Dispersal (Entropy) and Recognition (Information) as Foundations of Emergence and Dissolvence

The objective of this essay is to reflect on a possible relation between entropy and emergence. A qualitative, relational approach is followed. We begin by highlighting that entropy includes the concept of dispersal, relevant to our enquiry. Emergence in complex systems arises from the coordinated behavior of their parts. Coordination in turn necessitates recognition between parts, i.e., information exchange. What will be argued here is that the scope of recognition processes between parts is increased when preceded by their dispersal, which multiplies the number of encounters and creates a richer potential for recognition. A process intrinsic to emergence is dissolvence (aka submergence or top-down constraints), which participates in the information-entropy interplay underlying the creation, evolution and breakdown of higher-level entities.

A comparison of mean phase difference and generalized least squares for analyzing single-case data

The present study focuses on single-case data analysis and specifically on two procedures for quantifying differences between baseline and treatment measurements The first technique tested is based on generalized least squares regression analysis and is compared to a proposed non-regression technique, which allows obtaining similar information. The comparison is carried out in the context of generated data representing a variety of patterns (i.e., independent measurements, different serial dependence underlying processes, constant or phase-specific autocorrelation and data variability, different types of trend, and slope and level change). The results suggest that the two techniques perform adequately for a wide range of conditions and researchers can use both of them with certain guarantees. The regression-based procedure offers more efficient estimates, whereas the proposed non-regression procedure is more sensitive to intervention effects. Considering current and previous findings, some tentative recommendations are offered to applied researchers in order to help choosing among the plurality of single-case data analysis techniques.

The Uncertain generalized probabilistic weighted average and its application in the theory of expertons

A new model for dealing with decision making under risk by considering subjective and objective information in the same formulation is here presented. The uncertain probabilistic weighted average (UPWA) is also presented. Its main advantage is that it unifies the probability and the weighted average in the same formulation and considering the degree of importance that each case has in the analysis. Moreover, it is able to deal with uncertain environments represented in the form of interval numbers. We study some of its main properties and particular cases. The applicability of the UPWA is also studied and it is seen that it is very broad because all the previous studies that use the probability or the weighted average can be revised with this new approach. Focus is placed on a multi-person decision making problem regarding the selection of strategies by using the theory of expertons.

An operator formulation of the multiscale finite-volume method with correction function

The multiscale finite-volume (MSFV) method has been derived to efficiently solve large problems with spatially varying coefficients. The fine-scale problem is subdivided into local problems that can be solved separately and are coupled by a global problem. This algorithm, in consequence, shares some characteristics with two-level domain decomposition (DD) methods. However, the MSFV algorithm is different in that it incorporates a flux reconstruction step, which delivers a fine-scale mass conservative flux field without the need for iterating. This is achieved by the use of two overlapping coarse grids. The recently introduced correction function allows for a consistent handling of source terms, which makes the MSFV method a flexible algorithm that is applicable to a wide spectrum of problems. It is demonstrated that the MSFV operator, used to compute an approximate pressure solution, can be equivalently constructed by writing the Schur complement with a tangential approximation of a single-cell overlapping grid and incorporation of appropriate coarse-scale mass-balance equations.

On the success of generalized food deception in orchids : the role of sympatric rewarding species and pollinators

