955 resultados para BAND-SHAPE-ANALYSIS


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We find approximations to travelling breather solutions of the one-dimensional Fermi-Pasta-Ulam (FPU) lattice. Both bright breather and dark breather solutions are found. We find that the existence of localised (bright) solutions depends upon the coefficients of cubic and quartic terms of the potential energy, generalising an earlier inequality derived by James [CR Acad Sci Paris 332, 581, (2001)]. We use the method of multiple scales to reduce the equations of motion for the lattice to a nonlinear Schr{\"o}dinger equation at leading order and hence construct an asymptotic form for the breather. We show that in the absence of a cubic potential energy term, the lattice supports combined breathing-kink waveforms. The amplitude of breathing-kinks can be arbitrarily small, as opposed to traditional monotone kinks, which have a nonzero minimum amplitude in such systems. We also present numerical simulations of the lattice, verifying the shape and velocity of the travelling waveforms, and confirming the long-lived nature of all such modes.

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Two stocks of bluefin tuna (Thunnus thynnus) inhabit the north Atlantic; the western and eastern stocks spawn in the Gulf of Mexico and the Mediterranean Sea respectively. Trans-Atlantic movements occur outside spawning time whereas natal homing maintains stock structure. Commercial fisheries may exploit a mixed assemblage of both stocks. The incorporation of mixing rates into stock assessment is precluded by uncertainties surrounding stock discrimination. Otolith shape descriptors were used to characterise western and eastern stocks of Atlantic bluefin tuna in the present study and to estimate stock composition in catches of unknown origin. Otolith shape varied with length and between locations and years. Within a restricted size range (200-297-cm fork length (FL)) the two stocks were distinguished with an accuracy of 83%. Bayesian stock mixture analysis indicated that samples from the east Atlantic and Mediterranean were predominantly of eastern origin. The proportion assigned to the eastern stock showed slight spatial variation; however, overlapping 95% credible intervals indicated no significant difference (200-297 cm FL: central Atlantic, 73-100%; Straits of Gibraltar, 73-100%; Morocco, 50-99%; Portugal 64-100%). Otolith shape could be used in combination with other population markers to improve the accuracy of mixing rate estimates for Atlantic bluefin tuna.

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Statistical approaches to study extreme events require, by definition, long time series of data. In many scientific disciplines, these series are often subject to variations at different temporal scales that affect the frequency and intensity of their extremes. Therefore, the assumption of stationarity is violated and alternative methods to conventional stationary extreme value analysis (EVA) must be adopted. Using the example of environmental variables subject to climate change, in this study we introduce the transformed-stationary (TS) methodology for non-stationary EVA. This approach consists of (i) transforming a non-stationary time series into a stationary one, to which the stationary EVA theory can be applied, and (ii) reverse transforming the result into a non-stationary extreme value distribution. As a transformation, we propose and discuss a simple time-varying normalization of the signal and show that it enables a comprehensive formulation of non-stationary generalized extreme value (GEV) and generalized Pareto distribution (GPD) models with a constant shape parameter. A validation of the methodology is carried out on time series of significant wave height, residual water level, and river discharge, which show varying degrees of long-term and seasonal variability. The results from the proposed approach are comparable with the results from (a) a stationary EVA on quasi-stationary slices of non-stationary series and (b) the established method for non-stationary EVA. However, the proposed technique comes with advantages in both cases. For example, in contrast to (a), the proposed technique uses the whole time horizon of the series for the estimation of the extremes, allowing for a more accurate estimation of large return levels. Furthermore, with respect to (b), it decouples the detection of non-stationary patterns from the fitting of the extreme value distribution. As a result, the steps of the analysis are simplified and intermediate diagnostics are possible. In particular, the transformation can be carried out by means of simple statistical techniques such as low-pass filters based on the running mean and the standard deviation, and the fitting procedure is a stationary one with a few degrees of freedom and is easy to implement and control. An open-source MAT-LAB toolbox has been developed to cover this methodology, which is available at https://github.com/menta78/tsEva/(Mentaschi et al., 2016).

