The past distribution of pinus nigra arnold in northern iberia. Contribution from its macroremains.

The presence of Pinus nigra in central Spain, where its natural populations are very rare, has led to different interpretations of the current vegetation dynamics. Complementary to the available palynological evidence, macroremains provide local information of high taxonomic resolution that helps to reconstruct the palaeobiogeography of a given species. Here we present new macrofossil data from Tubilla del Lago, a small palaeolake located at the eastern part of the northern Iberian Meseta. We identified 17 wood samples and 71 cones on the basis of their wood anatomy and morphology, respectively. S ome of the fossil samples were radiocarbon dated (~4.230-3210 years cal BP). The results demonstrate the Holocene presence of P. nigra in the study area, where it is currently extinct. This evidence, together with other published palaeobotanical studies, indicates that the forests dominated by P. nigra must have had a larger importance on the landscape prior to the anthropogenic influence on the northern Iberian Meseta.

A new approach on the long term dynamics of neo's under Yarkorsky effect

To calculate the force associated with the Yarkovsky effect the temperature distribution on the surface of the asteroid should be determined; it depends on the asteroid orbit, size and shape, spin axis orientation and period, mass, density of surface layers, albedo, thermal conductivity, capacity and IR emissivity of the material. The uncertainty of many of these parameters invites to develop simplified methods to calculate the influence of the Yarkovsky effect on long term dynamics of asteroids. In this paper we present one of this method based in a special perturbation procedure developed in our group.

Icosahedral Ni nanowires formed from nanocontacts breaking: Identification and characterization by Molecular Dynamics

We present and discuss an algorithm to identify and characterize the long icosahedral structures (staggered pentagonal nanowires with 1-5-1-5 atomic structure) that appear in Molecular Dynamics simulations of metallic nanowires of different species subjected to stretching. The use of this algorithm allows the identification of pentagonal rings forming the icosahedral structure as well as the determination of its number np , and the maximum length of the pentagonal nanowire Lpm. The algorithm is tested with some ideal structures to show its ability to discriminate between pentagonal rings and other ring structures. We applied the algorithm to Ni nanowires with temperatures ranging between 4K and 865K, stretched along the [111], [100] and [110] directions. We studied statistically the formation of pentagonal nanowires obtaining the distributions of length Lpm and number of rings np as function of the temperature. The Lpm distribution presents a peaked shape, with peaks located at fixed distances whose separation corresponds to the distance between two consecutive pentagonal rings.

Spatio-temporal dynamics of viruses are differentially affected by parasitoids depending on the mode of transmission by their insect vectors.

Relationships between agents in multitrophic systems are complex and very specific. Insect-transmitted plant viruses are completely dependent on the behaviour and distribution patterns of their vectors. The presence of natural enemies may directly affect aphid behaviour and spread of plant viruses, as the escape response of aphids might cause a potential risk for virus dispersal. The spatio-temporal dynamics of Cucumber mosaic virus (CMV) and Cucurbit aphid-borne yellows virus (CABYV), transmitted by Aphis gossypii in a non-persistent and persistent manner, respectively, were evaluated at short and long term in the presence and absence of the aphid parasitoid, Aphidius colemani. SADIE methodology was used to study the distribution patterns of both the virus and its vector, and their degree of association. Results suggested that parasitoids promoted aphid dispersion at short term, which enhanced CMV spread, though consequences of parasitism suggest potential benefits for disease control at long term. Furthermore, A. colemani significantly limited the spread and incidence of the persistent virus CABYV at long term. The impact of aphid parasitoids on the dispersal of plant viruses with different transmission modes is discussed.

The Dynamics of High-Speed Railway Bridges: A Review of Design Issues and New Research for Lateral Dynamics

The dynamic effects of high-speed trains on viaducts are important issues for the design of the structures, as well as for the consideration of safe running conditions for the trains. In this work we start by reviewing the relevance of some basic design aspects. The significance of impact factor envelopes for moving loads is considered first. Resonance which may be achieved for high-speed trains requires dynamic analysis, for which some key aspects are discussed. The relevance of performing a longitudinal distribution of axle loads, the number of modes taken in analysis, and the consideration of vehicle-structure interaction are discussed with representative examples. The lateral dynamic effects of running trains on bridges is of importance for laterally compliant viaducts, such as some very tall structures erected in new high-speed lines. The relevance of this study is mainly for the safety of the traffic, considering both internal actions such as the hunting motion as well as external actions such as wind or earthquakes [1]. These studies require three-dimensional dynamic coupled vehicle-bridge models, and consideration of wheel to rail contact, a phenomenon which is complex and costly to model in detail. We describe here a fully nonlinear coupled model, described in absolute coordinates and incorporated into a commercial finite element framework [2]. The wheel-rail contact has been considered using a FastSim algorithm which provides a compromise between accuracy and computational cost, and captures the main nonlinear response of the contact interface. Two applications are presented, firstly to a vehicle subject to a strong wind gust traversing a bridge, showing the relevance of the nonlinear wheel-rail contact model as well as the dynamic interaction between bridge and vehicle. The second application is to a real HS viaduct with a long continuous deck and tall piers and high lateral compliance [3]. The results show the safety of the traffic as well as the importance of considering features such as track alignment irregularities.

