Nonlinear Resonance Interaction between Conjugate Circumferential Flexural Modes in Single-Walled Carbon Nanotubes

This paper presents an investigation on the dynamical properties of single-walled carbon nanotubes (SWCNTs), and nonlinear modal interaction and energy exchange are analysed in detail. Resonance interactions between two conjugate circumferential flexural modes (CFMs) are investigated. The nanotubes are analysed through a continuous shell model, and a thin shell theory is used to model the dynamics of the system; free-free boundary conditions are considered. The Rayleigh-Ritz method is applied to approximate linear eigenfunctions of the partial differential equations that govern the shell dynamics. An energy approach, based on Lagrange equations and series expansion of the displacements, is considered to reduce the initial partial differential equations to a set of nonlinear ordinary differential equations of motion. The model is validated in linear field (natural frequencies) by means of comparisons with literature. A convergence analysis is carried out in order to obtain the smallest modal expansion able to simulate the nonlinear regimes. The time evolution of the nonlinear energy distribution over the SWCNT surface is studied. The nonlinear dynamics of the system is analysed by means of phase portraits. The resonance interaction and energy transfer between the conjugate CFMs are investigated. A travelling wave moving along the circumferential direction of the SWCNT is observed

Forecasting high waters at Venice Lagoon using chaotic time series analisys and nonlinear neural netwoks

Time series analysis using nonlinear dynamics systems theory and multilayer neural networks models have been applied to the time sequence of water level data recorded every hour at 'Punta della Salute' from Venice Lagoon during the years 1980-1994. The first method is based on the reconstruction of the state space attractor using time delay embedding vectors and on the characterisation of invariant properties which define its dynamics. The results suggest the existence of a low dimensional chaotic attractor with a Lyapunov dimension, DL, of around 6.6 and a predictability between 8 and 13 hours ahead. Furthermore, once the attractor has been reconstructed it is possible to make predictions by mapping local-neighbourhood to local-neighbourhood in the reconstructed phase space. To compare the prediction results with another nonlinear method, two nonlinear autoregressive models (NAR) based on multilayer feedforward neural networks have been developed. From the study, it can be observed that nonlinear forecasting produces adequate results for the 'normal' dynamic behaviour of the water level of Venice Lagoon, outperforming linear algorithms, however, both methods fail to forecast the 'high water' phenomenon more than 2-3 hours ahead.Publicad

Analysis and simulation of metabolic networks: Application to HEPG2

Chemical toxicity in most of the cases has a metabolic component and metabolic pathways are the most studied biochemical reactions. For these reasons we have started to analyze modelling approaches for studying toxicity at molecular level using the metabolism and focusing in HepG2 cell lines. Two approaches have been investigated. The first consists on the analysis of metabolic fluxes in HepG2 under different toxicants concentrations by complex network analysis tools. This is important when a correlation between dose-response curves and metabolomic data has to be established. The second approach is based on the development and application of a simplified dynamic model of metabolism. This approach requires the specification of the biochemical reactions as well as their kinetic parameters and, therefore, at the moment, the degree of detail in the description of HepG2 metabolism is reduced. The results suggest that a combined approach starting from metabolic fluxes and then solving the kinetic equations as our experimental data and knowledge of metabolic pathways increases is the most promising avenue to develop a quantitative approach of toxicity at molecular level. In addition, there is the necessity to link the molecular level approach with the cell growth and mortality with an intermediate level that translates metabolism changes into measurable parameters in cell-based assays.JRC.DG.I.6-Systems toxicolog

Nonlinear vibration of continuous systems

Continuous systems, such as beams, membranes, plates, shells, and other structural/mechanical components, represent fundamental elements of mechanical systems in any field of engineering: Aerospace, Aeronautics, Automation, Automotive, Civil, Nuclear, Petroleum, and Railways. The modern designer is required to optimize structural elements to improve the performance-to-cost ratio, produce lightweight machines, and improve the efficiency. Such optimizations easily lead to a magnification of vibration/dynamic problems such as resonances, instabilities, and nonlinear behaviors. Therefore, the development of new methods of analysis, testing, and monitoring is greatly welcome. This special issue focuses on sharing recent advances and developments of theories, algorithms, and applications that involve the dynamics and vibrations of continuous systems. The contributions to this special issue include innovative theoretical studies, advanced numerical simulations, and new experimental approaches to investigate and better understand complex dynamic phenomena; more specifically, methods and theories for beams, membranes, plates, and shells; numerical approaches for structural elements; fluid-structure interaction; nonlinear acoustics; identification, diagnosis, friction models, and vehicle dynamics. Seventeen contributions have been received from all over the world: Canada, China, Kazakhstan, Italy, Macau, Spain, and USA. This shows the generalized interest on the topic. The following short description of the special issue content is organized by grouping the contributions in coherent subtopics

Nonlinear optical vibrations of single-walled carbon nanotubes.

We demonstrate a new specific phenomenon of the long-time resonant energy exchange in carbon nanotubes (CNTs), which is realized by two types of optical vibrations, the Circumferential Flexure Mode (CFM) and the Radial Breathing Mode (RBM). We show that the modified nonlinear Schrdinger equation, obtained in the framework of the nonlinear theory of elastic thin shells, allows us to describe the nonlinear dynamics of CNTs for specified frequency bands. Comparative analysis of the oscillations of the CFM and RBM branches shows the qualitative difference of nonlinear effects for these branches. While the nonlinear resonant interaction of the low-frequency modes in the CFM branch leads to energy capture in some domains of the CNT, the same interaction in the RBM branch does not demonstrate any tendency for energy localization. The reason lies in the distinction in the nonlinear terms in the equations of motion. While CFMs are characterized by soft polynomial nonlinearity, RBM dynamics is characterized by hard gradient nonlinearity. Moreover, in contrast to the CFM, the importance of nonlinearity in the case of RBM oscillations decreases as the length to radius ratio increases. Numerical integration of the equations of thin shell theory confirms the results of the analytical study

Nonlinear optical vibrations of single-walled carbon nanotubes.

