On-line event detection by recursive dynamic principal component analysis and gas sensor arrays under drift conditions

Leakage detection is an important issue in many chemical sensing applications. Leakage detection hy thresholds suffers from important drawbacks when sensors have serious drifts or they are affected by cross-sensitivities. Here we present an adaptive method based in a Dynamic Principal Component Analysis that models the relationships between the sensors in the may. In normal conditions a certain variance distribution characterizes sensor signals. However, in the presence of a new source of variance the PCA decomposition changes drastically. In order to prevent the influence of sensor drifts the model is adaptive and it is calculated in a recursive manner with minimum computational effort. The behavior of this technique is studied with synthetic signals and with real signals arising by oil vapor leakages in an air compressor. Results clearly demonstrate the efficiency of the proposed method.

An improved method for measuring soil microbial activity by gas phase flow injection analysis

The rate of carbon dioxide production is commonly used as a measure of microbial activity in the soil. The traditional method of CO2 determination involves trapping CO2 in an alkali solution and then determining CO2 concentration indirectly by titration of the remaining alkali in the solution. This method is still commonly employed in laboratories throughout the world due to its relative simplicity and the fact that it does not require expensive, specific equipment. However, there are several drawbacks: the method is time-consuming, requires large amounts of chemicals and the consistency of results depends on the operator's skills. With this in mind, an improved method was developed to analyze CO2 captured in alkali traps, which is cheap and relatively simple, with a substantially shorter sample handling time and reproducibility equivalent to the traditional titration method. A comparison of the concentration values determined by gas phase flow injection analysis (GPFIA) and titration showed no significant difference (p > 0.05), but GPFIA has the advantage that only a tenth of the sample volume of the titration method is required. The GPFIA system does not require the purchase of new, costly equipment but the device was constructed from items commonly found in laboratories, with suggestions for alternative configurations for other detection units. Furthermore, GPFIA for CO2 analysis can be equally applied to samples obtained from either the headspace of microcosms or from a sampling chamber that allows CO2 to be released from alkali trapping solutions. The optimised GPFIA method was applied to analyse CO2 released from degrading hydrocarbons from a site contaminated by diesel spillage.

Performance of a reciprocal shaker in mechanical dispersion of soil samples for particle-size analysis

The dispersion of the samples in soil particle-size analysis is a fundamental step, which is commonly achieved with a combination of chemical agents and mechanical agitation. The purpose of this study was to evaluate the efficiency of a low-speed reciprocal shaker for the mechanical dispersion of soil samples of different textural classes. The particle size of 61 soil samples was analyzed in four replications, using the pipette method to determine the clay fraction and sieving to determine coarse, fine and total sand fractions. The silt content was obtained by difference. To evaluate the performance, the results of the reciprocal shaker (RSh) were compared with data of the same soil samples available in reports of the Proficiency testing for Soil Analysis Laboratories of the Agronomic Institute of Campinas (Prolab/IAC). The accuracy was analyzed based on the maximum and minimum values defining the confidence intervals for the particle-size fractions of each soil sample. Graphical indicators were also used for data comparison, based on dispersion and linear adjustment. The descriptive statistics indicated predominantly low variability in more than 90 % of the results for sand, medium-textured and clay samples, and for 68 % of the results for heavy clay samples, indicating satisfactory repeatability of measurements with the RSh. Medium variability was frequently associated with silt, followed by the fine sand fraction. The sensitivity analyses indicated an accuracy of 100 % for the three main separates (total sand, silt and clay), in all 52 samples of the textural classes heavy clay, clay and medium. For the nine sand soil samples, the average accuracy was 85.2 %; highest deviations were observed for the silt fraction. In relation to the linear adjustments, the correlation coefficients of 0.93 (silt) or > 0.93 (total sand and clay), as well as the differences between the angular coefficients and the unit < 0.16, indicated a high correlation between the reference data (Prolab/IAC) and results obtained with the RSh. In conclusion, the mechanical dispersion by the reciprocal shaker of soil samples of different textural classes was satisfactory. The results allowed recommending the use of the equipment at low agitation for particle size- analysis. The advantages of this Brazilian apparatus are its low cost, the possibility to simultaneously analyze a great number of samples using ordinary, easily replaceable glass or plastic bottles.

