Flow-R, a model for susceptibility mapping of debris flows and other gravitational hazards at a regional scale

The development of susceptibility maps for debris flows is of primary importance due to population pressure in hazardous zones. However, hazard assessment by processbased modelling at a regional scale is difficult due to the complex nature of the phenomenon, the variability of local controlling factors, and the uncertainty in modelling parameters. A regional assessment must consider a simplified approach that is not highly parameter dependant and that can provide zonation with minimum data requirements. A distributed empirical model has thus been developed for regional susceptibility assessments using essentially a digital elevation model (DEM). The model is called Flow-R for Flow path assessment of gravitational hazards at a Regional scale (available free of charge under www.flow-r.org) and has been successfully applied to different case studies in various countries with variable data quality. It provides a substantial basis for a preliminary susceptibility assessment at a regional scale. The model was also found relevant to assess other natural hazards such as rockfall, snow avalanches and floods. The model allows for automatic source area delineation, given user criteria, and for the assessment of the propagation extent based on various spreading algorithms and simple frictional laws.We developed a new spreading algorithm, an improved version of Holmgren's direction algorithm, that is less sensitive to small variations of the DEM and that is avoiding over-channelization, and so produces more realistic extents. The choices of the datasets and the algorithms are open to the user, which makes it compliant for various applications and dataset availability. Amongst the possible datasets, the DEM is the only one that is really needed for both the source area delineation and the propagation assessment; its quality is of major importance for the results accuracy. We consider a 10m DEM resolution as a good compromise between processing time and quality of results. However, valuable results have still been obtained on the basis of lower quality DEMs with 25m resolution.

Machine learning algorithms for spatial data. Case studies: Environmental pollution, natural hazards, renewable resources

This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.

Patterns of Subject Mix in Higher Education Institutions : A First Empirical Analysis Using the AQUAMETH Database

Teaching and research are organised differently between subject domains: attempts to construct typologies of higher education institutions, however, often do not include quantitative indicators concerning subject mix which would allow systematic comparisons of large numbers of higher education institutions among different countries, as the availability of data for such indicators is limited. In this paper, we present an exploratory approach for the construction of such indicators. The database constructed in the AQUAMETH project, which includes also data disaggregated at the disciplinary level, is explored with the aim of understanding patterns of subject mix. For six European countries, an exploratory and descriptive analysis of staff composition divided in four large domains (medical sciences, engineering and technology, natural sciences and social sciences and humanities) is performed, which leads to a classification distinguishing between specialist and generalist institutions. Among the latter, a further distinction is made based on the presence or absence of a medical department. Preliminary exploration of this classification and its comparison with other indicators show the influence of long term dynamics on the subject mix of individual higher education institutions, but also underline disciplinary differences, for example regarding student to staff ratios, as well as national patterns, for example regarding the number of PhD degrees per 100 undergraduate students. Despite its many limitations, this exploratory approach allows defining a classification of higher education institutions that accounts for a large share of differences between the analysed higher education institutions.

Vulgariser les sciences sans l'appui des savants. Jean Lanteires et le Journal de Lausanne (1786-1792)

Popularizing science without the support of scholars. Jean Lanteires and the Journal de Lausanne (1786-1792). - Founded in 1786 by Jean Lanteires, the Journal de Lausanne is a widespread, weekly journal with the express aim of disseminating scientific knowledge among the lower and middle classes. Its articles are easily comprehensible and cover a wide range of topics from literature to agriculture, from natural sciences to charity. Considerable space is given to reader's questions and comments. The journal can be situated somewhere between an almanac and a scientific journal. Lanteires' attempt to solicit contributions from scholars of medicine and natural sciences received a dismissive response. Of the few articles written by specialists, the majority deal with agriculture and charity. Lanteires' difficult relationship with the scholarly community is reflected in the journal's content. This makes the Journal de Lausanne a privileged observatory for studying the social context of the vulgarization process in late-eighteenth-century Switzerland and Europe.

