841 resultados para Sensory system


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Theoretical accounts suggest that mirror neurons play a crucial role in social cognition. The current study used transcranial-magnetic stimulation (TMS) to investigate the association between mirror neuron activation and facialemotion processing, a fundamental aspect of social cognition, among healthy adults (n = 20). Facial emotion processing of static (but not dynamic) images correlated significantly with an enhanced motor response, proposed to reflect mirror neuron activation. These correlations did not appear to reflect general facial processing or pattern recognition, and provide support to current theoretical accounts linking the mirror neuron system to aspects of social cognition. We discuss the mechanism by which mirror neurons might facilitate facial emotion recognition.

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Anthropogenic elemental mercury (Hg0) emission is a serious worldwide environmental problem due to the extreme toxicity of the heavy metal to humans, plants and wildlife. Development of an accurate and cheap microsensor based online monitoring system which can be integrated as part of Hg0 removal and control processes in industry is still a major challenge. Here, we demonstrate that forming Au nanospike structures directly onto the electrodes of a quartz crystal microbalance (QCM) using a novel electrochemical route results in a self-regenerating, highly robust, stable, sensitive and selective Hg0 vapor sensor. The data from a 127 day continuous test performed in the presence of volatile organic compounds and high humidity levels, showed that the sensor with an electrodeposted sensitive layer had 260% higher response magnitude, 3.4 times lower detection limit (,22 mg/m3 or ,2.46 ppbv) and higher accuracy (98% Vs 35%) over a Au control based QCM (unmodified) when exposed to a Hg0 vapor concentration of 10.55 mg/m3 at 1016C. Statistical analysis of the long term data showed that the nano-engineered Hg0 sorption sites on the developed Au nanospikes sensitive layer play a critical role in the enhanced sensitivity and selectivity of the developed sensor towards Hg0 vapor.

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BACKGROUND: The evaluation of retinal image quality in cataract eyes has gained importance and the clinical modulation transfer functions (MTF) can obtained by aberrometer and double pass (DP) system. This study aimed to compare MTF derived from a ray tracing aberrometer and a DP system in early cataractous and normal eyes. METHODS: There were 128 subjects with 61 control eyes and 67 eyes with early cataract defined according to the Lens Opacities Classification System III. A laser ray-tracing wavefront aberrometer (iTrace) and a double pass (DP) system (OQAS) assessed ocular MTF for 6.0 mm pupil diameters following dilation. Areas under the MTF (AUMTF) and their correlations were analyzed. Stepwise multiple regression analysis assessed factors affecting the differences between iTrace- and OQAS-derived AUMTF for the early cataract group. RESULTS: For both early cataract and control groups, iTrace-derived MTFs were higher than OQAS-derived MTFs across a range of spatial frequencies (P < 0.01). No significant difference between the two groups occurred for iTrace-derived AUMTF, but the early cataract group had significantly smaller OQAS-derived AUMTF than did the control group (P < 0.01). AUMTF determined from both the techniques demonstrated significant correlations with nuclear opacities, higher-order aberrations (HOAs), visual acuity, and contrast sensitivity functions, while the OQAS-derived AUMTF also demonstrated significant correlations with age and cortical opacity grade. The factors significantly affecting the difference between iTrace and OQAS AUMTF were root-mean-squared HOAs (standardized beta coefficient = -0.63, P < 0.01) and age (standardized beta coefficient = 0.26, P < 0.01). CONCLUSIONS: MTFs determined from a iTrace and a DP system (OQAS) differ significantly in early cataractous and normal subjects. Correlations with visual performance were higher for the DP system. OQAS-derived MTF may be useful as an indicator of visual performance in early cataract eyes.