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This thesis aims to understand how cells coordinate their motion during collective migration. As previously shown, the motion of individually migrating cells is governed by wave-like cell shape dynamics. The mechanisms that regulate these dynamic behaviors in response to extracellular environment remain largely unclear. I applied shape dynamics analysis to Dictyostelium cells migrating in pairs and in multicellular streams and found that wave-like membrane protrusions are highly coupled between touching cells. I further characterized cell motion by using principle component analysis (PCA) to decompose complex cell shape changes into a serial shape change modes, from which I found that streaming cells exhibit localized anterior protrusion, termed front narrowing, to facilitate cell-cell coupling. I next explored cytoskeleton-based mechanisms of cell-cell coupling by measuring the dynamics of actin polymerization. Actin polymerization waves observed in individual cells were significantly suppressed in multicellular streams. Streaming cells exclusively produced F-actin at cell-cell contact regions, especially at cell fronts. I demonstrated that such restricted actin polymerization is associated with cell-cell coupling, as reducing actin polymerization with Latrunculin A leads to the assembly of F-actin at the side of streams, the decrease of front narrowing, and the decoupling of protrusion waves. My studies also suggest that collective migration is guided by cell-surface interactions. I examined the aggregation of Dictyostelim cells under distinct conditions and found that both chemical compositions of surfaces and surface-adhesion defects in cells result in altered collective migration patterns. I also investigated the shape dynamics of cells suspended on PEG-coated surfaces, which showed that coupling of protrusion waves disappears on touching suspended cells. These observations indicate that collective migration requires a balance between cell-cell and cell-surface adhesions. I hypothesized such a balance is reached via the regulation of cytoskeleton. Indeed, I found cells actively regulate cytoskeleton to retain optimal cell-surface adhesions on varying surfaces, and cells lacking the link between actin and surfaces (talin A) could not retain the optimal adhesions. On the other hand, suspended cells exhibited enhanced actin filament assembly on the periphery of cell groups instead of in cell-cell contact regions, which facilitates their aggregation in a clumping fashion.

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Size and shape tuneable ZnO nanostructures were prepared by a low frequency ultrasound (42 kHz) route using various organic solvents as the reaction media. The crystalline nature, lattice parameters and microstructural parameters such as microstrain, stress and energy density of the prepared ZnO nanostructures were revealed through X-ray diffraction (XRD) analysis. The organic solvents influenced the size and morphology of the ZnO nanostructures, and interesting morphological changes involving a spherical to triangular shaped transition were observed. The visible emission properties and lattice vibrational characteristics of the nanostructures were drastically modified by the changes in size and shape. Raman spectral measurements revealed the presence of multiphonon processes in the ZnO nanostructures. The intensity of the visible emission band was found to vary with the size and morphology of the structures. The strongest visible emission band corresponded to the structure with the largest surface/volume ratio and could be attributed to surface oxygen vacancies. The control over the size and morphology of ZnO nanostructures has been presented as a means of determining the intensity of the visible emission band

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Cosmic X-ray background synthesis models (Gilli 2007) require a significant fraction of obscured AGN, some of which are expected to be heavily obscured (Compton-thick), but the number density of observationally found obscured sources is still an open issue (Vignali 2010, 2014). This thesis work takes advantage of recent NuSTAR data and is based on a multiwavelength research approach. Gruppioni et al. 2016 compared the AGN bolometric luminosity, for a sample of local 12 micron Seyfert galaxies, derived from the SED decomposition to the same quantity obtained by the 2-10 keV luminosity (IPAC-NED). A difference up to two orders of magnitude resulted between these quantities for some sources. Thus, the intrinsic X-ray luminosity obtained correcting for the obscuration may be underestimated. In this thesis we have tested this hypothesis by re-analysing the X-ray spectra of three of the sources (UGC05101, NGC1194 and NGC3079), for which observations from NuSTAR and Chandra and/or XMM-Newton were available. This is meant to extend our analysis to energies above 10 keV and thus estimate the AGN column density as reliable as possible. For spectral fitting we made use of both the commonly used XSPEC package and the two very recent MYtorus and BNtorus physical models. The available wide bandpass allowed us to achieve new and more solid insights into the X-ray spectral properties of these sources. The measured absorption column densities are highly suggestive of heavy obscuration. Once corrected the X-ray AGN luminosity for the obscuration estimated through our spectral analysis, we compared the L(X) values in the 2-10 keV band with those derived from the MIR band, by means of the relation by Gandhi, 2009. As expected, the values derived from this relation are in good agreement with those we measured, indicating that the column densities were underestimated in the previous literature works.