Simulation of stromatolite growth using diffusion-limited aggregation and a discrete model of biogeochemical exchanges in microbial mat

Resume : Mieux comprendre les stromatolithes et les tapis microbiens est un sujet important en biogéosciences puisque cela aide à l'étude des premières formes de vie sur Terre, a mieux cerner l'écologie des communautés microbiennes et la contribution des microorganismes a la biominéralisation, et même à poser certains fondements dans les recherches en exobiologie. D'autre part, la modélisation est un outil puissant utilisé dans les sciences naturelles pour appréhender différents phénomènes de façon théorique. Les modèles sont généralement construits sur un système d'équations différentielles et les résultats sont obtenus en résolvant ce système. Les logiciels disponibles pour implémenter les modèles incluent les logiciels mathématiques et les logiciels généraux de simulation. L'objectif principal de cette thèse est de développer des modèles et des logiciels pour aider a comprendre, via la simulation, le fonctionnement des stromatolithes et des tapis microbiens. Ces logiciels ont été développés en C++ en ne partant d'aucun pré-requis de façon a privilégier performance et flexibilité maximales. Cette démarche permet de construire des modèles bien plus spécifiques et plus appropriés aux phénomènes a modéliser. Premièrement, nous avons étudié la croissance et la morphologie des stromatolithes. Nous avons construit un modèle tridimensionnel fondé sur l'agrégation par diffusion limitée. Le modèle a été implémenté en deux applications C++: un moteur de simulation capable d'exécuter un batch de simulations et de produire des fichiers de résultats, et un outil de visualisation qui permet d'analyser les résultats en trois dimensions. Après avoir vérifié que ce modèle peut en effet reproduire la croissance et la morphologie de plusieurs types de stromatolithes, nous avons introduit un processus de sédimentation comme facteur externe. Ceci nous a mené a des résultats intéressants, et permis de soutenir l'hypothèse que la morphologie des stromatolithes pourrait être le résultat de facteurs externes autant que de facteurs internes. Ceci est important car la classification des stromatolithes est généralement fondée sur leur morphologie, imposant que la forme d'un stromatolithe est dépendante de facteurs internes uniquement (c'est-à-dire les tapis microbiens). Les résultats avancés dans ce mémoire contredisent donc ces assertions communément admises. Ensuite, nous avons décidé de mener des recherches plus en profondeur sur les aspects fonctionnels des tapis microbiens. Nous avons construit un modèle bidimensionnel de réaction-diffusion fondé sur la simulation discrète. Ce modèle a été implémenté dans une application C++ qui permet de paramétrer et exécuter des simulations. Nous avons ensuite pu comparer les résultats de simulation avec des données du monde réel et vérifier que le modèle peut en effet imiter le comportement de certains tapis microbiens. Ainsi, nous avons pu émettre et vérifier des hypothèses sur le fonctionnement de certains tapis microbiens pour nous aider à mieux en comprendre certains aspects, comme la dynamique des éléments, en particulier le soufre et l'oxygène. En conclusion, ce travail a abouti à l'écriture de logiciels dédiés à la simulation de tapis microbiens d'un point de vue tant morphologique que fonctionnel, suivant deux approches différentes, l'une holistique, l'autre plus analytique. Ces logiciels sont gratuits et diffusés sous licence GPL (General Public License). Abstract : Better understanding of stromatolites and microbial mats is an important topic in biogeosciences as it helps studying the early forms of life on Earth, provides clues re- garding the ecology of microbial ecosystems and their contribution to biomineralization, and gives basis to a new science, exobiology. On the other hand, modelling is a powerful tool used in natural sciences for the theoretical approach of various phenomena. Models are usually built on a system of differential equations and results are obtained by solving that system. Available software to implement models includes mathematical solvers and general simulation software. The main objective of this thesis is to develop models and software able to help to understand the functioning of stromatolites and microbial mats. Software was developed in C++ from scratch for maximum performance and flexibility. This allows to build models much more specific to a phenomenon rather than general software. First, we studied stromatolite growth and morphology. We built a three-dimensional model based on diffusion-limited aggregation. The model was implemented in two C++ applications: a simulator engine, which can run a batch of simulations and produce result files, and a Visualization tool, which allows results to be analysed in three dimensions. After verifying that our model can indeed reproduce the growth and morphology of several types of stromatolites, we introduced a sedimentation process as an external factor. This lead to interesting results, and allowed to emit the hypothesis that stromatolite morphology may be the result of external factors as much as internal factors. This is important as stromatolite classification is usually based on their morphology, imposing that a stromatolite shape is dependant on internal factors only (i.e. the microbial mat). This statement is contradicted by our findings, Second, we decided to investigate deeper the functioning of microbial mats, We built a two-dimensional reaction-diffusion model based on discrete simulation, The model was implemented in a C++ application that allows setting and running simulations. We could then compare simulation results with real world data and verify that our model can indeed mimic the behaviour of some microbial mats. Thus, we have proposed and verified hypotheses regarding microbial mats functioning in order to help to better understand them, e.g. the cycle of some elements such as oxygen or sulfur. ln conclusion, this PhD provides a simulation software, dealing with two different approaches. This software is free and available under a GPL licence.

