957 resultados para Many body perturbation theory


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Quantitative scaling relationships among body mass, temperature and metabolic rate of organisms are still controversial, while resolution may be further complicated through the use of different and possibly inappropriate approaches to statistical analysis. We propose the application of a modelling strategy based on the theoretical approach of Akaike's information criteria and non-linear model fitting (nlm). Accordingly, we collated and modelled available data at intraspecific level on the individual standard metabolic rate of Antarctic microarthropods as a function of body mass (M), temperature (T), species identity (S) and high rank taxa to which species belong (G) and tested predictions from metabolic scaling theory (mass-metabolism allometric exponent b = 0.75, activation energy range 0.2-1.2 eV). We also performed allometric analysis based on logarithmic transformations (lm). Conclusions from lm and nlm approaches were different. Best-supported models from lm incorporated T, M and S. The estimates of the allometric scaling exponent linking body mass and metabolic rate resulted in a value of 0.696 +/- 0.105 (mean +/- 95% CI). In contrast, the four best-supported nlm models suggested that both the scaling exponent and activation energy significantly vary across the high rank taxa (Collembola, Cryptostigmata, Mesostigmata and Prostigmata) to which species belong, with mean values of b ranging from about 0.6 to 0.8. We therefore reached two conclusions: 1, published analyses of arthropod metabolism based on logarithmic data may be biased by data transformation; 2, non-linear models applied to Antarctic microarthropod metabolic rate suggest that intraspecific scaling of standard metabolic rate in Antarctic microarthropods is highly variable and can be characterised by scaling exponents that greatly vary within taxa, which may have biased previous interspecific comparisons that neglected intraspecific variability.

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This paper investigates the characteristics of the complex received signal in body area networks for two environments at the opposite ends of the multipath spectrum at 2.45 GHz. Important attributes of the complex channel such as the Gaussianity of the quadrature components and power imbalance, which form the basis of many popular fading models, are investigated. It is found that in anechoic environments the assumption of Gaussian distributed quadrature components will not always yield a satisfactory fit. Using a complex received signal model which considers a non-isotropic scattered signal contribution along with the presence of an optional dominant signal component, we use an autocorrelation function originally derived for mobile-to-mobile communications to model the temporal behavior of a range of dynamic body area network channels with considerable success. In reverberant environments, it was observed that the real part of the complex autocorrelation function for body area network channels decayed slightly quicker than that expected in traditional land mobile channels. © 2013 IEEE.

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Quantum annealing is a promising tool for solving optimization problems, similar in some ways to the traditional ( classical) simulated annealing of Kirkpatrick et al. Simulated annealing takes advantage of thermal fluctuations in order to explore the optimization landscape of the problem at hand, whereas quantum annealing employs quantum fluctuations. Intriguingly, quantum annealing has been proved to be more effective than its classical counterpart in many applications. We illustrate the theory and the practical implementation of both classical and quantum annealing - highlighting the crucial differences between these two methods - by means of results recently obtained in experiments, in simple toy-models, and more challenging combinatorial optimization problems ( namely, Random Ising model and Travelling Salesman Problem). The techniques used to implement quantum and classical annealing are either deterministic evolutions, for the simplest models, or Monte Carlo approaches, for harder optimization tasks. We discuss the pro and cons of these approaches and their possible connections to the landscape of the problem addressed.

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Despite the importance of laughter in social interactions it remains little studied in affective computing. Respiratory, auditory, and facial laughter signals have been investigated but laughter-related body movements have received almost no attention. The aim of this study is twofold: first an investigation into observers' perception of laughter states (hilarious, social, awkward, fake, and non-laughter) based on body movements alone, through their categorization of avatars animated with natural and acted motion capture data. Significant differences in torso and limb movements were found between animations perceived as containing laughter and those perceived as nonlaughter. Hilarious laughter also differed from social laughter in the amount of bending of the spine, the amount of shoulder rotation and the amount of hand movement. The body movement features indicative of laughter differed between sitting and standing avatar postures. Based on the positive findings in this perceptual study, the second aim is to investigate the possibility of automatically predicting the distributions of observer's ratings for the laughter states. The findings show that the automated laughter recognition rates approach human rating levels, with the Random Forest method yielding the best performance.

