GLOBAL WELL-POSEDNESS AND NON-LINEAR STABILITY OF PERIODIC TRAVELING WAVES FOR A SCHRODINGER-BENJAMIN-ONO SYSTEM

The objective of this paper is two-fold: firstly, we develop a local and global (in time) well-posedness theory for a system describing the motion of two fluids with different densities under capillary-gravity waves in a deep water flow (namely, a Schrodinger-Benjamin-Ono system) for low-regularity initial data in both periodic and continuous cases; secondly, a family of new periodic traveling waves for the Schrodinger-Benjamin-Ono system is given: by fixing a minimal period we obtain, via the implicit function theorem, a smooth branch of periodic solutions bifurcating a Jacobian elliptic function called dnoidal, and, moreover, we prove that all these periodic traveling waves are nonlinearly stable by perturbations with the same wavelength.

Modeling resting-state functional networks when the cortex falls asleep: local and global changes.

The transition from wakefulness to sleep represents the most conspicuous change in behavior and the level of consciousness occurring in the healthy brain. It is accompanied by similarly conspicuous changes in neural dynamics, traditionally exemplified by the change from "desynchronized" electroencephalogram activity in wake to globally synchronized slow wave activity of early sleep. However, unit and local field recordings indicate that the transition is more gradual than it might appear: On one hand, local slow waves already appear during wake; on the other hand, slow sleep waves are only rarely global. Studies with functional magnetic resonance imaging also reveal changes in resting-state functional connectivity (FC) between wake and slow wave sleep. However, it remains unclear how resting-state networks may change during this transition period. Here, we employ large-scale modeling of the human cortico-cortical anatomical connectivity to evaluate changes in resting-state FC when the model "falls asleep" due to the progressive decrease in arousal-promoting neuromodulation. When cholinergic neuromodulation is parametrically decreased, local slow waves appear, while the overall organization of resting-state networks does not change. Furthermore, we show that these local slow waves are structured macroscopically in networks that resemble the resting-state networks. In contrast, when the neuromodulator decrease further to very low levels, slow waves become global and resting-state networks merge into a single undifferentiated, broadly synchronized network.

Local and global consistency properties for student placement

In the context of resource allocation on the basis of priorities, Ergin (2002) identifies a necessary and sufficient condition on the priority structure such that the student-optimal stable mechanism satisfies a consistency principle. Ergin (2002) formulates consistency as a local property based on a fixed population of agents and fixed resources -- we refer to this condition as local consistency and to his condition on the priority structure as local acyclicity. We identify a related but stronger necessary and sufficient condition (unit acyclicity) on the priority structure such that the student-optimal stable mechanism satisfies a more standard global consistency property. Next, we provide necessary and sufficient conditions for the student-optimal stable mechanism to satisfy converse consistency principles. We identify a necessary and sufficient condition (local shift-freeness) on the priority structure such that the student-optimal stable mechanism satisfies local converse consistency. Interestingly, local acyclicity implies local shift-freeness and hence the student-optimal stable mechanism more frequently satisfies local converse consistency than local consistency. Finally, in order for the student-optimal stable mechanism to be globally conversely consistent, one again has to impose unit acyclicity on the priority structure. Hence, unit acyclicity is a necessary and sufficient condition on the priority structure for the student-optimal stable mechanism to satisfy global consistency or global converse consistency.

The effects of physiologically plausible connectivity structure on local and global dynamics in large scale brain models.

Functionally relevant large scale brain dynamics operates within the framework imposed by anatomical connectivity and time delays due to finite transmission speeds. To gain insight on the reliability and comparability of large scale brain network simulations, we investigate the effects of variations in the anatomical connectivity. Two different sets of detailed global connectivity structures are explored, the first extracted from the CoCoMac database and rescaled to the spatial extent of the human brain, the second derived from white-matter tractography applied to diffusion spectrum imaging (DSI) for a human subject. We use the combination of graph theoretical measures of the connection matrices and numerical simulations to explicate the importance of both connectivity strength and delays in shaping dynamic behaviour. Our results demonstrate that the brain dynamics derived from the CoCoMac database are more complex and biologically more realistic than the one based on the DSI database. We propose that the reason for this difference is the absence of directed weights in the DSI connectivity matrix.