We demonstrate a new specific phenomenon of the long-time resonant energy exchange in carbon nanotubes (CNTs), which is realized by two types of optical vibrations, the Circumferential Flexure Mode (CFM) and the Radial Breathing Mode (RBM). We show that the modified nonlinear Schrdinger equation, obtained in the framework of the nonlinear theory of elastic thin shells, allows us to describe the nonlinear dynamics of CNTs for specified frequency bands. Comparative analysis of the oscillations of the CFM and RBM branches shows the qualitative difference of nonlinear effects for these branches. While the nonlinear resonant interaction of the low-frequency modes in the CFM branch leads to energy capture in some domains of the CNT, the same interaction in the RBM branch does not demonstrate any tendency for energy localization. The reason lies in the distinction in the nonlinear terms in the equations of motion. While CFMs are characterized by soft polynomial nonlinearity, RBM dynamics is characterized by hard gradient nonlinearity. Moreover, in contrast to the CFM, the importance of nonlinearity in the case of RBM oscillations decreases as the length to radius ratio increases. Numerical integration of the equations of thin shell theory confirms the results of the analytical study

Description of stochastic and chaotic series using visibility graphs

Nonlinear time series analysis is an active field of research that studies the structure of complex signals in order to derive information of the process that generated those series, for understanding, modeling and forecasting purposes. In the last years, some methods mapping time series to network representations have been proposed. The purpose is to investigate on the properties of the series through graph theoretical tools recently developed in the core of the celebrated complex network theory. Among some other methods, the so-called visibility algorithm has received much attention, since it has been shown that series correlations are captured by the algorithm and translated in the associated graph, opening the possibility of building fruitful connections between time series analysis, nonlinear dynamics, and graph theory. Here we use the horizontal visibility algorithm to characterize and distinguish between correlated stochastic, uncorrelated and chaotic processes. We show that in every case the series maps into a graph with exponential degree distribution P (k) ~ exp(-{\lambda}k), where the value of {\lambda} characterizes the specific process. The frontier between chaotic and correlated stochastic processes, {\lambda} = ln(3/2), can be calculated exactly, and some other analytical developments confirm the results provided by extensive numerical simulations and (short) experimental time series

Dietary Nitrate: Effects on the health of weaning pigs and Antimicrobial activity on seven probiotic Bifidobacterium spp. strains

The potential role of nitrite as an antimicrobial substance in the stomach may be of some importance in the ecology of the gastrointestinal tract and in host physiology. It has been shown that nitrite, under the acidic conditions of the stomach, may kill gut pathogens like Salmonella enteritidis, Escherichia coli, Salmonella typhimurium, and Yersinia enterocolitica, whereas acid alone has only a bacteriostatic effect. An in vivo study was conducted in order to assess the effects of dietary nitrate on microbiota and on the health of the gut (particularly in the stomach and small intestine). 96 weaning pigs were fed a diet containing high nitrate levels (15 mg and 150 mg) and then challenged with Salmonella enterica serovar typhimurium. Differences in composition of the gut microbiota were assessed by analysing samples from the pigs: To date analysis of 48 pigs has been completed.. Preliminary results demonstrated no effect on the population densities of microbial groups either from the challenge or from nitrate intake. However, increasing the time from challenge decreased either the counts of LAB in the stomach and jejunum or of clostridia in the stomach. Bifidobacteria also decreased in the stomach contents as nitrate supplementation increased. Supplementing the feedstuff with high dietary nitrate intake and then challenging with Salmonella did not affect the gastric pH or the degree of ulceration in the pigs. The synergistic bactericidal effects of pH, nitrite and thiocyanate on seven probiotic Bifidobacterium spp. strains were also investigated in an in vitro study. The results of the in vitro study demonstrated that an inhibitory effect exists on the seven probiotic bifidobacteria investigated with an exposure longer than 2 hours and pH values < 5.0. Addition of thiocyanate also increased the susceptibility of the tested strains. In this in vitro study, the most resistant strains at all conditions were B. animalis subsp. lactis Ra 18 and P32 and B. choerinum Su 877, Su 837 and Su 891

SNPGreen : a Database to Navigate Across Plant SNP Arrays

In recent years, the use of genomic information in plant and animal species for genetic improvement, and related fields has become routine. In order to accommodate market requirements (i.e. genotyping cost), manufacturers of single nucleotide polymorphism (SNP) arrays, private companies and international consortia have developed a large number of arrays with different content and different SNP density. The number of currently available SNP arrays differs among species. There is a strong need to standardize and integrate array- specific (e.g. SNP IDs, allele coding) and species-specific (i.e. assemblies) SNP information. After the very positive response to SNPChiMp (bioinformatics.tecnoparco.org/SNPchimp), where we store and provide tools for the 6 major livestock species and more than 20 SNP arrays, we are now extending our family of tools to plant species. SNPGreen ( bioinformatics.tecnoparco.org/SNPgreen) currently includes 3 SNP arrays for Rice and Maize