Machine learning for geospatial data : algorithms, software tools and case studies

Résumé Cette thèse est consacrée à l'analyse, la modélisation et la visualisation de données environnementales à référence spatiale à l'aide d'algorithmes d'apprentissage automatique (Machine Learning). L'apprentissage automatique peut être considéré au sens large comme une sous-catégorie de l'intelligence artificielle qui concerne particulièrement le développement de techniques et d'algorithmes permettant à une machine d'apprendre à partir de données. Dans cette thèse, les algorithmes d'apprentissage automatique sont adaptés pour être appliqués à des données environnementales et à la prédiction spatiale. Pourquoi l'apprentissage automatique ? Parce que la majorité des algorithmes d'apprentissage automatiques sont universels, adaptatifs, non-linéaires, robustes et efficaces pour la modélisation. Ils peuvent résoudre des problèmes de classification, de régression et de modélisation de densité de probabilités dans des espaces à haute dimension, composés de variables informatives spatialisées (« géo-features ») en plus des coordonnées géographiques. De plus, ils sont idéaux pour être implémentés en tant qu'outils d'aide à la décision pour des questions environnementales allant de la reconnaissance de pattern à la modélisation et la prédiction en passant par la cartographie automatique. Leur efficacité est comparable au modèles géostatistiques dans l'espace des coordonnées géographiques, mais ils sont indispensables pour des données à hautes dimensions incluant des géo-features. Les algorithmes d'apprentissage automatique les plus importants et les plus populaires sont présentés théoriquement et implémentés sous forme de logiciels pour les sciences environnementales. Les principaux algorithmes décrits sont le Perceptron multicouches (MultiLayer Perceptron, MLP) - l'algorithme le plus connu dans l'intelligence artificielle, le réseau de neurones de régression généralisée (General Regression Neural Networks, GRNN), le réseau de neurones probabiliste (Probabilistic Neural Networks, PNN), les cartes auto-organisées (SelfOrganized Maps, SOM), les modèles à mixture Gaussiennes (Gaussian Mixture Models, GMM), les réseaux à fonctions de base radiales (Radial Basis Functions Networks, RBF) et les réseaux à mixture de densité (Mixture Density Networks, MDN). Cette gamme d'algorithmes permet de couvrir des tâches variées telle que la classification, la régression ou l'estimation de densité de probabilité. L'analyse exploratoire des données (Exploratory Data Analysis, EDA) est le premier pas de toute analyse de données. Dans cette thèse les concepts d'analyse exploratoire de données spatiales (Exploratory Spatial Data Analysis, ESDA) sont traités selon l'approche traditionnelle de la géostatistique avec la variographie expérimentale et selon les principes de l'apprentissage automatique. La variographie expérimentale, qui étudie les relations entre pairs de points, est un outil de base pour l'analyse géostatistique de corrélations spatiales anisotropiques qui permet de détecter la présence de patterns spatiaux descriptible par une statistique. L'approche de l'apprentissage automatique pour l'ESDA est présentée à travers l'application de la méthode des k plus proches voisins qui est très simple et possède d'excellentes qualités d'interprétation et de visualisation. Une part importante de la thèse traite de sujets d'actualité comme la cartographie automatique de données spatiales. Le réseau de neurones de régression généralisée est proposé pour résoudre cette tâche efficacement. Les performances du GRNN sont démontrées par des données de Comparaison d'Interpolation Spatiale (SIC) de 2004 pour lesquelles le GRNN bat significativement toutes les autres méthodes, particulièrement lors de situations d'urgence. La thèse est composée de quatre chapitres : théorie, applications, outils logiciels et des exemples guidés. Une partie importante du travail consiste en une collection de logiciels : Machine Learning Office. Cette collection de logiciels a été développée durant les 15 dernières années et a été utilisée pour l'enseignement de nombreux cours, dont des workshops internationaux en Chine, France, Italie, Irlande et Suisse ainsi que dans des projets de recherche fondamentaux et appliqués. Les cas d'études considérés couvrent un vaste spectre de problèmes géoenvironnementaux réels à basse et haute dimensionnalité, tels que la pollution de l'air, du sol et de l'eau par des produits radioactifs et des métaux lourds, la classification de types de sols et d'unités hydrogéologiques, la cartographie des incertitudes pour l'aide à la décision et l'estimation de risques naturels (glissements de terrain, avalanches). Des outils complémentaires pour l'analyse exploratoire des données et la visualisation ont également été développés en prenant soin de créer une interface conviviale et facile à l'utilisation. Machine Learning for geospatial data: algorithms, software tools and case studies Abstract The thesis is devoted to the analysis, modeling and visualisation of spatial environmental data using machine learning algorithms. In a broad sense machine learning can be considered as a subfield of artificial intelligence. It mainly concerns with the development of techniques and algorithms that allow computers to learn from data. In this thesis machine learning algorithms are adapted to learn from spatial environmental data and to make spatial predictions. Why machine learning? In few words most of machine learning algorithms are universal, adaptive, nonlinear, robust and efficient modeling tools. They can find solutions for the classification, regression, and probability density modeling problems in high-dimensional geo-feature spaces, composed of geographical space and additional relevant spatially referenced features. They are well-suited to be implemented as predictive engines in decision support systems, for the purposes of environmental data mining including pattern recognition, modeling and predictions as well as automatic data mapping. They have competitive efficiency to the geostatistical models in low dimensional geographical spaces but are indispensable in high-dimensional geo-feature spaces. The most important and popular machine learning algorithms and models interesting for geo- and environmental sciences are presented in details: from theoretical description of the concepts to the software implementation. The main algorithms and models considered are the following: multi-layer perceptron (a workhorse of machine learning), general regression neural networks, probabilistic neural networks, self-organising (Kohonen) maps, Gaussian mixture models, radial basis functions networks, mixture density networks. This set of models covers machine learning tasks such as classification, regression, and density estimation. Exploratory data analysis (EDA) is initial and very important part of data analysis. In this thesis the concepts of exploratory spatial data analysis (ESDA) is considered using both traditional geostatistical approach such as_experimental variography and machine learning. Experimental variography is a basic tool for geostatistical analysis of anisotropic spatial correlations which helps to understand the presence of spatial patterns, at least described by two-point statistics. A machine learning approach for ESDA is presented by applying the k-nearest neighbors (k-NN) method which is simple and has very good interpretation and visualization properties. Important part of the thesis deals with a hot topic of nowadays, namely, an automatic mapping of geospatial data. General regression neural networks (GRNN) is proposed as efficient model to solve this task. Performance of the GRNN model is demonstrated on Spatial Interpolation Comparison (SIC) 2004 data where GRNN model significantly outperformed all other approaches, especially in case of emergency conditions. The thesis consists of four chapters and has the following structure: theory, applications, software tools, and how-to-do-it examples. An important part of the work is a collection of software tools - Machine Learning Office. Machine Learning Office tools were developed during last 15 years and was used both for many teaching courses, including international workshops in China, France, Italy, Ireland, Switzerland and for realizing fundamental and applied research projects. Case studies considered cover wide spectrum of the real-life low and high-dimensional geo- and environmental problems, such as air, soil and water pollution by radionuclides and heavy metals, soil types and hydro-geological units classification, decision-oriented mapping with uncertainties, natural hazards (landslides, avalanches) assessments and susceptibility mapping. Complementary tools useful for the exploratory data analysis and visualisation were developed as well. The software is user friendly and easy to use.

