66 resultados para neurotrophic signals


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Conspicuous warning signals of unprofitable prey are a defense against visually hunting predators. They work because predators learn to associate unprofitability with bright coloration and because strong signals are detectable and memorable. However, many species that can be considered defended are not very conspicuous; they have weak warning signals. This phenomenon has previously been ignored in models and experiments. In addition, there is significant within- and among-species variation among predators in their search behavior, in their visual, cognitive, and learning abilities, and in their resistance to defenses. In this article we explore the effects of variable predators on models that combine positive frequency-dependent, frequency-independent, and negative frequency-dependent predation and show that weak signaling of aposematic species can evolve if predators vary in their tendency to attack defended prey.

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The Spotted Bowerbird, Chlamydera maculata, appears to be sexually monomorphic. We caught and marked 118 birds in central Queensland, and sexed 88 using molecular methods. We found that our catch was strongly male-biased, both at bower sites and at non-bower feeding sites. We continued to observe the bird's behaviour after their release and so sub-divided males into sexual status groups as either bower-owners or non-owners. We searched for morphological measures, subjectively judged colour differences and quantitatively collected spectral measures of the visual properties of the crest feathers that would allow us to separate birds of differing sex and status. We found that bower owners had larger crests than non-owner males or females and that crest area provided the most accurate predictor of a bird's sex and status in a discriminant function analysis. We studied a cohort of seven males who went from non-owners to bower owners over three years, and found that their change in status was accompanied by a change in crest size – the only significant change in their morphology. Crest size did not relate to the mating success of a bower-owner. Instead, we suggest why the crest may differ between status groups and the implications that this may have for the sexual behaviour of male and female Spotted Bowerbirds.

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In this paper, a novel bipolar time-spread (TS) echo hiding based watermarking method is proposed for stereo audio signals, to overcome the low robustness problem in the traditional TS echo hiding method. At the embedding, echo signals with opposite polarities are added to both channels of the host audio signal. This improves the imperceptibility of the watermarking scheme, since added watermarks have similar effects in both channels. Then decoding part is developed, in order to improve the robustness of the watermarking scheme against common attacks. Since these novel embedding and decoding methods utilize the advantage of two channels in stereo audio signals, it significantly reduces the interference of host signal at watermark extraction which is the main reason for error detection in the traditional TS echo hiding based watermarking under closed-loop attack. The effectiveness of the proposed watermarking scheme is theoretically analyzed and verified by simulations under common attacks. The proposed echo hiding method outperforms conventional TS echo hiding based watermarking when their perceptual qualities are similar.

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Dietary factors influence BDNF in animal studies, but there is no comparable data in clinical populations. We examined the effect of a dietary intervention on BDNF serum levels in 67 DSM-IV schizophrenic outpatients (51 males and 16 females). Two groups were assessed in a cross-sectional study: one on a hypocaloric diet (HD) and the other not on a hypocaloric diet. Weight, height and BMI data were collected concurrently with 5-ml blood sampling of each subject. BDNF levels were measured with a sandwich-ELISA. The blood sample was obtained a minimum of one month after the exposure to dietary intervention. Serum BDNF levels were significantly higher in patients on the HD (p = 0.023). Additional research examining the interaction among patterns of nutritional food behavior and underlying physiopathology may result in insights upon which evidence-based decisions regarding dietary interventions can be made in people identified with major psychiatric disorders, such as schizophrenia.

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The role of milk in providing nutrition for the young is well established. However, it is becoming apparent that milk has a more comprehensive role in programming and regulating growth and development of the suckled young, and an autocrine impact on the mammary gland so that it functions appropriately during the lactation cycle. This central role of milk is best studied in animal models, such as marsupials that have evolved a different lactation strategy to eutherians and allow researchers to more easily identify regulatory mechanisms that are not as readily apparent in eutherian species. For example, the tammar wallaby (Macropus eugenii) has evolved with a unique reproductive strategy of a short gestation, birth of an altricial young and a relatively long lactation during which the mother progressively changes the composition of the major, and many of the minor components of milk. Thus, in contrast to eutherians, there is a far greater investment in development of the young during lactation and it is likely that many of the signals that regulate development of eutherian embryos in utero are delivered by the milk. This requires the co-ordinated development and function of the mammary gland. Inappropriate timing of these signalling events in mammals may result in either limited or abnormal development of the young, and potentially a higher incidence of mature onset disease. The tammar is emerging as an attractive model to better understand the role of milk factors in these processes.

