41 resultados para Spatio-temporal changes
Resumo:
Physical systems with co-existence and interplay of processes featuring distinct spatio-temporal scales are found in various research areas ranging from studies of brain activity to astrophysics. The complexity of such systems makes their theoretical and experimental analysis technically and conceptually challenging. Here, we discovered that while radiation of partially mode-locked fibre lasers is stochastic and intermittent on a short time scale, it exhibits non-trivial periodicity and long-scale correlations over slow evolution from one round-trip to another. A new technique for evolution mapping of intensity autocorrelation function has enabled us to reveal a variety of localized spatio-temporal structures and to experimentally study their symbiotic co-existence with stochastic radiation. Real-time characterization of dynamical spatio-temporal regimes of laser operation is set to bring new insights into rich underlying nonlinear physics of practical active- and passive-cavity photonic systems.
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This paper describes experimental and numerical results of the plasma-assisted microfabrication of subwavelength structures by means of point-by point femtosecond laser inscription. It is shown that the spatio-temporal evolution of light and plasma patterns critically depend on input power. Subwavelength inscription corresponds to the supercritical propagation regimes when pulse power is several times self-focusing threshold. Experimental and numerical profiles show quantitative agreement.
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In recent years, the rapid spread of smartphones has led to the increasing popularity of Location-Based Social Networks (LBSNs). Although a number of research studies and articles in the press have shown the dangers of exposing personal location data, the inherent nature of LBSNs encourages users to publish information about their current location (i.e., their check-ins). The same is true for the majority of the most popular social networking websites, which offer the possibility of associating the current location of users to their posts and photos. Moreover, some LBSNs, such as Foursquare, let users tag their friends in their check-ins, thus potentially releasing location information of individuals that have no control over the published data. This raises additional privacy concerns for the management of location information in LBSNs. In this paper we propose and evaluate a series of techniques for the identification of users from their check-in data. More specifically, we first present two strategies according to which users are characterized by the spatio-temporal trajectory emerging from their check-ins over time and the frequency of visit to specific locations, respectively. In addition to these approaches, we also propose a hybrid strategy that is able to exploit both types of information. It is worth noting that these techniques can be applied to a more general class of problems where locations and social links of individuals are available in a given dataset. We evaluate our techniques by means of three real-world LBSNs datasets, demonstrating that a very limited amount of data points is sufficient to identify a user with a high degree of accuracy. For instance, we show that in some datasets we are able to classify more than 80% of the users correctly.
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The cell:cell bond between an immune cell and an antigen presenting cell is a necessary event in the activation of the adaptive immune response. At the juncture between the cells, cell surface molecules on the opposing cells form non-covalent bonds and a distinct patterning is observed that is termed the immunological synapse. An important binding molecule in the synapse is the T-cell receptor (TCR), that is responsible for antigen recognition through its binding with a major-histocompatibility complex with bound peptide (pMHC). This bond leads to intracellular signalling events that culminate in the activation of the T-cell, and ultimately leads to the expression of the immune eector function. The temporal analysis of the TCR bonds during the formation of the immunological synapse presents a problem to biologists, due to the spatio-temporal scales (nanometers and picoseconds) that compare with experimental uncertainty limits. In this study, a linear stochastic model, derived from a nonlinear model of the synapse, is used to analyse the temporal dynamics of the bond attachments for the TCR. Mathematical analysis and numerical methods are employed to analyse the qualitative dynamics of the nonequilibrium membrane dynamics, with the specic aim of calculating the average persistence time for the TCR:pMHC bond. A single-threshold method, that has been previously used to successfully calculate the TCR:pMHC contact path sizes in the synapse, is applied to produce results for the average contact times of the TCR:pMHC bonds. This method is extended through the development of a two-threshold method, that produces results suggesting the average time persistence for the TCR:pMHC bond is in the order of 2-4 seconds, values that agree with experimental evidence for TCR signalling. The study reveals two distinct scaling regimes in the time persistent survival probability density prole of these bonds, one dominated by thermal uctuations and the other associated with the TCR signalling. Analysis of the thermal fluctuation regime reveals a minimal contribution to the average time persistence calculation, that has an important biological implication when comparing the probabilistic models to experimental evidence. In cases where only a few statistics can be gathered from experimental conditions, the results are unlikely to match the probabilistic predictions. The results also identify a rescaling relationship between the thermal noise and the bond length, suggesting a recalibration of the experimental conditions, to adhere to this scaling relationship, will enable biologists to identify the start of the signalling regime for previously unobserved receptor:ligand bonds. Also, the regime associated with TCR signalling exhibits a universal decay rate for the persistence probability, that is independent of the bond length.
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In oscillatory reaction-diffusion systems, time-delay feedback can lead to the instability of uniform oscillations with respect to formation of standing waves. Here, we investigate how the presence of additive, Gaussian white noise can induce the appearance of standing waves. Combining analytical solutions of the model with spatio-temporal simulations, we find that noise can promote standing waves in regimes where the deterministic uniform oscillatory modes are stabilized. As the deterministic phase boundary is approached, the spatio-temporal correlations become stronger, such that even small noise can induce standing waves in this parameter regime. With larger noise strengths, standing waves could be induced at finite distances from the (deterministic) phase boundary. The overall dynamics is defined through the interplay of noisy forcing with the inherent reaction-diffusion dynamics.