Résumé : La production de nectar assure aux plantes entomophiles un important succès reproducteur. Malgré cela, de nombreuses espèces d'orchidées ne produisent pas de nectar. La majorité de ces orchidées dites trompeuses exploitent simplement l'instinct des pollinisateurs généralistes, qui les pousse à chercher du nectar dans les fleurs. Afin d'optimiser la récolte de nectar, les pollinisateurs apprennent à différencier les fleurs trompeuses des nectarifères, et à concentrer leurs visites sur ces dernières, au détriment des plantes trompeuses. Chez les orchidées non autogames, la reproduction est assurée uniquement par les pollinisateurs. L'apprentissage des pollinisateurs a donc un impact négatif sur la reproduction des orchidées trompeuses. Cependant, les caractéristiques d'une espèce trompeuse et des espèces nectarifères au sein d'une communauté végétale peuvent affecter l'apprentissage et le taux de visite des pollinisateurs aux plantes trompeuses. J'ai réalisé des expériences en milieu naturel et en milieu contrôlé, pour déterminer si les caractéristiques florales, spatiales et temporelles des communautés affectent le taux de visite et le succès reproducteur de plantes trompeuses. Une agrégation spatiale élevée des plantes trompeuses et des plantes nectarifères diminue le succès reproducteur des plantes trompeuses. De plus, les pollinisateurs visitent plus souvent l'espèce trompeuse Iorsque ses fleurs sont de couleur similaire à celles de l'espèce nectarifère. Cet effet bénéfique de la similarité pour la couleur des fleurs s'accentue si les deux espèces sont mélangées et proches spatialement, ou si l'espèce trompeuse fleurit après l'espèce nectarifère. Enfin, le comportement des pollinisateurs n'est pas tout de suite affecté lorsque les caractéristiques de la communauté changent. Les caractéristiques des communautés végétales affectent donc la reproduction des espèces trompeuses. Bien que L'absence de coûts associés à la production de nectar, l'exportation efficace de pollen et la production de graines de qualité dont bénéficient les orchidées trompeuses favorisent Ieur maintien, les caractéristiques de la communauté peuvent aussi y contribuer. Mon étude fournit donc une explication alternative et complémentaire au maintien des orchidées trompeuses. Je conclus par une discussion des implications possibles de ces résultats sur le maintien et l'évolution des orchidées trompeuses, en tenant compte de la dynamique des caractéristiques des communautés végétales naturelles. Abstract : Despite the importance of producing food to ensure a high reproductive success, many orchid species lack such rewards. The majority of deceptive orchids simply exploit the instinctive food-foraging behaviour of generalist pollinators. This strategy is termed generalized food deception. To optimize their foraging efficiency, pollinators can learn to discriminate deceptive from rewarding flowers and to focus their visits to the rewarding plants, to the disadvantage of the deceptive plants. Because the reproductive success of non-autogamous orchids entirely relies on pollinator visitation rate, pollinator learning decreases the reproductive success of deceptive orchids. However, the characteristics of deceptive and rewarding plants within a community may affect pollinator learning and visitation rate to a deceptive orchid. Therefore, the biological characteristics of natural plant communities may be crucial to the maintenance of generalized food deceptive orchids. My study focused on the floral, spatial and temporal characteristics of plant communities. I used both in and ex sitar experiments to investigate whether these characteristics influence pollinator visitation rates and the reproductive success of deceptive orchids. A high spatial aggregation of both deceptive and rewarding species decreased the reproductive success of the deceptive species. Also, being of similar flower colour to rewarding sympatric species increased pollinator visitation rates to a deceptive species. The beneficial effect of flower colour similarity was even more pronounced when both species were spatially closely mingled or when the deceptive species flowered after the rewarding species. Finally, pollinator behaviour was unaffected in the short term by a change in the characteristics of plant communities, indicating that pollinators need time to learn under new conditions. Thus, the characteristics of plant communities may crucially affect the reproductive success of deceptive orchids. Although the absence of costs associated with nectar production, the efficient pollen export and the high seed quality of deceptive orchids may favour their maintenance, the characteristics of plant communities may also contribute to it. Therefore, my study provides an alternative yet complementary explanation to the maintenance of generalized food deceptive orchids in natural populations. I discuss the possible implications for the maintenance and the evolution of generalized food deceptive orchids with regards to the floral and temporal dynamics of natural plant communities.

Multiscale assessment of plant diversity in wooded pastures of the Jura mountains

