898 resultados para Human Sciences


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In this chapter we described how the inclusion of a model of a human arm, combined with the measurement of its neural input and a predictor, can provide to a previously proposed teleoperator design robustness under time delay. Our trials gave clear indications of the superiority of the NPT scheme over traditional as well as the modified Yokokohji and Yoshikawa architectures. Its fundamental advantages are: the time-lead of the slave, the more efficient, and providing a more natural feeling manipulation, and the fact that incorporating an operator arm model leads to more credible stability results. Finally, its simplicity allows less likely to fail local control techniques to be employed. However, a significant advantage for the enhanced Yokokohji and Yoshikawa architecture results from the very fact that it’s a conservative modification of current designs. Under large prediction errors, it can provide robustness through directing the master and slave states to their means and, since it relies on the passivity of the mechanical part of the system, it would not confuse the operator. An experimental implementation of the techniques will provide further evidence for the performance of the proposed architectures. The employment of neural networks and fuzzy logic, which will provide an adaptive model of the human arm and robustifying control terms, is scheduled for the near future.

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The existence of a specialized imitation module in humans is hotly debated. Studies suggesting a specific imitation impairment in individuals with autism spectrum disorders (ASD) support a modular view. However, the voluntary imitation tasks used in these studies (which require socio-cognitive abilities in addition to imitation for successful performance) cannot support claims of a specific impairment. Accordingly, an automatic imitation paradigm (a ‘cleaner’ measure of imitative ability) was used to assess the imitative ability of 16 adults with ASD and 16 non-autistic matched control participants. Participants performed a prespecified hand action in response to observed hand actions performed either by a human or a robotic hand. On compatible trials the stimulus and response actions matched, while on incompatible trials the two actions did not match. Replicating previous findings, the Control group showed an automatic imitation effect: responses on compatible trials were faster than those on incompatible trials. This effect was greater when responses were made to human than to robotic actions (‘animacy bias’). The ASD group also showed an automatic imitation effect and a larger animacy bias than the Control group. We discuss these findings with reference to the literature on imitation in ASD and theories of imitation.

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We perform a multimodel detection and attribution study with climate model simulation output and satellite-based measurements of tropospheric and stratospheric temperature change. We use simulation output from 20 climate models participating in phase 5 of the Coupled Model Intercomparison Project. This multimodel archive provides estimates of the signal pattern in response to combined anthropogenic and natural external forcing (the finger-print) and the noise of internally generated variability. Using these estimates, we calculate signal-to-noise (S/N) ratios to quantify the strength of the fingerprint in the observations relative to fingerprint strength in natural climate noise. For changes in lower stratospheric temperature between 1979 and 2011, S/N ratios vary from 26 to 36, depending on the choice of observational dataset. In the lower troposphere, the fingerprint strength in observations is smaller, but S/N ratios are still significant at the 1% level or better, and range from three to eight. We find no evidence that these ratios are spuriously inflated by model variability errors. After removing all global mean signals, model fingerprints remain identifiable in 70% of the tests involving tropospheric temperature changes. Despite such agreement in the large-scale features of model and observed geographical patterns of atmospheric temperature change, most models do not replicate the size of the observed changes. On average, the models analyzed underestimate the observed cooling of the lower stratosphere and overestimate the warming of the troposphere. Although the precise causes of such differences are unclear, model biases in lower stratospheric temperature trends are likely to be reduced by more realistic treatment of stratospheric ozone depletion and volcanic aerosol forcing.

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Keyphrases are added to documents to help identify the areas of interest they contain. However, in a significant proportion of papers author selected keyphrases are not appropriate for the document they accompany: for instance, they can be classificatory rather than explanatory, or they are not updated when the focus of the paper changes. As such, automated methods for improving the use of keyphrases are needed, and various methods have been published. However, each method was evaluated using a different corpus, typically one relevant to the field of study of the method’s authors. This not only makes it difficult to incorporate the useful elements of algorithms in future work, but also makes comparing the results of each method inefficient and ineffective. This paper describes the work undertaken to compare five methods across a common baseline of corpora. The methods chosen were Term Frequency, Inverse Document Frequency, the C-Value, the NC-Value, and a Synonym based approach. These methods were analysed to evaluate performance and quality of results, and to provide a future benchmark. It is shown that Term Frequency and Inverse Document Frequency were the best algorithms, with the Synonym approach following them. Following these findings, a study was undertaken into the value of using human evaluators to judge the outputs. The Synonym method was compared to the original author keyphrases of the Reuters’ News Corpus. The findings show that authors of Reuters’ news articles provide good keyphrases but that more often than not they do not provide any keyphrases.

