855 resultados para human body
Resumo:
Music is a rich form of nonverbal communication, in which the movements that expert musicians make during performance can influence the perception of expressive and structural features of the music. Whether the actual skill of a musician is perceivable from vision of movement was examined. In Experiment 1, musicians and non-musicians rated performances by novice, intermediate and expert clarinettists from point-light animations of their movements, sound recordings, or both. Performances by clarinettists of more advanced skill level were rated significantly higher from vision of movements, although this effect was stronger when sound was also presented. In Experiment 2, movements and sound from the novice and expert clarinettists' performances were switched for half the presentations, and were matched for the rest. Ratings of novice music were significantly higher when presented with expert movements, although the opposite was not found for expert sound presented with novice movements. No perceptual effect of raters' own level of musicianship was found in either experiment. These results suggest that expertise is perceivable from vision of musicians' body movements, although perception of skill from sound is dominant. The results from Experiment 2 further indicate a cross-modal effect of vision and audition on the perception of musical expertise. © 2012 Elsevier B.V.
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In human motion analysis, the joint estimation of appearance, body pose and location parameters is not always tractable due to its huge computational cost. In this paper, we propose a Rao-Blackwellized Particle Filter for addressing the problem of human pose estimation and tracking. The advantage of the proposed approach is that Rao-Blackwellization allows the state variables to be splitted into two sets, being one of them analytically calculated from the posterior probability of the remaining ones. This procedure reduces the dimensionality of the Particle Filter, thus requiring fewer particles to achieve a similar tracking performance. In this manner, location and size over the image are obtained stochastically using colour and motion clues, whereas body pose is solved analytically applying learned human Point Distribution Models.
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Background: One-carbon metabolism involves both mitochondrial and cytosolic forms of folate-dependent enzymes in mammalian cells, but few in vivo data exist to characterize the biochemical processes involved.
Objective: We conducted a stable-isotopic investigation to determine the fates of exogenous serine and serine-derived one carbon units in homocysteine remethylation in hepatic and whole-body metabolism.
Design: A healthy man aged 23 y was administered [2,3,3 H-2(3)]serine and [5,5,5-H-2(3)]leucine by intravenous primed, constant infusion. Serial plasma samples were analyzed to determine the isotopic enrichment of free glycine, serine, leucine, methionine, and cystathionine. VLDL apolipoprotein B-100 served as an index of liver free amino acid labeling.
Results: [H-2(1)]Methionine and [H-2(2)]methionine were labeled through homocysteine remethylation. We propose that [H-2(2)]methionine occurs by remethylation with [H-2(2)]methyl groups (as 5-methyltetrahydrofolate) formed only from cytosolic processing of [H-2(3)]serine, whereas [H-2(1)]methionine is formed with labeled one-carbon units from mitochondrial oxidation of C-3 serine to [H-2(1)]formate to yield cytosolic [H-2(1)]methyl groups. The labeling pattern of cystathionine formed from homocysteine and labeled serine suggests that cystathionine is derived mainly from a serine pool different from that used in apolipoprotein B-100 synthesis.
Conclusions: The appearance of both [H-2(1)]- and [H-2(2)]methionine forms indicates that both cytosolic and mitochondrial metabolism of exogenous serine generates carbon units in vivo for methyl group production and homocysteine remethylation. This study also showed the utility of serine infusion and indicated functional roles of cytosolic and mitochondrial compartments in one-carbon metabolism.
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It is likely that humans have sought enhancements for themselves or their children for as long as they have recognised that improvements in individuals are a possibility. One genre of self-improvement in modern society can be called 'biomedical enhancements'. These include drugs, surgery and other medical interventions aimed at improving the mind, body or performance. This paper uses the case of human growth hormone (hGH) to examine the social nature of enhancements. Synthetic hGH was developed in 1985 by the pharmaceutical industry and was approved by the FDA for very specific uses, particularly treatment of growth hormone deficiency. However, it has also been promoted for a number of 'off label' uses, most of which can be deemed enhancements. Drugs approved for one treatment pave the way for use as enhancements for other problems. Claims have been made for hGH as a treatment for idiopathic shortness, as an anti-ageing agent and to improve athletic performance. Using the hGH case, we are able to distinguish three faces of biomedical enhancement: normalisation, repair and performance edge. Given deeply ingrained social and individual goals in American society, the temptations of biomedical enhancements provide inducement for individuals and groups to modify their situation. We examine the temptations of enhancement in terms of issues such as unnaturalness, fairness, risk and permanence, and shifting social meanings. In our conclusions, we outline the potentials and pitfalls of biomedical enhancement.
