974 resultados para TEMPORAL CORRELATION


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In this thesis a modified Canon IR optometer was used to record static and continuous responses of accommodation during sustained visual tasks. The instrument was assessed with regard to the ocular exit pupil used, its frequency response and noise levels. Experimental work concerned essentially the temporal characteristics and neurological basis of the accommodative mechanism. In the absence of visual stimuli, the accommodative system assumes a resting or tonic accommodative (TA) position, which may be modified by periods of sustained fixation. The rate of regression from a near task to TA in darkness has exhibited differences between regression rates for enunetropes (EMMs) compared with late-onset myopes (WMs). The rate of accommodative regression from a task set at 3D above TA was examined for a group of 10 EMMs and 10 LOMs for 3 conditions: saline, timolol and betaxolol. Timolol retarded the regression to TA for a sub-group of EMMs. The patterns of regression for the remaining emmetropes mirrored that for the LOMs, the drugs showing no difference in rate of regression compared with the saline condition. This provides support for the conjecture that LOMs and certain EMMs appear to be deficient in a sympathetic inhibitory component to the ciliary muscle which may attenuate adaptational changes in tonus and which leave them susceptible to the development of LOM. It is well established that the steady-state accommodative response is characterised by temporal changes in lens power having 2 dominant frequency components: a low frequency component (LFC: < 0.6Hz) and a high frequency component (HFC: 1.0-2.2Hz). This thesis investigates various aspects of these microfluctuations of accommodation.The HFC of accommodative fluctuations was shown to be present in central and peripheral lens zones, although the magnitude of the rms of accommodative microfluctuations was found to be reduced in the lens periphery. These findings concur with the proposal that the lens capsule acts as a force distributor, transmitting the tension from the zonules evenly over the whole of the lens surface.An investigation into the correlation between arterial pulse and the HFC of accommodative fluctuations showed that the peak frequency of the HFC was governed by the arterial pulse frequency. It was proposed that the microflucutations comprised a combination of neurological control (LFC) and physiological variations (HFC).The effect of timolol maleate on the steady-state accommodative response for a group of 10 emmetropes showed that timolol reduced significantly the rms of accommodative microfluctuations in treated but not untreated eyes. Consequently, the effect was considered to be locally, rather than systemically induced.The influence of the sympathetic system on within-task measurements of accommodation was examined by recording the accommodative response of 3 subjects to a sinusoidally moving target at 6 temporal frequencies from 0.05Hz to 0.5Hz for 3 drug conditions: saline, timolol and betaxolol. Timolol caused a reduced gain for frequencies below 0.3 whereas betaxolol reduced accommodative gain for all frequencies. It was proposed that the results for timolol were consistent with temporal response characteristics of sympathetic innervation of the ciliary muscle whereas the betaxolol results were thought to be a manifestation of fatigue resulting from the CNS depressant effect of the drug.

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The origin of linear instability resulting in rotating sheared accretion flows has remained a controversial subject for a long time. While some explanations of such non-normal transient growth of disturbances in the Rayleigh stable limit were available for magnetized accretion flows, similar instabilities in the absence of magnetic perturbations remained unexplained. This dichotomy was resolved in two recent publications by Chattopadhyay and co-workers [Mukhopadhyay and Chattopadhyay, J. Phys. A 46, 035501 (2013)1751-811310.1088/1751-8113/46/3/035501; Nath, Phys. Rev. E 88, 013010 (2013)PLEEE81539-375510.1103/PhysRevE.88.013010] where it was shown that such instabilities, especially for nonmagnetized accretion flows, were introduced through interaction of the inherent stochastic noise in the system (even a "cold" accretion flow at 3000 K is too "hot" in the statistical parlance and is capable of inducing strong thermal modes) with the underlying Taylor-Couette flow profiles. Both studies, however, excluded the additional energy influx (or efflux) that could result from nonzero cross correlation of a noise perturbing the velocity flow, say, with the noise that is driving the vorticity flow (or equivalently the magnetic field and magnetic vorticity flow dynamics). Through the introduction of such a time symmetry violating effect, in this article we show that nonzero noise cross correlations essentially renormalize the strength of temporal correlations. Apart from an overall boost in the energy rate (both for spatial and temporal correlations, and hence in the ensemble averaged energy spectra), this results in mutual competition in growth rates of affected variables often resulting in suppression of oscillating Alfven waves at small times while leading to faster saturations at relatively longer time scales. The effects are seen to be more pronounced with magnetic field fluxes where the noise cross correlation magnifies the strength of the field concerned. Another remarkable feature noted specifically for the autocorrelation functions is the removal of energy degeneracy in the temporal profiles of fast growing non-normal modes leading to faster saturation with minimum oscillations. These results, including those presented in the previous two publications, now convincingly explain subcritical transition to turbulence in the linear limit for all possible situations that could now serve as the benchmark for nonlinear stability studies in Keplerian accretion disks.

