Toward on-the-fly quantum mechanical/molecular mechanical (QM/MM) docking: development and benchmark of a scoring function.

We address the challenges of treating polarization and covalent interactions in docking by developing a hybrid quantum mechanical/molecular mechanical (QM/MM) scoring function based on the semiempirical self-consistent charge density functional tight-binding (SCC-DFTB) method and the CHARMM force field. To benchmark this scoring function within the EADock DSS docking algorithm, we created a publicly available dataset of high-quality X-ray structures of zinc metalloproteins ( http://www.molecular-modelling.ch/resources.php ). For zinc-bound ligands (226 complexes), the QM/MM scoring yielded a substantially improved success rate compared to the classical scoring function (77.0% vs 61.5%), while, for allosteric ligands (55 complexes), the success rate remained constant (49.1%). The QM/MM scoring significantly improved the detection of correct zinc-binding geometries and improved the docking success rate by more than 20% for several important drug targets. The performance of both the classical and the QM/MM scoring functions compare favorably to the performance of AutoDock4, AutoDock4Zn, and AutoDock Vina.

New features of the layer-by-layer deposition of microcrystalline silicon films revealed by spectroscopic ellipsometry and high resolution transmission electron microscopy

Spectroscopic ellipsometry and high resolution transmission electron microscopy have been used to characterize microcrystalline silicon films. We obtain an excellent agreement between the multilayer model used in the analysis of the optical data and the microscopy measurements. Moreover, thanks to the high resolution achieved in the microscopy measurements and to the improved optical models, two new features of the layer-by-layer deposition of microcrystalline silicon have been detected: i) the microcrystalline films present large crystals extending from the a-Si:H substrate to the film surface, despite the sequential process in the layer-by-layer deposition; and ii) a porous layer exists between the amorphous silicon substrate and the microcrystalline silicon film.

Architectural characterization of a delta-front reservoir analogue combining ground penetrating radar and electrical resistivity tomography: Roda Sandstone (Lower Eocene, Graus-Tremp basin, Spain)

Three-dimensional reconstruction of reservoir analogues can be improved combining data from different geophysical methods. Ground Penetrating Radar (GPR) and Electrical Resistivity Tomography (ERT) data are valuable tools, since they provide subsurface information from internal architecture and facies distribution of sedimentary rock bodies, enabling the upgrading of depositional models and heterogeneity reconstruction. The Lower Eocene Roda Sandstone is a well-known deltaic complex widely studied as a reservoir analogue that displays a series of sandstone wedges with a general NE to SW progradational trend. To provide a better understanding of internal heterogeneity of a 10m-thick progradational delta-front sandstone unit, 3D GPR data were acquired. In addition, common midpoints (CMP) to measure the sandstone subsoil velocity, test profiles with different frequency antennas (25, 50 and 100MHz) and topographic data for subsequent correction in the geophysical data were also obtained. Three ERT profiles were also acquired to further constrain GPR analysis. These geophysical results illustrate the geometry of reservoir analogue heterogeneities both depositional and diagenetic in nature, improving and complementing previous outcrop-derived data. GPR interpretation using radar stratigraphy principles and attributes analysis provided: 1)tridimensional geometry of major stratigraphic surfaces that define four units in the GPR Prism, 2) image the internal architecture of the units and their statistical study of azimuth and dips, useful for a quick determination of paleocurrent directions. These results were used to define the depositional architecture of the progradational sandbody that shows an arrangement in very-high-frequency sequences characterized by clockwise paleocurrent variations and decrease of the sedimentary flow, similar to those observed at a greater scale in the same system. This high-frequency sequential arrangement has been attributed to the autocyclic dynamics of a supply-dominated delta- front where fluvial and tidal currents are in competition. The resistivity models enhanced the viewing of reservoir quality associated with cement distribution caused by depositional and early diagenetic processes related to the development of transgressive and regressive systems tracts in igh-frequency sequences.

A novel set of DIP-STR markers for improved analysis of challenging DNA mixtures.

