MRA) is considered an imaging alternative to contrast enhanced MR angiography (CE-MRA) for patients with renal insufficiency. Lower intraluminal contrast in N-MRA often leads to failure of the segmentation process in commercial algorithms. This study introduces an in-house 3D model-based segmentation approach used to compare both sequences by automatic 3D lumen segmentation, allowing for evaluation of differences of aortic lumen diameters as well as differences in length comparing both acquisition techniques at every possible location. METHODS AND MATERIALS Sixteen healthy volunteers underwent 1.5-T-MR Angiography (MRA). For each volunteer, two different MR sequences were performed, CE-MRA: gradient echo Turbo FLASH sequence and N-MRA: respiratory-and-cardiac-gated, T2-weighted 3D SSFP. Datasets were segmented using a 3D model-based ellipse-fitting approach with a single seed point placed manually above the celiac trunk. The segmented volumes were manually cropped from left subclavian artery to celiac trunk to avoid error due to side branches. Diameters, volumes and centerline length were computed for intraindividual comparison. For statistical analysis the Wilcoxon-Signed-Ranked-Test was used. RESULTS Average centerline length obtained based on N-MRA was 239.0±23.4 mm compared to 238.6±23.5 mm for CE-MRA without significant difference (P=0.877). Average maximum diameter obtained based on N-MRA was 25.7±3.3 mm compared to 24.1±3.2 mm for CE-MRA (P<0.001). In agreement with the difference in diameters, volumes obtained based on N-MRA (100.1±35.4 cm(3)) were consistently and significantly larger compared to CE-MRA (89.2±30.0 cm(3)) (P<0.001). CONCLUSIONS 3D morphometry shows highly similar centerline lengths for N-MRA and CE-MRA, but systematically higher diameters and volumes for N-MRA.

Inter-observer agreement for diagnostic classification of esophageal motility disorders defined in high-resolution manometry

High-resolution esophageal manometry (HRM) is a recent development used in the evaluation of esophageal function. Our aim was to assess the inter-observer agreement for diagnosis of esophageal motility disorders using this technology. Practitioners registered on the HRM Working Group website were invited to review and classify (i) 147 individual water swallows and (ii) 40 diagnostic studies comprising 10 swallows using a drop-down menu that followed the Chicago Classification system. Data were presented using a standardized format with pressure contours without a summary of HRM metrics. The sequence of swallows was fixed for each user but randomized between users to avoid sequence bias. Participants were blinded to other entries. (i) Individual swallows were assessed by 18 practitioners (13 institutions). Consensus agreement (≤2/18 dissenters) was present for most cases of normal peristalsis and achalasia but not for cases of peristaltic dysmotility. (ii) Diagnostic studies were assessed by 36 practitioners (28 institutions). Overall inter-observer agreement was 'moderate' (kappa 0.51) being 'substantial' (kappa > 0.7) for achalasia type I/II and no lower than 'fair-moderate' (kappa >0.34) for any diagnosis. Overall agreement was somewhat higher among those that had performed >400 studies (n = 9; kappa 0.55) and 'substantial' among experts involved in development of the Chicago Classification system (n = 4; kappa 0.66). This prospective, randomized, and blinded study reports an acceptable level of inter-observer agreement for HRM diagnoses across the full spectrum of esophageal motility disorders for a large group of clinicians working in a range of medical institutions. Suboptimal agreement for diagnosis of peristaltic motility disorders highlights contribution of objective HRM metrics.

