An operator formulation of the multiscale finite-volume method with correction function

The multiscale finite-volume (MSFV) method has been derived to efficiently solve large problems with spatially varying coefficients. The fine-scale problem is subdivided into local problems that can be solved separately and are coupled by a global problem. This algorithm, in consequence, shares some characteristics with two-level domain decomposition (DD) methods. However, the MSFV algorithm is different in that it incorporates a flux reconstruction step, which delivers a fine-scale mass conservative flux field without the need for iterating. This is achieved by the use of two overlapping coarse grids. The recently introduced correction function allows for a consistent handling of source terms, which makes the MSFV method a flexible algorithm that is applicable to a wide spectrum of problems. It is demonstrated that the MSFV operator, used to compute an approximate pressure solution, can be equivalently constructed by writing the Schur complement with a tangential approximation of a single-cell overlapping grid and incorporation of appropriate coarse-scale mass-balance equations.

Molecular identification of an endemic Alpine mammal, Apodemus alpicola, using a PCR-based RFLP method

The ability of a PCR-based restriction fragment length polymorphism (RFLP) analysis of the cytochrome b (mtDNA) to distinguish Apodemus alpicola from two other Apodemus species was investigated. The partial sequencing of the cytochrome b allowed the identification of one enzyme as being potentially diagnostic. This was supported by an analysis of 131 specimens previously identified using morphometric and/or allozymic data, indicating that the PCR-based RFLP method provides a rapid and reliable tool for distinguishing A. alpicola from its two co-occurring congenerics. The method is applicable to samples taken in the field for ecological studies, and could easily be adapted to the identification of museum samples.

A simple gas chromatography method for the analysis of monoethanolamine in air

A simple method determining airborne monoethanolamine has been developed. Monoethanolamine determination has traditionally been difficult due to analytical separation problems. Even in recent sophisticated methods, this difficulty remains as the major issue often resulting in time-consuming sample preparations. Impregnated glass fiber filters were used for sampling. Desorption of monoethanolamine was followed by capillary GC analysis and nitrogen phosphorous selective detection. Separation was achieved using a specific column for monoethanolamines (35% diphenyl and 65% dimethyl polysiloxane). The internal standard was quinoline. Derivatization steps were not needed. The calibration range was 0.5-80 μg/mL with a good correlation (R(2) = 0.996). Averaged overall precisions and accuracies were 4.8% and -7.8% for intraday (n = 30), and 10.5% and -5.9% for interday (n = 72). Mean recovery from spiked filters was 92.8% for the intraday variation, and 94.1% for the interday variation. Monoethanolamine on stored spiked filters was stable for at least 4 weeks at 5°C. This newly developed method was used among professional cleaners and air concentrations (n = 4) were 0.42 and 0.17 mg/m(3) for personal and 0.23 and 0.43 mg/m(3) for stationary measurements. The monoethanolamine air concentration method described here was simple, sensitive, and convenient both in terms of sampling and analytical analysis.

A comparative study on inter and intralaboratory reproducibility of renin measurement with a conventional enzymatic method and a new chemiluminescent assay of immunoreactive renin.

BACKGROUND: The activity of the renin-angiotensin system is usually evaluated as plasma renin activity (PRA, ngAI/ml per h) but the reproducibility of this enzymatic assay is notoriously scarce. We compared the inter and intralaboratory reproducibilities of PRA with those of a new automated chemiluminescent assay, which allows the direct quantification of immunoreactive renin [chemiluminescent immunoreactive renin (CLIR), microU/ml]. METHODS: Aliquots from six pool plasmas of patients with very low to very high PRA levels were measured in 12 centres with both the enzymatic and the direct assays. The same methods were applied to three control plasma preparations with known renin content. RESULTS: In pool plasmas, mean PRA values ranged from 0.14 +/- 0.08 to 18.9 +/- 4.1 ngAI/ml per h, whereas those of CLIR ranged from 4.2 +/- 1.7 to 436 +/- 47 microU/ml. In control plasmas, mean values of PRA and of CLIR were always within the expected range. Overall, there was a significant correlation between the two methods (r = 0.73, P < 0.01). Similar correlations were found in plasmas subdivided in those with low, intermediate and high PRA. However, the coefficients of variation among laboratories found for PRA were always higher than those of CLIR, ranging from 59.4 to 17.1% for PRA, and from 41.0 to 10.7% for CLIR (P < 0.01). Also, the mean intralaboratory variability was higher for PRA than for CLIR, being respectively, 8.5 and 4.5% (P < 0.01). CONCLUSION: The measurement of renin with the chemiluminescent method is a reliable alternative to PRA, having the advantage of a superior inter and intralaboratory reproducibility.