Résumé La diminution de la biodiversité, à toutes les échelles spatiales et sur l'ensemble de la planète, compte parmi les problèmes les plus préoccupants de notre époque. En terme de conservation, il est aujourd'hui primordial de mieux comprendre les mécanismes qui créent et maintiennent la biodiversité dans les écosystèmes naturels ou anthropiques. La présente étude a pour principal objectif d'améliorer notre compréhension des patrons de biodiversité végétale et des mécanismes sous jacents, dans un écosystème complexe, riche en espèces et à forte valeur patrimoniale, les pâturages boisés jurassiens. Structure et échelle spatiales sont progressivement reconnues comme des dimensions incontournables dans l'étude des patrons de biodiversité. De plus, ces deux éléments jouent un rôle central dans plusieurs théories écologiques. Toutefois, peu d'hypothèses issues de simulations ou d'études théoriques concernant le lien entre structure spatiale du paysage et biodiversité ont été testées de façon empirique. De même, l'influence des différentes composantes de l'échelle spatiale sur les patrons de biodiversité est méconnue. Cette étude vise donc à tester quelques-unes de ces hypothèses et à explorer les patrons spatiaux de biodiversité dans un contexte multi-échelle, pour différentes mesures de biodiversité (richesse et composition en espèces) à l'aide de données de terrain. Ces données ont été collectées selon un plan d'échantillonnage hiérarchique. Dans un premier temps, nous avons testé l'hypothèse élémentaire selon laquelle la richesse spécifique (le nombre d'espèces sur une surface donnée) est liée à l'hétérogénéité environnementale quelque soit l'échelle. Nous avons décomposé l'hétérogénéité environnementale en deux parties, la variabilité des conditions environnementales et sa configuration spatiale. Nous avons montré que, en général, la richesse spécifique augmentait avec l'hétérogénéité de l'environnement : elle augmentait avec le nombre de types d'habitats et diminuait avec l'agrégation spatiale de ces habitats. Ces effets ont été observés à toutes les échelles mais leur nature variait en fonction de l'échelle, suggérant une modification des mécanismes. Dans un deuxième temps, la structure spatiale de la composition en espèces a été décomposée en relation avec 20 variables environnementales et 11 traits d'espèces. Nous avons utilisé la technique de partition de la variation et un descripteur spatial, récemment développé, donnant accès à une large gamme d'échelles spatiales. Nos résultats ont montré que la structure spatiale de la composition en espèces végétales était principalement liée à la topographie, aux échelles les plus grossières, et à la disponibilité en lumière, aux échelles les plus fines. La fraction non-environnementale de la variation spatiale de la composition spécifique avait une relation complexe avec plusieurs traits d'espèces suggérant un lien avec des processus biologiques tels que la dispersion, dépendant de l'échelle spatiale. Dans un dernier temps, nous avons testé, à plusieurs échelles spatiales, les relations entre trois composantes de la biodiversité : la richesse spécifique totale d'un échantillon (diversité gamma), la richesse spécifique moyenne (diversité alpha), mesurée sur des sous-échantillons, et les différences de composition spécifique entre les sous-échantillons (diversité beta). Les relations deux à deux entre les diversités alpha, beta et gamma ne suivaient pas les relations attendues, tout du moins à certaines échelles spatiales. Plusieurs de ces relations étaient fortement dépendantes de l'échelle. Nos résultats ont mis en évidence l'importance du rapport d'échelle (rapport entre la taille de l'échantillon et du sous-échantillon) lors de l'étude des patrons spatiaux de biodiversité. Ainsi, cette étude offre un nouvel aperçu des patrons spatiaux de biodiversité végétale et des mécanismes potentiels permettant la coexistence des espèces. Nos résultats suggèrent que les patrons de biodiversité ne peuvent être expliqués par une seule théorie, mais plutôt par une combinaison de théories. Ils ont également mis en évidence le rôle essentiel joué par la structure spatiale dans la détermination de la biodiversité, quelque soit le composant de la biodiversité considéré. Enfin, cette étude souligne l'importance de prendre en compte plusieurs échelles spatiales et différents constituants de l'échelle spatiale pour toute étude relative à la diversité spécifique. Abstract The world-wide loss of biodiversity at all scales has become a matter of urgent concern, and improving our understanding of local drivers of biodiversity in natural and anthropogenic ecosystems is now crucial for conservation. The main objective of this study was to further our comprehension of the driving forces controlling biodiversity patterns in a complex and diverse ecosystem of high conservation value, wooded pastures. Spatial pattern and scale are central to several ecological theories, and it is increasingly recognized that they must be taken -into consideration when studying biodiversity patterns. However, few hypotheses developed from simulations or theoretical studies have been tested using field data, and the evolution of biodiversity patterns with different scale components remains largely unknown. We test several such hypotheses and explore spatial patterns of biodiversity in a multi-scale context and using different measures of biodiversity (species richness and composition), with field data. Data were collected using a hierarchical sampling design. We first tested the simple hypothesis that species richness, the number of species in a given area, is related to environmental heterogeneity at all scales. We decomposed environmental heterogeneity into two parts: the variability of environmental conditions and its spatial configuration. We showed that species richness generally increased with environmental heterogeneity: species richness increased with increasing number of habitat types and with decreasing spatial aggregation of those habitats. Effects occurred at all scales but the nature of the effect changed with scale, suggesting a change in underlying mechanisms. We then decomposed the spatial structure of species composition in relation to environmental variables and species traits using variation partitioning and a recently developed spatial descriptor, allowing us to capture a wide range of spatial scales. We showed that the spatial structure of plant species composition was related to topography at the coarsest scales and insolation at finer scales. The non-environmental fraction of the spatial variation in species composition had a complex relationship with several species traits, suggesting a scale-dependent link to biological processes, particularly dispersal. Finally, we tested, at different spatial scales, the relationships between different components of biodiversity: total sample species richness (gamma diversity), mean species .richness (alpha diversity), measured in nested subsamples, and differences in species composition between subsamples (beta diversity). The pairwise relationships between alpha, beta and gamma diversity did not follow the expected patterns, at least at certain scales. Our result indicated a strong scale-dependency of several relationships, and highlighted the importance of the scale ratio when studying biodiversity patterns. Thus, our results bring new insights on the spatial patterns of biodiversity and the possible mechanisms allowing species coexistence. They suggest that biodiversity patterns cannot be explained by any single theory proposed in the literature, but a combination of theories is sufficient. Spatial structure plays a crucial role for all components of biodiversity. Results emphasize the importance of considering multiple spatial scales and multiple scale components when studying species diversity.