How to measure cortical folding from MR images: a step-by-step tutorial to compute local gyrification index.

Cortical folding (gyrification) is determined during the first months of life, so that adverse events occurring during this period leave traces that will be identifiable at any age. As recently reviewed by Mangin and colleagues(2), several methods exist to quantify different characteristics of gyrification. For instance, sulcal morphometry can be used to measure shape descriptors such as the depth, length or indices of inter-hemispheric asymmetry(3). These geometrical properties have the advantage of being easy to interpret. However, sulcal morphometry tightly relies on the accurate identification of a given set of sulci and hence provides a fragmented description of gyrification. A more fine-grained quantification of gyrification can be achieved with curvature-based measurements, where smoothed absolute mean curvature is typically computed at thousands of points over the cortical surface(4). The curvature is however not straightforward to comprehend, as it remains unclear if there is any direct relationship between the curvedness and a biologically meaningful correlate such as cortical volume or surface. To address the diverse issues raised by the measurement of cortical folding, we previously developed an algorithm to quantify local gyrification with an exquisite spatial resolution and of simple interpretation. Our method is inspired of the Gyrification Index(5), a method originally used in comparative neuroanatomy to evaluate the cortical folding differences across species. In our implementation, which we name local Gyrification Index (lGI(1)), we measure the amount of cortex buried within the sulcal folds as compared with the amount of visible cortex in circular regions of interest. Given that the cortex grows primarily through radial expansion(6), our method was specifically designed to identify early defects of cortical development. In this article, we detail the computation of local Gyrification Index, which is now freely distributed as a part of the FreeSurfer Software (http://surfer.nmr.mgh.harvard.edu/, Martinos Center for Biomedical Imaging, Massachusetts General Hospital). FreeSurfer provides a set of automated reconstruction tools of the brain's cortical surface from structural MRI data. The cortical surface extracted in the native space of the images with sub-millimeter accuracy is then further used for the creation of an outer surface, which will serve as a basis for the lGI calculation. A circular region of interest is then delineated on the outer surface, and its corresponding region of interest on the cortical surface is identified using a matching algorithm as described in our validation study(1). This process is repeatedly iterated with largely overlapping regions of interest, resulting in cortical maps of gyrification for subsequent statistical comparisons (Fig. 1). Of note, another measurement of local gyrification with a similar inspiration was proposed by Toro and colleagues(7), where the folding index at each point is computed as the ratio of the cortical area contained in a sphere divided by the area of a disc with the same radius. The two implementations differ in that the one by Toro et al. is based on Euclidian distances and thus considers discontinuous patches of cortical area, whereas ours uses a strict geodesic algorithm and include only the continuous patch of cortical area opening at the brain surface in a circular region of interest.

Clinal variation in a brown lemur (Eulemur spp.) hybrid zone: Combining morphological, genetic and climatic data to examine stability.

Studies of hybrid zones can inform our understanding of reproductive isolation and speciation. Two species of brown lemur (Eulemur rufifrons and E. cinereiceps) form an apparently stable hybrid zone in the Andringitra region of south-eastern Madagascar. The aim of this study was to identify factors that contribute to this stability. We sampled animals at 11 sites along a 90-km transect through the hybrid zone and examined variation in 26 microsatellites, the D-loop region of mitochondrial DNA, six pelage and nine morphological traits; we also included samples collected in more distant allopatric sites. Clines in these traits were noncoincident, and there was no increase in either inbreeding coefficients or linkage disequilibrium at the centre of the zone. These results could suggest that the hybrid zone is maintained by weak selection against hybrids, conforming to either the tension zone or geographical selection-gradient model. However, a closer examination of clines in pelage and microsatellites indicates that these clines are not sigmoid or stepped in shape but instead plateau at their centre. Sites within the hybrid zone also occur in a distinct habitat, characterized by greater seasonality in precipitation and lower seasonality in temperature. Together, these findings suggest that the hybrid zone may follow the bounded superiority model, with exogenous selection favouring hybrids within the transitional zone. These findings are noteworthy, as examples supporting the bounded superiority model are rare and may indicate a process of ecologically driven speciation without geographical isolation.