The geometric structure of the brain fiber pathways.

The structure of the brain as a product of morphogenesis is difficult to reconcile with the observed complexity of cerebral connectivity. We therefore analyzed relationships of adjacency and crossing between cerebral fiber pathways in four nonhuman primate species and in humans by using diffusion magnetic resonance imaging. The cerebral fiber pathways formed a rectilinear three-dimensional grid continuous with the three principal axes of development. Cortico-cortical pathways formed parallel sheets of interwoven paths in the longitudinal and medio-lateral axes, in which major pathways were local condensations. Cross-species homology was strong and showed emergence of complex gyral connectivity by continuous elaboration of this grid structure. This architecture naturally supports functional spatio-temporal coherence, developmental path-finding, and incremental rewiring with correlated adaptation of structure and function in cerebral plasticity and evolution.

Automated Lesion Detection-Based Symptome Mapping In Patients With Sensory Deficits

The human brain is the most complex structure known. With its high number of cells, number of connections and number of pathways it is the source of every thought in the world. It consumes 25% of our oxygen and suffers very fast from a disruption of its supply. An acute event, like a stroke, results in rapid dysfunction referable to the affected area. A few minutes without oxygen and neuronal cells die and subsequently degenerate. Changes in the brains incoming blood flow alternate the anatomy and physiology of the brain. All stroke events leave behind a brain tissue lesion. To rapidly react and improve the prediction of outcome in stroke patients, accurate lesion detection and reliable lesion-based function correlation would be very helpful. With a number of neuroimaging and clinical data of cerebral injured patients this study aims to investigate correlations of structural lesion locations with sensory functions.