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Impairments in social cognitive functioning are well documented in schizophrenia, however the neural basis of these deficits is unclear. A recent explanatory model of social cognition centers upon the activity of mirror neurons, which are cortical brain cells that become active during both the performance and observation of behavior. Here, we test for the first time whether mirror neuron functioning is reduced in schizophrenia. Fifteen individuals with schizophrenia or schizoaffective disorder and fifteen healthy controls completed a transcranial magnetic stimulation (TMS) experiment designed to assess mirror neuron activation. While patients demonstrated no abnormalities in cortical excitability, motor facilitation during action observation, putatively reflecting mirror neuron activity, was reduced in schizophrenia. Dysfunction within the mirror neuron system may contribute to the pathophysiology of schizophrenia.

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This paper reviews the use of multi-agent systems to model the impacts of high levels of photovoltaic (PV) system penetration in distribution networks and presents some preliminary data obtained from the Perth Solar City high penetration PV trial. The Perth Solar City trial consists of a low voltage distribution feeder supplying 75 customers where 29 consumers have roof top photovoltaic systems. Data is collected from smart meters at each consumer premises, from data loggers at the transformer low voltage (LV) side and from a nearby distribution network SCADA measurement point on the high voltage side (HV) side of the transformer. The data will be used to progressively develop MAS models.

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This paper presents an efficient algorithm for optimizing the operation of battery storage in a low voltage distribution network with a high penetration of PV generation. A predictive control solution is presented that uses wavelet neural networks to predict the load and PV generation at hourly intervals for twelve hours into the future. The load and generation forecast, and the previous twelve hours of load and generation history, is used to assemble load profile. A diurnal charging profile can be compactly represented by a vector of Fourier coefficients allowing a direct search optimization algorithm to be applied. The optimal profile is updated hourly allowing the state of charge profile to respond to changing forecasts in load.

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This paper details the initial design and planning of a Field Programmable Gate Array (FPGA) implemented control system that will enable a path planner to interact with a MAVLink based flight computer. The design is aimed at small Unmanned Aircraft Vehicles (UAV) under autonomous operation which are typically subject to constraints arising from limited on-board processing capabilities, power and size. An FPGA implementation for the de- sign is chosen for its potential to address such limitations through low power and high speed in-hardware computation. The MAVLink protocol offers a low bandwidth interface for the FPGA implemented path planner to communicate with an on-board flight computer. A control system plan is presented that is capable of accepting a string of GPS waypoints generated on-board from a previously developed in- hardware Genetic Algorithm (GA) path planner and feeding them to the open source PX4 autopilot, while simultaneously respond- ing with flight status information.

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We study the dynamics of front solutions in a three-component reaction–diffusion system via a combination of geometric singular perturbation theory, Evans function analysis, and center manifold reduction. The reduced system exhibits a surprisingly complicated bifurcation structure including a butterfly catastrophe. Our results shed light on numerically observed accelerations and oscillations and pave the way for the analysis of front interactions in a parameter regime where the essential spectrum of a single front approaches the imaginary axis asymptotically.

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The ability to function in a nocturnal and ground-dwelling niche requires a unique set of sensory specializations. The New Zealand kiwi has shifted away from vision, instead relying on auditory and tactile stimuli to function in its environment and locate prey. Behavioral evidence suggests that kiwi also rely on their sense of smell, using olfactory cues in foraging and possibly also in communication and social interactions. Anatomical studies appear to support these observations: the olfactory bulbs and tubercles have been suggested to be large in the kiwi relative to other birds, although the extent of this enlargement is poorly understood. In this study, we examine the size of the olfactory bulbs in kiwi and compare them with 55 other bird species, including emus, ostriches, rheas, tinamous, and 2 extinct species of moa (Dinornithiformes). We also examine the cytoarchitecture of the olfactory bulbs and olfactory epithelium to determine if any neural specializations beyond size are present that would increase olfactory acuity. Kiwi were a clear outlier in our analysis, with olfactory bulbs that are proportionately larger than those of any other bird in this study. Emus, close relatives of the kiwi, also had a relative enlargement of the olfactory bulbs, possibly supporting a phylogenetic link to well-developed olfaction. The olfactory bulbs in kiwi are almost in direct contact with the olfactory epithelium, which is indeed well developed and complex, with olfactory receptor cells occupying a large percentage of the epithelium. The anatomy of the kiwi olfactory system supports an enhancement for olfactory sensitivities, which is undoubtedly associated with their unique nocturnal niche.