A Generalized Model Study of Scour Around Bridge Piers and Abutments, HR-24, 1953

Four classes of variables are apparent in the problem of scour around bridge piers and abutments--geometry of piers and abutments, stream-flow characteristics, sediment characteristics, and geometry of site. The laboratory investigation, from its inception, has been divided into four phases based on these classes. In each phase the variables in three of the classes are held constant and those in the pertinent class are varied. To date, the first three phases have been studied. Typical scour bole patterns related to the geometry of the pier or abutment have been found. For equilibrium conditions of scour with uniform sand, the velocity of flow and the sand size do not appear to have any measurable effects on the depth of scour. This result is especially encouraging in the search for correlation between model and prototype since it would indicate that, primarily, only the depth of flow might be involved in the scale effect. The technique of model testing has been simplified, therefore, because rate of sediment transportation does not need to be scaled. Prior to the establishment of equilibrium conditions, however, depths of scour in excess of those for equilibrium conditions have been found. A concept of active scour as an imbalance between sediment transport capacity and rate of sediment supply has been used to explain the laboratory observations.

Fourier transform convolution integrals applied to generalized Born molecular volume.

Generalized Born methods are currently among the solvation models most commonly used for biological applications. We reformulate the generalized Born molecular volume method initially described by (Lee et al, 2003, J Phys Chem, 116, 10606; Lee et al, 2003, J Comp Chem, 24, 1348) using fast Fourier transform convolution integrals. Changes in the initial method are discussed and analyzed. Finally, the method is extensively checked with snapshots from common molecular modeling applications: binding free energy computations and docking. Biologically relevant test systems are chosen, including 855-36091 atoms. It is clearly demonstrated that, precision-wise, the proposed method performs as good as the original, and could better benefit from hardware accelerated boards.

Kinetic equations for difussion in the presence of entropic barriers

We use the mesoscopic nonequilibrium thermodynamics theory to derive the general kinetic equation of a system in the presence of potential barriers. The result is applied to a description of the evolution of systems whose dynamics is influenced by entropic barriers. We analyze in detail the case of diffusion in a domain of irregular geometry in which the presence of the boundaries induces an entropy barrier when approaching the exact dynamics by a coarsening of the description. The corresponding kinetic equation, named the Fick-Jacobs equation, is obtained, and its validity is generalized through the formulation of a scaling law for the diffusion coefficient which depends on the shape of the boundaries. The method we propose can be useful to analyze the dynamics of systems at the nanoscale where the presence of entropy barriers is a common feature.

