998 resultados para animal noise


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Objetivou-se, com este trabalho, avaliar a influência das variáveis ambientais nos níveis de ruídos emitidos por suínos e quantificar as faixas em dB comparativamente às condições de conforto térmico estabelecidas pela literatura. O experimento foi conduzido em câmara climática, onde foram alojados cinco leitões em fase de creche, submetidos à variação na temperatura ambiente de 20°C a 38°C e umidade relativa de 50% a 80%. Decibelímetros foram instalados para o registro dos níveis de ruídos e sensores dataloggers para os dados de temperatura e umidade relativa. O nível de atividade foi utilizado para quantificar a movimentação dos animais por intermédio de análise de imagens. Análises de correlação e regressão foram aplicadas nos dados para análise estatística. As variáveis ambientais influenciam na emissão de ruídos pelos leitões quando expostos a diferentes condições térmicas. Os níveis de ruídos foram estabelecidos em faixas de acordo com a condição térmica a que animais foram submetidos. Para a condição de conforto (20 a 23°C), níveis de ruídos na faixa de 70 a 75dB; condição de alerta (23 a 30°C), níveis de ruídos na faixa de 60 a 70dB e para condição de estresse térmico (acima de 30°C), na faixa de 55 a 60dB.

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Objetivou-se, com este trabalho, avaliar a influência das variáveis ambientais nos níveis de ruídos emitidos por suínos e quantificar as faixas em dB comparativamente às condições de conforto térmico estabelecidas pela literatura. O experimento foi conduzido em câmara climática, onde foram alojados cinco leitões em fase de creche, submetidos à variação na temperatura ambiente de 20°C a 38°C e umidade relativa de 50% a 80%. Decibelímetros foram instalados para o registro dos níveis de ruídos e sensores dataloggers para os dados de temperatura e umidade relativa. O nível de atividade foi utilizado para quantificar a movimentação dos animais por intermédio de análise de imagens. Análises de correlação e regressão foram aplicadas nos dados para análise estatística. As variáveis ambientais influenciam na emissão de ruídos pelos leitões quando expostos a diferentes condições térmicas. Os níveis de ruídos foram estabelecidos em faixas de acordo com a condição térmica a que animais foram submetidos. Para a condição de conforto (20 a 23°C), níveis de ruídos na faixa de 70 a 75dB; condição de alerta (23 a 30°C), níveis de ruídos na faixa de 60 a 70dB e para condição de estresse térmico (acima de 30°C), na faixa de 55 a 60dB.

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Monitoring the natural environment is increasingly important as habit degradation and climate change reduce theworld’s biodiversity.We have developed software tools and applications to assist ecologists with the collection and analysis of acoustic data at large spatial and temporal scales.One of our key objectives is automated animal call recognition, and our approach has three novel attributes. First, we work with raw environmental audio, contaminated by noise and artefacts and containing calls that vary greatly in volume depending on the animal’s proximity to the microphone. Second, initial experimentation suggested that no single recognizer could dealwith the enormous variety of calls. Therefore, we developed a toolbox of generic recognizers to extract invariant features for each call type. Third, many species are cryptic and offer little data with which to train a recognizer. Many popular machine learning methods require large volumes of training and validation data and considerable time and expertise to prepare. Consequently we adopt bootstrap techniques that can be initiated with little data and refined subsequently. In this paper, we describe our recognition tools and present results for real ecological problems.

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Animal models typically require a known genetic pedigree to estimate quantitative genetic parameters. Here we test whether animal models can alternatively be based on estimates of relatedness derived entirely from molecular marker data. Our case study is the morphology of a wild bird population, for which we report estimates of the genetic variance-covariance matrices (G) of six morphological traits using three methods: the traditional animal model; a molecular marker-based approach to estimate heritability based on Ritland's pairwise regression method; and a new approach using a molecular genealogy arranged in a relatedness matrix (R) to replace the pedigree in an animal model. Using the traditional animal model, we found significant genetic variance for all six traits and positive genetic covariance among traits. The pairwise regression method did not return reliable estimates of quantitative genetic parameters in this population, with estimates of genetic variance and covariance typically being very small or negative. In contrast, we found mixed evidence for the use of the pedigree-free animal model. Similar to the pairwise regression method, the pedigree-free approach performed poorly when the full-rank R matrix based on the molecular genealogy was employed. However, performance improved substantially when we reduced the dimensionality of the R matrix in order to maximize the signal to noise ratio. Using reduced-rank R matrices generated estimates of genetic variance that were much closer to those from the traditional model. Nevertheless, this method was less reliable at estimating covariances, which were often estimated to be negative. Taken together, these results suggest that pedigree-free animal models can recover quantitative genetic information, although the signal remains relatively weak. It remains to be determined whether this problem can be overcome by the use of a more powerful battery of molecular markers and improved methods for reconstructing genealogies.