Hypothetical metaphysics of nature

The paper first sketches out a reply to the underdetermination challenge and the incommensurability challenge that rebuts the sceptical conclusions of these challenges and that is sufficient to lay the ground for the project of a metaphysics of nature. That metaphysics is as hypothetical as are our scientific theories. The paper then explains how can one can argue for certain views in the metaphysics of nature based on our current fundamental physical theories, namely the commitments to a tenseless theory of time and existence instead of a tensed one, to events instead of substances, and to relations instead of intrinsic properties. Finally, the paper mentions the themes of causation, laws and dispositions.

Interlaboratory comparison of size measurements on nanoparticles using nanoparticle tracking analysis (NTA)

One of the key challenges in the field of nanoparticle (NP) analysis is in producing reliable and reproducible characterisation data for nanomaterials. This study looks at the reproducibility using a relatively new, but rapidly adopted, technique, Nanoparticle Tracking Analysis (NTA) on a range of particle sizes and materials in several different media. It describes the protocol development and presents both the data and analysis of results obtained from 12 laboratories, mostly based in Europe, who are primarily QualityNano members. QualityNano is an EU FP7 funded Research Infrastructure that integrates 28 European analytical and experimental facilities in nanotechnology, medicine and natural sciences with the goal of developing and implementing best practice and quality in all aspects of nanosafety assessment. This study looks at both the development of the protocol and how this leads to highly reproducible results amongst participants. In this study, the parameter being measured is the modal particle size.

Rockfall characterisation and structural protection: A review

Rockfall is an extremely rapid process involving long travel distances. Due to these features, when an event occurs, the ability to take evasive action is practically zero and, thus, the risk of injury or loss of life is high. Damage to buildings and infrastructure is quite likely. In many cases, therefore, suitable protection measures are necessary. This contribution provides an overview of previous and current research on the main topics related to rockfall. It covers the onset of rockfall and runout modelling approaches, as well as hazard zoning and protection measures. It is the aim of this article to provide an in-depth knowledge base for researchers and practitioners involved in projects dealing with the rockfall protection of infrastructures, who may work in the fields of civil or environmental engineering, risk and safety, the earth and natural sciences.

Esquisse d'une anthropologie clinique I. Anthropopsychiatrie et anthropologie sémiotique

La psychiatrie (la clinique psychopathologique en général) connaît en ce début de XXIe siècle une situation complexe. Coincée entre naturalisation de l'esprit et constructionnisme social, la possibilité de contribuer à la constitution d'une science autonome qui traite de la souffrance psychique est aujourd'hui problématique. Les nombreux réductionnismes à l'oeuvre, de type nosographique, diagnostique, psychopharmacologique, les concurrences épistémologiques et les dogmatismes des modèles psychothérapeutiques, dessinent un paysage où s'engager à poursuivre la voie d'une psychiatrie spécifiquement humaine et articulée aux sciences naturelles relève de la gageure. C'est le défi de l'anthropologie clinique. Deux articles lui sont consacrés. Dans ce premier article, après avoir fait le constat de certaines impasses qui menacent la psychiatrie contemporaine et rappelé les origines du projet de l'anthropologique clinique, les auteurs présentent les deux démarches qui la fondent, chacune opérant dans un esprit d'interdisciplinarité : l'anthropopsychiatrie de Jacques Schotte et l'anthropologie sémiotique formulée par Jean Lassègue, Victor Rosenthal et Yves-Marie Visetti. Un deuxième article déploiera le potentiel intégratif d'un tel paradigme, constitué sur la base de ces deux démarches conjointes. Psychiatry (psychopathology clinics in general) is in a complex situation at the beginning of 21st century. Wedged between mind naturalization and social constructionism, the possibility of contributing to the establishment of an autonomous science that deals with mental suffering is problematic today. The many nosographic, diagnostic, psychopharmacological reductionisms at work as well as the competing epistemologies and the dogmatisms of psychotherapeutic models draw a challenging landscape for those following the path of a specifically human psychiatry articulated to natural sciences. This is the challenge of clinical anthropology which is presented in two parts. In the first part, after examining several dead ends which threaten contemporary psychiatry and pointing out the origins of the clinical anthropology project, the authors present its two foundational approaches. Each approach driven by a spirit of interdisciplinarity : Jacques Schotte's anthropopsychiatry and the semiotic anthropology as formulated by Jean Lassègue, Victor Rosenthal and Yves-Marie Visetti. A second part will describe the integrative potential of such a paradigm, based on these two joint approaches.