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We present experimental measurements of intensity spatiotemporal dynamics in quasi-CW Raman fiber laser. Depending on the power, the laser operates in different spatio-temporal regimes varying from partial mode-locking near the generation threshold to almost stochastic radiation and a generation of short-lived pulses at high power. The transitions between the generation regimes are evident in intensity spatio-temporal dynamics. Two-dimensional auto-correlation functions provide an additional insight into temporal and spatial properties of the observed regimes.

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Quantifying the relationship between mesozooplankton and water quality parameters identifies the factors that structure the mesozooplankton community and can be used to generate hypotheses regarding the mechanisms that control the mesozooplankton population and potentially the trophic network. To investigate this relationship, mesozooplankton and water quality data were collected in Florida Bay from 1994 to 2004. Three key characteristics were found in the mesozooplankton community structure: (1) there are significant differences between the four sub-regions of Florida Bay; (2) there is a break in May of 1997 with significant differences before and after this date; and (3) there is a positive correlation between mesozooplankton abundance and salinity. The latter two characteristics are closely correlated with predator abundance, indicating the importance of top-down control. Hypersaline periods appear to provide a refuge from predators, allowing mesozooplankton to increase in abundance despite the increased physiological stress.

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Computer networks produce tremendous amounts of event-based data that can be collected and managed to support an increasing number of new classes of pervasive applications. Examples of such applications are network monitoring and crisis management. Although the problem of distributed event-based management has been addressed in the non-pervasive settings such as the Internet, the domain of pervasive networks has its own characteristics that make these results non-applicable. Many of these applications are based on time-series data that possess the form of time-ordered series of events. Such applications also embody the need to handle large volumes of unexpected events, often modified on-the-fly, containing conflicting information, and dealing with rapidly changing contexts while producing results with low-latency. Correlating events across contextual dimensions holds the key to expanding the capabilities and improving the performance of these applications. This dissertation addresses this critical challenge. It establishes an effective scheme for complex-event semantic correlation. The scheme examines epistemic uncertainty in computer networks by fusing event synchronization concepts with belief theory. Because of the distributed nature of the event detection, time-delays are considered. Events are no longer instantaneous, but duration is associated with them. Existing algorithms for synchronizing time are split into two classes, one of which is asserted to provide a faster means for converging time and hence better suited for pervasive network management. Besides the temporal dimension, the scheme considers imprecision and uncertainty when an event is detected. A belief value is therefore associated with the semantics and the detection of composite events. This belief value is generated by a consensus among participating entities in a computer network. The scheme taps into in-network processing capabilities of pervasive computer networks and can withstand missing or conflicting information gathered from multiple participating entities. Thus, this dissertation advances knowledge in the field of network management by facilitating the full utilization of characteristics offered by pervasive, distributed and wireless technologies in contemporary and future computer networks.