Law and science: risk assessment and risk management in the WTO agreement on the application of sanitary and phytosanitary measures

Assessing and managing risks relating to the consumption of food stuffs for humans and to the environment has been one of the most complex legal issues in WTO law, ever since the Agreement on Sanitary and Phytosanitary Measures was adopted at the end of the Uruguay Round and entered into force in 1995. The problem was expounded in a number of cases. Panels and the Appellate Body adopted different philosophies in interpreting the agreement and the basic concept of risk assessment as defined in Annex A para. 4 of the Agreement. Risk assessment entails fundamental question on law and science. Different interpretations reflect different underlying perceptions of science and its relationship to the law. The present thesis supported by the Swiss National Research Foundation undertakes an in-depth analysis of these underlying perceptions. The author expounds the essence and differences of positivism and relativism in philosophy and natural sciences. He clarifies the relationship of fundamental concepts such as risk, hazards and probability. This investigation is a remarkable effort on the part of lawyer keen to learn more about the fundamentals based upon which the law – often unconsciously – is operated by the legal profession and the trade community. Based upon these insights, he turns to a critical assessment of jurisprudence both of panels and the Appellate Body. Extensively referring and discussing the literature, he deconstructs findings and decisions in light of implied and assumed underlying philosophies and perceptions as to the relationship of law and science, in particular in the field of food standards. Finding that both positivism and relativism does not provide adequate answers, the author turns critical rationalism and applies the methodologies of falsification developed by Karl R. Popper. Critical rationalism allows combining discourse in science and law and helps preparing the ground for a new approach to risk assessment and risk management. Linking the problem to the doctrine of multilevel governance the author develops a theory allocating risk assessment to international for a while leaving the matter of risk management to national and democratically accountable government. While the author throughout the thesis questions the possibility of separating risk assessment and risk management, the thesis offers new avenues which may assist in structuring a complex and difficult problem

A Transatlantic Trade and Investment Partnership Agreement: Implications for Swiss Agriculture

To say that regionalism is gaining momentum has become an understatement. To mourn the lack of progress in multilateral trade rule-making is a commonplace in the discourse of politicians regretting the WTO negotiation standstill, and of “know-what-to-do” academics. The real problem is the uneven level-playing field resulting from increasing differences of rules and obligations. The Transatlantic Trade and Investment Partnership Agreement (TTIP) is a very ambitious project. WTI studies in 2014 have shown that the implications for Switzerland could be enormous. But even the combined market power of the two TTIP participants – the EU and the USA – will not level the playing field impairing the regulatory framework, and the market access barriers for trade in agriculture. Such differences will remain in three areas which, incidentally, are also vital for a global response to the food security challenge to feed 9 billion people before the year 2050: market access, non-tariff barriers, and trade-distorting domestic support programmes. This means that without multilateral progress the TTIP and other so-called mega-regionals, if successfully concluded, will exacerbate rather than lessen trade distortions. While this makes farmers in rich countries safer from competition, competitive production in all countries will be hampered. Consequently, and notwithstanding the many affirmations to the contrary, farm policies worldwide will continue to only address farmer security without increasing global food security. What are the implications of the TTIP for Swiss agriculture? This article, commissioned by Waseda University in Tokyo, finds that the failure to achieve further reforms – including a number of areas where earlier reforms have been reversed – is presenting Switzerland and Swiss agriculture with a terrible dilemma in the eventuality of a successful conclusion of the TTIP. If Swiss farm production is to survive for more than another generation, continuous reform efforts are required, and over-reliance on the traditional instruments of border protection and product support is to be avoided. Without a substantial TTIP obliging Switzerland to follow suit, autonomous reforms will remain extremely fragile.

Gas adsorption and desorption effects on cylinders and their importance for long-term gas records

