Data-driven topo-climatic mapping with machine learning methods

Automatic environmental monitoring networks enforced by wireless communication technologies provide large and ever increasing volumes of data nowadays. The use of this information in natural hazard research is an important issue. Particularly useful for risk assessment and decision making are the spatial maps of hazard-related parameters produced from point observations and available auxiliary information. The purpose of this article is to present and explore the appropriate tools to process large amounts of available data and produce predictions at fine spatial scales. These are the algorithms of machine learning, which are aimed at non-parametric robust modelling of non-linear dependencies from empirical data. The computational efficiency of the data-driven methods allows producing the prediction maps in real time which makes them superior to physical models for the operational use in risk assessment and mitigation. Particularly, this situation encounters in spatial prediction of climatic variables (topo-climatic mapping). In complex topographies of the mountainous regions, the meteorological processes are highly influenced by the relief. The article shows how these relations, possibly regionalized and non-linear, can be modelled from data using the information from digital elevation models. The particular illustration of the developed methodology concerns the mapping of temperatures (including the situations of Föhn and temperature inversion) given the measurements taken from the Swiss meteorological monitoring network. The range of the methods used in the study includes data-driven feature selection, support vector algorithms and artificial neural networks.

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.

Transcranial direct current stimulation for the treatment of focal hand dystonia.

The treatment of writer's cramp, a task-specific focal hand dystonia, needs new approaches. A deficiency of inhibition in the motor cortex might cause writer's cramp. Transcranial direct current stimulation modulates cortical excitability and may provide a therapeutic alternative. In this randomized, double-blind, sham-controlled study, we investigated the efficacy of cathodal stimulation of the contralateral motor cortex in 3 sessions in 1 week. Assessment over a 2-week period included clinical scales, subjective ratings, kinematic handwriting analysis, and neurophysiological evaluation. Twelve patients with unilateral dystonic writer's cramp were investigated; 6 received transcranial direct current and 6 sham stimulation. Cathodal transcranial direct current stimulation had no favorable effects on clinical scales and failed to restore normal handwriting kinematics and cortical inhibition. Subjective worsening remained unexplained, leading to premature study termination. Repeated sessions of cathodal transcranial direct current stimulation of the motor cortex yielded no favorable results supporting a therapeutic potential in writer's cramp.

Direct Thy-1/alphaVbeta3 integrin interaction mediates neuron to astrocyte communication.

Thy-1 is an abundant neuronal glycoprotein of poorly defined function. We recently provided evidence indicating that Thy-1 clusters a beta3-containing integrin in astrocytes to induce tyrosine phosphorylation, RhoA activation and the formation of focal adhesions and stress fibers. To date, the alpha subunit partner of beta3 integrin in DI TNC1 astrocytes is unknown. Similarly, the ability of neuronal, membrane-bound Thy-1 to trigger astrocyte signaling via integrin engagement remains speculation. Here, evidence that alphav forms an alphavbeta3 heterodimer in DI TNC1 astrocytes was obtained. In neuron-astrocyte association assays, the presence of either anti-alphav or anti-beta3 integrin antibodies reduced cell-cell interaction demonstrating the requirement of both integrin subunits for this association. Moreover, anti-Thy-1 antibodies blocked stimulation of astrocytes by neurons but not the binding of these two cell types. Thus, neuron-astrocyte association involved binding between molecular components in addition to the Thy-1-integrin; however, the signaling events leading to focal adhesion formation in astrocytes depended exclusively on the latter interaction. Additionally, wild-type (RLD) but not mutated (RLE) Thy-1 was shown to directly interact with alphavbeta3 integrin by Surface Plasmon Resonance analysis. This interaction was promoted by divalent cations and was species-independent. Together, these results demonstrate that the alphavbeta3 integrin heterodimer interacts directly with Thy-1 present on neuronal cells to stimulate astrocytes.

Assessing the possible direct effect of birth weight on childhood blood pressure : a sensitivity analysis.