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A combination of statistical and interpolation methods and Geographic Information System (GIS) spatial analysis was used to evaluate the spatial and temporal changes in groundwater Cl− concentrations in Collier and Lee Counties (southwestern Florida), and Miami-Dade and Broward Counties (southeastern Florida), since 1985. In southwestern Florida, the average Cl− concentrations in the shallow wells (0–43 m) in Collier and Lee Counties increased from 132 mg L−1 in 1985 to 230 mg L−1 in 2000. The average Cl− concentrations in the deep wells (>43 m) of southwestern Florida increased from 392 mg L−1 in 1985 to 447 mg L−1 in 2000. Results also indicated a positive correlation between the mean sea level and Cl− concentrations and between the mean sea level and groundwater levels for the shallow wells. Concentrations in the Biscayne Aquifer (southeastern Florida) were significantly higher than those of southwestern Florida. The average Cl− concentrations increased from 159 mg L−1 in 1985 to 470 mg L−1 in 2010 for the shallow wells (<33 m) and from 1360 mg L−1 in 1985 to 2050 mg L−1 in 2010 for the deep wells (>33 m). In the Biscayne Aquifer, wells showed a positive or negative correlation between mean sea level and Cl− concentrations according to their location with respect to the saltwater intrusion line. Wells located inland behind canal control structures and west of the saltwater intrusion line showed negative correlation values, whereas wells located east of the saltwater intrusion line showed positive values. Overall, the results indicated that since 1985, there was a potential decline in the available freshwater resources estimated at about 12–17% of the available drinking-quality groundwater of the southeastern study area located in the Biscayne Aquifer.

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The soil heat flux and soil thermal diffusivity are important components of the surface energy balance, especially in ar id and semi-arid regions. The obj ective of this work was to carry out to estimate the soil heat flux from th e soil temperature measured at a single depth, based on the half-order time derivative met hod proposed by Wang and Bras (1999), and to establish a method capable of es timating the thermal diffusivity of the soil, based on the half order derivative, from the temporal series of soil temperature at two depths. The results obtained in the estimates of soil heat flux were compared with the values of soil heat flux measured through flux plates, and the thermal di ffusivity estimated was compared with the measurements carried out in situ. The results obtained showed excellent concordance between the estimated and measured soil heat flux, with correlation (r), coeffici ent of determination (R 2 ) and standard error (W/m 2 ) of: r = 0.99093, R 2 = 0.98194 and error = 2.56 (W/m 2 ) for estimated period of 10 days; r = 0,99069, R 2 = 0,98147 and error = 2.59 (W/m 2 ) for estimated period of 30 days; and r = 0,98974, R 2 = 0,97958 and error = 2.77 (W/m 2 ) for estimated period of 120 days. The values of thermal di ffusivity estimated by the proposed method showed to be coherent and consis tent with in situ measured va lues, and with the values found in the literature usi ng conventional methods.

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Pre-treatment HCV quasispecies complexity and diversity may predict response to interferon based anti-viral therapy. The objective of this study was to retrospectively (1) examine temporal changes in quasispecies prior to the start of therapy and (2) investigate extensively quasispecies evolution in a group of 10 chronically infected patients with genotype 3a, treated with pegylated alpha 2a-Interferon and ribavirin. The degree of sequence heterogeneity within the hypervariable region 1 was assessed by analyzing 20-30 individual clones in serial serum samples. Genetic parameters, including amino acid Shannon entropy, Hamming distance and genetic distance were calculated for each sample. Treatment outcome was divided into (1) sustained virological responders (SVR) and (2) treatment failure (TF).Our results indicate, (1) quasispecies complexity and diversity are lower in the SVR group, (2) quasispecies vary temporally and (3) genetic heterogeneity at baseline can be used to predict treatment outcome. We discuss the results from the perspective of replicative homeostasis. We discuss the results from the perspective of replicative homeostasis.

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Recent research into resting-state functional magnetic resonance imaging (fMRI) has shown that the brain is very active during rest. This thesis work utilizes blood oxygenation level dependent (BOLD) signals to investigate the spatial and temporal functional network information found within resting-state data, and aims to investigate the feasibility of extracting functional connectivity networks using different methods as well as the dynamic variability within some of the methods. Furthermore, this work looks into producing valid networks using a sparsely-sampled sub-set of the original data.

In this work we utilize four main methods: independent component analysis (ICA), principal component analysis (PCA), correlation, and a point-processing technique. Each method comes with unique assumptions, as well as strengths and limitations into exploring how the resting state components interact in space and time.