Debating the centre : the theory of principal qualificand (mukhyavisesya) in classical Indian philosophy

The theory of language has occupied a special place in the history of Indian thought. Indian philosophers give particular attention to the analysis of the cognition obtained from language, known under the generic name of śābdabodha. This term is used to denote, among other things, the cognition episode of the hearer, the content of which is described in the form of a paraphrase of a sentence represented as a hierarchical structure. Philosophers submit the meaning of the component items of a sentence and their relationship to a thorough examination, and represent the content of the resulting cognition as a paraphrase centred on a meaning element, that is taken as principal qualificand (mukhyaviśesya) which is qualified by the other meaning elements. This analysis is the object of continuous debate over a period of more than a thousand years between the philosophers of the schools of Mimāmsā, Nyāya (mainly in its Navya form) and Vyākarana. While these philosophers are in complete agreement on the idea that the cognition of sentence meaning has a hierarchical structure and share the concept of a single principal qualificand (qualified by other meaning elements), they strongly disagree on the question which meaning element has this role and by which morphological item it is expressed. This disagreement is the central point of their debate and gives rise to competing versions of this theory. The Mïmāmsakas argue that the principal qualificand is what they call bhāvanā ̒bringing into being̒, ̒efficient force̒ or ̒productive operation̒, expressed by the verbal affix, and distinct from the specific procedures signified by the verbal root; the Naiyāyikas generally take it to be the meaning of the word with the first case ending, while the Vaiyākaranas take it to be the operation expressed by the verbal root. All the participants rely on the Pāninian grammar, insofar as the Mimāmsakas and Naiyāyikas do not compose a new grammar of Sanskrit, but use different interpretive strategies in order to justify their views, that are often in overt contradiction with the interpretation of the Pāninian rules accepted by the Vaiyākaranas. In each of the three positions, weakness in one area is compensated by strength in another, and the cumulative force of the total argumentation shows that no position can be declared as correct or overall superior to the others. This book is an attempt to understand this debate, and to show that, to make full sense of the irreconcilable positions of the three schools, one must go beyond linguistic factors and consider the very beginnings of each school's concern with the issue under scrutiny. The texts, and particularly the late texts of each school present very complex versions of the theory, yet the key to understanding why these positions remain irreconcilable seems to lie elsewhere, this in spite of extensive argumentation involving a great deal of linguistic and logical technicalities. Historically, this theory arises in Mimāmsā (with Sabara and Kumārila), then in Nyāya (with Udayana), in a doctrinal and theological context, as a byproduct of the debate over Vedic authority. The Navya-Vaiyākaranas enter this debate last (with Bhattoji Dïksita and Kaunda Bhatta), with the declared aim of refuting the arguments of the Mïmāmsakas and Naiyāyikas by bringing to light the shortcomings in their understanding of Pāninian grammar. The central argument has focused on the capacity of the initial contexts, with the network of issues to which the principal qualificand theory is connected, to render intelligible the presuppositions and aims behind the complex linguistic justification of the classical and late stages of this debate. Reading the debate in this light not only reveals the rationality and internal coherence of each position beyond the linguistic arguments, but makes it possible to understand why the thinkers of the three schools have continued to hold on to three mutually exclusive positions. They are defending not only their version of the principal qualificand theory, but (though not openly acknowledged) the entire network of arguments, linguistic and/or extra-linguistic, to which this theory is connected, as well as the presuppositions and aims underlying these arguments.

Interest rates mapping

The present study deals with the analysis and mapping of Swiss franc interest rates. Interest rates depend on time and maturity, defining term structure of the interest rate curves (IRC). In the present study IRC are considered in a two-dimensional feature space - time and maturity. Exploratory data analysis includes a variety of tools widely used in econophysics and geostatistics. Geostatistical models and machine learning algorithms (multilayer perceptron and Support Vector Machines) were applied to produce interest rate maps. IR maps can be used for the visualisation and pattern perception purposes, to develop and to explore economical hypotheses, to produce dynamic asset-liability simulations and for financial risk assessments. The feasibility of an application of interest rates mapping approach for the IRC forecasting is considered as well. (C) 2008 Elsevier B.V. All rights reserved.