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The wave energy industry is entering a new phase of pre-commercial and commercial deployments of full-scale devices, so better understanding of seaway variability is critical to the successful operation of devices. The response of Wave Energy Converters to incident waves govern their operational performance and for many devices, this is highly dependent on spectral shape due to their resonant properties. Various methods of wave measurement are presented, along with analysis techniques and empirical models. Resource assessments, device performance predictions and monitoring of operational devices will often be based on summary statistics and assume a standard spectral shape such as Pierson-Moskowitz or JONSWAP. Furthermore, these are typically derived from the closest available wave data, frequently separated from the site on scales in the order of 1km. Therefore, variability of seaways from standard spectral shapes and spatial inconsistency between the measurement point and the device site will cause inaccuracies in the performance assessment. This thesis categorises time and frequency domain analysis techniques that can be used to identify changes in a sea state from record to record. Device specific issues such as dimensional scaling of sea states and power output are discussed along with potential differences that arise in estimated and actual output power of a WEC due to spectral shape variation. This is investigated using measured data from various phases of device development.

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An overview is given of a user interaction monitoring and analysis framework called BaranC. Monitoring and analysing human-digital interaction is an essential part of developing a user model as the basis for investigating user experience. The primary human-digital interaction, such as on a laptop or smartphone, is best understood and modelled in the wider context of the user and their environment. The BaranC framework provides monitoring and analysis capabilities that not only records all user interaction with a digital device (e.g. smartphone), but also collects all available context data (such as from sensors in the digital device itself, a fitness band or a smart appliances). The data collected by BaranC is recorded as a User Digital Imprint (UDI) which is, in effect, the user model and provides the basis for data analysis. BaranC provides functionality that is useful for user experience studies, user interface design evaluation, and providing user assistance services. An important concern for personal data is privacy, and the framework gives the user full control over the monitoring, storing and sharing of their data.

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This article presents an inventory what theorists describe as the definition of domain analysis. Survey writings on and of domain analyses for their distinct attributes and arguments. Compile these components and attributes, linking them to their function, and from there. Describe a proposed ideal form of domain analysis. Evidence that while the debate about the substance and form of the epistemic and ontological character of domain analysis will continue, some might find it useful to give shape to their ideas using a particular form that follows function. If our purpose is to delineate and communicate what it is that we are analyzing when we engage in domain analysis, then I hope this small contribution can be of use.

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This paper aims to establish possible tourism demand scenarios of European travellers to Portugal based on the relationship with changing population structures. A combination of the EuROBAROMETER report 370 (“Attitudes of Europeans towards Tourism in 2013”) and the cohort-component method for population projections will allow the development of different possible tourism demand scenarios. Following the European report, individuals who travelled in 2013 were most likely to live in a household with two or more individuals. Thus, if elderly couples are together till later in their life and in better physiological shape, it is possible that the number of elderly individuals travelling for tourism purposes will increase in the near future. If we can expect tourists from developing countries to be younger due to their demographic dynamics than those from developed countries, where the ageing population is growing fast, we can expect that the percentage of the elderly among tourists will increase. Furthermore, the 2013 European report found that the combination of socio-demographic variables, such as, age, population, gender, household dimension, country of residence and trip purpose explained tourism demand scenarios for Portugal, confirming that seniors and families evidence a paramount sense of importance for the destination. In the literature there is a lack of discussion about the effects of demography in the future and the role of an ageing population in tourism demand choice patterns. We aim to contribute to filling this gap. Consequently, we strongly believe that this paper contributes to the literature by introducing a new field of discussion about the importance of demographic changes in shaping travel trends.

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This paper aims to establish possible tourism demand scenarios of European travellers to Portugal based on the relationship with changing population structures. A combination of the EUROBAROMETER report 370 (“Attitudes of Europeans towards Tourism in 2013”) and the cohort-component method for population projections will allow the development of different possible tourism demand scenarios. Following the European report, individuals who travelled in 2013 were most likely to live in a household with two or more individuals. Thus, if elderly couples are together till later in their life and in better physiological shape, it is possible that the number of elderly individuals travelling for tourism purposes will increase in the near future. If we can expect tourists from developing countries to be younger due to their demographic dynamics than those from developed countries, where the ageing population is growing fast, we can expect that the percentage of the elderly among tourists will increase. Furthermore, the 2013 European report found that the combination of socio-demographic variables, such as, age, population, gender, household dimension, country of residence and trip purpose explained tourism demand scenarios for Portugal, confirming that seniors and families evidence a paramount sense of importance for the destination. In the literature there is a lack of discussion about the effects of demography in the future and the role of an ageing population in tourism demand choice patterns. We aim to contribute to filling this gap. Consequently, we strongly believe that this paper contributes to the literature by introducing a new field of discussion about the importance of demographic changes in shaping travel trends.