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Exposure assessment is a critical part of epidemiological studies into the effect of mycotoxins on human health. Whilst exposure assessment can be made by estimating the quantity of ingested toxins from food analysis and questionnaire data, the use of biological markers (biomarkers) of exposure can provide a more accurate measure of individual level of exposure in reflecting the internal dose. Biomarkers of exposure can include the excreted toxin or its metabolites, as well as the products of interaction between the toxin and macromolecules such as protein and DNA. Samples in which biomarkers may be analysed include urine, blood, other body fluids and tissues, with urine and blood being the most accessible for human studies. Here we describe the development of biomarkers of exposure for the assessment of three important mycotoxins; aflatoxin, fumonisin and deoxynivalenol. A number of different biomarkers and methods have been developed that can be applied to human population studies, and these approaches are reviewed in the context of their application to molecular epidemiology research.
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Laughter is a frequently occurring social signal and an important part of human non-verbal communication. However it is often overlooked as a serious topic of scientific study. While the lack of research in this area is mostly due to laughter’s non-serious nature, it is also a particularly difficult social signal to produce on demand in a convincing manner; thus making it a difficult topic for study in laboratory settings. In this paper we provide some techniques and guidance for inducing both hilarious laughter and conversational laughter. These techniques were devised with the goal of capturing mo- tion information related to laughter while the person laughing was either standing or seated. Comments on the value of each of the techniques and general guidance as to the importance of atmosphere, environment and social setting are provided.
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3-Deoxyglucosone (3-DG) is a reactive dicarbonyl sugar thought to be a key intermediate in the nonenzymatic polymerization and browning of proteins by glucose. 3-DG may be formed in vivo from fructose, fructose 3-phosphate, or Amadori adducts to protein, such as N epsilon-fructoselysine (FL), all of which are known to be elevated in body fluids or tissues in diabetes. Modification of proteins by 3-DG formed in vivo is thought to be limited by enzymatic reduction of 3-DG to less reactive species, such as 3-deoxyfructose (3-DF). In this study, we have measured 3-DF, as a metabolic fingerprint of 3-DG, in plasma and urine from a group of diabetic patients and control subjects. Plasma and urinary 3-DF concentrations were significantly increased in the diabetic compared with the control population (0.853 +/- 0.189 vs. 0.494 +/- 0.072 microM, P <0.001, and 69.9 +/- 44.2 vs. 38.7 +/- 16.1 nmol/mg creatinine, P <0.001, respectively). Plasma and urinary 3-DF concentrations correlated strongly with one another, with HbA1c (P <0.005 in all cases), and with urinary FL (P <0.02 and P = 0.005, respectively). The overall increase in 3-DF concentrations in plasma and urine in diabetes and their correlation with other indexes of glycemic control suggest that increased amounts of 3-DG are formed in the body during hyperglycemia in diabetes and then metabolized to 3-DF. These observations are consistent with a role for increased formation of the dicarbonyl sugar 3-DG in the accelerated browning of tissue proteins in diabetes.
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Smart Spaces, Ambient Intelligence, and Ambient Assisted Living are environmental paradigms that strongly depend on their capability to recognize human actions. While most solutions rest on sensor value interpretations and video analysis applications, few have realized the importance of incorporating common-sense capabilities to support the recognition process. Unfortunately, human action recognition cannot be successfully accomplished by only analyzing body postures. On the contrary, this task should be supported by profound knowledge of human agency nature and its tight connection to the reasons and motivations that explain it. The combination of this knowledge and the knowledge about how the world works is essential for recognizing and understanding human actions without committing common-senseless mistakes. This work demonstrates the impact that episodic reasoning has in improving the accuracy of a computer vision system for human action recognition. This work also presents formalization, implementation, and evaluation details of the knowledge model that supports the episodic reasoning.
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Average height is an important indicator of people’s well-being. It is also a relatively undistorted and easy-to-measure indicator, which makes it particularly suitable for comparisons across time and space. Drawing upon an extensive body of research, the chapter describes the strengths and weaknesses of this indicator. It finds that during the 19th century, average height in Western Offshoots was much higher than elsewhere. Differences between Western Europe and the rest of the world (Eastern Europe, East Asia) were marginal, in spite of the much higher real incomes in the former region. This changed after about 1870, when people’s height began to increase in Western Europe, whereas this lagged behind elsewhere. Africans were relatively tall during much of the period studied, but experienced declining height in many countries after the 1960s. People in Southeast Asia stayed relatively short throughout the period.