Multiple Kernel Learning of Environmental Data. Case study: Analysis and Mapping of Wind Fields

The paper presents the Multiple Kernel Learning (MKL) approach as a modelling and data exploratory tool and applies it to the problem of wind speed mapping. Support Vector Regression (SVR) is used to predict spatial variations of the mean wind speed from terrain features (slopes, terrain curvature, directional derivatives) generated at different spatial scales. Multiple Kernel Learning is applied to learn kernels for individual features and thematic feature subsets, both in the context of feature selection and optimal parameters determination. An empirical study on real-life data confirms the usefulness of MKL as a tool that enhances the interpretability of data-driven models.

Data Acquisition and Computer Plotting of Delamtect Data, HR-269, 1985

The overall system is designed to permit automatic collection of delamination field data for bridge decks. In addition to measuring and recording the data in the field, the system provides for transferring the recorded data to a personal computer for processing and plotting. This permits rapid turnaround from data collection to a finished plot of the results in a fraction of the time previously required for manual analysis of the analog data captured on a strip chart recorder. In normal operation the Delamtect provides an analog voltage for each of two channels which is proportional to the extent of any delamination. These voltages are recorded on a strip chart for later visual analysis. An event marker voltage, produced by a momentary push button on the handle, is also provided by the Delamtect and recorded on a third channel of the analog recorder.

Full-waveform inversion of cross-hole ground-penetrating radar data to characterize a gravel aquifer close to the Thur River, Switzerland

Cross-hole radar tomography is a useful tool for mapping shallow subsurface electrical properties viz. dielectric permittivity and electrical conductivity. Common practice is to invert cross-hole radar data with ray-based tomographic algorithms using first arrival traveltimes and first cycle amplitudes. However, the resolution of conventional standard ray-based inversion schemes for cross-hole ground-penetrating radar (GPR) is limited because only a fraction of the information contained in the radar data is used. The resolution can be improved significantly by using a full-waveform inversion that considers the entire waveform, or significant parts thereof. A recently developed 2D time-domain vectorial full-waveform crosshole radar inversion code has been modified in the present study by allowing optimized acquisition setups that reduce the acquisition time and computational costs significantly. This is achieved by minimizing the number of transmitter points and maximizing the number of receiver positions. The improved algorithm was employed to invert cross-hole GPR data acquired within a gravel aquifer (4-10 m depth) in the Thur valley, Switzerland. The simulated traces of the final model obtained by the full-waveform inversion fit the observed traces very well in the lower part of the section and reasonably well in the upper part of the section. Compared to the ray-based inversion, the results from the full-waveform inversion show significantly higher resolution images. At either side, 2.5 m distance away from the cross-hole plane, borehole logs were acquired. There is a good correspondence between the conductivity tomograms and the natural gamma logs at the boundary of the gravel layer and the underlying lacustrine clay deposits. Using existing petrophysical models, the inversion results and neutron-neutron logs are converted to porosity. Without any additional calibration, the values obtained for the converted neutron-neutron logs and permittivity results are very close and similar vertical variations can be observed. The full-waveform inversion provides in both cases additional information about the subsurface. Due to the presence of the water table and associated refracted/reflected waves, the upper traces are not well fitted and the upper 2 m in the permittivity and conductivity tomograms are not reliably reconstructed because the unsaturated zone is not incorporated into the inversion domain.

Concrete Pavement Mixture Design and Analysis (MDA): An Innovative Approach To Proportioning Concrete Mixtures, TPF-5(205), 2015

Mixture proportioning is routinely a matter of using a recipe based on a previously produced concrete, rather than adjusting the proportions based on the needs of the mixture and the locally available materials. As budgets grow tighter and increasing attention is being paid to sustainability metrics, greater attention is beginning to be focused on making mixtures that are more efficient in their usage of materials yet do not compromise engineering performance. Therefore, a performance-based mixture proportioning method is needed to provide the desired concrete properties for a given project specification. The proposed method should be user friendly, easy to apply in practice, and flexible in terms of allowing a wide range of material selection. The objective of this study is to further develop an innovative performance-based mixture proportioning method by analyzing the relationships between the selected mix characteristics and their corresponding effects on tested properties. The proposed method will provide step-by-step instructions to guide the selection of required aggregate and paste systems based on the performance requirements. Although the provided guidance in this report is primarily for concrete pavements, the same approach can be applied to other concrete applications as well.