Comparison of turbulence models for the computational fluid dynamics simulation of wind turbine wakes in the atmospheric boundary layer

An elliptic computational fluid dynamics wake model based on the actuator disk concept is used to simulate a wind turbine, approximated by a disk upon which a distribution of forces, defined as axial momentum sources, is applied on an incoming non-uniform shear flow. The rotor is supposed to be uniformly loaded with the exerted forces estimated as a function of the incident wind speed, thrust coefficient and rotor diameter. The model is assessed in terms of wind speed deficit and added turbulence intensity for different turbulence models and is validated from experimental measurements of the Sexbierum wind turbine experiment.

Collective Organization of Complex Networks: Emergent Scales, Vulnerability, and Targeting of Desired Dynamics

Cuando una colectividad de sistemas dinámicos acoplados mediante una estructura irregular de interacciones evoluciona, se observan dinámicas de gran complejidad y fenómenos emergentes imposibles de predecir a partir de las propiedades de los sistemas individuales. El objetivo principal de esta tesis es precisamente avanzar en nuestra comprensión de la relación existente entre la topología de interacciones y las dinámicas colectivas que una red compleja es capaz de mantener. Siendo este un tema amplio que se puede abordar desde distintos puntos de vista, en esta tesis se han estudiado tres problemas importantes dentro del mismo que están relacionados entre sí. Por un lado, en numerosos sistemas naturales y artificiales que se pueden describir mediante una red compleja la topología no es estática, sino que depende de la dinámica que se desarrolla en la red: un ejemplo son las redes de neuronas del cerebro. En estas redes adaptativas la propia topología emerge como consecuencia de una autoorganización del sistema. Para conocer mejor cómo pueden emerger espontáneamente las propiedades comúnmente observadas en redes reales, hemos estudiado el comportamiento de sistemas que evolucionan según reglas adaptativas locales con base empírica. Nuestros resultados numéricos y analíticos muestran que la autoorganización del sistema da lugar a dos de las propiedades más universales de las redes complejas: a escala mesoscópica, la aparición de una estructura de comunidades, y, a escala macroscópica, la existencia de una ley de potencias en la distribución de las interacciones en la red. El hecho de que estas propiedades aparecen en dos modelos con leyes de evolución cuantitativamente distintas que siguen unos mismos principios adaptativos sugiere que estamos ante un fenómeno que puede ser muy general, y estar en el origen de estas propiedades en sistemas reales. En segundo lugar, proponemos una medida que permite clasificar los elementos de una red compleja en función de su relevancia para el mantenimiento de dinámicas colectivas. En concreto, estudiamos la vulnerabilidad de los distintos elementos de una red frente a perturbaciones o grandes fluctuaciones, entendida como una medida del impacto que estos acontecimientos externos tienen en la interrupción de una dinámica colectiva. Los resultados que se obtienen indican que la vulnerabilidad dinámica es sobre todo dependiente de propiedades locales, por tanto nuestras conclusiones abarcan diferentes topologías, y muestran la existencia de una dependencia no trivial entre la vulnerabilidad y la conectividad de los elementos de una red. Finalmente, proponemos una estrategia de imposición de una dinámica objetivo genérica en una red dada e investigamos su validez en redes con diversas topologías que mantienen regímenes dinámicos turbulentos. Se obtiene como resultado que las redes heterogéneas (y la amplia mayora de las redes reales estudiadas lo son) son las más adecuadas para nuestra estrategia de targeting de dinámicas deseadas, siendo la estrategia muy efectiva incluso en caso de disponer de un conocimiento muy imperfecto de la topología de la red. Aparte de la relevancia teórica para la comprensión de fenómenos colectivos en sistemas complejos, los métodos y resultados propuestos podrán dar lugar a aplicaciones en sistemas experimentales y tecnológicos, como por ejemplo los sistemas neuronales in vitro, el sistema nervioso central (en el estudio de actividades síncronas de carácter patológico), las redes eléctricas o los sistemas de comunicaciones. ABSTRACT The time evolution of an ensemble of dynamical systems coupled through an irregular interaction scheme gives rise to dynamics of great of complexity and emergent phenomena that cannot be predicted from the properties of the individual systems. The main objective of this thesis is precisely to increase our understanding of the interplay between the interaction topology and the collective dynamics that a complex network can support. This is a very broad subject, so in this thesis we will limit ourselves to the study of three relevant problems that have strong connections among them. First, it is a well-known fact that in many natural and manmade systems that can be represented as complex networks the topology is not static; rather, it depends on the dynamics taking place on the network (as it happens, for instance, in the neuronal networks in the brain). In these adaptive networks the topology itself emerges from the self-organization in the system. To better understand how the properties that are commonly observed in real networks spontaneously emerge, we have studied the behavior of systems that evolve according to local adaptive rules that are empirically motivated. Our numerical and analytical results show that self-organization brings about two of the most universally found properties in complex networks: at the mesoscopic scale, the appearance of a community structure, and, at the macroscopic scale, the existence of a power law in the weight distribution of the network interactions. The fact that these properties show up in two models with quantitatively different mechanisms that follow the same general adaptive principles suggests that our results may be generalized to other systems as well, and they may be behind the origin of these properties in some real systems. We also propose a new measure that provides a ranking of the elements in a network in terms of their relevance for the maintenance of collective dynamics. Specifically, we study the vulnerability of the elements under perturbations or large fluctuations, interpreted as a measure of the impact these external events have on the disruption of collective motion. Our results suggest that the dynamic vulnerability measure depends largely on local properties (our conclusions thus being valid for different topologies) and they show a non-trivial dependence of the vulnerability on the connectivity of the network elements. Finally, we propose a strategy for the imposition of generic goal dynamics on a given network, and we explore its performance in networks with different topologies that support turbulent dynamical regimes. It turns out that heterogeneous networks (and most real networks that have been studied belong in this category) are the most suitable for our strategy for the targeting of desired dynamics, the strategy being very effective even when the knowledge on the network topology is far from accurate. Aside from their theoretical relevance for the understanding of collective phenomena in complex systems, the methods and results here discussed might lead to applications in experimental and technological systems, such as in vitro neuronal systems, the central nervous system (where pathological synchronous activity sometimes occurs), communication systems or power grids.