Kernel-based Mapping of Meteorological Fields in Complex Orography

Due to the advances in sensor networks and remote sensing technologies, the acquisition and storage rates of meteorological and climatological data increases every day and ask for novel and efficient processing algorithms. A fundamental problem of data analysis and modeling is the spatial prediction of meteorological variables in complex orography, which serves among others to extended climatological analyses, for the assimilation of data into numerical weather prediction models, for preparing inputs to hydrological models and for real time monitoring and short-term forecasting of weather.In this thesis, a new framework for spatial estimation is proposed by taking advantage of a class of algorithms emerging from the statistical learning theory. Nonparametric kernel-based methods for nonlinear data classification, regression and target detection, known as support vector machines (SVM), are adapted for mapping of meteorological variables in complex orography.With the advent of high resolution digital elevation models, the field of spatial prediction met new horizons. In fact, by exploiting image processing tools along with physical heuristics, an incredible number of terrain features which account for the topographic conditions at multiple spatial scales can be extracted. Such features are highly relevant for the mapping of meteorological variables because they control a considerable part of the spatial variability of meteorological fields in the complex Alpine orography. For instance, patterns of orographic rainfall, wind speed and cold air pools are known to be correlated with particular terrain forms, e.g. convex/concave surfaces and upwind sides of mountain slopes.Kernel-based methods are employed to learn the nonlinear statistical dependence which links the multidimensional space of geographical and topographic explanatory variables to the variable of interest, that is the wind speed as measured at the weather stations or the occurrence of orographic rainfall patterns as extracted from sequences of radar images. Compared to low dimensional models integrating only the geographical coordinates, the proposed framework opens a way to regionalize meteorological variables which are multidimensional in nature and rarely show spatial auto-correlation in the original space making the use of classical geostatistics tangled.The challenges which are explored during the thesis are manifolds. First, the complexity of models is optimized to impose appropriate smoothness properties and reduce the impact of noisy measurements. Secondly, a multiple kernel extension of SVM is considered to select the multiscale features which explain most of the spatial variability of wind speed. Then, SVM target detection methods are implemented to describe the orographic conditions which cause persistent and stationary rainfall patterns. Finally, the optimal splitting of the data is studied to estimate realistic performances and confidence intervals characterizing the uncertainty of predictions.The resulting maps of average wind speeds find applications within renewable resources assessment and opens a route to decrease the temporal scale of analysis to meet hydrological requirements. Furthermore, the maps depicting the susceptibility to orographic rainfall enhancement can be used to improve current radar-based quantitative precipitation estimation and forecasting systems and to generate stochastic ensembles of precipitation fields conditioned upon the orography.

A Multi-SNP Locus-Association Method Reveals a Substantial Fraction of the Missing Heritability.

