On a new algorithm for time step integration of nonlinear systems

A new implicit algorithm for time step integration of finite element structural dynamic equations is presented. Convergence, stability and numerical damping properties are discussed. Due to the way nonlinear structural behavior is taken into account, the algorithm is expected to compare favorably with existing ones. Some simple numerical results are presented. A related explicit algorithm is also derived and shortly discussed

A framework for the construction of generative models for mesoscale structure in multilayer networks

Multilayer networks allow one to represent diverse and coupled connectivity patterns—such as time-dependence, multiple subsystems, or both—that arise in many applications and which are difficult or awkward to incorporate into standard network representations. In the study of multilayer networks, it is important to investigate mesoscale (i.e., intermediate-scale) structures, such as dense sets of nodes known as communities, to discover network features that are not apparent at the microscale or the macroscale. The ill-defined nature of mesoscale structure and its ubiquity in empirical networks make it crucial to develop generative models that can produce the features that one encounters in empirical networks. Key purposes of such models include generating synthetic networks with empirical properties of interest, benchmarking mesoscale-detection methods and algorithms, and inferring structure in empirical multilayer networks. In this paper, we introduce a framework for the construction of generative models for mesoscale structures in multilayer networks. Our framework provides a standardized set of generative models, together with an associated set of principles from which they are derived, for studies of mesoscale structures in multilayer networks. It unifies and generalizes many existing models for mesoscale structures in fully ordered (e.g., temporal) and unordered (e.g., multiplex) multilayer networks. One can also use it to construct generative models for mesoscale structures in partially ordered multilayer networks (e.g., networks that are both temporal and multiplex). Our framework has the ability to produce many features of empirical multilayer networks, and it explicitly incorporates a user-specified dependency structure between layers. We discuss the parameters and properties of our framework, and we illustrate examples of its use with benchmark models for community-detection methods and algorithms in multilayer networks

GENES ON THE MOVE: CANDIDATE GENES AND LONG-DISTANCE MIGRATION IN BIRDS

Bird migration is an adaptive strategy evolved to exploit the seasonal changes of resources by moving to different areas at different times of the year, as these become suitable. Migratory birds reach the breeding grounds when the food supplies enable them to breed and leave towards more suitable areas before the ecological conditions deteriorate; to this end, they must anticipate the changes in ecological conditions by weeks or even months to prepare for migration. Tis is allowed by the by the existence of an endogenous control of the annual schedule, that is kept in phase with seasons by means of external cues, such as photoperiod. The occurrence of a tight endogenous control of migration hint that migration is under a strong genetic influence and the broad among-species, -populations and -individuals differences in migratory traits are partly triggered by variation at genes controlling migratory behaviour. Identifying which genes underline the phenotypic variation observed in natural populations, and to which extent, is of broad evolutionary and conservation interest. It has been suggested that variation in migratory traits could be the outcome of polymorphism at relatively few regions or loci with additive effects on a variety other genes. Hence, in recent years, several studies have focused on the polymorphism of phenological candidate genes, that may explain the variability of behavioural traits. Most of the phenological candidate genes studied so far are involved in the \u2018core circadian oscillator\u2019 (CCO), an auto-regulated negative feedback loop that modulates the photoperiodic response and sets the circadian and circannual rhythms. The Clock and Adcyap1 genes are among the best studied candidate genes involved in the photoperiodic response and in the circannual rhythmicity. Both the genes show a polymorphism in short tandem repeat sequences that may affect the gene function or the post-transcriptional processes and that have been linked to variation in the timing of seasonal events and other behavioural traits in several vertebrate species. However, no study has investigated the effect of Clock and Adcyap1 genotype on migration phenology and on migration distance directly in wild birds. Hence, the aim of this thesis is to investigate whether polymorphism at candidate genes affects the timing of migration and the migration distance in avian species, with particular reference to Clock and Adcyap1 genes. I found Clock allele size to predict the timing the timing of migration in different long-distance migratory bird species. The direction of the association was coherent with previous studies and across species (longer allele being associated with a delayed phenology), the only exception being the willow warbler (Phylloscopus trochilus). Moreover, Adcyap1 allele size was associated with the migration distance in a Nearctic-Neotropical migratory bird. In such species the genotype-phenotype association was stronger among the northern, long-distance migratory populations than among the southern ones. Finally, I found that Clock allele size increased with breeding latitude across species and that Clock gene diversity was depleted among the species migrating over longer distances, that show delayed and more concentrated migration periods. To conclude, the findings from this thesis deepen our understanding of the role of polymorphism at candidate gene in shaping avian behaviour, by highlighting that Clock and Adcyap1 polymorphisms are involved in the control of migration