To estimate the possible direct effect of birth weight on blood pressure, it is conventional to condition on the mediator, current weight. Such conditioning can induce bias. Our aim was to assess the potential biasing effect of U, an unmeasured common cause of current weight and blood pressure, on the estimate of the controlled direct effect of birth weight on blood pressure, with the help of sensitivity analyses. We used data from a school-based study conducted in Switzerland in 2005-2006 (n = 3,762; mean age = 12.3 years). A small negative association was observed between birth weight and systolic blood pressure (linear regression coefficient βbw = -0.3 mmHg/kg, 95% confidence interval: -0.9, 0.3). The association was strengthened upon adjustment for current weight (βbw|C = -1.5 mmHg/kg, 95% confidence interval: -2.1, -0.9). Sensitivity analyses revealed that the negative conditional association was explained by U only if U was relatively strongly associated with blood pressure and if there was a large difference in the prevalence of U between low-birth weight and normal-birth weight children. This weakens the hypothesis that the negative relationship between birth weight and blood pressure arises only from collider-stratification bias induced by conditioning on current weight.

JARID2 is a direct target of the PAX3-FOXO1 fusion protein and inhibits myogenic differentiation of rhabdomyosarcoma cells.

Rhabdomyosarcomas (RMS) are the most frequent soft-tissue sarcoma in children and characteristically show features of developing skeletal muscle. The alveolar subtype is frequently associated with a PAX3-FOXO1 fusion protein that is known to contribute to the undifferentiated myogenic phenotype of RMS cells. Histone methylation of lysine residues controls developmental processes in both normal and malignant cell contexts. Here we show that JARID2, which encodes a protein known to recruit various complexes with histone-methylating activity to their target genes, is significantly overexpressed in RMS with PAX3-FOXO1 compared with the fusion gene-negative RMS (t-test; P < 0.0001). Multivariate analyses showed that higher JARID2 levels are also associated with metastases at diagnosis, independent of fusion gene status and RMS subtype (n = 120; P = 0.039). JARID2 levels were altered by silencing or overexpressing PAX3-FOXO1 in RMS cell lines with and without the fusion gene, respectively. Consistent with this, we demonstrated that JARID2 is a direct transcriptional target of the PAX3-FOXO1 fusion protein. Silencing JARID2 resulted in reduced cell proliferation coupled with myogenic differentiation, including increased expression of Myogenin (MYOG) and Myosin Light Chain (MYL1) in RMS cell lines representative of both the alveolar and embryonal subtypes. Induced myogenic differentiation was associated with a decrease in JARID2 levels and this phenotype could be rescued by overexpressing JARID2. Furthermore, we that showed JARID2 binds to and alters the methylation status of histone H3 lysine 27 in the promoter regions of MYOG and MYL1 and that the interaction of JARID2 at these promoters is dependent on EED, a core component of the polycomb repressive complex 2 (PRC2). Therefore, JARID2 is a downstream effector of PAX3-FOXO1 that maintains an undifferentiated myogenic phenotype that is characteristic of RMS. JARID2 and other components of PRC2 may represent novel therapeutic targets for treating RMS patients.

Direct evidence for the existence of dairying farms in prehistoric Central Europe (4th millennium BC)

The molecular and isotopic chemistry of organic residues from archaeological potsherds was used to obtain further insight into the dietary trends and economies at the Constance lake-shore Neolithic settlements. The archaeological organic residues from the Early Late Neolithic (3922-3902 BC) site Hornstaad-Hornle IA/Germany are, at present, the oldest archaeological samples analysed at the Institute of Mineralogy and Geochemistry of the University of Lausanne. The approach includes 13C/12C and 15N/14N ratios of the bulk organic residues, fatty acids distribution and 13C/12C ratios of individual fatty acids. The results are compared with those obtained from the over 500 years younger Neolithic (3384-3370 BC) settlement of Arbon Bleiche 3/Switzerland and with samples of modern vegetable oils and fat of animals that have been fed exclusively on C3 forage grasses. The overall fatty acid composition (C9 to C24 range, maximizing at C14 and C16), the bulk 13C/12C and 15N/14N ratios (delta13C, delta15N) and the 13C/12C ratios of palmitic (C16:0), stearic (C18:0) and oleic acids (C18:1) of the organic residues indicate that most of the studied samples (25 from 47 samples and 5 from 41 in the delta13C18:0 vs. delta13C16:0 and delta13C18:0 vs. delta13C18:1 diagrams, respectively) from Hornstaad-Hornle IA and Arbon Bleiche 3 sherds contain fat residues of pre-industrial ruminant milk, and young suckling calf/lamb adipose. These data provide direct proof of milk and meat (mainly from young suckling calves) consumption and farming practices for a sustainable dairying in Neolithic villages in central Europe around 4000 BC.dagger

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.

Direct comparison of 3D spiral vs. Cartesian gradient-echo coronary magnetic resonance angiography.