Structure and kinematics of the Siviez-Mischabel nappe in the Mattertal (western Alps of Switzerland) = Structure et cinématique de la nappe de Siviez-Mischabel le long de la vallée de Zermatt (Alpes de Suisse occidentale)

Résumé Cette étude porte sur le flanc inverse de la nappe de Siviez-Mischabel et sur les unités tectoniques sous jacentes (zone de Stalden supérieur et zone Houillère) dans la vallée menant à Zermatt. L'étude structurale du granite permien de Randa (orthogneiss oeillé) permet de mieux comprendre les effets de la déformation alpine sur les roches de socle. La cartographie détaillée de l'orthogneiss et de son encaissant, ainsi que l'étude lithostratigraphique des terrains sédimentaires associés permettent de proposer un schéma structural et cinématique du flanc inverse de la nappe de Siviez-Mischabel et de mieux comprendre ses relations avec les unités tectoniques sous-jacentes. L'analyse structurale de l'orthogneiss de Randa et de son encaissant révèle la superposition de plusieurs phases de déformation ductile. Cet orthogneiss formé sous des conditions métamorphiques du faciès schiste vert possède une forte schistosité alpine avec au moins deux linéations d'extension. La première, L1, orientée NW-SE est associée à la mise en place de la nappe. La seconde, L2, orientée SW-NE, se corrèle au cisaillement ductile du Simplon. La quantification de la déformation au moyen de la méthode de Fry sur les faciès porphyriques donne des ellipses à rapports axiaux compris entre 1.9 et 5.3, en accord avec les valeurs obtenues par d'autres marqueurs {tourmalines étirées, fibres). Les valeurs mesurées parallèlement à L1 ou L2 sont très semblables. La méthode de Fry a nécessité une étude théorique préalable afin de vérifier son applicabilité aux orthogneiss oeillés. La méthode requiert une distribution spatiale homogène et isotrope des marqueurs utilisés. Les tests statistiques effectués ont révélé que les phénocristaux de feldspath alcalin satisfont à cette condition et qu'ils peuvent être utilisés comme marqueur de la déformation au moyen de la méthode de Fry. Les valeurs obtenues révèlent l'importance du cisaillement ductile du Simplon sur la géométrie de la nappe dans la région d'étude. Le levé cartographique a permis d'améliorer la lithostratigraphie de la base de la nappe de Siviez-Mischabel. Trois formations en position renversée peuvent être observées sous les gneiss formant le coeur de la nappe. Ces trois formations forment le coeur du synclinal de St-Niklaus qui connecte la nappe de Siviez-Mischabel à la zone de Stalden supérieur. La datation par U-Pb de zircons détritiques et magmatiques par LA-ICP-MS permet de contraindre l'âge des formations observées (probablement Carbonifère à Trias précoce). Ces données ont des répercussions importantes sur la structure de la nappe dans la région, prouvant l'existence de plusieurs plis avec des séries normales et renversées bien préservées. La définition et la datation de ces formations, ainsi que leur identification dans la-Zone- Houillère avoisinante permettent de mieux comprendre la géométrie initiale et les relations tectoniques des nappes du Pennique moyen dans la vallée de Zermatt. Summary This study investigates the overturned limb of the Siviez-Mischabel nappe and underlying tectonic units (Upper Stalden zone and Houillère zone) in the Mattertal area. Detailed structural analysis in the Permian Randa granite (augen orthogneiss) allows a better understanding of the Alpine deformation effects on basement rocks. Detailed mapping of this orthogneiss and surrounding rocks, and the study of the lithostratigraphy in the related sedimentary horizons allow the proposition of a structural and kinematic model for the overturned limb of the Siviez-Mischabel and to better understand the relations with the underlying tectonic units. The structural analysis of the Randa orthogneiss and surrounding rocks revealed the superposition of several phases of ductile deformation. This orthogneiss formed under greenschist facies metamorphic conditions displays a strong Alpine foliation with at least two stretching lineations. The first lineation, L1, is oriented NW-SE and is related to the nappe emplacement northward. The second one, L2, is related to the Simplon ductile shear zone. Strain estimation using the Fry method has been performed on porphyritic facies of the Randa orthogneiss. The obtained ellipses have axial ratios varying between 1.9 and 5.3, in agreement with strain estimation obtained from other markers (stretched turmalines, fringes). The strain values are very similar if measured parallel to L1 or to L2. A theoretical approach was necessary to verify the relevant application of the Fry method to augen orthogneiss. This method requires that the distribution of the used markers has to be homogeneous and isotropic. Statistical tests have been done and revealed that K-feldspar phenocrysts satisfy these conditions and can be used as strain markers with the Fry method. The obtained strain measurements revealed the importance of the Simplon ductile shear zone on the geometry of the nappe in the studied area. Mapping has improved the lithostratigraphy at the base of the Siviez-Mischabel nappe. Three overturned formations can be observed below the gneisses forming the core of the nappe. These three formations form the St-Niklaus syncline, which connects the Siviez-Mischabel nappe to the underlying Upper Stalden zone. U-Pb dating of detrital and magmatic zircons by LA-ICPMS allowed the age of the observed formations to be constrained (presumably Carboniferous to Early Triassic). This data has critical implications for nappe structure in the region, composed of few recumbent folds with well preserved normal and overturned limbs. The definition and dating of these formations, as well as their identification in the adjacent "Houillère Zone" improve the understanding of the geometry and tectonic relations of the Middle Penninic nappes in the Mattertal.