There are many known examples of multiple semi-independent associations at individual loci; such associations might arise either because of true allelic heterogeneity or because of imperfect tagging of an unobserved causal variant. This phenomenon is of great importance in monogenic traits but has not yet been systematically investigated and quantified in complex-trait genome-wide association studies (GWASs). Here, we describe a multi-SNP association method that estimates the effect of loci harboring multiple association signals by using GWAS summary statistics. Applying the method to a large anthropometric GWAS meta-analysis (from the Genetic Investigation of Anthropometric Traits consortium study), we show that for height, body mass index (BMI), and waist-to-hip ratio (WHR), 3%, 2%, and 1%, respectively, of additional phenotypic variance can be explained on top of the previously reported 10% (height), 1.5% (BMI), and 1% (WHR). The method also permitted a substantial increase (by up to 50%) in the number of loci that replicate in a discovery-validation design. Specifically, we identified 74 loci at which the multi-SNP, a linear combination of SNPs, explains significantly more variance than does the best individual SNP. A detailed analysis of multi-SNPs shows that most of the additional variability explained is derived from SNPs that are not in linkage disequilibrium with the lead SNP, suggesting a major contribution of allelic heterogeneity to the missing heritability.

Chances and limits of method restriction: a detailed analysis of suicide methods in Switzerland.

The objective of this study was to estimate the potential of method restriction as a public health strategy in suicide prevention. Data from the Swiss Federal Statistical Office and the Swiss Institutes of Forensic Medicine from 2004 were gathered and categorized into suicide submethods according to accessibility to restriction of means. Of suicides in Switzerland, 39.2% are accessible to method restriction. The highest proportions were found in private weapons (13.2%), army weapons (10.4%), and jumps from hot-spots (4.6%). The presented method permits the estimation of the suicide prevention potential of a country by method restriction and the comparison of restriction potentials between suicide methods. In Switzerland, reduction of firearm suicides has the highest potential to reduce the total number of suicides.

Development and validation of a gas chromatography-negative chemical ionization tandem mass spectrometry method for the determination of ethyl glucuronide in hair and its application to forensic toxicology.

Ethyl glucuronide (EtG) is a minor and direct metabolite of ethanol. EtG is incorporated into the growing hair allowing retrospective investigation of chronic alcohol abuse. In this study, we report the development and the validation of a method using gas chromatography-negative chemical ionization tandem mass spectrometry (GC-NCI-MS/MS) for the quantification of EtG in hair. EtG was extracted from about 30 mg of hair by aqueous incubation and purified by solid-phase extraction (SPE) using mixed mode extraction cartridges followed by derivation with perfluoropentanoic anhydride (PFPA). The analysis was performed in the selected reaction monitoring (SRM) mode using the transitions m/z 347-->163 (for the quantification) and m/z 347-->119 (for the identification) for EtG, and m/z 352-->163 for EtG-d(5) used as internal standard. For validation, we prepared quality controls (QC) using hair samples taken post mortem from 2 subjects with a known history of alcoholism. These samples were confirmed by a proficiency test with 7 participating laboratories. The assay linearity of EtG was confirmed over the range from 8.4 to 259.4 pg/mg hair, with a coefficient of determination (r(2)) above 0.999. The limit of detection (LOD) was estimated with 3.0 pg/mg. The lower limit of quantification (LLOQ) of the method was fixed at 8.4 pg/mg. Repeatability and intermediate precision (relative standard deviation, RSD%), tested at 4 QC levels, were less than 13.2%. The analytical method was applied to several hair samples obtained from autopsy cases with a history of alcoholism and/or lesions caused by alcohol. EtG concentrations in hair ranged from 60 to 820 pg/mg hair.

Accuracy profile validation of a new analytical method for propane measurement using headspace-gas chromatography-mass spectrometry