New insights into antikaon-nucleon scattering and the structure of the Lambda(1405)

We perform a combined analysis of antikaon-nucleon scattering cross sections and the recent SIDDHARTA kaonic hydrogen data in the framework of a coupled-channel Bethe-Salpeter approach at next-to-leading order in the chiral expansion of the effective potential. We find a precise description of the antikaon-proton scattering amplitudes and are able to extract accurate values of the scattering lengths, a0=-1.81^+0.30_-0.28 + i 0.92^+0.29_-0.23 fm, a1=+0.48^+0.12_-0.11 + i 0.87^+0.26_-0.20 fm. We also discuss the two-pole structure of the Lambda(1405).Comment: 7 pages, 4 figure

How Equalization Techniques Affect the TCP Performance of MC-CDMA Systems in Correlated Fading Channels

This paper investigates the impact of several equalization techniques for multicarrier code division multiple access systems on the performance at both lower and upper layers (i.e., physical and TCP layers). Classical techniques such as maximal ratio combining, equal gain combining, orthogonality restoring combining, minimum mean square error, as well as a partial equalization (PE) are investigated in time- and frequency-correlated fading channels with various numbers of interferers. Their impact on the performance at upper level is then studied. The results are obtained through an integrated simulation platform carefully reproducing all main aspects affecting the quality of service perceived by the final user, allowing an investigation of the real gain produced by signal processing techniques at TCP level

A New Measurement of Kaonic Hydrogen X rays

The $\bar{K}N$ system at threshold is a sensitive testing ground for low energy QCD, especially for the explicit chiral symmetry breaking. Therefore, we have measured the $K$-series x rays of kaonic hydrogen atoms at the DA$\Phi$NE electron-positron collider of Laboratori Nazionali di Frascati, and have determined the most precise values of the strong-interaction energy-level shift and width of the $1s$ atomic state. As x-ray detectors, we used large-area silicon drift detectors having excellent energy and timing resolution, which were developed especially for the SIDDHARTA experiment. The shift and width were determined to be $\epsilon_{1s} = -283 \pm 36 \pm 6 {(syst)}$ eV and $\Gamma_{1s} = 541 \pm 89 {(stat)} \pm 22 {(syst)}$ eV, respectively. The new values will provide vital constraints on the theoretical description of the low-energy $\bar{K}N$ interaction.Comment: 5 figures, submitted to Physics Letters

The unimportance of the spurious root of time integration algorithms for structural dynamics

Most commonly used second-order-accurate, dissipative time integration algorithms for structural dynamics possess a spurious root. For an algorithm to be accurate, it has been suggested that the spurious root must be small and ideally be zero in the low-frequency limit. In the paper we show that good accuracy can be achieved even if the spurious root does not tend towards zero in the low-frequency limit. This permits more flexibility in the design of time integration algorithms. As an example, we present an algorithm that has greater accuracy than several other dissipative algorithms even though for all frequencies its spurious root is non-zero. We also show that the degraded performance of the Bazzi-Ρ algorithm is not due to its non-zero spurious root.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/50422/1/1640100803_ftp.pd

An Optimal Self-Stabilizing Firing Squad

Consider a fully connected network where up to $t$ processes may crash, and all processes start in an arbitrary memory state. The self-stabilizing firing squad problem consists of eventually guaranteeing simultaneous response to an external input. This is modeled by requiring that the non-crashed processes "fire" simultaneously if some correct process received an external "GO" input, and that they only fire as a response to some process receiving such an input. This paper presents FireAlg, the first self-stabilizing firing squad algorithm. The FireAlg algorithm is optimal in two respects: (a) Once the algorithm is in a safe state, it fires in response to a GO input as fast as any other algorithm does, and (b) Starting from an arbitrary state, it converges to a safe state as fast as any other algorithm does.Comment: Shorter version to appear in SSS0