961 resultados para inclusions in time scales


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We provide some properties for absolutely continuous functions in time scales. Then we consider a class of dynamical inclusions in time scales and extend to this class a convergence result of a sequence of almost inclusion trajectories to a limit which is actually a trajectory of the inclusion in question. We also introduce the so called Euler solution to dynamical systems in time scales and prove its existence. A combination of the existence of Euler solutions with the compactness type result described above ensures the existence of an actual trajectory for the dynamical inclusion when the setvalued vector field is nonempty, compact, convex and has closed graph. © 2012 Springer-Verlag.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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The Sun-Earth connection is studied using long-term measurements from the Sun and from the Earth. The auroral activity is shown to correlate to high accuracy with the smoothed sunspot numbers. Similarly, both geomagnetic activity and global surface temperature anomaly can be linked to cyclic changes in the solar activity. The interlinked variations in the solar magnetic activity and in the solar irradiance cause effects that can be observed both in the Earth's biosphere and in the electromagnetic environment. The long-term data sets suggest that the increase in geomagnetic activity and surface temperatures are related (at least partially) to longer-term solar variations, which probably include an increasing trend superposed with a cyclic behavior with a period of about 90 years.

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In this paper we consider the problem of differential inclusion in time scales whose vector field is a multifunction, that is, a function that maps points to sets. It is provided conditions of existence without requiring compactness of the vector field; it is required that the vector field is closed, convex, and lower semicontinuous. In previous work in literature, it is required that the field is either scalar or compact, convex, and has closed graph.

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The role of nutrients, such as phosphorus (P), and their impact on primary productivity and the fluctuations in atmospheric CO2 over glacial-interglacial periods are intensely debated. Suggestions as to the importance of P evolved from an earlier proposal that P actively participated in changing productivity rates and therefore climate change, to most recent ones that changes in the glacial ocean inventory of phosphorus were important but not influential if compared to other macronutrients, such as nitrate. Using new data coming from a selection of ODP sites, we analyzed the distribution of oceanic P sedimentary phases and calculate reactive P burial fluxes, and we show how P burial fluxes changed over the last glacial-interglacial period at these sites. Concentrations of reactive P are generally lower during glacial times, while mass accumulation rates (MAR) of reactive P show higher variability. If we extrapolate for the analyzed sites, we may assume that in general glacial burial fluxes of reactive P are lower than those during interglacial periods by about 8%, because the lack of burial of reactive P on the glacial shelf reduced in size, was apparently not compensated by burial in other regions of the ocean. Using the calculated changes in P burial, we evaluate their possible impact on the phosphate inventory in the world oceans. Using a simple mathematical approach, we find that these changes alone could have increased the phosphate inventory of glacial ocean waters by 17-40% compared to interglacial stages. Variations in the distribution of sedimentary P phases at the investigated sites seem to indicate that at the onset of interglacial stages, shallower sites experienced an increase in reactive P concentrations, which seems to point to P-richer waters at glacial terminations. All these findings would support the Shelf-Nutrient Hypothesis, which assumes that during glacial low stands nutrients are transferred from shallow sites to deep sea with possible feedback on the carbon cycle.

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We propose to show in this paper, that the time series obtained from biological systems such as human brain are invariably nonstationary because of different time scales involved in the dynamical process. This makes the invariant parameters time dependent. We made a global analysis of the EEG data obtained from the eight locations on the skull space and studied simultaneously the dynamical characteristics from various parts of the brain. We have proved that the dynamical parameters are sensitive to the time scales and hence in the study of brain one must identify all relevant time scales involved in the process to get an insight in the working of brain.

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The play operator has a fundamental importance in the theory of hysteresis. It was studied in various settings as shown by P. Krejci and Ph. Laurencot in 2002. In that work it was considered the Young integral in the frame of Hilbert spaces. Here we study the play in the frame of the regulated functions (that is: the ones having only discontinuities of the first kind) on a general time scale T (that is: with T being a nonempty closed set of real numbers) with values in a Banach space. We will be showing that the dual space in this case will be defined as the space of operators of bounded semivariation if we consider as the bilinearity pairing the Cauchy-Stieltjes integral on time scales.

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The aim of this paper is to compare 18 reference evapotranspiration models to the standard Penman-Monteith model in the Jaboticabal, Sao Paulo, region for the following time scales: daily, 5-day, 15-day and seasonal. A total of 5 years of daily meteorological data was used for the following analyses: accuracy (mean absolute percentage error, Mape), precision (R-2) and tendency (bias) (systematic error, SE). The results were also compared at the 95% probability level with Tukey's test. The Priestley-Taylor (1972) method was the most accurate for all time scales, the Tanner-Pelton (1960) method was the most accurate in the winter, and the Thornthwaite (1948) method was the most accurate of the methods that only used temperature data in the equations.

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Despite the huge number of works considering fractional derivatives or derivatives on time scales some basic facts remain to be evaluated. Here we will be showing that the fractional derivative of monomials is in fact an entire derivative considered on an appropriate time scale.