Propane can be responsible for several types of lethal intoxication and explosions. Quantifying it would be very helpful to determine in some cases the cause of death. Some gas chromatography-mass spectrometry (GC-MS) methods of propane measurements do already exist. The main drawback of these GC-MS methods described in the literature is the absence of a specific propane internal standard necessary for accurate quantitative analysis. The main outcome of the following study was to provide an innovative Headspace-GC-MS method (HS-GC-MS) applicable to the routine determination of propane concentration in forensic toxicology laboratories. To date, no stable isotope of propane is commercially available. The development of an in situ generation of standards is thus presented. An internal-labeled standard gas (C3DH7) is generated in situ by the stoichiometric formation of propane by the reaction of deuterated water (D2O) with Grignard reagent propylmagnesium chloride (C3H7MgCl). The method aims to use this internal standard to quantify propane concentrations and, therefore, to obtain precise measurements. Consequently, a complete validation with an accuracy profile according to two different guidelines, the French Society of Pharmaceutical Sciences and Techniques (SFSTP) and the Gesellschaft für toxikologische und Forensische Chemie (GTFCh), is presented.

Predictive analysis and mapping of indoor radon concentrations in a complex environment using kernel estimation: an application to Switzerland.

PURPOSE: The aim of this study was to develop models based on kernel regression and probability estimation in order to predict and map IRC in Switzerland by taking into account all of the following: architectural factors, spatial relationships between the measurements, as well as geological information. METHODS: We looked at about 240,000 IRC measurements carried out in about 150,000 houses. As predictor variables we included: building type, foundation type, year of construction, detector type, geographical coordinates, altitude, temperature and lithology into the kernel estimation models. We developed predictive maps as well as a map of the local probability to exceed 300 Bq/m(3). Additionally, we developed a map of a confidence index in order to estimate the reliability of the probability map. RESULTS: Our models were able to explain 28% of the variations of IRC data. All variables added information to the model. The model estimation revealed a bandwidth for each variable, making it possible to characterize the influence of each variable on the IRC estimation. Furthermore, we assessed the mapping characteristics of kernel estimation overall as well as by municipality. Overall, our model reproduces spatial IRC patterns which were already obtained earlier. On the municipal level, we could show that our model accounts well for IRC trends within municipal boundaries. Finally, we found that different building characteristics result in different IRC maps. Maps corresponding to detached houses with concrete foundations indicate systematically smaller IRC than maps corresponding to farms with earth foundation. CONCLUSIONS: IRC mapping based on kernel estimation is a powerful tool to predict and analyze IRC on a large-scale as well as on a local level. This approach enables to develop tailor-made maps for different architectural elements and measurement conditions and to account at the same time for geological information and spatial relations between IRC measurements.

A treatment planning method for sequentially combining radiopharmaceutical therapy and external radiation therapy.

PURPOSE: Effective cancer treatment generally requires combination therapy. The combination of external beam therapy (XRT) with radiopharmaceutical therapy (RPT) requires accurate three-dimensional dose calculations to avoid toxicity and evaluate efficacy. We have developed and tested a treatment planning method, using the patient-specific three-dimensional dosimetry package 3D-RD, for sequentially combined RPT/XRT therapy designed to limit toxicity to organs at risk. METHODS AND MATERIALS: The biologic effective dose (BED) was used to translate voxelized RPT absorbed dose (D(RPT)) values into a normalized total dose (or equivalent 2-Gy-fraction XRT absorbed dose), NTD(RPT) map. The BED was calculated numerically using an algorithmic approach, which enabled a more accurate calculation of BED and NTD(RPT). A treatment plan from the combined Samarium-153 and external beam was designed that would deliver a tumoricidal dose while delivering no more than 50 Gy of NTD(sum) to the spinal cord of a patient with a paraspinal tumor. RESULTS: The average voxel NTD(RPT) to tumor from RPT was 22.6 Gy (range, 1-85 Gy); the maximum spinal cord voxel NTD(RPT) from RPT was 6.8 Gy. The combined therapy NTD(sum) to tumor was 71.5 Gy (range, 40-135 Gy) for a maximum voxel spinal cord NTD(sum) equal to the maximum tolerated dose of 50 Gy. CONCLUSIONS: A method that enables real-time treatment planning of combined RPT-XRT has been developed. By implementing a more generalized conversion between the dose values from the two modalities and an activity-based treatment of partial volume effects, the reliability of combination therapy treatment planning has been expanded.