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The growing ecological awareness of Ocean Sprawl impacts is promoting the adoption of eco-engineering strategies to enhance the ecological performance of coastal infrastructures. Biomimicry, as an eco-engineering tool, aims to design infrastructure more suitable for wildlife by manipulating structural factors to mimic natural habitats. However, little is known about the extent to which natural and artificial substrates differ in their structure and to what extent such differences affect the biota. To fill these knowledge gaps and consequently design biomimetic surfaces, I initially explored how much physical structure diverges between various types of natural and artificial substrates and tested to what extent differences in physical structure and material composition affect the epibenthic communities. By mean of an in-field mensurative experiment and a systematic review coupled with a meta-analysis, I found that, although communities tended to differ between natural and artificial coastal habitats, both physical structure and material composition reported an overall mild effect on epibenthic communities. However, an informed choice of building material and an appropriate combination of multiple structural manipulations can promote ecological benefits at multiple levels, from increasing the ecological performance in situ to reducing the impacts during the production process. Thus, I combined my findings in a final experiment, still in progress, where I am testing the combined role of shape, brightness and inclination of biomimetic surfaces I have designed in producing benefits at multiple levels. Overall, I suggest that biomimicry has the potential to increase the ecological value of artificial habitats especially when a wide range of aspects is simultaneously considered. Indeed, none of the structural factors, individually, can fully mimic the “natural conditions” to effectively improve the ecological performance of the artificial substrates. This emphasizes the need to include in future works a multi-level perspective to fully achieve the great potential of biomimicry.

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Today’s data are increasingly complex and classical statistical techniques need growingly more refined mathematical tools to be able to model and investigate them. Paradigmatic situations are represented by data which need to be considered up to some kind of trans- formation and all those circumstances in which the analyst finds himself in the need of defining a general concept of shape. Topological Data Analysis (TDA) is a field which is fundamentally contributing to such challenges by extracting topological information from data with a plethora of interpretable and computationally accessible pipelines. We con- tribute to this field by developing a series of novel tools, techniques and applications to work with a particular topological summary called merge tree. To analyze sets of merge trees we introduce a novel metric structure along with an algorithm to compute it, define a framework to compare different functions defined on merge trees and investigate the metric space obtained with the aforementioned metric. Different geometric and topolog- ical properties of the space of merge trees are established, with the aim of obtaining a deeper understanding of such trees. To showcase the effectiveness of the proposed metric, we develop an application in the field of Functional Data Analysis, working with functions up to homeomorphic reparametrization, and in the field of radiomics, where each patient is represented via a clustering dendrogram.

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The integration of quantitative data from movement analysis technologies is reshaping the analysis of athletes’ performances and injury mitigation, e.g., anterior cruciate ligament (ACL) rupture. Most of the movement assessments are performed in laboratory environments. Recent progress provides the chance to shift the paradigm to a more ecological approach with sport-specific elements and a closer examination of “real” movement patterns associated with performance and (ACL) injury risk. The present PhD thesis aimed at investigating the on-field motion patterns related to performance and injury prevention in young football players. The objectives of the thesis were: (I) in-lab measures of high-dynamics movements were used to validate wearable inertial sensors technology; (II) in-laboratory and on-field agility movement tasks were compared to inspect the effect of football-specific environment; (III) on-field analysis was conducted to challenge wearable sensors technology in the assessment of dangerous movement patterns towards the ACL rupture; (IV) an overview of technologies that could shape present and future assessment of ACL injury risk in daily practice was presented. The validity of wearables in the assessment of high-dynamics movements was confirmed. Relevant differences emerged between the movements performed in a laboratory setting and on the football pitch, supporting the inclusion of an ecological dynamics approach in preventive protocols. The on-field analysis of football-specific movement tasks demonstrated good reliability of wearable sensors and the presence of residual dangerous patterns in the injured players. A tool to inspect at-risk movement patterns on the field through objective measurements was presented. It discussed how potential alternatives to wearable inertial sensors embrace artificial intelligence and closer collaboration between clinical and technical expertise. The present thesis was meant to contribute to setting the basis for data-driven prevention protocols. A deeper comprehension of injury-related principles and counteractions will contribute to preserving athletes’ careers and health over time.