An epidemiologic study to determine the prevalence of the HLA-B*5701 allele among HIV-positive patients in Europe.

OBJECTIVES: HLA-B*5701 is a major histocompatibility complex class I allele associated with an immunologically-mediated hypersensitivity reaction to abacavir. The objectives of this study were to evaluate HLA-B*5701 prevalence among European, HIV-1-infected patients and to compare the local and central laboratory screening results. METHODS: Data were combined from six multicentre, prospective studies involving 10 European countries in which HIV-1-infected patients (irrespective of treatment experience or previous HLA-B*5701 screening), >or=18 years of age, were evaluated for HLA-B*5701 carriage, determined by the central and local laboratory methods. RESULTS: A total of 9720 patients from 272 centres were included in the analysis. The overall estimate of HLA-B*5701 prevalence in Europe was 4.98%, with country-specific estimates ranging from 1.53 to 7.75%. HLA-B*5701 prevalence was highest in the self-reported white population (6.49%) and lowest in the black population (0.39%). Local laboratory results had a high specificity (99.9%) and sensitivity (99.2%) when compared with the central laboratory results. CONCLUSION: This study supports data from previous studies regarding the prevalence of HLA-B*5701 in the HIV population and the variation of HLA-B*5701 prevalence between different racial groups. The high specificity and sensitivity of local laboratory results, suggests that clinicians can be confident in using local laboratories for pretreatment HLA-B*5701 screening. However, it is essential that local laboratories participate in HLA-B*5701-specific quality assurance programs to maintain 100% sensitivity. In HIV-infected patients, pretreatment HLA-B*5701 screening may allow more informed decisions regarding abacavir use and has the potential to significantly reduce the frequency of abacavir-related hypersensitivity reactions and costs associated with managing these reactions.

Stochastic inversion of tracer test and electrical geophysical data to estimate hydraulic conductivities.

Quantifying the spatial configuration of hydraulic conductivity (K) in heterogeneous geological environments is essential for accurate predictions of contaminant transport, but is difficult because of the inherent limitations in resolution and coverage associated with traditional hydrological measurements. To address this issue, we consider crosshole and surface-based electrical resistivity geophysical measurements, collected in time during a saline tracer experiment. We use a Bayesian Markov-chain-Monte-Carlo (McMC) methodology to jointly invert the dynamic resistivity data, together with borehole tracer concentration data, to generate multiple posterior realizations of K that are consistent with all available information. We do this within a coupled inversion framework, whereby the geophysical and hydrological forward models are linked through an uncertain relationship between electrical resistivity and concentration. To minimize computational expense, a facies-based subsurface parameterization is developed. The Bayesian-McMC methodology allows us to explore the potential benefits of including the geophysical data into the inverse problem by examining their effect on our ability to identify fast flowpaths in the subsurface, and their impact on hydrological prediction uncertainty. Using a complex, geostatistically generated, two-dimensional numerical example representative of a fluvial environment, we demonstrate that flow model calibration is improved and prediction error is decreased when the electrical resistivity data are included. The worth of the geophysical data is found to be greatest for long spatial correlation lengths of subsurface heterogeneity with respect to wellbore separation, where flow and transport are largely controlled by highly connected flowpaths.

GacS sensor domains pertinent to the regulation of exoproduct formation and to the biocontrol potential of Pseudomonas fluorescens CHA0.

In the root-colonizing biocontrol strain CHA0 of Pseudomonas fluorescens, cell density-dependent synthesis of extracellular, plant-beneficial secondary metabolites and enzymes is positively regulated by the GacS/GacA two-component system. Mutational analysis of the GacS sensor kinase using improved single-copy vectors showed that inactivation of each of the three conserved phosphate acceptor sites caused an exoproduct null phenotype (GacS-), whereas deletion of the periplasmic loop domain had no significant effect on the expression of exoproduct genes. Strain CHA0 is known to synthesize a solvent-extractable extracellular signal that advances and enhances the expression of exoproduct genes during the transition from exponential to stationary growth phase when maximal exoproduct formation occurs. Mutational inactivation of either GacS or its cognate response regulator GacA abolished the strain's response to added signal. Deletion of the linker domain of the GacS sensor kinase caused signal-independent, strongly elevated expression of exoproduct genes at low cell densities. In contrast to the wild-type strain CHA0, the gacS linker mutant and a gacS null mutant were unable to protect tomato plants from crown and root rot caused by Fusarium oxysporum f. sp. radicis-lycopersici in a soil-less microcosm, indicating that, at least in this plant-pathogen system, there is no advantage in using a signal-independent biocontrol strain.

