940 resultados para Fractal descriptors
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Evidence exists that many natural facts are described better as a fractal. Although fractals are very useful for describing nature, it is also appropiate to review the concept of random fractal in finance. Due to the extraordinary importance of Brownian motion in physics, chemistry or biology, we will consider the generalization that supposes fractional Brownian motion introduced by Mandelbrot.The main goal of this work is to analyse the existence of long range dependence in instantaneous forward rates of different financial markets. Concretelly, we perform an empirical analysis on the Spanish, Mexican and U.S. interbanking interest rate. We work with three time series of daily data corresponding to 1 day operations from 28th March 1996 to 21st May 2002. From among all the existing tests on this matter we apply the methodology proposed in Taqqu, Teverovsky and Willinger (1995).
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PURPOSE: This longitudinal study aimed at comparing heart rate variability (HRV) in elite athletes identified either in 'fatigue' or in 'no-fatigue' state in 'real life' conditions. METHODS: 57 elite Nordic-skiers were surveyed over 4 years. R-R intervals were recorded supine (SU) and standing (ST). A fatigue state was quoted with a validated questionnaire. A multilevel linear regression model was used to analyze relationships between heart rate (HR) and HRV descriptors [total spectral power (TP), power in low (LF) and high frequency (HF) ranges expressed in ms(2) and normalized units (nu)] and the status without and with fatigue. The variables not distributed normally were transformed by taking their common logarithm (log10). RESULTS: 172 trials were identified as in a 'fatigue' and 891 as in 'no-fatigue' state. All supine HR and HRV parameters (Beta+/-SE) were significantly different (P<0.0001) between 'fatigue' and 'no-fatigue': HRSU (+6.27+/-0.61 bpm), logTPSU (-0.36+/-0.04), logLFSU (-0.27+/-0.04), logHFSU (-0.46+/-0.05), logLF/HFSU (+0.19+/-0.03), HFSU(nu) (-9.55+/-1.33). Differences were also significant (P<0.0001) in standing: HRST (+8.83+/-0.89), logTPST (-0.28+/-0.03), logLFST (-0.29+/-0.03), logHFST (-0.32+/-0.04). Also, intra-individual variance of HRV parameters was larger (P<0.05) in the 'fatigue' state (logTPSU: 0.26 vs. 0.07, logLFSU: 0.28 vs. 0.11, logHFSU: 0.32 vs. 0.08, logTPST: 0.13 vs. 0.07, logLFST: 0.16 vs. 0.07, logHFST: 0.25 vs. 0.14). CONCLUSION: HRV was significantly lower in 'fatigue' vs. 'no-fatigue' but accompanied with larger intra-individual variance of HRV parameters in 'fatigue'. The broader intra-individual variance of HRV parameters might encompass different changes from no-fatigue state, possibly reflecting different fatigue-induced alterations of HRV pattern.
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L'estudi de diversos descriptors paleoambientals com ara el pol·len, les diatomees i la sedimentologia, realitzat en sediments procedents del llac de Sanabria (NO de la península Ibèrica), ha aportat informació sobre les oscil·lacions climàtiques atribuïdes als períodes càlids tardoromà i medieval, així com a la petita edat del gel. Entre els anys 440 i 950 dC, el clima es caracteritzà per temperatures suaus i un règim de precipitacions mediterrani, malgrat l¿existència de pulsacions més fredes vers els anys 530 i 700 dC. Les evidències pol·líniques dels usos del sòl indiquen l'extensió d¿activitats ramaderes i agrícoles. Aquesta fase correspon al final del període càlid romà i al període càlid medieval. El canvi de condicions climàtiques es produeix entre els anys 950 i 1100 dC, moment en què els valors mínims de matèria orgànica, pol·len arbori, concentració de diatomees, nitrogen total (TN) i mida del gra indiquen temperatures més baixes i un règim de precipitacions més regular. Aquest període correspon a
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The effects of experimental phosphorus enrichments on alkaline phosphatase activity (APA) of the seagrass Posidonia oceanica (L.) Delile were tested. Short-term additions (as phosphate, 12 hours, in the laboratory) decreased APA by 18-2896, depending on the plant part considered (roots, young leaves or old leaves). The values of APA after this treatment were well correlated with interna1 phosphorus pools (as P concentration in plant tissues). Long-term additions (as phosphate, added to the sediment, 1 month in situ) decreased APA by 40-75%, also depending on the plant part. We conclude that alkaline phosphatase activity is a good indicator of P deficiency in this seagrass. We used this indicator to assess the P-nutritional status in a series of meadows in the NW Mediterranean, finding a high geographical variability, but correlations between APA and basic features of the meadows (carbonate content of the sediment, organic content of the sediment, shoot density, etc.) were not significant. Consequently, phosphorus deficiency does not seem to be directly related to these descriptors.