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The particular microenvironment of the skeletal muscle can be the site of complex immune reactions. Toll-like receptors (TLRs) mediate inflammatory stimuli from pathogens and endogenous danger signals and link the innate and adaptive immune system. We investigated innate immune responses in human muscle. Analyzing TLR1-9 mRNA in cultured myoblasts and rhabdomyosarcoma cells, we found constitutive expression of TLR3. The TLR3 ligand Poly (I:C), a synthetic analog of dsRNA, and IFN-gamma increased TLR3 levels. TLR3 was mainly localized intracellularly and regulated at the protein level. Poly (I:C) challenge 1) activated nuclear factor-kappaB (NF-kappaB), 2) increased IL-8 release, and 3) up-regulated NKG2D ligands and NK-cell-mediated lysis of muscle cells. We examined muscle biopsy specimens of 6 HIV patients with inclusion body myositis/polymyositis (IBM/PM), 7 cases of sporadic IBM and 9 nonmyopathic controls for TLR3 expression. TLR3 mRNA levels were elevated in biopsy specimens from patients with IBM and HIV-myopathies. Muscle fibers in inflammatory myopathies expressed TLR3 in close proximity of infiltrating mononuclear cells. Taken together, our study suggests an important role of TLR3 in the immunobiology of muscle, and has substantial implications for the understanding of the pathogenesis of inflammatory myopathies or therapeutic interventions like vaccinations or gene transfer.
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In this paper a 3D human pose tracking framework is presented. A new dimensionality reduction method (Hierarchical Temporal Laplacian Eigenmaps) is introduced to represent activities in hierarchies of low dimensional spaces. Such a hierarchy provides increasing independence between limbs, allowing higher flexibility and adaptability that result in improved accuracy. Moreover, a novel deterministic optimisation method (Hierarchical Manifold Search) is applied to estimate efficiently the position of the corresponding body parts. Finally, evaluation on public datasets such as HumanEva demonstrates that our approach achieves a 62.5mm-65mm average joint error for the walking activity and outperforms state-of-the-art methods in terms of accuracy and computational cost.
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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.
Resumo:
Despite its importance in social interactions, laughter remains little studied in affective computing. Intelligent virtual agents are often blind to users’ laughter and unable to produce convincing laughter themselves. Respiratory, auditory, and facial laughter signals have been investigated but laughter-related body movements have received less attention. The aim of this study is threefold. First, to probe human laughter perception by analyzing patterns of categorisations of natural laughter animated on a minimal avatar. Results reveal that a low dimensional space can describe perception of laughter “types”. Second, to investigate observers’ perception of laughter (hilarious, social, awkward, fake, and non-laughter) based on animated avatars generated from natural and acted motion-capture data. Significant differences in torso and limb movements are found between animations perceived as laughter and those perceived as non-laughter. Hilarious laughter also differs from social laughter. Different body movement features were indicative of laughter in sitting and standing avatar postures. Third, to investigate automatic recognition of laughter to the same level of certainty as observers’ perceptions. Results show recognition rates of the Random Forest model approach human rating levels. Classification comparisons and feature importance analyses indicate an improvement in recognition of social laughter when localized features and nonlinear models are used.
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Paired Associative Stimulation (PAS) has come to prominence as a potential therapeutic intervention for the treatment of brain injury/disease, and as an experimental method with which to investigate Hebbian principles of neural plasticity in humans. Prototypically, a single electrical stimulus is directed to a peripheral nerve in advance of transcranial magnetic stimulation (TMS) delivered to the contralateral primary motor cortex (M1). Repeated pairing of the stimuli (i.e., association) over an extended period may increase or decrease the excitability of corticospinal projections from M1, in manner that depends on the interstimulus interval (ISI). It has been suggested that these effects represent a form of associative long-term potentiation (LTP) and depression (LTD) that bears resemblance to spike-timing dependent plasticity (STDP) as it has been elaborated in animal models. With a large body of empirical evidence having emerged since the cardinal features of PAS were first described, and in light of the variations from the original protocols that have been implemented, it is opportune to consider whether the phenomenology of PAS remains consistent with the characteristic features that were initially disclosed. This assessment necessarily has bearing upon interpretation of the effects of PAS in relation to the specific cellular pathways that are putatively engaged, including those that adhere to the rules of STDP. The balance of evidence suggests that the mechanisms that contribute to the LTP- and LTD-type responses to PAS differ depending on the precise nature of the induction protocol that is used. In addition to emphasizing the requirement for additional explanatory models, in the present analysis we highlight the key features of the PAS phenomenology that require interpretation.
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Despite pattern recognition methods for human behavioral analysis has flourished in the last decade, animal behavioral analysis has been almost neglected. Those few approaches are mostly focused on preserving livestock economic value while attention on the welfare of companion animals, like dogs, is now emerging as a social need. In this work, following the analogy with human behavior recognition, we propose a system for recognizing body parts of dogs kept in pens. We decide to adopt both 2D and 3D features in order to obtain a rich description of the dog model. Images are acquired using the Microsoft Kinect to capture the depth map images of the dog. Upon depth maps a Structural Support Vector Machine (SSVM) is employed to identify the body parts using both 3D features and 2D images. The proposal relies on a kernelized discriminative structural classificator specifically tailored for dogs independently from the size and breed. The classification is performed in an online fashion using the LaRank optimization technique to obtaining real time performances. Promising results have emerged during the experimental evaluation carried out at a dog shelter, managed by IZSAM, in Teramo, Italy.