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Prey species often possess defences (e.g. toxins) coupled with warning signals (i.e. aposematism). There is growing evidence that the expression of aposematic signals often varies within species and correlates with the strength of chemical defences. This has led to the speculation that such signals may be 'honest', with signal reliability ensured by the costliness of producing or maintaining aposematic traits. We reared larval seven-spot ladybirds (Coccinella septempunctata) on a Low or High aphid diet and measured the effects on warning signal expression (elytral carotenoid pigmentation, conspicuousness, spot size), levels of defensive alkaloids (precoccinelline, coccinelline), and relationships between these traits. High-diet individuals had greater total precoccinelline levels, and elytra carotenoid concentrations at adulthood which was detectable to a typical avian predator. However, larval diet did not significantly affect adult body mass or size, spot size or coccinelline levels. Elytra carotenoid concentrations correlated positively with total precoccinelline levels in both diet groups and sexes. However, the relationship between elytra carotenoid concentrations and total levels of coccinelline depended on sex: in both diet groups, elytra carotenoids and coccinelline levels were positively correlated in females, but negatively correlated in males. Spot size and coccinelline levels correlated positively in Low-diet individuals, but negatively in High-diet individuals. These results point to physiological linkages between components of aposematism, which are modulated by resource (i.e. food) availability and affect the honesty of signals. Developmental diet, but also sex, influenced the relationships between signals and toxin levels. Ladybirds are sexually size dimorphic, and thus in comparison with males, females may be more susceptible to resource limitation and more likely to be honest signallers. © 2012 The Authors. Functional Ecology © 2012 British Ecological Society.

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Significant world events often cause the behavioral convergence of the expression of shared sentiment. This paper examines the use of the blogosphere as a framework to study user psychological behaviors, using their sentiment responses as a form of ‘sensor’ to infer real-world events of importance automatically. We formulate a novel temporal sentiment index function using quantitative measure of the valence value of bearing words in blog posts in which the set of affective bearing words is inspired from psychological research in emotion structure. The annual local minimum and maximum of the proposed sentiment signal function are utilized to extract significant events of the year and corresponding blog posts are further analyzed using topic modeling tools to understand their content. The paper then examines the correlation of topics discovered in relation to world news events reported by the mainstream news service provider, Cable News Network, and by using the Google search engine. Next, aiming at understanding sentiment at a finer granularity over time, we propose a stochastic burst detection model, extended from the work of Kleinberg, to work incrementally with stream data. The proposed model is then used to extract sentimental bursts occurring within a specific mood label (for example, a burst of observing ‘shocked’). The blog posts at those time indices are analyzed to extract topics, and these are compared to real-world news events. Our comprehensive set of experiments conducted on a large-scale set of 12 million posts from Livejournal shows that the proposed sentiment index function coincides well with significant world events while bursts in sentiment allow us to locate finer-grain external world events.

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This research presented improved watermarking methods for mono and stereo audio signals. To enhance the performance, novel methods are developed using echo hiding techniques and patchwork-based algorithms. The superior performances of the proposed methods are demonstrated by theoretical analysis and simulation examples, in comparison with the existing methods.

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In this paper, the Fuzzy ARTMAP (FAM) neural network is used to classify metal detector signals into different categories for automated target discrimination. Feature extraction of the metal detector signals is conducted using a wavelet transform technique. The FAM neural network is then employed to classify the extracted features into different target groups. A series of experiments using individual FAM networks and a voting FAM network is conducted. Promising classification accuracy rates are obtained from using individual and voting FAM networks, respectively. The experimental outcomes positively demonstrate the effectiveness of the generated features, and of the FAM network in classifying metal detector signals for automated target discrimination tasks.