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OBJECTIVES: A survey was undertaken among Swiss occupational hygienists and other professionals to identify the different exposure assessment methods used, the contextual parameters observed and the uses, difficulties and possible developments of exposure models for field application. METHODS: A questionnaire was mailed to 121 occupational hygienists, all members of the Swiss Occupational Hygiene Society. A shorter questionnaire was also sent to registered occupational physicians and selected safety specialists. Descriptive statistics and multivariate analyses were performed. RESULTS: The response rate for occupational hygienists was 60%. The so-called expert judgement appeared to be the most widely used method, but its efficiency and reliability were both judged with very low scores. Long-term sampling was perceived as the most efficient and reliable method. Various determinants of exposure, such as emission rate and work activity, were often considered important, even though they were not included in the exposure assessment processes. Near field local phenomena determinants were also judged important for operator exposure estimation. CONCLUSION: Exposure models should be improved to integrate factors which are more easily accessible to practitioners. Descriptors of emission and local phenomena should also be included.
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The reliable and objective assessment of chronic disease state has been and still is a very significant challenge in clinical medicine. An essential feature of human behavior related to the health status, the functional capacity, and the quality of life is the physical activity during daily life. A common way to assess physical activity is to measure the quantity of body movement. Since human activity is controlled by various factors both extrinsic and intrinsic to the body, quantitative parameters only provide a partial assessment and do not allow for a clear distinction between normal and abnormal activity. In this paper, we propose a methodology for the analysis of human activity pattern based on the definition of different physical activity time series with the appropriate analysis methods. The temporal pattern of postures, movements, and transitions between postures was quantified using fractal analysis and symbolic dynamics statistics. The derived nonlinear metrics were able to discriminate patterns of daily activity generated from healthy and chronic pain states.
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In this work, the calcium-induced aggregation of phosphatidylserine liposomes is probed by means of the analysis of the kinetics of such process as well as the aggregate morphology. This novel characterization of liposome aggregation involves the use of static and dynamic light-scattering techniques to obtain kinetic exponents and fractal dimensions. For salt concentrations larger than 5 mM, a diffusion-limited aggregation regime is observed and the Brownian kernel properly describes the time evolution of the diffusion coefficient. For slow kinetics, a slightly modified multiple contact kernel is required. In any case, a time evolution model based on the numerical resolution of Smoluchowski's equation is proposed in order to establish a theoretical description for the aggregating system. Such a model provides an alternative procedure to determine the dimerization constant, which might supply valuable information about interaction mechanisms between phospholipid vesicles.
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In the last few years, a need to account for molecular flexibility in drug-design methodologies has emerged, even if the dynamic behavior of molecular properties is seldom made explicit. For a flexible molecule, it is indeed possible to compute different values for a given conformation-dependent property and the ensemble of such values defines a property space that can be used to describe its molecular variability; a most representative case is the lipophilicity space. In this review, a number of applications of lipophilicity space and other property spaces are presented, showing that this concept can be fruitfully exploited: to investigate the constraints exerted by media of different levels of structural organization, to examine processes of molecular recognition and binding at an atomic level, to derive informative descriptors to be included in quantitative structure--activity relationships and to analyze protein simulations extracting the relevant information. Much molecular information is neglected in the descriptors used by medicinal chemists, while the concept of property space can fill this gap by accounting for the often-disregarded dynamic behavior of both small ligands and biomacromolecules. Property space also introduces some innovative concepts such as molecular sensitivity and plasticity, which appear best suited to explore the ability of a molecule to adapt itself to the environment variously modulating its property and conformational profiles. Globally, such concepts can enhance our understanding of biological phenomena providing fruitful descriptors in drug-design and pharmaceutical sciences.
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The present research studies the spatial patterns of the distribution of the Swiss population (DSP). This description is carried out using a wide variety of global spatial structural analysis tools such as topological, statistical and fractal measures, which enable the estimation of the spatial degree of clustering of a point pattern. A particular attention is given to the analysis of the multifractality to characterize the spatial structure of the DSP at different scales. This will be achieved by measuring the generalized q-dimensions and the singularity spectrum. This research is based on high quality data of the Swiss Population Census of the Year 2000 at a hectometric resolution (grid 100 x 100 m) issued by the Swiss Federal Statistical Office (FSO).
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Descriptors: music performance anxiety, respiration, hyperventilation Surveys indicate that high-anxious musicians may suffer from hyperventilation (HV) before or during performance. Reported symptoms include shortness of breath, fast/ deep breathing and thumping heart. However, no study has yet tested if these selfreported symptoms reflect actual cardiorespiratory activity. Themain goal of this study was to determine if MPA is manifested physiologically in specific correlates of cardiorespiratory activity associated with HV.We studied 74 professional music students from Swiss Music Academies. In this study, we compared the most anxious students (highanxious; n 5 20) with the least anxious students (low-anxious; n 5 23) based on their self-reported performance anxiety. We measured cardiorespiratory patterns with the Lifeshirt system, end-tidal CO2 with a capnograph (EtCO2, a good non-invasive estimator of HV), self-perceived physiological activation and affective experience in three situations on different days: baseline, performance without audience, and performance with audience. Comparing measures for the private vs. the public concert, high- compared to low-anxious students showed a significant drop in EtCO2 before the public concert and reported larger increases in anxiety, tension, palpitations and breathing difficulties. In contrast, heart rate, respiratory rate and volume did not differ significantly between groups. The results of this study support the hypothesis thatMPA may be associated with a tendency to hyperventilate and, thus, point to a potential hyperventilation problem in high-anxious music students.