ADC mapping of chronic cerebral hypoperfusion induced by carotid artery stenosis.

BACKGROUND: Carotid artery stenosis is associated with the occurrence of acute and chronic ischemic lesions that increase with age in the elderly population. Diffusion Imaging and ADC mapping may be an appropriate method to investigate patients with chronic hypoperfusion consecutive to carotid stenosis. This non-invasive technique allows to investigate brain integrity and structure, in particular hypoperfusion induced by carotid stenosis diseases. The aim of this study was to evaluate the impact of a carotid stenosis on the parenchyma using ADC mapping. METHODS: Fifty-nine patients with symptomatic (33) and asymptomatic (26) carotid stenosis were recruited from our multidisciplinary consultation. Both groups demonstrated a similar degree of stenosis. All patients underwent MRI of the brain including diffusion-weighted MR imaging with ADC mapping. Regions of interest were defined in the anterior and posterior paraventricular regions both ipsilateral and contralateral to the stenosis (anterior circulation). The same analysis was performed for the thalamic and occipital regions (posterior circulation). RESULTS: ADC values of the affected vascular territory were significantly higher on the side of the stenosis in the periventricular anterior (P<0.001) and posterior (P<0.01) area. There was no difference between ipsilateral and contralateral ADC values in the thalamic and occipital regions. CONCLUSIONS: We have shown that carotid stenosis is associated with significantly higher ADC values in the anterior circulation, probably reflecting an impact of chronic hypoperfusion on the brain parenchyma in symptomatic and asymptomatic patients. This is consistent with previous data in the literature.

Cytoskeletal and DNA structure abnormalities result from bypass of requirement for the cdc10 start gene in the fission yeast Schizosaccharomyces pombe.

The cdc10 gene of the fission yeast S. pombe is required for traverse of the start control in late G1 and commitment to the mitotic cell cycle. To increase our understanding of the events which occur at start, a pseudoreversion analysis was undertaken to identify genes whose products may interact with cdc10 or bypass the requirement for it. A single gene, sct1+ (suppressor of cdc ten), has been identified, mutation of which suppresses all conditional alleles and a null allele of cdc10. Bypass of the requirement for cdc10+ function by sct1-1 mutations leads to pleiotropic defects, including microtubule, microfilament and nuclear structural abnormalities. Our data suggest that sct1 encodes a protein that is dependent upon cdc10+ either for its normal function or expression, or is a component of a checkpoint that monitors execution of p85cdc10 function.

Mapping genetic variants associated with beta-adrenergic responses in inbred mice.