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Changes in bioavailability of phosphorus (P) during pedogenesis and ecosystem development have been shown for geogenic calcium phosphate (Ca-P). However, very little is known about long-term changes of biogenic Ca-P in soil. Long-term transformation characteristics of biogenic Ca-P were examined using anthropogenic soils along a chronosequence from centennial to millennial time scales. Phosphorus fractionation of Anthrosols resulted in overall consistency with the Walker and Syers model of geogenic Ca-P transformation during pedogenesis. The biogenic Ca-P (e.g., animal and fish bones) disappeared to 3% of total P within the first ca. 2,000 years of soil development. This change concurred with increases in P adsorbed on metal-oxides surfaces, organic P, and occluded P at different pedogenic time. Phosphorus K-edge X-ray absorption near-edge structure (XANES) spectroscopy revealed that the crystalline and therefore thermodynamically most stable biogenic Ca-P was transformed into more soluble forms of Ca-P over time. While crystalline hydroxyapatite (34% of total P) dominated Ca-P species after about 600-1,000 years, beta-tricalcium phosphate increased to 16% of total P after 900-1,100 years, after which both Ca-P species disappeared. Iron-associated P was observable concurrently with Ca-P disappearance. Soluble P and organic P determined by XANES maintained relatively constant (58-65%) across the time scale studied. Disappearance of crystalline biogenic Ca-P on a time scale of a few thousand years appears to be ten times faster than that of geogenic Ca-P.

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Neural dynamic processes correlated over several time scales are found in vivo, in stimulus-evoked as well as spontaneous activity, and are thought to affect the way sensory stimulation is processed. Despite their potential computational consequences, a systematic description of the presence of multiple time scales in single cortical neurons is lacking. In this study, we injected fast spiking and pyramidal (PYR) neurons in vitro with long-lasting episodes of step-like and noisy, in-vivo-like current. Several processes shaped the time course of the instantaneous spike frequency, which could be reduced to a small number (1-4) of phenomenological mechanisms, either reducing (adapting) or increasing (facilitating) the neuron's firing rate over time. The different adaptation/facilitation processes cover a wide range of time scales, ranging from initial adaptation (<10 ms, PYR neurons only), to fast adaptation (<300 ms), early facilitation (0.5-1 s, PYR only), and slow (or late) adaptation (order of seconds). These processes are characterized by broad distributions of their magnitudes and time constants across cells, showing that multiple time scales are at play in cortical neurons, even in response to stationary stimuli and in the presence of input fluctuations. These processes might be part of a cascade of processes responsible for the power-law behavior of adaptation observed in several preparations, and may have far-reaching computational consequences that have been recently described.

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Since no single experimental or modeling technique provides data that allow a description of transport processes in clays and clay minerals at all relevant scales, several complementary approaches have to be combined to understand and explain the interplay between transport relevant phenomena. In this paper molecular dynamics simulations (MD) were used to investigate the mobility of water in the interlayer of montmorillonite (Mt), and to estimate the influence of mineral surfaces and interlayer ions on the water diffusion. Random Walk (RW) simulations based on a simplified representation of pore space in Mt were used to estimate and understand the effect of the arrangement of Mt particles on the meso- to macroscopic diffusivity of water. These theoretical calculations were complemented with quasielastic neutron scattering (QENS) measurements of aqueous diffusion in Mt with two pseudo-layers of water performed at four significantly different energy resolutions (i.e. observation times). The size of the interlayer and the size of Mt particles are two characteristic dimensions which determine the time dependent behavior of water diffusion in Mt. MD simulations show that at very short time scales water dynamics has the characteristic features of an oscillatory motion in the cage formed by neighbors in the first coordination shell. At longer time scales, the interaction of water with the surface determines the water dynamics, and the effect of confinement on the overall water mobility within the interlayer becomes evident. At time scales corresponding to an average water displacement equivalent to the average size of Mt particles, the effects of tortuosity are observed in the meso- to macroscopic pore scale simulations. Consistent with the picture obtained in the simulations, the QENS data can be described using a (local) 3D diffusion at short observation times, whereas at sufficiently long observation times a 2D diffusive motion is clearly observed. The effects of tortuosity measured in macroscopic tracer diffusion experiments are in qualitative agreement with RW simulations. By using experimental data to calibrate molecular and mesoscopic theoretical models, a consistent description of water mobility in clay minerals from the molecular to the macroscopic scale can be achieved. In turn, simulations help in choosing optimal conditions for the experimental measurements and the data interpretation. (C) 2014 Elsevier B.V. All rights reserved.

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Cognitive neuroscience boils down to describing the ways in which cognitive function results from brain activity. In turn, brain activity shows complex fluctuations, with structure at many spatio-temporal scales. Exactly how cognitive function inherits the physical dimensions of neural activity, though, is highly non-trivial, and so are generally the corresponding dimensions of cognitive phenomena. As for any physical phenomenon, when studying cognitive function, the first conceptual step should be that of establishing its dimensions. Here, we provide a systematic presentation of the temporal aspects of task-related brain activity, from the smallest scale of the brain imaging technique's resolution, to the observation time of a given experiment, through the characteristic time scales of the process under study. We first review some standard assumptions on the temporal scales of cognitive function. In spite of their general use, these assumptions hold true to a high degree of approximation for many cognitive (viz. fast perceptual) processes, but have their limitations for other ones (e.g., thinking or reasoning). We define in a rigorous way the temporal quantifiers of cognition at all scales, and illustrate how they qualitatively vary as a function of the properties of the cognitive process under study. We propose that each phenomenon should be approached with its own set of theoretical, methodological and analytical tools. In particular, we show that when treating cognitive processes such as thinking or reasoning, complex properties of ongoing brain activity, which can be drastically simplified when considering fast (e.g., perceptual) processes, start playing a major role, and not only characterize the temporal properties of task-related brain activity, but also determine the conditions for proper observation of the phenomena. Finally, some implications on the design of experiments, data analyses, and the choice of recording parameters are discussed.