Penetration Characteristics of Asphalt in a Recycled Mixture, MLR-79-03, 1979

Samples of both recycled and nonrecycled asphaltic concrete were extracted in increments by the Abson Recovery Method and the penetration of the asphalt from each increment determined. The recycled projects were plantsite operations containing various amounts of virgin gravel. Cored samples were taken from the pavements on Kossuth County roads that were constructed as recycled projects in 1975, 1976, and 1977. Cored samples were also taken from a Kossuth County paving project done in 1975, that was not recycled. Comparison mix samples from 1978 construction projects in Marshall and Woodbury Counties of non - recycled projects are included. The test data from the penetrations of the recovered asphalt indicates that mixing of the old and new asphalt occurs very extensively in the hot recycling process. In laboratory controlled conditions it is difficult to coat aggregates with different penetration asphalts and prevent them from mixing.

The homeostatic psyche: Freudian theory and somatic markers.

After years of reciprocal lack of interest, if not opposition, neuroscience and psychoanalysis are poised for a renewed dialogue. This article discusses some aspects of the Freudian metapsychology and its link with specific biological mechanisms. It highlights in particular how the physiological concept of homeostasis resonates with certain fundamental concepts of psychoanalysis. Similarly, the authors underline how the Freud and Damasio theories of brain functioning display remarkable complementarities, especially through their common reference to Meynert and James. Furthermore, the Freudian theory of drives is discussed in the light of current neurobiological evidences of neural plasticity and trace formation and of their relationships with the processes of homeostasis. The ensuing dynamics between traces and homeostasis opens novel avenues to consider inner life in reference to the establishment of fantasies unique to each subject. The lack of determinism, within a context of determinism, implied by plasticity and reconsolidation participates in the emergence of singularity, the creation of uniqueness and the unpredictable future of the subject. There is a gap in determinism inherent to biology itself. Uniqueness and discontinuity: this should today be the focus of the questions raised in neuroscience. Neuroscience needs to establish the new bases of a "discontinuous" biology. Psychoanalysis can offer to neuroscience the possibility to think of discontinuity. Neuroscience and psychoanalysis meet thus in an unexpected way with regard to discontinuity and this is a new point of convergence between them.

The Implied Book and the Narrative Text. On a Blind Spot in Narratological Theory - from a Media Studies Perspective

The article is concerned with the formal definition of a largely unnoticed factor in narrative structure. Based on the assumptions that (1) the semantics of a written text depend, among other factors, directly on its visual alignment in space, that (2) the formal structure of a text has to meet that of its spatial presentation and that (3) these assumptions hold true also for narrative texts (which, however, in modern times typically conceal their spatial dimensions by a low-key linear layout), it is argued that, how ever low-key, the expected material shape of a given narrative determines the configuration of its plot by its author. The ,implied book' thus denotes an author's historically assumable, not necessarily conscious idea of how his text, which is still in the process of creation, will be dimensionally presented and under these circumstances visually absorbed. Assuming that an author's knowledge of this later (potentially) substantiated material form influences the composition, the implied book is to be understood as a text-genetically determined, structuring moment of the text. Historically reconstructed, it thus serves the methodical analysis of structural characteristics of a completed text.

From caging to rouse dynamics in polymer melts with intramolecular barriers: a critical test of the mode coupling theory

By means of computer simulations and solution of the equations of the mode coupling theory (MCT),we investigate the role of the intramolecular barriers on several dynamic aspects of nonentangled polymers. The investigated dynamic range extends from the caging regime characteristic of glass-formers to the relaxation of the chain Rouse modes. We review our recent work on this question,provide new results, and critically discuss the limitations of the theory. Solutions of the MCT for the structural relaxation reproduce qualitative trends of simulations for weak and moderate barriers. However, a progressive discrepancy is revealed as the limit of stiff chains is approached. This dis-agreement does not seem related with dynamic heterogeneities, which indeed are not enhanced by increasing barrier strength. It is not connected either with the breakdown of the convolution approximation for three-point static correlations, which retains its validity for stiff chains. These findings suggest the need of an improvement of the MCT equations for polymer melts. Concerning the relaxation of the chain degrees of freedom, MCT provides a microscopic basis for time scales from chain reorientation down to the caging regime. It rationalizes, from first principles, the observed deviations from the Rouse model on increasing the barrier strength. These include anomalous scaling of relaxation times, long-time plateaux, and nonmonotonous wavelength dependence of the mode correlators.