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Distributed representations (DR) of cortical channels are pervasive in models of spatio-temporal vision. A central idea that underpins current innovations of DR stems from the extension of 1-D phase into 2-D images. Neurophysiological evidence, however, provides tenuous support for a quadrature representation in the visual cortex, since even phase visual units are associated with broader orientation tuning than odd phase visual units (J.Neurophys.,88,455–463, 2002). We demonstrate that the application of the steering theorems to a 2-D definition of phase afforded by the Riesz Transform (IEEE Trans. Sig. Proc., 49, 3136–3144), to include a Scale Transform, allows one to smoothly interpolate across 2-D phase and pass from circularly symmetric to orientation tuned visual units, and from more narrowly tuned odd symmetric units to even ones. Steering across 2-D phase and scale can be orthogonalized via a linearizing transformation. Using the tiltafter effect as an example, we argue that effects of visual adaptation can be better explained by via an orthogonal rather than channel specific representation of visual units. This is because of the ability to explicitly account for isotropic and cross-orientation adaptation effect from the orthogonal representation from which both direct and indirect tilt after-effects can be explained.
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We report for the first time, rogue waves generation in a mode-locked fiber laser that worked in multiple-soliton state in which hundreds of solitons occupied the whole laser cavity. Using real-time spatio-temporal intensity dynamics measurements, it is unveiled that nonlinear soliton collision accounts for the formation of rogue waves in this laser state. The nature of interactions between solitons are also discussed. Our observation may suggest similar formation mechanisms of rogue waves in other systems.
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OBJECTIVE: To determine the laminar distribution of the pathological changes in the cerebral cortex in progressive supranuclear palsy (PSP). METHOD: The distribution of the abnormally enlarged neurons (EN), surviving neurons, neurofibrillary tangles (NFT), glial inclusions (GI), tufted astrocytes (TA), and neuritic plaques (NP) were studied across the cortex in tau immunolabeled sections of frontal and temporal cortex in 8 cases of PSP. RESULTS: The distribution of the NFT was highly variable with no consistent pattern of laminar distribution. The GI were distributed either in the lower laminae or uniformly across the cortex. Surviving neurons exhibited either a density peak in the upper laminae or a bimodal distribution was present with density peaks in the upper and lower laminae. The EN and glial cell nuclei were distributed primarily in the lower cortical laminae. There were positive correlations between the densities of the EN and glial cell nuclei and negative correlations between the surviving neurons and glial cells. No correlations were present between the densities of the NFT and GI. CONCLUSION: Cortical pathology in PSP predominantly affects the lower laminae but may spread to affect the upper laminae in some cases. The NFT and GI may have different laminar distributions and gliosis occurs concurrently with neuronal enlargement.
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OBJECTIVE: To determine the distribution of the pathological changes in the neocortex in multiple-system atrophy (MSA). METHOD: The vertical distribution of the abnormal neurons (neurons with enlarged or atrophic perikarya), surviving neurons, glial cytoplasmic inclusions (GCI) and neuronal cytoplasmic inclusions (NI) were studied in alpha-synuclein-stained material of frontal and temporal cortex in ten cases of MSA. RESULTS: Abnormal neurons exhibited two common patterns of distribution, viz., density was either maximal in the upper cortex or a bimodal distribution was present with a density peak in the upper and lower cortex. The NI were either located in the lower cortex or were more uniformly distributed down the cortical profile. The distribution of the GCI varied considerably between gyri and cases. The density of the glial cell nuclei was maximal in the lower cortex in the majority of gyri. In a number of gyri, there was a positive correlation between the vertical densities of the abnormal neurons, the total number of surviving neurons, and the glial cell nuclei. The vertical densities of the GCI were not correlated with those of the surviving neurons or glial cells but the GCI and NI were positively correlated in a small number of gyri. CONCLUSION: The data suggest that there is significant degeneration of the frontal and temporal lobes in MSA, the lower laminae being affected more significantly than the upper laminae. Cortical degeneration in MSA is likely to be secondary to pathological changes occurring within subcortical areas.
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Neuronal intermediate filament inclusion disease (NIFID) is a new neurodegenerative disease characterized histologically by the presence of neuronal cytoplasmic inclusions (NI) immunopositive for intermediate filament proteins, neuronal loss, swollen achromatic neurons (SN), and gliosis. We studied the spatial patterns of these pathological changes parallel to the pia mater in gyri of the temporal lobe in four cases of NIFID. Both the NI and SN occurred in clusters that were regularly distributed parallel to the pia mater, the cluster sizes of the SN being significantly greater than those of the NI. In a significant proportion of areas studied, there was a spatial correlation between the clusters of NI and those of the SN and with the density of the surviving neurons. In addition, the clusters of surviving neurons were negatively correlated (out of phase) with the clusters of glial cell nuclei. The pattern of clustering of these histological features suggests that there is degeneration of the cortico-cortical projections in NIFID leading to the formation of NI and SN within the same vertical columns of cells. The glial cell reaction may be a response to the loss of neurons rather than to the appearance of the NI or SN.
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Objective: To quantify the densities of neurofilament inclusions (NI), swollen achromatic neurons, surviving neurons and glial cells in a novel neurofilamentopathy neurofilament inclusion disease (NID). Material: Sectionsof temporal lobe from 4 cases of NID stained with an antibody raised to neurofilament proteins. Method: Densities of the pathological changes were estimated in the various gyri of the temporal lobe, hippocampus and dentate gyrus. Results: Densities of the NI and swollen achromatic neurons (SN) were greater in the cerebral cortical gyri than in the hippocampus and dentate gyrus. Lesion density was relatively constant between gyri and between the CA sectors of the hippocampus. In cortical gyri, the density of the NI, SN and glial cell nuclei was greater in laminae II/III than laminae V/VI. Densities of the NI were negatively correlated with the surviving neurons and positively correlated with the glial cell nuclei. The density of the SN was positively correlated with that of the surviving neurons. Conclusion: The pathology of NID morphologically resembles that of Pick's disease (PD) and corticobasal degeneration (CBD), but there are distinct differences between NID and these disorders supporting the hypothesis that NID is a novel and unique type of neurodegenerative disease.