Local and global error models to improve uncertainty quantification

In groundwater applications, Monte Carlo methods are employed to model the uncertainty on geological parameters. However, their brute-force application becomes computationally prohibitive for highly detailed geological descriptions, complex physical processes, and a large number of realizations. The Distance Kernel Method (DKM) overcomes this issue by clustering the realizations in a multidimensional space based on the flow responses obtained by means of an approximate (computationally cheaper) model; then, the uncertainty is estimated from the exact responses that are computed only for one representative realization per cluster (the medoid). Usually, DKM is employed to decrease the size of the sample of realizations that are considered to estimate the uncertainty. We propose to use the information from the approximate responses for uncertainty quantification. The subset of exact solutions provided by DKM is then employed to construct an error model and correct the potential bias of the approximate model. Two error models are devised that both employ the difference between approximate and exact medoid solutions, but differ in the way medoid errors are interpolated to correct the whole set of realizations. The Local Error Model rests upon the clustering defined by DKM and can be seen as a natural way to account for intra-cluster variability; the Global Error Model employs a linear interpolation of all medoid errors regardless of the cluster to which the single realization belongs. These error models are evaluated for an idealized pollution problem in which the uncertainty of the breakthrough curve needs to be estimated. For this numerical test case, we demonstrate that the error models improve the uncertainty quantification provided by the DKM algorithm and are effective in correcting the bias of the estimate computed solely from the MsFV results. The framework presented here is not specific to the methods considered and can be applied to other combinations of approximate models and techniques to select a subset of realizations

Local and Global Feature Extraction for Invariant Object Recognition

Perceiving the world visually is a basic act for humans, but for computers it is still an unsolved problem. The variability present innatural environments is an obstacle for effective computer vision. The goal of invariant object recognition is to recognise objects in a digital image despite variations in, for example, pose, lighting or occlusion. In this study, invariant object recognition is considered from the viewpoint of feature extraction. Thedifferences between local and global features are studied with emphasis on Hough transform and Gabor filtering based feature extraction. The methods are examined with respect to four capabilities: generality, invariance, stability, and efficiency. Invariant features are presented using both Hough transform and Gabor filtering. A modified Hough transform technique is also presented where the distortion tolerance is increased by incorporating local information. In addition, methods for decreasing the computational costs of the Hough transform employing parallel processing and local information are introduced.

Developing markets of energy biomass – local and global perspectives

The thesis explores global and national-level issues related to the development of markets for biomass for energy. The thesis consists of five separate papers and provides insights on selected issues. The aim of Paper I was to identify methodological and statistical challenges in assessing international solid and liquid biofuels trade and provide an overview of the Finnish situation with respect to the status of international solid and liquid biofuels trade. We found that, for the Finnish case, it is possible to qualify direct and indirect trade volumes of biofuels. The study showed that indirect trade of biofuels has a highly significant role in Finland and may be a significant sector also in global biofuels trade. The purpose of Paper II was to provide a quantified insight into Finnish prospects for meeting the national 2020 renewable energy targets and concurrently becoming a largescale producer of forest-biomass-based second-generation biofuels for feeding increasing demand in European markets. We found that Finland has good opportunities to realise a scenario to meet 2020 renewable energy targets and for large-scale production of wood-based biofuels. The potential net export of transport biofuels from Finland in 2020 would correspond to 2–3% of European demand. Paper III summarises the global status of international solid and liquid biofuels trade as illuminated by several separate sources. International trade of biofuels was estimated at nearly 1 EJ for 2006. Indirect trade of biofuels through trading of industrial roundwood and material by-products comprises the largest proportion of the trading, with a share of about two thirds. The purpose of Paper IV was to outline a comprehensive picture of the coverage of various certification schemes and sustainability principles relating to the entire value-added chain of biomass and bioenergy. Regardless of the intensive work that has been done in the field of sustainability schemes and principles concerning use of biomass for energy, weaknesses still exist. The objective of Paper V was to clarify the alternative scenarios for the international biomass market until 2020 and identify the underlying steps needed toward a wellfunctioning and sustainable market for biomass for energy purposes. An overall conclusion drawn from this analysis concerns the enormous opportunities related to the utilisation of biomass for energy in the coming decades.