Currently available molecular biology tools allow forensic scientists to characterize DNA evidence found at crime scenes for a large variety of samples, including those of limited quantity and quality, and achieve high levels of individualization. Yet, standard forensic markers provide limited or no results when applied to mixed DNA samples where the contributors are present in very different proportions (unbalanced DNA mixtures). This becomes an issue mostly for the analysis of trace samples collected on the victim or from touched objects. To this end, we recently proposed an innovative type of genetic marker, named DIP-STR that relies on pairing deletion/insertion polymorphisms (DIP) with standard short tandem repeats (STR). This novel compound marker allows detection of the minor DNA contributor in a DNA mixture of any gender and cellular origin with unprecedented resolution (beyond a DNA ratio of 1:1000). To provide a novel analytical tool useful in practice to common forensic laboratories, this article describes the first set of 10 DIP-STR markers selected according to forensic technical standards. The novel DIP-STR regions are short (between 146 and 271 bp), include only highly polymorphic tri-, tetra- and pentanucleotide tandem repeats and are located on different chromosomes or chromosomal arms to provide statistically independent results. This novel set of DIP-STR can target the amplification of 0.03-0.1 ng of DNA when mixed with a 1000-fold excess of major DNA. DIP-STR relative allele frequencies are estimated based on a survey of 103 Swiss individuals. Finally, this study provides an estimate of the occurrence of informative alleles and a calculation of the corresponding random match probability of the detected minor DIP-STR genotype assessed across 10,506 pairwise conceptual mixtures.

New kernel functions and learning methods for text and data mining

Recent advances in machine learning methods enable increasingly the automatic construction of various types of computer assisted methods that have been difficult or laborious to program by human experts. The tasks for which this kind of tools are needed arise in many areas, here especially in the fields of bioinformatics and natural language processing. The machine learning methods may not work satisfactorily if they are not appropriately tailored to the task in question. However, their learning performance can often be improved by taking advantage of deeper insight of the application domain or the learning problem at hand. This thesis considers developing kernel-based learning algorithms incorporating this kind of prior knowledge of the task in question in an advantageous way. Moreover, computationally efficient algorithms for training the learning machines for specific tasks are presented. In the context of kernel-based learning methods, the incorporation of prior knowledge is often done by designing appropriate kernel functions. Another well-known way is to develop cost functions that fit to the task under consideration. For disambiguation tasks in natural language, we develop kernel functions that take account of the positional information and the mutual similarities of words. It is shown that the use of this information significantly improves the disambiguation performance of the learning machine. Further, we design a new cost function that is better suitable for the task of information retrieval and for more general ranking problems than the cost functions designed for regression and classification. We also consider other applications of the kernel-based learning algorithms such as text categorization, and pattern recognition in differential display. We develop computationally efficient algorithms for training the considered learning machines with the proposed kernel functions. We also design a fast cross-validation algorithm for regularized least-squares type of learning algorithm. Further, an efficient version of the regularized least-squares algorithm that can be used together with the new cost function for preference learning and ranking tasks is proposed. In summary, we demonstrate that the incorporation of prior knowledge is possible and beneficial, and novel advanced kernels and cost functions can be used in algorithms efficiently.

Respiratory health effects of fifteen years of improved collective protection in a wheat-processing worker population.

INTRODUCTION: Occupational exposure to grain dust causes respiratory symptoms and pathologies. To decrease these effects, major changes have occurred in the grain processing industry in the last twenty years. However, there are no data on the effects of these changes on workers' respiratory health. OBJECTIVES: The aim of this study was to evaluate the respiratory health of grain workers and farmers involved in different steps of the processing industry of wheat, the most frequently used cereal in Europe, fifteen years after major improvements in collective protective equipment due to mechanisation. MATERIALS AND METHOD: Information on estimated personal exposure to wheat dust was collected from 87 workers exposed to wheat dust and from 62 controls. Lung function (FEV1, FVC, and PEF), exhaled nitrogen monoxide (FENO) and respiratory symptoms were assessed after the period of highest exposure to wheat during the year. Linear regression models were used to explore the associations between exposure indices and respiratory effects. RESULTS: Acute symptoms - cough, sneezing, runny nose, scratchy throat - were significantly more frequent in exposed workers than in controls. Increased mean exposure level, increased cumulative exposure and chronic exposure to more than 6 mg.m (-3) of inhaled wheat dust were significantly associated with decreased spirometric parameters, including FEV1 and PEF (40 ml and 123 ml.s (-1) ), FEV1 and FVC (0.4 ml and 0.5 ml per 100 h.mg.m (-3) ), FEV1 and FVC (20 ml and 20 ml per 100 h at >6 mg.m (-3) ). However, no increase in FENO was associated with increased exposure indices. CONCLUSIONS: The lung functions of wheat-related workers are still affected by their cumulative exposure to wheat dust, despite improvements in the use of collective protective equipment.