Red clover grown in a mixture with grasses : yield, persistence and dynamics of quality characteristics

Selostus: Puna-apilan pysyvyys apila-heinänurmessa sekä seosnurmen satoisuus ja laadun muutokset erilaisissa kasvuoloissa

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.

Genes, environment and sex : perspectives from ectothermic vertebrates

RESUMELes modèles classiques sur l'évolution des chromosomes sexuels supposent que des gènes sexe- antagonistes s'accumulent sur les chromosomes sexuels, entraînant ainsi l'apparition d'une région non- recombinante, qui se répand progressivement en favorisant l'accumulation de mutations délétères. En accord avec cette théorie, les chromosomes sexuels que l'on observe aujourd'hui chez les mammifères et les oiseaux sont considérablement différenciés. En revanche, chez la plupart des vertébrés ectothermes, les chromosomes sexuels sont indifférenciés et il existe une impressionnante diversité de mécanismes de détermination du sexe. Au cours de cette thèse, j'ai étudié l'évolution des chromosomes sexuels chez les vertébrés ectothermes, en outre pour mieux comprendre ce contraste avec les vertébrés endothermes. L'hypothèse « high-turnover » postule que les chromosomes sexuels sont remplacés régulièrement à partir d'autosomes afin d'éviter leur dégénérescence. L'hypothèse « fountain-of-youth » propose que la recombinaison entre le chromosome X et le chromosome Y au sein de femelles XY empêche la dégénérescence. Les résultats de ma thèse, basés sur des études théoriques et empiriques, suggèrent que les deux processus peuvent être entraînés par l'environnement et ainsi jouent un rôle important dans l'évolution des chromosomes sexuels chez les vertébrés ectothermes.SUMMARYClassical models of sex-chromosome evolution assume that sexually antagonistic genes accumulate on sex chromosomes leading to a non-recombining region, which progressively expands and favors the accumulation of deleterious mutations. Concordant with this theory, sex chromosomes in extant mammals and birds are considerably differentiated. In most ectothermic vertebrates, such as frogs, however, sex chromosomes are undifferentiated and a striking diversity of sex determination systems is observed. This thesis was aimed to investigate this apparent contrast of sex chromosome evolution between endothermic and ectothermic vertebrates. The "high-turnover" hypothesis holds that sex chromosomes arose regularly from autosomes preventing decay. The "fountain-of-youth" hypothesis posits that sex chromosomes undergo episodic X-Y recombination in sex-reversed XY females, thereby purging ("rejuvenating") the Y chromosome. We suggest that both processes likely played an important role in sex chromosome evolution of ectothermic vertebrates. The literature largely views sex determination as a dichotomous process: individual sex is assumed to be determined either by genetic (genotypic sex determination, GSD) or by environmental factors (environmental sex determination, ESD), most often temperature (temperature sex determination, TSD). We endorsed an alternative view, which sees GSD and TSD as the ends of a continuum. The conservatism of molecular processes among different systems of sex determination strongly supports the continuum view. We proposed to define sex as a threshold trait underlain by a liability factor, and reaction norms allowing modeling interactions between genotypic and temperature effects. We showed that temperature changes (due to e.g., climatic changes or range expansions) are expected to provoke turnovers in sex-determination mechanisms maintaining homomorphic sex chromosomes. The balanced lethal system of crested newts might be the result of such a sex determination turnover, originating from two variants of ancient Y-chromosomes. Observations from a group of tree frogs, on the other hand, supported the 'fountain of youth' hypothesis. We then showed that low rates of sex- reversals in species with GSD might actually be adaptive considering joint effects of deleterious mutation purging and sexually antagonistic selection. Ongoing climatic changes are expected to threaten species with TSD by biasing population sex ratios. In contrast, species with GSD are implicitly assumed immune against such changes, because genetic systems are thought to necessarily produce even sex ratios. We showed that this assumption may be wrong and that sex-ratio biases by climatic changes may represent a previously unrecognized extinction threat for some GSD species.