β-blockers and β-agonists are primarily used to treat cardiovascular diseases. Inter-individual variability in response to both drug classes is well recognized, yet the identity and relative contribution of the genetic players involved are poorly understood. This work is the first genome-wide association study (GWAS) addressing the values and susceptibility of cardiovascular-related traits to a selective β(1)-blocker, Atenolol (ate), and a β-agonist, Isoproterenol (iso). The phenotypic dataset consisted of 27 highly heritable traits, each measured across 22 inbred mouse strains and four pharmacological conditions. The genotypic panel comprised 79922 informative SNPs of the mouse HapMap resource. Associations were mapped by Efficient Mixed Model Association (EMMA), a method that corrects for the population structure and genetic relatedness of the various strains. A total of 205 separate genome-wide scans were analyzed. The most significant hits include three candidate loci related to cardiac and body weight, three loci for electrocardiographic (ECG) values, two loci for the susceptibility of atrial weight index to iso, four loci for the susceptibility of systolic blood pressure (SBP) to perturbations of the β-adrenergic system, and one locus for the responsiveness of QTc (p<10(-8)). An additional 60 loci were suggestive for one or the other of the 27 traits, while 46 others were suggestive for one or the other drug effects (p<10(-6)). Most hits tagged unexpected regions, yet at least two loci for the susceptibility of SBP to β-adrenergic drugs pointed at members of the hypothalamic-pituitary-thyroid axis. Loci for cardiac-related traits were preferentially enriched in genes expressed in the heart, while 23% of the testable loci were replicated with datasets of the Mouse Phenome Database (MPD). Altogether these data and validation tests indicate that the mapped loci are relevant to the traits and responses studied.

Value added logistical support service: logistics cost structure and performance in the new concept. Part 3

The aim of this study is to present an Activity-Based Costing spreadsheet tool for analyzing the logistics costs. The tool can be used both by customer-companies and logistics service providers. The study discusses the influence of different activity models on costs. Additionally this paper discusses about the logistical performance across the total supply chain This study is carried out using ananalytical research approach and literature material has been used for supplementing the concerned research approach. Cost structure analysis was based on the theory of activity-based management. This study was outlined to spare part logistics in machine-shop industry. The outlines of logistics services and logisticalperformance discussed in this report are based on the new logistics business concept (LMS-concept), which has been presented earlier in the Valssi-project. Oneof the aims of this study is to increase awareness of different activity modelson logistics costs. The report paints an overall picture about the business environment and requirements for the new logistics concept.

In Search of Corporate Renewal: How to Benefit from Corporate Venturing?

Despite the rapid change in today's business environment there are relatively few studies about corporate renewal. This study aims for its part at filling that research gap by studying the concepts of strategy, corporate renewal, innovation and corporate venturing. Its purpose is to enhance our understanding of how established companies operating in dynamic and global environment can benefit from their corporate venturing activities. The theoretical part approaches the research problem in corporate and venture levels. Firstly, it focuses on mapping the determinants of strategy and suggests using industry, location, resources, knowledge, structure and culture, market, technology and business model to assess the environment and using these determinants to optimize speed and magnitude of change.Secondly, it concludes that the choice of innovation strategy is dependent on the type and dimensions of innovation and suggests assessing market, technology, business model as well as novelty and complexity related to each of them for choosing an optimal context for developing innovations further. Thirdly, it directsattention on processes through which corporate renewal takes place. On corporate level these processes are identified as strategy formulation, strategy formation and strategy implementation. On the venture level the renewal processes are identified as learning, leveraging and nesting. The theoretical contribution of this study, the framework of strategic corporate venturing, joins corporate and venture level management issues together and concludes that strategy processes and linking processes are the mechanism through which continuous corporate renewaltakes place. The framework of strategic corporate venturing proposed by this study is a new way to illustrate the role of corporate venturing as a purposefullybuilt, different view of a company's business environment. The empirical part extended the framework by enhancing our understanding of the link between corporate renewal and corporate venturing in its real life environment in three Finnish companies: Metso, Nokia and TeliaSonera. Characterizing companies' environmentwith the determinants of strategy identified in this study provided a structured way to analyze their competitive position and renewal challenges that they arefacing. More importantly the case studies confirmed that a link between corporate renewal and corporate venturing exists and found out that the link is not as straight forward as indicated by the theory. Furthermore, the case studies enhanced the framework by indicating a sequence according to which the processes work. Firstly, the induced strategy processes strategy formulation and strategy implementation set the scene for corporate venturing context and management processes and leave strategy formation for the venture. Only after that can strategies formed by ventures come back to the corporate level - and if found viable in the corporate level be formalized through formulation and implementation. With the help of the framework of strategic corporate venturing the link between corporaterenewal and corporate venturing can be found and managed. The suggested response to the continuous need for change is continuous renewal i.e. institutionalizing corporate renewal in the strategy processes of the company. As far as benefiting from venturing is concerned the answer lies in deliberately managing venturing in a context different to the mainstream businesses and establishing efficientlinking processes to exploit the renewal potential of individual ventures.

Localization and fine structure of a vaccinia virus gene encoding an envelope antigen.