Web based interactive educational software introducing semiconductor laser dynamics: Sound Of Lasers (SOL)

In this work, educational software for intuitive understanding of the basic dynamic processes of semiconductor lasers is presented. The proposed tool is addressed to the students of optical communication courses, encouraging self consolidation of the subjects learned in lectures. The semiconductor laser model is based on the well known rate equations for the carrier density, photon density and optical phase. The direct modulation of the laser is considered with input parameters which can be selected by the user. Different options for the waveform, amplitude and frequency of thpoint. Simulation results are plotted for carrier density and output power versus time. Instantaneous frequency variations of the laser output are numerically shifted to the audible frequency range and sent to the computer loudspeakers. This results in an intuitive description of the “chirp” phenomenon due to amplitude-phase coupling, typical of directly modulated semiconductor lasers. In this way, the student can actually listen to the time resolved spectral content of the laser output. By changing the laser parameters and/or the modulation parameters,consequent variation of the laser output can be appreciated in intuitive manner. The proposed educational tool has been previously implemented by the same authors with locally executable software. In the present manuscript, we extend our previous work to a web based platform, offering improved distribution and allowing its use to the wide audience of the web.

Effect of the Legume Plant Host on Rhizobial Soil Population Dynamics

Rhizobium leguminosarum bv viciae (Rlv) is a soil bacterium able to establish specific root-nodule symbioses with legumes of four different genera: Pisum, Vicia, Lens and Lathyrus. Rlv isolates from nodules of any of these legumes can nodulate any of them; however, it has been shown that plants select specific rhizobial genotypes from those present in the soil (1,2). We have previously shown this at the genomic level by following a population genomics approach. Pool genomic sequences from 100 isolates from each of four plant species: P. sativum, L. culinaris, V. faba and V. sativa, show different, specific profiles at the single nucleotide polymorphism (SNP) level for relevant genes. In this work, the extent of Rlv selection from a well-characterized soil population by different legume plant hosts: P. sativum, L. culinaris, V. faba and V. sativa, after a medium-term mesocosm study is described. Direct soil isolates from each of these mesocosm studies have been tested for specific rhizobial genes (glnII and fnrN) and symbiotic genes (nodC and nifH). Different populations were characterized further by Sanger sequencing of both the rpoB phylogenetic marker gene and the symbiotic genes nodC and nifH. The distribution and size of the rhizobial population for each legume host showed changes during the medium-term mesocosm study. Particularly, a non-symbiotic group of rhizobia was enriched by all four hosts, in contrast to the symbiotic rhizobia profile, which was specific for each legume plant host.