Correlation is perhaps the simplest technique. Using this technique, resting-state patterns can be identified based on how similar the time profile is to a seed region’s time profile. However, this method requires a seed region and can only identify one resting state network at a time. This simple correlation technique is able to reproduce the resting state network using subject data from one subject’s scan session as well as with 16 subjects.

Independent component analysis, the second technique, has established software programs that can be used to implement this technique. ICA can extract multiple components from a data set in a single analysis. The disadvantage is that the resting state networks it produces are all independent of each other, making the assumption that the spatial pattern of functional connectivity is the same across all the time points. ICA is successfully able to reproduce resting state connectivity patterns for both one subject and a 16 subject concatenated data set.

Using principal component analysis, the dimensionality of the data is compressed to find the directions in which the variance of the data is most significant. This method utilizes the same basic matrix math as ICA with a few important differences that will be outlined later in this text. Using this method, sometimes different functional connectivity patterns are identifiable but with a large amount of noise and variability.

To begin to investigate the dynamics of the functional connectivity, the correlation technique is used to compare the first and second halves of a scan session. Minor differences are discernable between the correlation results of the scan session halves. Further, a sliding window technique is implemented to study the correlation coefficients through different sizes of correlation windows throughout time. From this technique it is apparent that the correlation level with the seed region is not static throughout the scan length.

The last method introduced, a point processing method, is one of the more novel techniques because it does not require analysis of the continuous time points. Here, network information is extracted based on brief occurrences of high or low amplitude signals within a seed region. Because point processing utilizes less time points from the data, the statistical power of the results is lower. There are also larger variations in DMN patterns between subjects. In addition to boosted computational efficiency, the benefit of using a point-process method is that the patterns produced for different seed regions do not have to be independent of one another.

This work compares four unique methods of identifying functional connectivity patterns. ICA is a technique that is currently used by many scientists studying functional connectivity patterns. The PCA technique is not optimal for the level of noise and the distribution of the data sets. The correlation technique is simple and obtains good results, however a seed region is needed and the method assumes that the DMN regions is correlated throughout the entire scan. Looking at the more dynamic aspects of correlation changing patterns of correlation were evident. The last point-processing method produces a promising results of identifying functional connectivity networks using only low and high amplitude BOLD signals.

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Computer networks produce tremendous amounts of event-based data that can be collected and managed to support an increasing number of new classes of pervasive applications. Examples of such applications are network monitoring and crisis management. Although the problem of distributed event-based management has been addressed in the non-pervasive settings such as the Internet, the domain of pervasive networks has its own characteristics that make these results non-applicable. Many of these applications are based on time-series data that possess the form of time-ordered series of events. Such applications also embody the need to handle large volumes of unexpected events, often modified on-the-fly, containing conflicting information, and dealing with rapidly changing contexts while producing results with low-latency. Correlating events across contextual dimensions holds the key to expanding the capabilities and improving the performance of these applications. This dissertation addresses this critical challenge. It establishes an effective scheme for complex-event semantic correlation. The scheme examines epistemic uncertainty in computer networks by fusing event synchronization concepts with belief theory. Because of the distributed nature of the event detection, time-delays are considered. Events are no longer instantaneous, but duration is associated with them. Existing algorithms for synchronizing time are split into two classes, one of which is asserted to provide a faster means for converging time and hence better suited for pervasive network management. Besides the temporal dimension, the scheme considers imprecision and uncertainty when an event is detected. A belief value is therefore associated with the semantics and the detection of composite events. This belief value is generated by a consensus among participating entities in a computer network. The scheme taps into in-network processing capabilities of pervasive computer networks and can withstand missing or conflicting information gathered from multiple participating entities. Thus, this dissertation advances knowledge in the field of network management by facilitating the full utilization of characteristics offered by pervasive, distributed and wireless technologies in contemporary and future computer networks.