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We have explored the potential of deep Raman spectroscopy, specifically surface enhanced spatially offset Raman spectroscopy (SESORS), for non-invasive detection from within animal tissue, by employing SERS-barcoded nanoparticle (NP) assemblies as the diagnostic agent. This concept has been experimentally verified in a clinic-relevant backscattered Raman system with an excitation line of 785 nm under ex vivo conditions. We have shown that our SORS system, with a fixed offset of 2-3 mm, offered sensitive probing of injected QTH-barcoded NP assemblies through animal tissue containing both protein and lipid. In comparison to that of non-aggregated SERS-barcoded gold NPs, we have demonstrated that the tailored SERS-barcoded aggregated NP assemblies have significantly higher detection sensitivity. We report that these NP assemblies can be readily detected at depths of 7-8 mm from within animal proteinaceous tissue with high signal-to-noise (S/N) ratio. In addition they could also be detected from beneath 1-2 mm of animal tissue with high lipid content, which generally poses a challenge due to high absorption of lipids in the near-infrared region. We have also shown that the signal intensity and S/N ratio at a particular depth is a function of the SERS tag concentration used and that our SORS system has a QTH detection limit of 10-6 M. Higher detection depths may possibly be obtained with optimization of the NP assemblies, along with improvements in the instrumentation. Such NP assemblies offer prospects for in vivo, non-invasive detection of tumours along with scope for incorporation of drugs and their targeted and controlled release at tumour sites. These diagnostic agents combined with drug delivery systems could serve as a “theranostic agent”, an integration of diagnostics and therapeutics into a single platform.

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The present article describes a beautiful contribution of Alan Turing to our understanding of how animal coat patterns form. The question that Turing posed was the following. A collection of identical cells (or processors for that matter), all running the exact same program, and all communicating with each other in the exact same way, should always be in the same state. Yet they produce nonhomogeneous periodic patterns, like those seen on animal coats. How does this happen? Turing gave an elegant explanation for this phenomenon, namely that differences between the cells due to small amounts of random noise can actually be amplified into structured periodic patterns. We attempt to describe his core conceptual contribution below.

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The reasons why animal populations decline in response to anthropogenic noise are still poorly understood. To understand how populations are affected by noise, we must understand how individuals are affected by noise. By modifying the acoustic environment experimentally, we studied the potential relationship between noise levels and both spatial and singing behaviour in the European robin (Erithacus rubecula). We found that with increasing noise levels, males were more likely to move away from the noise source and changed their singing behaviour. Our results provide the first experimental evidence in a free ranging species, that not merely the presence of noise causes changes in behaviour and distribution, but that the level of noise pollution plays a crucial role as well. Our results have important implications for estimating the impact of infrastructure which differs in the level of noise produced. Thus, governmental planning bodies should not only consider the physical effect on the landscape when assessing the impact of new infrastructure, but also the noise levels emitted, which may reduce the loss of suitable habitats available for animals. © 2012 The Author(s) Published by the Royal Society. All rights reserved.

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Animal color pattern phenotypes evolve rapidly. What influences their evolution? Because color patterns are used in communication, selection for signal efficacy, relative to the intended receiver's visual system, may explain and predict the direction of evolution. We investigated this in bowerbirds, whose color patterns consist of plumage, bower structure, and ornaments and whose visual displays are presented under predictable visual conditions. We used data on avian vision, environmental conditions, color pattern properties, and an estimate of the bowerbird phylogeny to test hypotheses about evolutionary effects of visual processing. Different components of the color pattern evolve differently. Plumage sexual dimorphism increased and then decreased, while overall (plumage plus bower) visual contrast increased. The use of bowers allows relative crypsis of the bird but increased efficacy of the signal as a whole. Ornaments do not elaborate existing plumage features but instead are innovations (new color schemes) that increase signal efficacy. Isolation between species could be facilitated by plumage but not ornaments, because we observed character displacement only in plumage. Bowerbird color pattern evolution is at least partially predictable from the function of the visual system and from knowledge of different functions of different components of the color patterns. This provides clues to how more constrained visual signaling systems may evolve.

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Animal communication plays a crucial role in many species, and it involves a sender producing a signal and a receiver responding to that signal. The shape of a signal is determined by selection pressures acting upon it. One factor that exerts selection on acoustic signals is the acoustic environment through which the signal is transmitted. Recent experimental studies clearly show that senders adjust their signals in response to increased levels of anthropogenic noise. However, to understand how noise affects the whole process of communication, it is vital to know how noise affects the receiver’s response during vocal interactions. Therefore, we experimentally manipulated ambient noise levels to expose male European robins (Erithacus rubecula) to two playback treatments consisting of the same song: one with noise and another one without noise. We found that males responding to a conspecific in a noise polluted environment increased minimum frequency and decreased song complexity and song duration. Thus, we show that the whole process of communication is affected by noise, not just the behaviour of the sender.

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Older adults frequently report that they can hear what they have been told but cannot understand the meaning. This is particularly true in noisy conditions, where the additional challenge of suppressing irrelevant noise (i.e. a competing talker) adds another layer of difficulty to their speech understanding. Hearing aids improve speech perception in quiet, but their success in noisy environments has been modest, suggesting that peripheral hearing loss may not be the only factor in the older adult’s perceptual difficulties. Recent animal studies have shown that auditory synapses and cells undergo significant age-related changes that could impact the integrity of temporal processing in the central auditory system. Psychoacoustic studies carried out in humans have also shown that hearing loss can explain the decline in older adults’ performance in quiet compared to younger adults, but these psychoacoustic measurements are not accurate in describing auditory deficits in noisy conditions. These results would suggest that temporal auditory processing deficits could play an important role in explaining the reduced ability of older adults to process speech in noisy environments. The goals of this dissertation were to understand how age affects neural auditory mechanisms and at which level in the auditory system these changes are particularly relevant for explaining speech-in-noise problems. Specifically, we used non-invasive neuroimaging techniques to tap into the midbrain and the cortex in order to analyze how auditory stimuli are processed in younger (our standard) and older adults. We will also attempt to investigate a possible interaction between processing carried out in the midbrain and cortex.