Bayesian Markov-chain-Monte-Carlo inversion of time-lapse cross hole ground-penetrating radar data to characterize the vadose zone at the Arrenaes field site, Denmark

The ground-penetrating radar (GPR) geophysical method has the potential to provide valuable information on the hydraulic properties of the vadose zone because of its strong sensitivity to soil water content. In particular, recent evidence has suggested that the stochastic inversion of crosshole GPR traveltime data can allow for a significant reduction in uncertainty regarding subsurface van Genuchten-Mualem (VGM) parameters. Much of the previous work on the stochastic estimation of VGM parameters from crosshole GPR data has considered the case of steady-state infiltration conditions, which represent only a small fraction of practically relevant scenarios. We explored in detail the dynamic infiltration case, specifically examining to what extent time-lapse crosshole GPR traveltimes, measured during a forced infiltration experiment at the Arreneas field site in Denmark, could help to quantify VGM parameters and their uncertainties in a layered medium, as well as the corresponding soil hydraulic properties. We used a Bayesian Markov-chain-Monte-Carlo inversion approach. We first explored the advantages and limitations of this approach with regard to a realistic synthetic example before applying it to field measurements. In our analysis, we also considered different degrees of prior information. Our findings indicate that the stochastic inversion of the time-lapse GPR data does indeed allow for a substantial refinement in the inferred posterior VGM parameter distributions compared with the corresponding priors, which in turn significantly improves knowledge of soil hydraulic properties. Overall, the results obtained clearly demonstrate the value of the information contained in time-lapse GPR data for characterizing vadose zone dynamics.

Growth promoting signaling by tenascin-C [corrected].

Tenascin-C is an adhesion-modulating extracellular matrix molecule that is highly expressed in tumor stroma and stimulates tumor cell proliferation. Adhesion of T98G glioblastoma cells to a fibronectin substratum is inhibited by tenascin-C. To address the mechanism of action, we performed a RNA expression analysis of T89G cells grown in the presence or absence of tenascin-C and found that tenascin-C down-regulates tropomyosin-1. Upon overexpression of tropomyosin-1, cell spreading on a fibronectin/tenascin-C substratum was restored, indicating that tenascin-C destabilizes actin stress fibers through down-regulation of tropomyosin-1. Tenascin-C also increased the expression of the endothelin receptor type A and stimulated the corresponding mitogen-activated protein kinase signaling pathway, which triggers extracellular signal-regulated kinase 1/2 phosphorylation and c-Fos expression. Tenascin-C additionally caused down-regulation of the Wnt inhibitor Dickkopf 1. In consequence, Wnt signaling was enhanced through stabilization of beta-catenin and stimulated the expression of the beta-catenin target Id2. Finally, our in vivo data derived from astrocytoma tissue arrays link increased tenascin-C and Id2 expression with high malignancy. Because increased endothelin and Wnt signaling, as well as reduced tropomyosin-1 expression, are closely linked to transformation and tumorigenesis, we suggest that tenascin-C specifically modulates these signaling pathways to enhance proliferation of glioma cells.

Development of data sheets for statistical evaluation of fatigue data

To enable a mathematically and physically sound execution of the fatigue test and a correct interpretation of its results, statistical evaluation methods are used to assist in the analysis of fatigue testing data. The main objective of this work is to develop step-by-stepinstructions for statistical analysis of the laboratory fatigue data. The scopeof this project is to provide practical cases about answering the several questions raised in the treatment of test data with application of the methods and formulae in the document IIW-XIII-2138-06 (Best Practice Guide on the Statistical Analysis of Fatigue Data). Generally, the questions in the data sheets involve some aspects: estimation of necessary sample size, verification of the statistical equivalence of the collated sets of data, and determination of characteristic curves in different cases. The series of comprehensive examples which are given in this thesis serve as a demonstration of the various statistical methods to develop a sound procedure to create reliable calculation rules for the fatigue analysis.