Understanding the enhanced synchronization of delay-coupled networks with fluctuating topology

We study the dynamics of networks with coupling delay, from which the connectivity changes over time. The synchronization properties are shown to depend on the interplay of three time scales: the internal time scale of the dynamics, the coupling delay along the network links and time scale at which the topology changes. Concentrating on a linearized model, we develop an analytical theory for the stability of a synchronized solution. In two limit cases, the system can be reduced to an “effective” topology: in the fast switching approximation, when the network fluctuations are much faster than the internal time scale and the coupling delay, the effective network topology is the arithmetic mean over the different topologies. In the slow network limit, when the network fluctuation time scale is equal to the coupling delay, the effective adjacency matrix is the geometric mean over the adjacency matrices of the different topologies. In the intermediate regime, the system shows a sensitive dependence on the ratio of time scales, and on the specific topologies, reproduced as well by numerical simulations. Our results are shown to describe the synchronization properties of fluctuating networks of delay-coupled chaotic maps.     

An independent component analysis-based approach on ballistocardiogram artifact removing

Interest about simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data acquisition has rapidly increased during the last years because of the possibility that the combined method offers to join temporal and spatial resolution, providing in this way a powerful tool to investigate spontaneous and evoked brain activities. However, several intrinsic features of MRI scanning become sources of artifacts on EEG data. Noise sources of a highly predictable nature such as those related to the pulse MRI sequence and those determined by magnetic gradient switching during scanning do not represent a major problem and can be easily removed. On the contrary, the ballistocardiogram (BCG) artifact, a large signal visible on all EEG traces and related to cardiac activity inside the magnetic field, is determined by sources that are not fully stereotyped and causing important limitations in the use of artifact-removing strategies. Recently, it has been proposed to use independent component analysis (ICA) to remove BCG artifact from EEG signals. ICA is a statistical algorithm that allows blind separation of statistically independent sources when the only available information is represented by their linear combination. An important drawback with most ICA algorithms is that they exhibit a stochastic behavior: each run yields slightly different results such that the reliability of the estimated sources is difficult to assess. In this preliminary report, we present a method based on running the FastICA algorithm many times with slightly different initial conditions. Clustering structure in the signal space of the obtained components provides us with a new way to assess the reliability of the estimated sources.     

On the role of the colloidal stability of mesoporous silica nanoparticles as gene delivery vectors

Mesoporous silica nanoparticles have been synthesized and functionalized with four different types of molecules containing amino groups, i.e., with primary amines only, with quaternary amines, with quaternized cyclic amines, or with polyethylenimine (PEI), which is formed by primary, secondary, and tertiary amines. These nanoparticles were then incubated with reporter plasmids and the ability of the resulting complexes to transfect human cells was studied. Only nanoparticles functionalized with PEI were efficient for transfection. The agglomeration behavior and the electrokinetic potential of the nanoparticle–plasmid complexes have been studied, as well as their cell internalization behavior using a fluorescent-labeled plasmid that allows its monitorization by confocal microscopy. The results indicate that the efficiency of PEI-functionalized nanoparticles for transfection resides to some extent in the different characteristics imparted to the nanoparticles regarding agglomeration and surface charge behavior.     

Two-dimensional infrared spectroscopy detected by chirped pulse upconversion

A two-dimensional (2D) infrared spectrum of Mn2(CO)10 is measured by using chirped-pulse upconversion (CPU) of the nonlinear signal field plus a reference local oscillator. By converting the spectrum to the visible, a silicon CCD camera can be used. The method offers an attractive alternative to direct IR detection due to the technological maturity of silicon and its greater intrinsic detectivity over HgCdTe. Using CPU, we acquired a rephasing 2D IR spectrum in a few seconds.     

Textural changes during CO2 activation of chars: A fractal approach

In this paper two series of active carbons obtained at different flow rates of the activating agent, CO₂, are characterized in order to establish the different mechanisms of pore development during the activation step. This study complements previous works on textural development during the different steps in the process of obtaining active carbons: coal oxidation, coal pyrolysis and char gasification. As the characteristics of the original and intermediate materials are of capital importance in the pore development of active carbons, the properties of the active carbons, precursor chars and coals were considered and analyzed together. Mercury porosimetry and helium picnometry were used to determine classical textural parameters as well as to perform a more detailed study of the pore volume generation during the different conditions of the activation step. Data obtained from the mercury porosimetry determinations was also employed for fractal determinations according to the methodologies proposed by Friesen and Mikula, Zhang and Li and the procedure of Neimark. Average surface fractal dimensions as well as fractal profiles and local surface fractal dimensions were calculated. The use of different flow rates during the activation step produces changes not only in the ordinary textural parameters but also in the fractal characteristics of the active carbons. Activation at higher flow rates leads to smoother fractal profiles and also to lower values of the average surface fractal dimensions of the active carbons.     

General symmetries in optimal control

In this paper we study general symmetries for optimal control problems making use of the geometric formulation proposed in [7]. This framework allows us to reduce the number of equations associated with optimal control problems with symmetry and compare the solutions of the original system with the solutions of the reduced one. The reconstruction of the optimal controls starting from the reduced problem is also explored.     

Wavelet-based ultra-high compression of multidimensional NMR data sets

The application of a lossy data compression algorithm based on wavelet transform to 2D NMR spectra is presented. We show that this algorithm affords rapid and extreme compression ratios (e.g., 800:1), providing high quality reconstructed 2D spectra. The algorithm was evaluated to ensure that qualitative and quantitative information are retained in the compressed NMR spectra. Whilst the maximum compression ratio that can be achieved depends on the number of signals and on the difference between the most and the least intense peaks (dynamic range), a compression ratio of 80:1 is affordable even for the challenging case of homonuclear 2D experiments of large biomolecules.     

Letter: Models of Relativistic Particle with Curvature and Torsion Revisited

Models, describing relativistic particles, where Lagrangian densities depend linearly on both the curvature and the torsion of the trajectories, are revisited in D=3 space forms. The moduli spaces of trajectories are completely and explicitly determined using the Lancret program. The moduli subspaces of closed solitons in the three sphere are also determined.