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Short-term changes in sea surface conditions controlling the thermohaline circulation in the northern North Atlantic are expected to be especially efficient in perturbing global climate stability. Here we assess past variability of sea surface temperature (SST) in the northeast Atlantic and Norwegian Sea during Marine Isotope Stage (MIS) 2 and, in particular, during the Last Glacial Maximum (LGM). Five high-resolution SST records were established on a meridional transect (53°N-72°N) to trace centennial-scale oscillations in SST and sea-ice cover. We used three independent computational techniques (SIMMAX modern analogue technique, Artificial Neural Networks (ANN), and Revised Analog Method (RAM)) to reconstruct SST from planktonic foraminifer census counts. SIMMAX and ANN reproduced short-term SST oscillations of similar magnitude and absolute levels, while RAM, owing to a restrictive analog selection, appears less suitable for reconstructing "cold end" SST. The SIMMAX and ANN SST reconstructions support the existence of a weak paleo-Norwegian Current during Dansgaard-Oeschger (DO) interstadials number 4, 3, 2, and 1. During the LGM, two warm incursions of 7°C water to occurred in the northern North Atlantic but ended north of the Iceland Faroe Ridge. A rough numerical estimate shows that the near-surface poleward heat transfer from 53° across the Iceland-Faroe Ridge up to to 72° N dropped to less than 60% of the modern value during DO interstadials and to almost zero during DO stadials. Summer sea ice was generally confined to the area north of 70°N and only rarely expanded southward along the margins of continental ice sheets. Internal LGM variability of North Atlantic (>40°N) SST in the GLAMAP 2000 compilation (Sarnthein et al., 2003, doi:10.1029/2002PA000771; Pflaumann et al., 2003, doi:10.1029/2002PA000774) indicates maximum instability in the glacial subpolar gyre and at the Iberian Margin, while in the Nordic Seas, SST was continuously low.

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O presente estudo, propõe-se explorar a relação entre os constructos de solidão e depressão, contribuindo para esclarecer em que medida a primeira pode ser considerada uma entidade diagnóstica separada da depressão ou pelo contrário, apenas percebida na relação com a mesma. Pretendeu-se averiguar se existem indivíduos sem depressão que apresentem significativos níveis de solidão. Nesta análise privilegiamos, ainda, a perspetiva temporal, pretendemos verificar se há diferenças significativas na evolução do sentimento de solidão, após o período intervalar de três meses. Participaram, neste estudo, uma amostra de 60 indivíduos com idades compreendidas entre os 40 e os 86 anos, sendo a média aproximada de 52 anos. Os instrumentos utilizados para recolher os dados foram um breve Questionário Sociodemográfico; a adaptação portuguesa da Escala de Solidão da UCLA e a Escala Geriátrica de Depressão (GDS). Os dados foram submetidos a análise pelos princípios da estatística paramétrica. Neste estudo a fidedignidade global demonstrou ser elevada sendo o valor de Alpha Cronbach’s de 0,939.A hipótese central foi confirmada constatando-se que, apesar de existir uma associação estatisticamente significativa entre a solidão e a depressão, existem indivíduos sem depressão que apresentam elevados níveis de solidão (p>0,001). Não se verificou uma relação de prevalência da solidão no género feminino e a mesma foi maior em grupos etários mais elevados, no entanto, essa diferença não se revelou estatisticamente significativa. Recorrendo aos testes do qui-quadrado da independência; de concordância Kappa de cohen e ao teste t de student, concluiu-se que existe uma associação significativa de concordância moderada entre a solidão, ao longo do tempo. Esta conclusão reforça a análise da manutenção dos níveis de solidão quando não existe intervenção terapêutica específica. / This study aims to explore the relationship between the constructs of loneliness and depression, helping to clarify how far the former can be considered a separate diagnostic entity of depression or on the contrary, only perceived in relation to the same. We sought to determine whether there are individuals without depression who present significant levels of loneliness. In this analysis we also focus on the temporal perspective. We plan to check for statistically significant differences in the evolution of the feeling of loneliness after a three month period. A sample of 60 individuals aged between 40 and 86, with an average age of approximately 52, participated in this study. The instruments used to collect the data were a brief Sociodemographic Questionnaire, the Portuguese adaptation of the UCLA Loneliness Scale and the Geriatric Depression Scale (GDS). The data were subjected to an analysis based on the principles of parametric statistics. In this study the overall reliability proved to be high, Cronbach's alpha value being 0,939. A central hypothesis was confirmed verifying that, although there is a statistically significant association between loneliness and depression, there are individuals without depression presenting high levels of loneliness (p <0.001). There was no ratio of loneliness prevaling in females and the same was higher in older age groups, but this difference did not prove to be statistically significant. Using Cohen’s Kappa chi-square independance and agreement tests; and the Student t test, we concluded that there is a significant association of a moderate correlation in loneliness over time. This reinforces the analysis that loneliness levels are maintained when there is no specific therapeutic intervention.