Development of phase retrieval algorithm and techniques for optical spectrum analysis

Coherent anti-Stokes Raman scattering is the powerful method of laser spectroscopy in which significant successes are achieved. However, the non-linear nature of CARS complicates the analysis of the received spectra. The objective of this Thesis is to develop a new phase retrieval algorithm for CARS. It utilizes the maximum entropy method and the new wavelet approach for spectroscopic background correction of a phase function. The method was developed to be easily automated and used on a large number of spectra of different substances.. The algorithm was successfully tested on experimental data.

Undergraduate palliative care teaching in Swiss medical faculties: a nationwide survey and improved learning objectives.

BACKGROUND: In 2007, a first survey on undergraduate palliative care teaching in Switzerland has revealed major heterogeneity of palliative care content, allocation of hours and distribution throughout the 6 year curriculum in Swiss medical faculties. This second survey in 2012/13 has been initiated as part of the current Swiss national strategy in palliative care (2010 - 2015) to serve as a longitudinal monitoring instrument and as a basis for redefinition of palliative care learning objectives and curriculum planning in our country. METHODS: As in 2007, a questionnaire was sent to the deans of all five medical faculties in Switzerland in 2012. It consisted of eight sections: basic background information, current content and hours in dedicated palliative care blocks, current palliative care content in other courses, topics related to palliative care presented in other courses, recent attempts at improving palliative care content, palliative care content in examinations, challenges, and overall summary. Content analysis was performed and the results matched with recommendations from the EAPC for undergraduate training in palliative medicine as well as with recommendations from overseas countries. RESULTS: There is a considerable increase in palliative care content, academic teaching staff and hours in all medical faculties compared to 2007. No Swiss medical faculty reaches the range of 40 h dedicated specifically to palliative care as recommended by the EAPC. Topics, teaching methods, distribution throughout different years and compulsory attendance still differ widely. Based on these results, the official Swiss Catalogue of Learning Objectives (SCLO) was complemented with 12 new learning objectives for palliative and end of life care (2013), and a national basic script for palliative care was published (2015). CONCLUSION: Performing periodic surveys of palliative care teaching at national medical faculties has proven to be a useful tool to adapt the national teaching framework and to improve the recognition of palliative medicine as an integral part of medical training.

Efficient total variation algorithm for fetal MRI reconstruction

Fetal MRI reconstruction aims at finding a high-resolution image given a small set of low-resolution images. It is usually modeled as an inverse problem where the regularization term plays a central role in the reconstruction quality. Literature has considered several regularization terms s.a. Dirichlet/Laplacian energy [1], Total Variation (TV)based energies [2,3] and more recently non-local means [4]. Although TV energies are quite attractive because of their ability in edge preservation, standard explicit steepest gradient techniques have been applied to optimize fetal-based TV energies. The main contribution of this work lies in the introduction of a well-posed TV algorithm from the point of view of convex optimization. Specifically, our proposed TV optimization algorithm for fetal reconstruction is optimal w.r.t. the asymptotic and iterative convergence speeds O(1/n(2)) and O(1/root epsilon), while existing techniques are in O(1/n) and O(1/epsilon). We apply our algorithm to (1) clinical newborn data, considered as ground truth, and (2) clinical fetal acquisitions. Our algorithm compares favorably with the literature in terms of speed and accuracy.