CBIR Using Local and Global Properties of Image Sub-blocks

This paper proposes a content based image retrieval (CBIR) system using the local colour and texture features of selected image sub-blocks and global colour and shape features of the image. The image sub-blocks are roughly identified by segmenting the image into partitions of different configuration, finding the edge density in each partition using edge thresholding, morphological dilation and finding the corner density in each partition. The colour and texture features of the identified regions are computed from the histograms of the quantized HSV colour space and Gray Level Co- occurrence Matrix (GLCM) respectively. A combined colour and texture feature vector is computed for each region. The shape features are computed from the Edge Histogram Descriptor (EHD). Euclidean distance measure is used for computing the distance between the features of the query and target image. Experimental results show that the proposed method provides better retrieving result than retrieval using some of the existing methods

A non-autonomous strongly damped wave equation: Existence and continuity of the pullback attractor

In this paper we consider the strongly damped wave equation with time-dependent terms u(tt) - Delta u - gamma(t)Delta u(t) + beta(epsilon)(t)u(t) = f(u), in a bounded domain Omega subset of R(n), under some restrictions on beta(epsilon)(t), gamma(t) and growth restrictions on the nonlinear term f. The function beta(epsilon)(t) depends on a parameter epsilon, beta(epsilon)(t) -> 0. We will prove, under suitable assumptions, local and global well-posedness (using the uniform sectorial operators theory), the existence and regularity of pullback attractors {A(epsilon)(t) : t is an element of R}, uniform bounds for these pullback attractors, characterization of these pullback attractors and their upper and lower semicontinuity at epsilon = 0. (C) 2010 Elsevier Ltd. All rights reserved.

Local and global magnetic properties of Zn1-xCoxO and Mn-doped GaAs thin films

Amorphous and crystalline thin films of Mn-doped(0.5%-10%) GaAs and crystalline thin films of Zn1-xCoxO(x = 3%-20%) were investigated by means of magnetic susceptibility and electron spin resonance (ESR). For the Mn-doped GaAs samples, our results show the absence of ferromagnetic ordering for the amorphous films in the 300 > T > 2 K temperature range, in contrast to the ferromagnetism found in crystalline films for T-C < 110 K. A single ESR line with a temperature independent g-value (g similar to 2) is observed for the amorphous films, and the behavior of this ESR linewidth depends on the level of crystallinity of the film. For the Mn-doped GaAs crystalline films, only a ferromagnetic mode is observed for T < TC when the film is ferromagnetic. Turning now the Zn1-xCoxO films, ferromagnetic loops were observed at room temperature for these films. The magnetization data show an increasing of the saturation magnetization M. as a function of x reaching a maximum value for x approximate to 10%. ESR experiments at T = 300 K in the same films show a strong anisotropic ferromagnetic mode (FMR) for x = 0.10.

An investigations on local and global behavior of a (SMA) oscillator of 3 - DOF driven by a limited power supply

SMART material systems offer great possibilities in terms of providing novel and economical solutions to engineering problems. The technological advantages of these materials over traditional ones are due to their unique microstructure and molecular properties. Smart materials such as shape memory alloys (SMA), has been used in such diverse areas of engineering science, nowadays. In this paper, we present a numerical investigation of the dynamics interaction of a nonideal structure (NIS). We analyze the phenomenon of the passage through resonance region in the steady state processes. We remarked that this kind of problem can lead to the so-called Sommerfeld effect: steady state frequencies of the DC motor will usually increase as more power (voltage) is given to it in a step-by-step fashion. When a resonance condition with the structure it is reached, the better part of this energy it is consumed to generate large amplitude vibrations of the foundation without sensible change of the motor frequency as before. The results obtained by using numerical simulations are discussed in details. Copyright © 2009 by ASME.