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Understanding the role of the diet in determining human health and disease is one major objective of modern nutrition. Mammalian biocomplexity necessitates the incorporation of systems biology technologies into contemporary nutritional research. Metabonomics is a powerful approach that simultaneously measures the low-molecular-weight compounds in a biological sample, enabling the metabolic status of a biological system to be characterized. Such biochemical profiles contain latent information relating to inherent parameters, such as the genotype, and environmental factors, including the diet and gut microbiota. Nutritional metabonomics, or nutrimetabonomics, is being increasingly applied to study molecular interactions between the diet and the global metabolic system. This review discusses three primary areas in which nutrimetabonomics has enjoyed successful application in nutritional research: the illumination of molecular relationships between nutrition and biochemical processes; elucidation of biomarker signatures of food components for use in dietary surveillance; and the study of complex trans-genomic interactions between the mammalian host and its resident gut microbiome. Finally, this review illustrates the potential for nutrimetabonomics in nutritional science as an indispensable tool to achieve personalized nutrition.

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One of the most pervasive assumptions about human brain evolution is that it involved relative enlargement of the frontal lobes. We show that this assumption is without foundation. Analysis of five independent data sets using correctly scaled measures and phylogenetic methods reveals that the size of human frontal lobes, and of specific frontal regions, is as expected relative to the size of other brain structures. Recent claims for relative enlargement of human frontal white matter volume, and for relative enlargement shared by all great apes, seem to be mistaken. Furthermore, using a recently developed method for detecting shifts in evolutionary rates, we find that the rate of change in relative frontal cortex volume along the phylogenetic branch leading to humans was unremarkable and that other branches showed significantly faster rates of change. Although absolute and proportional frontal region size increased rapidly in humans, this change was tightly correlated with corresponding size increases in other areas andwhole brain size, and with decreases in frontal neuron densities. The search for the neural basis of human cognitive uniqueness should therefore focus less on the frontal lobes in isolation and more on distributed neural networks.

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Environmental change research often relies on simplistic, static models of human behaviour in social-ecological systems. This limits understanding of how social-ecological change occurs. Integrative, process-based behavioural models, which include feedbacks between action, and social and ecological system structures and dynamics, can inform dynamic policy assessment in which decision making is internalised in the model. These models focus on dynamics rather than states. They stimulate new questions and foster interdisciplinarity between and within the natural and social sciences.

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Probiotics are live microorganisms that confer a health benefit on the host when administered in appropriate amounts. Over 700 randomized, controlled, human studies have been conducted with probiotics thus far, with the results providing strong support for the use of probiotics in the clinical prevention or treatment of gastrointestinal tract disorders and metabolic syndrome. The present review is based on webinar presentations that were developed by the American Gastroenterological Association (AGA) in partnership with the International Scientific Association for Probiotics and Prebiotics (ISAPP) and the North American branch of the International Life Sciences Institute (ILSI North America). The presentations provided gastroenterologists and researchers with fundamental and current scientific information on the influence of gut microbiota on human health and disease, as well as clinical intervention strategies and practical guidelines for the use of probiotics and prebiotics.

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Direct effects of soil or its constituents on human health are through its ingestion, inhalation or absorption. The soil contains many infectious organisms that may enter the human body through these pathways, but it also provides organisms on which our earliest antibiotics are based. Indirect effects of soil arise from the quantity and quality of food that humans consume. Trace elements can have both beneficial and toxic effects on humans, especially where the range for optimal intake is narrow. We focus on four trace elements (iodine, iron, selenium and zinc) whose deficiencies have substantial effects on human health. As the world’s population increases issues of food security become more pressing, as does the need to sustain soil fertility and minimize its degradation. Lack of adequate food and food of poor nutritional quality lead to differing degrees of under-nutrition, which in turn causes ill health. Soil and land are finite resources and agricultural land is under severe competition from other uses. Relationships between soil and health are often difficult to extricate because of the many confounding factors present. Nevertheless, recent scientific understanding of soil processes and factors that affect human health are enabling greater insight into the effects of soil on our health. Multidisciplinary research that includes soil science, agronomy, agricultural sustainability, toxicology, epidemiology and the medical sciences will facilitate the discovery of new antibiotics, a greater understanding of how materials added to soil used for food production affect health and deciphering of the complex relationships between soil and human health.

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Taphonomic studies regularly employ animal analogues for human decomposition due to ethical restrictions relating to the use of human tissue. However, the validity of using animal analogues in soil decomposition studies is still questioned. This study compared the decomposition of skeletal muscle tissues (SMTs) from human (Homo sapiens), pork (Sus scrofa), beef (Bos taurus), and lamb (Ovis aries) interred in soil microcosms. Fixed interval samples were collected from the SMT for microbial activity and mass tissue loss determination; samples were also taken from the underlying soil for pH, electrical conductivity, and nutrient (potassium, phosphate, ammonium, and nitrate) analysis. The overall patterns of nutrient fluxes and chemical changes in nonhuman SMT and the underlying soil followed that of human SMT. Ovine tissue was the most similar to human tissue in many of the measured parameters. Although no single analogue was a precise predictor of human decomposition in soil, all models offered close approximations in decomposition dynamics.