74 research outputs found

    Effect of Anthropogenic Landscape Features on Population Genetic Differentiation of Przewalski's Gazelle: Main Role of Human Settlement

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    Anthropogenic landscapes influence evolutionary processes such as population genetic differentiation, however, not every type of landscape features exert the same effect on a species, hence it is necessary to estimate their relative effect for species management and conservation. Przewalski's gazelle (Procapra przewalskii), which inhabits a human-altered area on Qinghai-Tibet Plateau, is one of the most endangered antelope species in the world. Here, we report a landscape genetic study on Przewalski's gazelle. We used skin and fecal samples of 169 wild gazelles collected from nine populations and thirteen microsatellite markers to assess the genetic effect of anthropogenic landscape features on this species. For comparison, the genetic effect of geographical distance and topography were also evaluated. We found significant genetic differentiation, six genetic groups and restricted dispersal pattern in Przewalski's gazelle. Topography, human settlement and road appear to be responsible for observed genetic differentiation as they were significantly correlated with both genetic distance measures [FST/(1−FST) and F′ST/(1−F′ST)] in Mantel tests. IBD (isolation by distance) was also inferred as a significant factor in Mantel tests when genetic distance was measured as FST/(1−FST). However, using partial Mantel tests, AICc calculations, causal modeling and AMOVA analysis, we found that human settlement was the main factor shaping current genetic differentiation among those tested. Altogether, our results reveal the relative influence of geographical distance, topography and three anthropogenic landscape-type on population genetic differentiation of Przewalski's gazelle and provide useful information for conservation measures on this endangered species

    Morphologic signs of ICH using MRI and MRA

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    A Semantics for Tracing Declarative Multi-Paradigm Programs

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    We introduce the theoretical basis for tracing lazy functional logic computations in a declarative multi-paradigm language like Curry. Tracing computations is a difficult task due to the subtleties of the underlying operational semantics which combines laziness and non-determinism. In this work, we define an instrumented operational semantics that generates not only the computed values and bindings but also an appropriate data structure—a sort of redex trail—which can be used to trace computations at an adequate level of abstraction. In contrast to previous approaches, which rely solely on a transformation to instrument source programs, the formal definition of a tracing semantics improves the understanding of the tracing process. Furthermore, it allows us to formally prove the correctness of the computed trail. A prototype implementation of a tracer based on this semantics demonstrates the usefulness of our approach

    A Semantics for Tracing Declarative Multi-Paradigm Programs

    No full text
    We introduce the theoretical basis for tracing lazy functional logic computations in a declarative multi-paradigm language like Curry. Tracing computations is a difficult task due to the subtleties of the underlying operational semantics which combines laziness and non-determinism. In this work, we define an instrumented operational semantics that generates not only the computed values and bindings but also an appropriate data structure—a sort of redex trail—which can be used to trace computations at an adequate level of abstraction. In contrast to previous approaches, which rely solely on a transformation to instrument source programs, the formal definition of a tracing semantics improves the understanding of the tracing process. Furthermore, it allows us to formally prove the correctness of the computed trail. A prototype implementation of a tracer based on this semantics demonstrates the usefulness of our approach

    Childbirth satisfaction and perceptions of control: Postnatal psychological implications

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    2020 MA Healthcare Ltd. All rights reserved. Background Satisfaction with childbirth is associated with a number of factors prior to and during birth, including perceived control during labour, and has implications for postnatal psychological health. Methods A total of 38 pregnant women recruited prior to 20-weeks gestation completed questionnaires regarding perceptions of control during, and satisfaction with, childbirth, mental health and maternal attachment at two-months postpartum. Birth details and breastfeeding difficulties were obtained from hospital records. Results Satisfaction with childbirth was associated with perceived control and a physiological birth, and perceived control was associated with a physiological birth and midwife-led continuity of care. At two-months postpartum, satisfaction with childbirth was associated with fewer depressive symptoms, while perceived control was associated with fewer anxiety symptoms. Discussion It is important for healthcare providers to implement practices that support birthing satisfaction, such as provision of midwife-led continuity of care. Healthcare provision should also provide psychological support to mothers whose birthing experience was unsatisfactory and tailor additional support during early breastfeeding for these women

    CollaGen: Collaboration between automatic cartographic Generalisation Processes

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    International audienceCartographic generalisation seeks to summarise geographical information to produce legible maps at smaller scales. Past research led to the development of many automated cartographic generalisation processes, each one being more or less specialised to a particular problem: a landscape like urban areas, a data theme like land use, a cartographic conflict like linear symbol overlap or most of the time of mix of the three. This paper deals with the development of a model allowing collaborative generalisation i.e. the collaboration between automatic processes like these in order to tackle the generalisation of a complete map. CollaGen, our proposed model, allows to partition data in geographic spaces and to find to best suited process to generalise each space. The applications of a process on a space are automatically orchestrated. Interoperability between processes is managed thanks to formal constraints and side effects are monitored after each process application. Results from CollaGen prototype are shown and discussed
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