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A large body of empirical research shows that psychosocial risk factors (PSRFs) such as low socio-economic status, social isolation, stress, type-D personality, depression and anxiety increase the risk of incident coronary heart disease (CHD) and also contribute to poorer health-related quality of life (HRQoL) and prognosis in patients with established CHD. PSRFs may also act as barriers to lifestyle changes and treatment adherence and may moderate the effects of cardiac rehabilitation (CR). Furthermore, there appears to be a bidirectional interaction between PSRFs and the cardiovascular system. Stress, anxiety and depression affect the cardiovascular system through immune, neuroendocrine and behavioural pathways. In turn, CHD and its associated treatments may lead to distress in patients, including anxiety and depression. In clinical practice, PSRFs can be assessed with single-item screening questions, standardised questionnaires, or structured clinical interviews. Psychotherapy and medication can be considered to alleviate any PSRF-related symptoms and to enhance HRQoL, but the evidence for a definite beneficial effect on cardiac endpoints is inconclusive. A multimodal behavioural intervention, integrating counselling for PSRFs and coping with illness should be included within comprehensive CR. Patients with clinically significant symptoms of distress should be referred for psychological counselling or psychologically focused interventions and/or psychopharmacological treatment. To conclude, the success of CR may critically depend on the interdependence of the body and mind and this interaction needs to be reflected through the assessment and management of PSRFs in line with robust scientific evidence, by trained staff, integrated within the core CR team.

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Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P < 5 × 10(-8)), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for ∼2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.

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Variability in metabolic scaling in animals, the relationship between metabolic rate (R) and body mass (M), has been a source of debate and controversy for decades. R is proportional to M-b, the precise value of b much debated, but historically considered equal in all organisms. Recent metabolic theory, however, predicts b to vary among species with ecology and metabolic level, and may also vary within species under different abiotic conditions. Under climate change, most species will experience increased temperatures, and marine organisms will experience the additional stressor of decreased seawater pH ('ocean acidification'). Responses to these environmental changes are modulated by myriad species-specific factors. Body-size is a fundamental biological parameter, but its modulating role is relatively unexplored. Here, we show that changes to metabolic scaling reveal asymmetric responses to stressors across body-size ranges; b is systematically decreased under increasing temperature in three grazing molluscs, indicating smaller individuals were more responsive to warming. Larger individuals were, however, more responsive to reduced seawater pH in low temperatures. These alterations to the allometry of metabolism highlight abiotic control of metabolic scaling, and indicate that responses to climate warming and ocean acidification may be modulated by body-size.

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Since the late nineteenth-century works of criminologists Lombroso and Lacassagne, tattoos in Europe have been commonly associated with deviant bodies. Like many other studies of tattoos of non-indigenous origin, the locus of our research is the convict body. Given the corporeal emphasis of prison records, we argue that tattoos form a crucial part of the power dynamic. Tattoos in the carceral context embody an inherent paradox of their being a component in the reidentification of 'habitual criminals'. We argue that their presence can be regarded as an expression of convict agency: by the act of imprinting unique identifiers on their bodies, convicts boldly defied the official gaze, while equally their description in official records exacted power over the deviant body. Cursory findings show an alignment with other national studies; corporeal inscriptions in Ireland were more prevalent in men's prisons than women's and associated, however loosely, with certain occupations. For instance, maritime and military motifs find representation. Recidivists were more likely to have tattoos than first-time offenders; inscriptions were described as monotone, rudimentary in design and incorporated a limited range of impressions. Further to our argument that tattoos form an expression of convict defiance of prison authority, we have found an unusual idiosyncrasy in the convict record, that is, that the agency of photography, while undermined in general terms, was manipulated by prison officers.

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Species-area relationships (SAR) are fundamental in the understanding of biodiversity patterns and of critical importance for predicting species extinction risk worldwide. Despite the enormous attention given to SAR in the form of many individual analyses, little attempt has been made to synthesize these studies. We conducted a quantitative meta-analysis of 794 SAR, comprising a wide span of organisms, habitats and locations. We identified factors reflecting both pattern-based and dynamic approaches to SAR and tested whether these factors leave significant imprints on the slope and strength of SAR. Our analysis revealed that SAR are significantly affected by variables characterizing the sampling scheme, the spatial scale, and the types of organisms or habitats involved. We found that steeper SAR are generated at lower latitudes and by larger organisms. SAR varied significantly between nested and independent sampling schemes and between major ecosystem types, but not generally between the terrestrial and the aquatic realm. Both the fit and the slope of the SAR were scale-dependent. We conclude that factors dynamically regulating species richness at different spatial scales strongly affect the shape of SAR. We highlight important consequences of this systematic variation in SAR for ecological theory, conservation management and extinction risk predictions.