It is well known that gases adsorb on many surfaces, in particular metal surfaces. There are two main forms responsible for these effects (i) physisorption and (ii) chemisorption. Physisorption is associated with lower binding energies in the order of 1–10 kJ mol−¹, compared to chemisorption which ranges from 100 to 1000 kJ mol−¹. Furthermore, chemisorption only forms monolayers, contrasting physisorption that can form multilayer adsorption. The reverse process is called desorption and follows similar mathematical laws; however, it can be influenced by hysteresis effects. In the present experiment, we investigated the adsorption/desorption phenomena on three steel and three aluminium cylinders containing compressed air in our laboratory and under controlled conditions in a climate chamber, respectively. Our observations from completely decanting one steel and two aluminium cylinders are in agreement with the pressure dependence of physisorption for CO₂, CH₄, and H₂O. The CO₂ results for both cylinder types are in excellent agreement with the pressure dependence of a monolayer adsorption model. However, mole fraction changes due to adsorption on aluminium (< 0.05 and 0 ppm for CO₂ and H₂O) were significantly lower than on steel (< 0.41 ppm and about < 2.5 ppm, respectively). The CO₂ amount adsorbed (5.8 × 1019 CO₂ molecules) corresponds to about the fivefold monolayer adsorption, indicating that the effective surface exposed for adsorption is significantly larger than the geometric surface area. Adsorption/desorption effects were minimal for CH₄ and for CO but require further attention since they were only studied on one aluminium cylinder with a very low mole fraction. In the climate chamber, the cylinders were exposed to temperatures between −10 and +50 °C to determine the corresponding temperature coefficients of adsorption. Again, we found distinctly different values for CO₂, ranging from 0.0014 to 0.0184 ppm °C−¹ for steel cylinders and −0.0002 to −0.0003 ppm °C−¹ for aluminium cylinders. The reversed temperature dependence for aluminium cylinders points to significantly lower desorption energies than for steel cylinders and due to the small values, they might at least partly be influenced by temperature, permeation from/to sealing materials, and gas-consumption-induced pressure changes. Temperature coefficients for CH₄, CO, and H₂O adsorption were, within their error bands, insignificant. These results do indicate the need for careful selection and usage of gas cylinders for high-precision calibration purposes such as requested in trace gas applications.

Intervals for the assessment of measurement agreement: Similarities, differences, and consequences of incorrect interpretations

Several intervals have been proposed to quantify the agreement of two methods intended to measure the same quantity in the situation where only one measurement per method and subject is available. The limits of agreement are probably the most well-known among these intervals, which are all based on the differences between the two measurement methods. The different meanings of the intervals are not always properly recognized in applications. However, at least for small-to-moderate sample sizes, the differences will be substantial. This is illustrated both using the width of the intervals and on probabilistic scales related to the definitions of the intervals. In particular, for small-to-moderate sample sizes, it is shown that limits of agreement and prediction intervals should not be used to make statements about the distribution of the differences between the two measurement methods or about a plausible range for all future differences. Care should therefore be taken to ensure the correct choice of the interval for the intended interpretation.

Multiple imputation for missing continuous and dichotomous data: The effects of patterns of missingness and variable correlations on type I error with small samples

The purpose of this study is to investigate the effects of predictor variable correlations and patterns of missingness with dichotomous and/or continuous data in small samples when missing data is multiply imputed. Missing data of predictor variables is multiply imputed under three different multivariate models: the multivariate normal model for continuous data, the multinomial model for dichotomous data and the general location model for mixed dichotomous and continuous data. Subsequent to the multiple imputation process, Type I error rates of the regression coefficients obtained with logistic regression analysis are estimated under various conditions of correlation structure, sample size, type of data and patterns of missing data. The distributional properties of average mean, variance and correlations among the predictor variables are assessed after the multiple imputation process. ^ For continuous predictor data under the multivariate normal model, Type I error rates are generally within the nominal values with samples of size n = 100. Smaller samples of size n = 50 resulted in more conservative estimates (i.e., lower than the nominal value). Correlation and variance estimates of the original data are retained after multiple imputation with less than 50% missing continuous predictor data. For dichotomous predictor data under the multinomial model, Type I error rates are generally conservative, which in part is due to the sparseness of the data. The correlation structure for the predictor variables is not well retained on multiply-imputed data from small samples with more than 50% missing data with this model. For mixed continuous and dichotomous predictor data, the results are similar to those found under the multivariate normal model for continuous data and under the multinomial model for dichotomous data. With all data types, a fully-observed variable included with variables subject to missingness in the multiple imputation process and subsequent statistical analysis provided liberal (larger than nominal values) Type I error rates under a specific pattern of missing data. It is suggested that future studies focus on the effects of multiple imputation in multivariate settings with more realistic data characteristics and a variety of multivariate analyses, assessing both Type I error and power. ^