Social learning in otters

The use of information provided by others to tackle life's challenges is widespread, but should not be employed indiscriminately if it is to be adaptive. Evidence is accumulating that animals are indeed selective and adopt ‘social learning strategies’. However, studies have generally focused on fish, bird and primate species. Here we extend research on social learning strategies to a taxonomic group that has been neglected until now: otters (subfamily Lutrinae). We collected social association data on captive groups of two gregarious species: smooth-coated otters (Lutrogale perspicillata), known to hunt fish cooperatively in the wild, and Asian short-clawed otters (Aonyx cinereus), which feed individually on prey requiring extractive foraging behaviours. We then presented otter groups with a series of novel foraging tasks, and inferred social transmission of task solutions with network-based diffusion analysis. We show that smooth-coated otters can socially learn how to exploit novel food sources and may adopt a ‘copy when young’ strategy. We found no evidence for social learning in the Asian short-clawed otters. Otters are thus a promising model system for comparative research into social learning strategies, while conservation reintroduction programmes may benefit from facilitating the social transmission of survival skills in these vulnerable specie

Behavioural homogenisation with spillovers in a normative domain

The importance of culture for human social evolution hinges largely on the extent to which culture supports outcomes that would not otherwise occur. An especially controversial claim is that social learning leads groups to coalesce around group-typical behaviours and associated social norms that spill over to shape choices in asocial settings. To test this, we conducted an experiment with 878 groups of participants in 116 communities in Sudan. Participants watched a short film and evaluated the appropriate way to behave in the situation dramatized in the film. Each session consisted of an asocial condition in which participants provided private evaluations and a social condition in which they provided public evaluations. Public evaluations allowed for social learning. Across sessions, we randomized the order of the two conditions. Public choices dramatically increased the homogeneity of normative evaluations. When the social condition was first, this homogenizing effect spilled over to subsequent asocial conditions. The asocial condition when first was thus alone in producing distinctly heterogeneous groups. Altogether, information about the choices of others led participants to converge rapidly on similar normative evaluations that continued to hold sway in subsequent asocial settings. These spillovers were at least partly owing to the combined effects of conformity and self-consistency. Conformity dominated self-consistency when the two mechanisms were in conflict, but self-consistency otherwise produced choices that persisted through time. Additionally, the tendency to conform was heterogeneous. Females conformed more than males, and conformity increased with the number of other people a decision-maker observed before making her own choice

Gaussian Process Pseudo-Likelihood Models for Sequence Labeling

Several machine learning problems arising in natural language processing can be modeled as a sequence labeling problem. We provide Gaussian process models based on pseudo-likelihood approximation to perform sequence labeling. Gaussian processes (GPs) provide a Bayesian approach to learning in a kernel based framework. The pseudo-likelihood model enables one to capture long range dependencies among the output components of the sequence without becoming computationally intractable. We use an efficient variational Gaussian approximation method to perform inference in the proposed model. We also provide an iterative algorithm which can effectively make use of the information from the neighboring labels to perform prediction. The ability to capture long range dependencies makes the proposed approach useful for a wide range of sequence labeling problems. Numerical experiments on some sequence labeling data sets demonstrate the usefulness of the proposed approach.Comment: 18 pages, 5 figure

The dynamics of apparent horizons in Robinson-Trautman spacetimes

We present an alternative scheme of finding apparent horizons based on spectral methods applied to Robinson-Trautman spacetimes. We have considered distinct initial data such as representing the spheroids of matter and the head-on collision of two non-rotating black holes. The evolution of the apparent horizon is presented. We have obtained in some cases a mass gap between the final Bondi and apparent horizon masses, whose implications were briefly commented in the light of the thermodynamics of black holes.Comment: 9 pages, 7 figure

Background risk of breast cancer and the association between physical activity and mammographic density

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A single-photon transistor using nano-scale surface plasmons

It is well known that light quanta (photons) can interact with each other in nonlinear media, much like massive particles do, but in practice these interactions are usually very weak. Here we describe a novel approach to realize strong nonlinear interactions at the single-photon level. Our method makes use of recently demonstrated efficient coupling between individual optical emitters and tightly confined, propagating surface plasmon excitations on conducting nanowires. We show that this system can act as a nonlinear two-photon switch for incident photons propagating along the nanowire, which can be coherently controlled using quantum optical techniques. As a novel application, we discuss how the interaction can be tailored to create a single-photon transistor, where the presence or absence of a single incident photon in a ``gate'' field is sufficient to completely control the propagation of subsequent ``signal'' photons.Comment: 20 pages, 4 figure

Quantifying the effects of temperature on mosquito and parasite traits that determine the transmission potential of human malaria