The major antigen on the envelope of extracellular vaccinia virus particles is a polypeptide with an apparent molecular weight of 37,000 (p37K; G. Hiller and K. Weber, J. Virol. 55:651-659, 1985). The gene encoding p37K was mapped in the vaccinia virus genome by hybrid selection of RNA followed by in vitro translation. p37K was then identified among the in vitro translation products by immunoprecipitation with a monoclonal antibody. The gene is located close to the right-hand end of the HindIII F fragment. The corresponding region of the DNA was sequenced, and an open reading frame encoding a polypeptide of 41,748 daltons was observed. The 5' end of the mRNA, as defined by nuclease S1 analysis, maps within only a few nucleotides of the translation initiation codon. Examination of the DNA sequence around the putative initiation site of transcription revealed a characteristic sequence, TAAATG, which includes the ATG translation initiation codon and which is conserved in all but one late gene so far analyzed. It is therefore likely that this sequence is an important regulatory signal for late gene expression in vaccinia virus.

Single acquisition electrical property mapping based on relative coil sensitivities: A proof-of-concept demonstration.

PURPOSE: All methods presented to date to map both conductivity and permittivity rely on multiple acquisitions to compute quantitatively the magnitude of radiofrequency transmit fields, B1+. In this work, we propose a method to compute both conductivity and permittivity based solely on relative receive coil sensitivities ( B1-) that can be obtained in one single measurement without the need to neither explicitly perform transmit/receive phase separation nor make assumptions regarding those phases. THEORY AND METHODS: To demonstrate the validity and the noise sensitivity of our method we used electromagnetic finite differences simulations of a 16-channel transceiver array. To experimentally validate our methodology at 7 Tesla, multi compartment phantom data was acquired using a standard 32-channel receive coil system and two-dimensional (2D) and 3D gradient echo acquisition. The reconstructed electric properties were correlated to those measured using dielectric probes. RESULTS: The method was demonstrated both in simulations and in phantom data with correlations to both the modeled and bench measurements being close to identity. The noise properties were modeled and understood. CONCLUSION: The proposed methodology allows to quantitatively determine the electrical properties of a sample using any MR contrast, with the only constraint being the need to have 4 or more receive coils and high SNR. Magn Reson Med, 2014. © 2014 Wiley Periodicals, Inc.

Vulnerability as a heuristic for interdisciplinary research: Assessing the thematic and methodological structure of empirical life-course studies

Changes in human lives are studied in psychology, sociology, and adjacent fields as outcomes of developmental processes, institutional regulations and policies, culturally and normatively structured life courses, or empirical accounts. However, such studies have used a wide range of complementary, but often divergent, concepts. This review has two aims. First, we report on the structure that has emerged from scientific life course research by focusing on abstracts from longitudinal and life course studies beginning with the year 2000. Second, we provide a sense of the disciplinary diversity of the field and assess the value of the concept of 'vulnerability' as a heuristic tool for studying human lives. Applying correspondence analysis to 10,632 scientific abstracts, we find a disciplinary divide between psychology and sociology, and observe indications of both similarities of-and differences between-studies, driven at least partly by the data and methods employed. We also find that vulnerability takes a central position in this scientific field, which leads us to suggest several reasons to see value in pursuing theory development for longitudinal and life course studies in this direction.

Effect of pressure on La2(WO4)3 with a modulated scheelite-type structure

We have studied the effect of pressure on the structural and vibrational properties of lanthanum tritungstate La2(WO4)3. This compound crystallizes under ambient conditions in the modulated scheelite-type structure known as the α phase. We have performed x-ray diffraction and Raman scattering measurements up to a pressure of 20 GPa, as well as ab initio calculations within the framework of the density functional theory. Up to 5 GPa, the three methods provide a similar picture of the evolution under pressure of α-La2(WO4)3. At 5 GPa, we begin to observe some structural changes, and above 6 GPa we find that the x-ray patterns cannot be indexed as a single phase. However, we find that a mixture of two phases with C2/c symmetry accounts for all diffraction peaks. Our ab initio study confirms the existence of several C2/c structures, which are very close in energy in this compression range. According to our measurements, a state with medium-range order appears at pressures above 9 and 11 GPa, from x-ray diffraction and Raman experiments, respectively. Based upon our theoretical calculations we propose several high-pressure candidates with high cationic coordinations at these pressures. The compound evolves into a partially amorphous phase at pressures above 20 GPa.