80 research outputs found

    Only females in poor condition display a clear preference and prefer males with an average badge

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    <p>Abstract</p> <p>Background</p> <p>Female condition-dependent variation in mate preference may have important evolutionary implications, not only within the same population but also among populations. There are few experiments, however, on how condition and/or genotype influences female mate preferences. The black throat patch of the male house sparrow, <it>Passer domesticus</it>, is an intensively studied plumage trait. It is often referred to as a 'badge of status' and seems to be involved in female mate choice, but differences exist among populations. Between-population variation in mate preference may occur for condition-dependent mate preferences. We tested the hypothesis that female preference may vary with female quality (body condition). Therefore, we measured female preference for badge size using an aviary two-choice test in which females were presented with two males that had different sizes of badges (enlarged or averaged).</p> <p>Results</p> <p>Overall we did not find a female preference for enlarged or average badges, but low-quality females spent more time near average badge males. Conversely, high-quality females did not show a clear preference.</p> <p>Conclusions</p> <p>Collectively, these results indicate that female preference varies with female quality. Differences in female condition are causes of within-population variation in mating preferences. To our knowledge, our results provide one of the first experimental evidences that variation in preference for a male ornament is associated with female condition. In our study, however, only females of low condition displayed a clear mate preference. Differences observed among populations could be partly explained by differences in female condition.</p

    An Investigation on Online Versus Batch Learning in Predicting User Behaviour

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    An investigation on how to produce a fast and accurate prediction of user behaviour on the Web is conducted. First, the problem of predicting user behaviour as a classification task is formulated and then the main problems of such real-time predictions are specified: the accuracy and time complexity of the prediction. Second, a method for comparison of online and batch (offline) algorithms used for user behaviour prediction is proposed. Last, the performance of these algorithms using the data from a popular question and answer platform, Stack Overflow, is empirically explored. It is demonstrated that a simple online learning algorithm outperforms state-of-the-art batch algorithms and performs as well as a deep learning algorithm, Deep Belief Networks. The proposed method for comparison of online and offline algorithms as well as the provided experimental evidence can be used for choosing a machine learning set-up for predicting user behaviour on the Web in scenarios where the accuracy and the time performance are of main concern

    Bearded Reedlings Adjust Their Pair-Bond Behaviour in Relation to the Sex and Attractiveness of Unpaired Conspecifics

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    An individual's investment in mating or keeping a pair bond intact may be influenced not only by the attractiveness of its current mate, but also by that of other potential mates. In this study, we investigated the effect of relative attractiveness on pair-bond behaviour in bearded reedlings, Panurus biarmicus. We showed that mate attractiveness, in terms of beard length in males and tail length in females, influenced courtship behaviour when the pair was kept isolated. In the presence of a conspecific, contact initiations within a pair increased. This increment was mainly related to the sex of the unpaired conspecific, however, and less to differences in attractiveness between the current partner and the unpaired conspecific. Female contact initiations towards potential extra mates were independent of male attractiveness, whereas male contact behaviour was significantly influenced by female attractiveness. However, females displayed more contact initiations to their current mate when they were less attractive than the unpaired females. Males decreased their overtures towards other females with increasing attractiveness of their current mates. Overall, our results suggested that, when there was a risk of losing their mate, bearded reedlings adjust their pair-bond investment mainly in response to the presence or absence of a competitor, and fine-tune investment to a lesser extent in response to the attractiveness of that potential competitor

    Female house sparrows "count on" male genes: experimental evidence for MHC-dependent mate preference in birds

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    <p>Abstract</p> <p>Background</p> <p>Females can potentially assess the quality of potential mates using their secondary sexual traits, and obtain "good genes" that increase offspring fitness. Another potential indirect benefit from mating preferences is genetic compatibility, which does not require extravagant or viability indicator traits. Several studies with mammals and fish indicate that the genes of the major histocompatibility complex (MHC) influence olfactory cues and mating preferences, and such preferences confer genetic benefits to offspring. We investigated whether individual MHC diversity (class I) influences mating preferences in house sparrows (<it>Passer domesticus</it>).</p> <p>Results</p> <p>Overall, we found no evidence that females preferred males with high individual MHC diversity. Yet, when we considered individual MHC allelic diversity of the females, we found that females with a low number of alleles were most attracted to males carrying a high number of MHC alleles, which might reflect a mating-up preference by allele counting.</p> <p>Conclusions</p> <p>This is the first experimental evidence for MHC-dependent mating preferences in an avian species to our knowledge. Our findings raise questions about the underlying mechanisms through which birds discriminate individual MHC diversity among conspecifics, and they suggest a novel mechanism through which mating preferences might promote the evolution of MHC polymorphisms and generate positive selection for duplicated MHC loci.</p

    B-cell epitope prediction through a graph model

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    Background Prediction of B-cell epitopes from antigens is useful to understand the immune basis of antibody-antigen recognition, and is helpful in vaccine design and drug development. Tremendous efforts have been devoted to this long-studied problem, however, existing methods have at least two common limitations. One is that they only favor prediction of those epitopes with protrusive conformations, but show poor performance in dealing with planar epitopes. The other limit is that they predict all of the antigenic residues of an antigen as belonging to one single epitope even when multiple non-overlapping epitopes of an antigen exist. Results In this paper, we propose to divide an antigen surface graph into subgraphs by using a Markov Clustering algorithm, and then we construct a classifier to distinguish these subgraphs as epitope or non-epitope subgraphs. This classifier is then taken to predict epitopes for a test antigen. On a big data set comprising 92 antigen-antibody PDB complexes, our method significantly outperforms the state-of-the-art epitope prediction methods, achieving 24.7% higher averaged f-score than the best existing models. In particular, our method can successfully identify those epitopes with a non-planarity which is too small to be addressed by the other models. Our method can also detect multiple epitopes whenever they exist
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