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The sensory systems of the New Zealand kiwi appear to be uniquely adapted to occupy a nocturnal ground-dwelling niche. In addition to well-developed tactile and olfactory systems, the auditory system shows specializations of the ear, which are maintained along the central nervous system. Here, we provide a detailed description of the auditory nerve, hair cells, and stereovillar bundle orientation of the hair cells in the North Island brown kiwi. The auditory nerve of the kiwi contained about 8,000 fibers. Using the number of hair cells and innervating nerve fibers to calculate a ratio of average innervation density showed that the afferent innervation ratio in kiwi was denser than in most other birds examined. The average diameters of cochlear afferent axons in kiwi showed the typical gradient across the tonotopic axis. The kiwi basilar papilla showed a clear differentiation of tall and short hair cells. The proportion of short hair cells was higher than in the emu and likely reflects a bias towards higher frequencies represented on the kiwi basilar papilla. The orientation of the stereovillar bundles in the kiwi basilar papilla showed a pattern similar to that in most other birds but was most similar to that of the emu. Overall, many features of the auditory nerve, hair cells, and stereovilli bundle orientation in the kiwi are typical of most birds examined. Some features of the kiwi auditory system do, however, support a high-frequency specialization, specifically the innervation density and generally small size of hair-cell somata, whereas others showed the presumed ancestral condition similar to that found in the emu.

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Background In vision, there is a trade-off between sensitivity and resolution, and any eye which maximises information gain at low light levels needs to be large. This imposes exacting constraints upon vision in nocturnal flying birds. Eyes are essentially heavy, fluid-filled chambers, and in flying birds their increased size is countered by selection for both reduced body mass and the distribution of mass towards the body core. Freed from these mass constraints, it would be predicted that in flightless birds nocturnality should favour the evolution of large eyes and reliance upon visual cues for the guidance of activity. Methodology/Principal Findings We show that in Kiwi (Apterygidae), flightlessness and nocturnality have, in fact, resulted in the opposite outcome. Kiwi show minimal reliance upon vision indicated by eye structure, visual field topography, and brain structures, and increased reliance upon tactile and olfactory information. Conclusions/Significance This lack of reliance upon vision and increased reliance upon tactile and olfactory information in Kiwi is markedly similar to the situation in nocturnal mammals that exploit the forest floor. That Kiwi and mammals evolved to exploit these habitats quite independently provides evidence for convergent evolution in their sensory capacities that are tuned to a common set of perceptual challenges found in forest floor habitats at night and which cannot be met by the vertebrate visual system. We propose that the Kiwi visual system has undergone adaptive regressive evolution driven by the trade-off between the relatively low rate of gain of visual information that is possible at low light levels, and the metabolic costs of extracting that information.

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BACKGROUND This paper describes the first national burden of disease study for South Africa. The main focus is the burden due to premature mortality, i.e. years of life lost (YLLs). In addition, estimates of the burden contributed by morbidity, i.e. the years lived with disability (YLDs), are obtained to calculate disability-adjusted life years (DALYs); and the impact of AIDS on premature mortality in the year 2010 is assessed. METHOD Owing to the rapid mortality transition and the lack of timely data, a modelling approach has been adopted. The total mortality for the year 2000 is estimated using a demographic and AIDS model. The non-AIDS cause-of-death profile is estimated using three sources of data: Statistics South Africa, the National Department of Home Affairs, and the National Injury Mortality Surveillance System. A ratio method is used to estimate the YLDs from the YLL estimates. RESULTS The top single cause of mortality burden was HIV/AIDS followed by homicide, tuberculosis, road traffic accidents and diarrhoea. HIV/AIDS accounted for 38% of total YLLs, which is proportionately higher for females (47%) than for males (33%). Pre-transitional diseases, usually associated with poverty and underdevelopment, accounted for 25%, non-communicable diseases 21% and injuries 16% of YLLs. The DALY estimates highlight the fact that mortality alone underestimates the burden of disease, especially with regard to unintentional injuries, respiratory disease, and nervous system, mental and sense organ disorders. The impact of HIV/AIDS is expected to more than double the burden of premature mortality by the year 2010. CONCLUSION This study has drawn together data from a range of sources to develop coherent estimates of premature mortality by cause. South Africa is experiencing a quadruple burden of disease comprising the pre-transitional diseases, the emerging chronic diseases, injuries, and HIV/AIDS. Unless interventions that reduce morbidity and delay morbidity become widely available, the burden due to HIV/AIDS can be expected to grow very rapidly in the next few years. An improved base of information is needed to assess the morbidity impact more accurately.