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The spike-diffuse-spike (SDS) model describes a passive dendritic tree with active dendritic spines. Spine-head dynamics is modeled with a simple integrate-and-fire process, whilst communication between spines is mediated by the cable equation. In this paper we develop a computational framework that allows the study of multiple spiking events in a network of such spines embedded on a simple one-dimensional cable. In the first instance this system is shown to support saltatory waves with the same qualitative features as those observed in a model with Hodgkin-Huxley kinetics in the spine-head. Moreover, there is excellent agreement with the analytically calculated speed for a solitary saltatory pulse. Upon driving the system with time varying external input we find that the distribution of spines can play a crucial role in determining spatio-temporal filtering properties. In particular, the SDS model in response to periodic pulse train shows a positive correlation between spine density and low-pass temporal filtering that is consistent with the experimental results of Rose and Fortune [1999, Mechanisms for generating temporal filters in the electrosensory system. The Journal of Experimental Biology 202, 1281-1289]. Further, we demonstrate the robustness of observed wave properties to natural sources of noise that arise both in the cable and the spine-head, and highlight the possibility of purely noise induced waves and coherent oscillations.

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Optical full-field measurement methods such as Digital Image Correlation (DIC) provide a new opportunity for measuring deformations and vibrations with high spatial and temporal resolution. However, application to full-scale wind turbines is not trivial. Elaborate preparation of the experiment is vital and sophisticated post processing of the DIC results essential. In the present study, a rotor blade of a 3.2 MW wind turbine is equipped with a random black-and-white dot pattern at four different radial positions. Two cameras are located in front of the wind turbine and the response of the rotor blade is monitored using DIC for different turbine operations. In addition, a Light Detection and Ranging (LiDAR) system is used in order to measure the wind conditions. Wind fields are created based on the LiDAR measurements and used to perform aeroelastic simulations of the wind turbine by means of advanced multibody codes. The results from the optical DIC system appear plausible when checked against common and expected results. In addition, the comparison of relative out-of-plane blade deflections shows good agreement between DIC results and aeroelastic simulations.

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In this project, have been studied to determine the appropriate model to spatial, temporal and diversity of demersal fishes in the Sea of Oman, including Trichiuridae, Nemipteridae, Haemulidae, Arridae, Synodontidae, Batoidfishes, Carangidae, Scianidae, Carchariniformes and Serranidae. This research became operational from catch data during 2003 to 2013 (in 2007, due to the lack of ship failed). Processing and calculations was evaluated by using the software Excel, SPSS, Arc GIS and table curve 3D highest biomass and abundance was showed in strata A and C and 10-30 m depth layers was showed the best condition biomass. In other words, highest biomass was showed in the eastern region in the Oman Sea than the central and western regions. Batoidfishes and Trichiuridae had the highest biomass .Depth factors was showed a significant correlation with the biomass. Scianidae, Serranidae and Haemulidae were showed a large decline. Synodontidae was showed a very large increase. The largest of Shannon index belong to central and western region of the Oman Sea. The highest Shannon index was showed 10-20 and 50-100 m, respectively. The Distribution maps based on the biomass was analyzed by using Arc GIS software. So that were identified in the first time in a ten-year period and carefully catch stations any economic of aquatic group. In conclusion, the depth can be found in the pattern of distribution, abundance and diversity of fish from away the beach so that follow specific pattern.