The minimum tree for a given zero-entropy period

We answer the following question: given any n∈ℕ, which is the minimum number of endpoints en of a tree admitting a zero-entropy map f with a periodic orbit of period n? We prove that en=s1s2…sk−∑i=2ksisi+1…sk, where n=s1s2…sk is the decomposition of n into a product of primes such that si≤si+1 for 1≤ientropy: if f has a periodic orbit of period m with em>e, then the topological entropy of f is positive

Wave-height hazard analysis in Eastern Coast of Spain : Bayesian approach using generalized Pareto distribution

Standard practice of wave-height hazard analysis often pays little attention to the uncertainty of assessed return periods and occurrence probabilities. This fact favors the opinion that, when large events happen, the hazard assessment should change accordingly. However, uncertainty of the hazard estimates is normally able to hide the effect of those large events. This is illustrated using data from the Mediterranean coast of Spain, where the last years have been extremely disastrous. Thus, it is possible to compare the hazard assessment based on data previous to those years with the analysis including them. With our approach, no significant change is detected when the statistical uncertainty is taken into account. The hazard analysis is carried out with a standard model. Time-occurrence of events is assumed Poisson distributed. The wave-height of each event is modelled as a random variable which upper tail follows a Generalized Pareto Distribution (GPD). Moreover, wave-heights are assumed independent from event to event and also independent of their occurrence in time. A threshold for excesses is assessed empirically. The other three parameters (Poisson rate, shape and scale parameters of GPD) are jointly estimated using Bayes' theorem. Prior distribution accounts for physical features of ocean waves in the Mediterranean sea and experience with these phenomena. Posterior distribution of the parameters allows to obtain posterior distributions of other derived parameters like occurrence probabilities and return periods. Predictives are also available. Computations are carried out using the program BGPE v2.0

Spatiotemporal adaptive multiscale multiphysics simulations of two-phase flow

We present a spatiotemporal adaptive multiscale algorithm, which is based on the Multiscale Finite Volume method. The algorithm offers a very efficient framework to deal with multiphysics problems and to couple regions with different spatial resolution. We employ the method to simulate two-phase flow through porous media. At the fine scale, we consider a pore-scale description of the flow based on the Volume Of Fluid method. In order to construct a global problem that describes the coarse-scale behavior, the equations are averaged numerically with respect to auxiliary control volumes, and a Darcy-like coarse-scale model is obtained. The space adaptivity is based on the idea that a fine-scale description is only required in the front region, whereas the resolution can be coarsened elsewhere. Temporal adaptivity relies on the fact that the fine-scale and the coarse-scale problems can be solved with different temporal resolution (longer time steps can be used at the coarse scale). By simulating drainage under unstable flow conditions, we show that the method is able to capture the coarse-scale behavior outside the front region and to reproduce complex fluid patterns in the front region.

Estimating parameters for generalized mass action models using constraint propagation.

As modern molecular biology moves towards the analysis of biological systems as opposed to their individual components, the need for appropriate mathematical and computational techniques for understanding the dynamics and structure of such systems is becoming more pressing. For example, the modeling of biochemical systems using ordinary differential equations (ODEs) based on high-throughput, time-dense profiles is becoming more common-place, which is necessitating the development of improved techniques to estimate model parameters from such data. Due to the high dimensionality of this estimation problem, straight-forward optimization strategies rarely produce correct parameter values, and hence current methods tend to utilize genetic/evolutionary algorithms to perform non-linear parameter fitting. Here, we describe a completely deterministic approach, which is based on interval analysis. This allows us to examine entire sets of parameters, and thus to exhaust the global search within a finite number of steps. In particular, we show how our method may be applied to a generic class of ODEs used for modeling biochemical systems called Generalized Mass Action Models (GMAs). In addition, we show that for GMAs our method is amenable to the technique in interval arithmetic called constraint propagation, which allows great improvement of its efficiency. To illustrate the applicability of our method we apply it to some networks of biochemical reactions appearing in the literature, showing in particular that, in addition to estimating system parameters in the absence of noise, our method may also be used to recover the topology of these networks.