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This paper presents a performance-based optimisation approach for conducting trade-off analysis between safety (roads) and condition (bridges and roads). Safety was based on potential for improvement (PFI). Road condition was based on surface distresses and bridge condition was based on apparent age per subcomponent. The analysis uses a non-monetised optimisation that expanded upon classical Pareto optimality by observing performance across time. It was found that achievement of good results was conditioned by the availability of early age treatments and impacted by a frontier effect preventing the optimisation algorithm from realising of the long-term benefits of deploying actions when approaching the end of the analysis period. A disaggregated bridge condition index proved capable of improving levels of service in bridge subcomponents.

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We describe an investigation into how Massey University’s Pollen Classifynder can accelerate the understanding of pollen and its role in nature. The Classifynder is an imaging microscopy system that can locate, image and classify slide based pollen samples. Given the laboriousness of purely manual image acquisition and identification it is vital to exploit assistive technologies like the Classifynder to enable acquisition and analysis of pollen samples. It is also vital that we understand the strengths and limitations of automated systems so that they can be used (and improved) to compliment the strengths and weaknesses of human analysts to the greatest extent possible. This article reviews some of our experiences with the Classifynder system and our exploration of alternative classifier models to enhance both accuracy and interpretability. Our experiments in the pollen analysis problem domain have been based on samples from the Australian National University’s pollen reference collection (2,890 grains, 15 species) and images bundled with the Classifynder system (400 grains, 4 species). These samples have been represented using the Classifynder image feature set.We additionally work through a real world case study where we assess the ability of the system to determine the pollen make-up of samples of New Zealand honey. In addition to the Classifynder’s native neural network classifier, we have evaluated linear discriminant, support vector machine, decision tree and random forest classifiers on these data with encouraging results. Our hope is that our findings will help enhance the performance of future releases of the Classifynder and other systems for accelerating the acquisition and analysis of pollen samples.

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We describe an investigation into how Massey University's Pollen Classifynder can accelerate the understanding of pollen and its role in nature. The Classifynder is an imaging microscopy system that can locate, image and classify slide based pollen samples. Given the laboriousness of purely manual image acquisition and identification it is vital to exploit assistive technologies like the Classifynder to enable acquisition and analysis of pollen samples. It is also vital that we understand the strengths and limitations of automated systems so that they can be used (and improved) to compliment the strengths and weaknesses of human analysts to the greatest extent possible. This article reviews some of our experiences with the Classifynder system and our exploration of alternative classifier models to enhance both accuracy and interpretability. Our experiments in the pollen analysis problem domain have been based on samples from the Australian National University's pollen reference collection (2890 grains, 15 species) and images bundled with the Classifynder system (400 grains, 4 species). These samples have been represented using the Classifynder image feature set. In addition to the Classifynder's native neural network classifier, we have evaluated linear discriminant, support vector machine, decision tree and random forest classifiers on these data with encouraging results. Our hope is that our findings will help enhance the performance of future releases of the Classifynder and other systems for accelerating the acquisition and analysis of pollen samples. © 2013 AIP Publishing LLC.