While 3D thin-slab coronary magnetic resonance angiography (MRA) has traditionally been performed using a Cartesian acquisition scheme, spiral k-space data acquisition offers several potential advantages. However, these strategies have not been directly compared in the same subjects using similar methodologies. Thus, in the present study a comparison was made between 3D coronary MRA using Cartesian segmented k-space gradient-echo and spiral k-space data acquisition schemes. In both approaches the same spatial resolution was used and data were acquired during free breathing using navigator gating and prospective slice tracking. Magnetization preparation (T(2) preparation and fat suppression) was applied to increase the contrast. For spiral imaging two different examinations were performed, using one or two spiral interleaves, during each R-R interval. Spiral acquisitions were found to be superior to the Cartesian scheme with respect to the signal-to-noise ratio (SNR) and contrast-to-noise-ratio (CNR) (both P < 0.001) and image quality. The single spiral per R-R interval acquisition had the same total scan duration as the Cartesian acquisition, but the single spiral had the best image quality and a 2.6-fold increase in SNR. The double-interleaf spiral approach showed a 50% reduction in scanning time, a 1.8-fold increase in SNR, and similar image quality when compared to the standard Cartesian approach. Spiral 3D coronary MRA appears to be preferable to the Cartesian scheme. The increase in SNR may be "traded" for either shorter scanning times using multiple consecutive spiral interleaves, or for enhanced spatial resolution.

Direct numerical simulations of interface dynamics to link capillary pressure and total surface energy

The flow of two immiscible fluids through a porous medium depends on the complex interplay between gravity, capillarity, and viscous forces. The interaction between these forces and the geometry of the medium gives rise to a variety of complex flow regimes that are difficult to describe using continuum models. Although a number of pore-scale models have been employed, a careful investigation of the macroscopic effects of pore-scale processes requires methods based on conservation principles in order to reduce the number of modeling assumptions. In this work we perform direct numerical simulations of drainage by solving Navier-Stokes equations in the pore space and employing the Volume Of Fluid (VOF) method to track the evolution of the fluid-fluid interface. After demonstrating that the method is able to deal with large viscosity contrasts and model the transition from stable flow to viscous fingering, we focus on the macroscopic capillary pressure and we compare different definitions of this quantity under quasi-static and dynamic conditions. We show that the difference between the intrinsic phase-average pressures, which is commonly used as definition of Darcy-scale capillary pressure, is subject to several limitations and it is not accurate in presence of viscous effects or trapping. In contrast, a definition based on the variation of the total surface energy provides an accurate estimate of the macroscopic capillary pressure. This definition, which links the capillary pressure to its physical origin, allows a better separation of viscous effects and does not depend on the presence of trapped fluid clusters.

The direct peroxisome proliferator-activated receptor target fasting-induced adipose factor (FIAF/PGAR/ANGPTL4) is present in blood plasma as a truncated protein that is increased by fenofibrate treatment.

The fasting-induced adipose factor (FIAF, ANGPTL4, PGAR, HFARP) was previously identified as a novel adipocytokine that was up-regulated by fasting, by peroxisome proliferator-activated receptor agonists, and by hypoxia. To further characterize FIAF, we studied regulation of FIAF mRNA and protein in liver and adipose cell lines as well as in human and mouse plasma. Expression of FIAF mRNA was up-regulated by peroxisome proliferator-activated receptor alpha (PPARalpha) and PPARbeta/delta agonists in rat and human hepatoma cell lines and by PPARgamma and PPARbeta/delta agonists in mouse and human adipocytes. Transactivation, chromatin immunoprecipitation, and gel shift experiments identified a functional PPAR response element within intron 3 of the FIAF gene. At the protein level, in human and mouse blood plasma, FIAF was found to be present both as the native protein and in a truncated form. Differentiation of mouse 3T3-L1 adipocytes was associated with the production of truncated FIAF, whereas in human white adipose tissue and SGBS adipocytes, only native FIAF could be detected. Interestingly, truncated FIAF was produced by human liver. Treatment with fenofibrate, a potent PPARalpha agonist, markedly increased plasma levels of truncated FIAF, but not native FIAF, in humans. Levels of both truncated and native FIAF showed marked interindividual variation but were not associated with body mass index and were not influenced by prolonged semistarvation. Together, these data suggest that FIAF, similar to other adipocytokines such as adiponectin, may partially exert its function via a truncated form.