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Community-level patterns of functional traits relate to community assembly and ecosystem functioning. By modelling the changes of different indices describing such patterns - trait means, extremes and diversity in communities - as a function of abiotic gradients, we could understand their drivers and build projections of the impact of global change on the functional components of biodiversity. We used five plant functional traits (vegetative height, specific leaf area, leaf dry matter content, leaf nitrogen content and seed mass) and non-woody vegetation plots to model several indices depicting community-level patterns of functional traits from a set of abiotic environmental variables (topographic, climatic and edaphic) over contrasting environmental conditions in a mountainous landscape. We performed a variation partitioning analysis to assess the relative importance of these variables for predicting patterns of functional traits in communities, and projected the best models under several climate change scenarios to examine future potential changes in vegetation functional properties. Not all indices of trait patterns within communities could be modelled with the same level of accuracy: the models for mean and extreme values of functional traits provided substantially better predictive accuracy than the models calibrated for diversity indices. Topographic and climatic factors were more important predictors of functional trait patterns within communities than edaphic predictors. Overall, model projections forecast an increase in mean vegetation height and in mean specific leaf area following climate warming. This trend was important at mid elevation particularly between 1000 and 2000 m asl. With this study we showed that topographic, climatic and edaphic variables can successfully model descriptors of community-level patterns of plant functional traits such as mean and extreme trait values. However, which factors determine the diversity of functional traits in plant communities remains unclear and requires more investigations.
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The work presented here is part of a larger study to identify novel technologies and biomarkers for early Alzheimer disease (AD) detection and it focuses on evaluating the suitability of a new approach for early AD diagnosis by non-invasive methods. The purpose is to examine in a pilot study the potential of applying intelligent algorithms to speech features obtained from suspected patients in order to contribute to the improvement of diagnosis of AD and its degree of severity. In this sense, Artificial Neural Networks (ANN) have been used for the automatic classification of the two classes (AD and control subjects). Two human issues have been analyzed for feature selection: Spontaneous Speech and Emotional Response. Not only linear features but also non-linear ones, such as Fractal Dimension, have been explored. The approach is non invasive, low cost and without any side effects. Obtained experimental results were very satisfactory and promising for early diagnosis and classification of AD patients.
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The Learning Affect Monitor (LAM) is a new computer-based assessment system integrating basic dimensional evaluation and discrete description of affective states in daily life, based on an autonomous adapting system. Subjects evaluate their affective states according to a tridimensional space (valence and activation circumplex as well as global intensity) and then qualify it using up to 30 adjective descriptors chosen from a list. The system gradually adapts to the user, enabling the affect descriptors it presents to be increasingly relevant. An initial study with 51 subjects, using a 1 week time-sampling with 8 to 10 randomized signals per day, produced n = 2,813 records with good reliability measures (e.g., response rate of 88.8%, mean split-half reliability of .86), user acceptance, and usability. Multilevel analyses show circadian and hebdomadal patterns, and significant individual and situational variance components of the basic dimension evaluations. Validity analyses indicate sound assignment of qualitative affect descriptors in the bidimensional semantic space according to the circumplex model of basic affect dimensions. The LAM assessment module can be implemented on different platforms (palm, desk, mobile phone) and provides very rapid and meaningful data collection, preserving complex and interindividually comparable information in the domain of emotion and well-being.
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In this work we propose a method to quantify written signatures from digitalized images based on the use of Elliptical Fourier Descriptors (EFD). As usually signatures are not represented as a closed contour, and being that a necessary condition in order to apply EFD, we have developed a method that represents the signatures by means of a set of closed contours. One of the advantages of this method is that it can reconstruct the original shape from all the coefficients, or an approximated shape from a reduced set of them finding the appropriate number of EFD coefficients required for preserving the important information in each application. EFD provides accurate frequency information, thus the use of EFD opens many possibilities. The method can be extended to represent other kind of shapes.
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Defining the limits of an urban agglomeration is essential both for fundamental and applied studies in quantitative and theoretical geography. A simple and consistent way for defining such urban clusters is important for performing different statistical analysis and comparisons. Traditionally, agglomerations are defined using a rather qualitative approach based on various statistical measures. This definition varies generally from one country to another, and the data taken into account are different. In this paper, we explore the use of the City Clustering Algorithm (CCA) for the agglomeration definition in Switzerland. This algorithm provides a systemic and easy way to define an urban area based only on population data. The CCA allows the specification of the spatial resolution for defining the urban clusters. The results from different resolutions are compared and analysed, and the effect of filtering the data investigated. Different scales and parameters allow highlighting different phenomena. The study of Zipf's law using the visual rank-size rule shows that it is valid only for some specific urban clusters, inside a narrow range of the spatial resolution of the CCA. The scale where emergence of one main cluster occurs can also be found in the analysis using Zipf's law. The study of the urban clusters at different scales using the lacunarity measure - a complementary measure to the fractal dimension - allows to highlight the change of scale at a given range.