Malaria transmission is known to be strongly impacted by temperature. The current understanding of how temperature affects mosquito and parasite life history traits derives from a limited number of empirical studies. These studies, some dating back to the early part of last century, are often poorly controlled, have limited replication, explore a narrow range of temperatures, and use a mixture of parasite and mosquito species. Here, we use a single pairing of the Asian mosquito vector, An. stephensi and the human malaria parasite, P. falciparum to conduct a comprehensive evaluation of the thermal performance curves of a range of mosquito and parasite traits relevant to transmission. We show that biting rate, adult mortality rate, parasite development rate, and vector competence are temperature sensitive. Importantly, we find qualitative and quantitative differences to the assumed temperature-dependent relationships. To explore the overall implications of temperature for transmission, we first use a standard model of relative vectorial capacity. This approach suggests a temperature optimum for transmission of 29°C, with minimum and maximum temperatures of 12°C and 38°C, respectively. However, the robustness of the vectorial capacity approach is challenged by the fact that the empirical data violate several of the model's simplifying assumptions. Accordingly, we present an alternative model of relative force of infection that better captures the observed biology of the vector-parasite interaction. This model suggests a temperature optimum for transmission of 26°C, with a minimum and maximum of 17°C and 35°C, respectively. The differences between the models lead to potentially divergent predictions for the potential impacts of current and future climate change on malaria transmission. The study provides a framework for more detailed, system-specific studies that are essential to develop an improved understanding on the effects of temperature on malaria transmission

Relation of Serum Estrogen Metabolites with Terminal Duct Lobular Unit Involution Among Women Undergoing Diagnostic Image-Guided Breast Biopsy

Higher levels of circulating estrogens and estrogen metabolites (EMs) have been associated with higher breast cancer risk. In breast tissues, reduced levels of terminal duct lobular unit (TDLU) involution, as reflected by higher numbers of TDLUs and acini per TDLU, have also been linked to elevated breast cancer risk. However, it is unknown whether reduced TDLU involution mediates the risk associated with circulating EMs. In a cross-sectional analysis of 94 premenopausal and 92 postmenopausal women referred for clinical breast biopsy at an academic facility in Vermont, we examined the associations of 15 EMs, quantified using liquid chromatography-tandem mass spectrometry, with the number of TDLUs and acini count/TDLU using zero-inflated Poisson regression with a robust variance estimator and ordinal logistic regression models, respectively. All analyses were stratified by menopausal status and adjusted for potential confounders. Among premenopausal women, comparing the highest vs. the lowest tertiles, levels of unconjugated estradiol (risk ratio (RR) = 1.74, 95 % confidence interval (CI) = 1.06-2.87, p trend = 0.03), 2-hydroxyestrone (RR = 1.74, 95 % CI = 1.01-3.01, p trend = 0.04), and 4-hydroxyestrone (RR = 1.74, 95 % CI = 0.99-3.06, p trend = 0.04) were associated with significantly higher TDLU count. Among postmenopausal women, higher levels of estradiol (RR = 2.09, 95 % CI = 1.01-4.30, p trend = 0.04) and 16α-hydroxyestrone (RR = 2.27, 95 % CI = 1.29-3.99, p trend = 0.02) were significantly associated with higher TDLU count. Among postmenopausal women, higher levels of EMs, specifically conjugated estrone and 2- and 4-pathway catechols, were also associated with higher acini count/TDLU. Our data suggest that higher levels of serum EMs are generally associated with lower levels of TDLU involution

Does delayed measurement affect patient reports of provider performance? Implications for performance measurement of medical assistance with tobacco cessation: A Dental PBRN study

<p>Abstract</p> <p>Background:</p> <p>We compared two methods of measuring provider performance of tobacco control activities: immediate "exit cards" versus delayed telephone follow-up surveys. Current standards, e.g. HEDIS, use delayed patient measures that may over or under-estimate overall performance.</p> <p>Methods:</p> <p>Patients completed exit cards in 60 dental practices immediately after a visit to measure whether the provider "asked" about tobacco use, and "advised" the patient to quit. One to six months later patients were asked the same questions by telephone survey. Using the exit cards as the standard, we quantified performance and calculated sensitivity (agreement of those responding yes on telephone surveys compared with exit cards) and specificity (agreement of those responding no) of the delayed measurement.</p> <p>Results:</p> <p>Among 150 patients, 21% reporting being asked about tobacco use on the exit cards and 30% reporting being asked in the delayed surveys. The sensitivity and specificity were 50% and 75%, respectively. Similarly, among 182 tobacco users, 38% reported being advised to quit on the exit cards and this increased to 51% on the delayed surveys. The sensitivity and specificity were 75% and 64%, respectively. Increasing the delay from the visit to the telephone survey resulted in increasing disagreement.</p> <p>Conclusion:</p> <p>Patient reports differed considerably in immediate versus delayed measures. These results have important implications because they suggest that our delayed measures may over-estimate performance. The immediate exit cards should be included in the armamentarium of tools for measuring providers' performance of tobacco control, and perhaps other service delivery.</p