Question Waves: A multicast query routing algorithm for social search

This paper describes Question Waves, an algorithm that can be applied to social search protocols, such as Asknext or Sixearch. In this model, the queries are propagated through the social network, with faster propagation through more trustable acquaintances. Question Waves uses local information to make decisions and obtain an answer ranking. With Question Waves, the answers that arrive first are the most likely to be relevant, and we computed the correlation of answer relevance with the order of arrival to demonstrate this result. We obtained correlations equivalent to the heuristics that use global knowledge, such as profile similarity among users or the expertise value of an agent. Because Question Waves is compatible with the social search protocol Asknext, it is possible to stop a search when enough relevant answers have been found; additionally, stopping the search early only introduces a minimal risk of not obtaining the best possible answer. Furthermore, Question Waves does not require a re-ranking algorithm because the results arrive sorted

Treatment of micropollutants in municipal wastewater: study of a sequential batch biofilter

All the experimental part of this final project was done at Laboratoire de Biotechnologie Environnementale (LBE) from the École Polytechnique Fédérale de Lausanne (EPFL), Switzerland, during 6 months (November 2013- May 2014). A fungal biofilter composed of woodchips was designed in order to remove micropollutants from the effluents of waste water treatment plants. Two fungi were tested: Pleurotus ostreatus and Trametes versicolor in order to evaluate their efficiency for the removal of two micropollutants: the anti-inflammatory drug naproxen and the antibiotic sulfamethoxazole,. Although Trametes versicolor was able to degrade quickly naproxen, this fungus was not any more active after one week of operation in the filter. Pleurotus ostreatus was, on contrary, able to survive more than 3 months in the filter, showing good removal efficiencies of naproxen and sulfamethoxazole during all this period, in tap water but also in real treated municipal wastewater. Several other experiments have provided insight on the removal mechanisms of these micropollutants in the fungal biofilter (degradation and adsorption) and also allowed to model the removal trend. Fungal treatment with Pleurotus ostreatus grown on wood substrates appeared to be a promising solution to improve micropollutants removal in wastewater.

Combining T2-preparation with spectral and spatial selectivity for improved coronary MRA