Fusion of the extended modified liquid drop model for nucleation and dynamical nucleation theory

We present a new phenomenological approach to nucleation, based on the combination of the extended modified liquid drop model and dynamical nucleation theory. The new model proposes a new cluster definition, which properly includes the effect of fluctuations, and it is consistent both thermodynamically and kinetically. The model is able to predict successfully the free energy of formation of the critical nucleus, using only macroscopic thermodynamic properties. It also accounts for the spinodal and provides excellent agreement with the result of recent simulations.

Multidelayed random walks: Theory and application to the neolithic transition in Europe

We present a model in which particles (or individuals of a biological population) disperse with a rest time between consecutive motions (or migrations) which may take several possible values from a discrete set. Particles (or individuals) may also react (or reproduce). We derive a new equation for the effective rest time T˜ of the random walk. Application to the neolithic transition in Europe makes it possible to derive more realistic theoretical values for its wavefront speed than those following from the single-delayed framework presented previously [J. Fort and V. Méndez, Phys. Rev. Lett. 82, 867 (1999)]. The new results are consistent with the archaeological observations of this important historical process

Senescence rates are determined by ranking on the fast-slow life-history continuum.

Comparative analyses of survival senescence by using life tables have identified generalizations including the observation that mammals senesce faster than similar-sized birds. These generalizations have been challenged because of limitations of life-table approaches and the growing appreciation that senescence is more than an increasing probability of death. Without using life tables, we examine senescence rates in annual individual fitness using 20 individual-based data sets of terrestrial vertebrates with contrasting life histories and body size. We find that senescence is widespread in the wild and equally likely to occur in survival and reproduction. Additionally, mammals senesce faster than birds because they have a faster life history for a given body size. By allowing us to disentangle the effects of two major fitness components our methods allow an assessment of the robustness of the prevalent life-table approach. Focusing on one aspect of life history - survival or recruitment - can provide reliable information on overall senescence.

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.

Reaction-diffusion lattice gas: Theory and computer results

We report on the study of nonequilibrium ordering in the reaction-diffusion lattice gas. It is a kinetic model that relaxes towards steady states under the simultaneous competition of a thermally activated creation-annihilation $(reaction$) process at temperature T, and a diffusion process driven by a heat bath at temperature T?T. The phase diagram as one varies T and T, the system dimension d, the relative priori probabilities for the two processes, and their dynamical rates is investigated. We compare mean-field theory, new Monte Carlo data, and known exact results for some limiting cases. In particular, no evidence of Landau critical behavior is found numerically when d=2 for Metropolis rates but Onsager critical points and a variety of first-order phase transitions.

Cooperation and game theory, free software or the #15m movement: Two examples for universities

Closing talk of the Open Access Week 2011 at the UOC, by Josep Jover. Why do altruistic strategies beat selfish ones in the spheres of both free software and the #15m movement? The #15m movement, like software but unlike tangible goods, cannot be owned. It can be used (by joining it) by an indeterminate number of people without depriving anyone else of the chance to do the same. And that turns everything on its head: how universities manage information and what their mission is in this new society. In the immediate future, universities will be valued not for the information they harbour, which will always be richer and more extensive beyond their walls, but rather for their capacity to create critical masses, whether of knowledge research, skill-building, or networks of peers... universities must implement the new model or risk becoming obsolete.