Cardiovascular disease is the leading cause of death worldwide. Within this subset, coronary artery disease (CAD) is the most prevalent. Magnetic resonance angiography (MRA) is an emerging technique that provides a safe, non-invasive way of assessing CAD progression. To generate contrast between tissues, MR images are weighted according to the magnetic properties of those tissues. In cardiac MRI, T2 contrast, which is governed by the rate of transverse signal loss, is often created through the use of a T2-Preparation module. T2-Preparation, or T2-Prep, is a magnetization preparation scheme used to improve blood/myocardium contrast in cardiac MRI. T2-Prep methods generally use a non-selective +90°, 180°, 180°, -90° train of radiofrequency (RF) pulses (or variant thereof), to tip magnetization into the transverse plane, allow it to evolve, and then to restore it to the longitudinal plane. A key feature in this process is the combination of a +90° and -90° RF pulse. By changing either one of these, a mismatch occurs between signal excitation and restoration. This feature can be exploited to provide additional spectral or spatial selectivity. In this work, both of these possibilities are explored. The first - spectral selectivity - has been examined as a method of improving fat saturation in coronary MRA. The second - spatial selectivity - has been examined as a means of reducing imaging time by decreasing the field of view, and as a method of reducing artefacts originating from the tissues surrounding the heart. Two additional applications, parallel imaging and self-navigation, are also presented. This thesis is thus composed of four sections. The first, "A Fat Signal Suppression for Coronary MRA at 3T using a Water-Selective Adiabatic T2-Preparation Technique", was originally published in the journal Magnetic Resonance in Medicine (MRM) with co-authors Ruud B. van Heeswijk and Matthias Stuber. The second, "Combined T2-Preparation and 2D Pencil Beam Inner Volume Selection", again with co-authors Ruud van Heeswijk and Matthias Stuber, was also published in the journal MRM. The third, "A cylindrical, inner volume selecting 2D-T2-Prep improves GRAPPA-accelerated image quality in MRA of the right coronary artery", written with co-authors Jerome Yerly and Matthias Stuber, has been submitted to the "Journal of Cardiovascular Magnetic Resonance", and the fourth, "Combined respiratory self-navigation and 'pencil-beam' 2D-T2 -Prep for free-breathing, whole-heart coronary MRA", with co¬authors Jerome Chaptinel, Giulia Ginami, Gabriele Bonanno, Simone Coppo, Ruud van Heeswijk, Davide Piccini, and Matthias Stuber, is undergoing internal review prior to submission to the journal MRM. -- Les maladies cardiovasculaires sont la cause principale de décès dans le monde : parmi celles-ci, les maladies coronariennes sont les plus répandues. L'angiographie par résonance magnétique (ARM) est une technique émergente qui fournit une manière sûre, non invasive d'évaluer la progression de la coronaropathie. Pour obtenir un contraste entre les tissus, les images d'IRM sont pondérées en fonction des propriétés magnétiques de ces tissus. En IRM cardiaque, le contraste en T2, qui est lié à la décroissance du signal transversal, est souvent créé grâce à l'utilisàtion d'un module de préparation T2. La préparation T2, ou T2-Prep, est un système de préparation de l'aimantation qui est utilisé pour améliorer le contraste entre le sang et le myocarde lors d'une IRM cardiaque. Les méthodes de T2-Prep utilisent généralement une série non-sélective d'impulsions de radiofréquence (RF), typiquement [+ 90°, 180°, 180°, -90°] ou une variante, qui bascule l'aimantation dans le plan transversal, lui permet d'évoluer, puis la restaure dans le plan longitudinal. Un élément clé de ce processus est la combinaison des impulsions RF de +90° et -90°. En changeant l'une ou l'autre des impulsions, un décalage se produit entre l'excitation du signal et de la restauration. Cette fonction peut être exploitée pour fournir une sélectivité spectrale ou spatiale. Dans cette thèse, les deux possibilités sont explorées. La première - la sélectivité spectrale - a été examinée comme une méthode d'améliorer la saturation de la graisse dans l'IRM coronarienne. La deuxième - la sélectivité spatiale - a été étudiée comme un moyen de réduire le temps d'imagerie en diminuant le champ de vue, et comme une méthode de réduction des artefacts provenant des tissus entourant le coeur. Deux applications supplémentaires, l'imagerie parallèle et la self-navigation, sont également présentées. Cette thèse est ainsi composée de quatre sections. La première, "A Fat Signal Suppression for Coronary MRA at 3T using a Water-Selective Adiabatic T2-Preparation Technique", a été publiée dans la revue médicale Magnetic Resonance .in Medicine (MRM) avec les co-auteurs Ruud B. van Heeswijk et Matthias Stuber. La deuxième, Combined T2-Preparation and 2D Pencil Beam Inner Volume Selection", encore une fois avec les co-auteurs Ruud van Heeswijk et Matthias Stuber, a également été publiée dans le journal MRM. La troisième, "A cylindrical, inner volume selecting 2D-T2-Prep improves GRAPPA- accelerated image quality in MRA of the right coronary artery", écrite avec les co-auteurs Jérôme Yerly et Matthias Stuber, a été présentée au "Journal of Cardiovascular Magnetic Resonance", et la quatrième, "Combined respiratory self-navigation and 'pencil-beam' 2D-T2 -Prep for free-breathing, whole-heart coronary MRA", avec les co-auteurs Jérôme Chaptinel, Giulia Ginami, Gabriele Bonanno , Simone Coppo, Ruud van Heeswijk, Davide Piccini, et Matthias Stuber, subit un examen interne avant la soumission à la revue MRM.

A Hierarchical Approach for Multi-task Logistic Regression

Peer-reviewed

Pose-based SLAM with probabilistic scan matching algorithm using a mechanical scanned imaging sonar

This paper proposes a pose-based algorithm to solve the full SLAM problem for an autonomous underwater vehicle (AUV), navigating in an unknown and possibly unstructured environment. The technique incorporate probabilistic scan matching with range scans gathered from a mechanical scanning imaging sonar (MSIS) and the robot dead-reckoning displacements estimated from a Doppler velocity log (DVL) and a motion reference unit (MRU). The proposed method utilizes two extended Kalman filters (EKF). The first, estimates the local path travelled by the robot while grabbing the scan as well as its uncertainty and provides position estimates for correcting the distortions that the vehicle motion produces in the acoustic images. The second is an augment state EKF that estimates and keeps the registered scans poses. The raw data from the sensors are processed and fused in-line. No priory structural information or initial pose are considered. The algorithm has been tested on an AUV guided along a 600 m path within a marina environment, showing the viability of the proposed approach