852 resultados para Inference.


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Genome-wide studies of African populations have the potential to reveal powerful insights into the evolution of our species, as these diverse populations have been exposed to intense selective pressures imposed by infectious diseases, diet, and environmental factors. Within Africa, the Sahel Belt extensively overlaps the geographical center of several endemic infections such as malaria, trypanosomiasis, meningitis, and hemorrhagic fevers. We screened 2.5 million single nucleotide polymorphisms in 161 individuals from 13 Sahelian populations, which together with published data cover Western, Central, and Eastern Sahel, and include both nomadic and sedentary groups. We confirmed the role of this Belt as a main corridor for human migrations across the continent. Strong admixture was observed in both Central and Eastern Sahelian populations, with North Africans and Near Eastern/Arabians, respectively, but it was inexistent in Western Sahelian populations. Genome-wide local ancestry inference in admixed Sahelian populations revealed several candidate regions that were significantly enriched for non-autochthonous haplotypes, and many showed to be under positive selection. The DARC gene region in Arabs and Nubians was enriched for African ancestry, whereas the RAB3GAP1/LCT/MCM6 region in Oromo, the TAS2R gene family in Fulani, and the ALMS1/NAT8 in Turkana and Samburu were enriched for non-African ancestry. Signals of positive selection varied in terms of geographic amplitude. Some genomic regions were selected across the Belt, the most striking example being the malaria-related DARC gene. Others were Western-specific (oxytocin, calcium, and heart pathways), Eastern-specific (lipid pathways), or even population-restricted (TAS2R genes in Fulani, which may reflect sexual selection).

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Inter-individual heterogeneity is evident in aging; education level is known to contribute for this heterogeneity. Using a cross-sectional study design and network inference applied to resting-state fMRI data, we show that aging was associated with decreased functional connectivity in a large cortical network. On the other hand, education level, as measured by years of formal education, produced an opposite effect on the long-term. These results demonstrate the increased brain efficiency in individuals with higher education level that may mitigate the impact of age on brain functional connectivity.

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First published online: December 16, 2014.

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Dissertação de mestrado em Educação Especial (área de especialização em Dificuldades de Aprendizagem Específicas)

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In recent decades, an increased interest has been evidenced in the research on multi-scale hierarchical modelling in the field of mechanics, and also in the field of wood products and timber engineering. One of the main motivations for hierar-chical modelling is to understand how properties, composition and structure at lower scale levels may influence and be used to predict the material properties on a macroscopic and structural engineering scale. This chapter presents the applicability of statistic and probabilistic methods, such as the Maximum Likelihood method and Bayesian methods, in the representation of timber’s mechanical properties and its inference accounting to prior information obtained in different importance scales. These methods allow to analyse distinct timber’s reference properties, such as density, bending stiffness and strength, and hierarchically consider information obtained through different non, semi or destructive tests. The basis and fundaments of the methods are described and also recommendations and limitations are discussed. The methods may be used in several contexts, however require an expert’s knowledge to assess the correct statistic fitting and define the correlation arrangement between properties.

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In Ireland, although flatfish form a valuable fishery, little is known about the smallest, the dab Limanda limanda. In this study, a variety of parameters of reproductive development, including ovarian phase description, gonadosomatic index (GSI), hepatosomatic index (HSI), relative condition (Kn) and oocyte size were analysed to provide information on the dab’s reproductive cycle and spawning periods. Sampling were collected monthly over an 18-month period using bottom trawls of the Irish coastline. A six phase macroscopic guide was developed for both sexes of dab, and verified using histology. In comparisons of macroscopic and microscopic phases, there was high agreement in the proposed female guide (86%), with males demonstratively lower (62%). No significant bias was observed between the the two reproductive methods. When the male macroscopic guide was examined, misclassification was high in phase 5 and phase 5 (41%), with 96% of misclassification occurring in adjacent phases. The sampled population was primarily composed of females, with ratios of females to males 1:0.6, although the predominance of females was less noticeable during the reproductive season. Oocyte growth in dab follows asynchronous development, and spawn over a protracted period indicating a batch spawning strategy. Spawning occurred mainly in early spring, with total regeneration of gonads by May. The length at which 50% of the population was reproductively mature was identified as 14cm and 17cm, for male and female dab, respectively. Precision and bias in age determinations using whole otoliths to age dab was investigated using six age readers from various institutions. Low levels of precision were obtained (CV: 10-23%) inferring the need for an alternative methodology. Precision and bias was influence by the level of experience of the reader, with ageing error attributed to interpretative differences and difficulty in edge determination. Sectioned otolith age determinations were subsequently compared to whole otolith age determinations using two age readers experienced in dab ageing. Although increased precision was observed in whole otoliths from previous estimates (CV=0%, 0% APE), sectioned otoliths were used for growth models. This was based on multinominal logistic regression on age length keys developed using both ageing methods. Biological data (length and age) for both sexes was applied to four growth models, where the Akaike criterion and Multi model Inference indicated the logistic model as having the best fit to the collected data. In general, female dab attained a longer length then males, with growth rates significantly different between the two sexes. Length weight relationships between the two sexes were also significantly different.

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Expert System, Inference Engine, Protection Coordination, Protection Device

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We use a threshold seemingly unrelated regressions specification to assess whether the Central and East European countries (CEECs) are synchronized in their business cycles to the Euro-area. This specification is useful in two ways: First, it takes into account the common institutional factors and the similarities across CEECs in their process of economic transition. Second, it captures business cycle asymmetries by allowing for the presence of two distinct regimes for the CEECs. As the CEECs are strongly affected by the Euro-area these regimes may be associated with Euro-area expansions and contractions. We discuss representation, estimation by maximum likelihood and inference. The methodology is illustrated by using monthly industrial production in 8 CEECs. The results show that apart from Lithuania the rest of the CEECs experience “normal” growth when the Euro-area contracts and “high” growth when the Euro-area expands. Given that the CEECs are “catching up” with the Euro-area this result shows that most CEECs seem synchronized to the Euro-area cycle. Keywords: Threshold SURE; asymmetry; business cycles; CEECs. JEL classification: C33; C50; E32.

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Oxytocin (OT) is thought to play an important role in human interpersonal information processing and behavior. By inference, OT should facilitate empathic responding, i.e. the ability to feel for others and to take their perspective. In two independent double-blind, placebo-controlled between-subjects studies, we assessed the effect of intranasally administered OT on affective empathy and perspective taking, whilst also examining potential sex differences (e.g., women being more empathic than men). In study 1, we provided 96 participants (48 men) with an empathy scenario and recorded self reports of empathic reactions to the scenario, while in study 2, a sample of 120 individuals (60 men) performed a computerized implicit perspective taking task. Whilst results from Study 1 showed no influence of OT on affective empathy, we found in Study 2 that OT exerted an effect on perspective taking ability in men. More specifically, men responded faster than women in the placebo group but they responded as slowly as women in the OT group. We conjecture that men in the OT group adopted a social perspective taking strategy, such as did women in both groups, but not men in the placebo group. On the basis of results across both studies, we suggest that self-report measures (such as used in Study 1) might be less sensitive to OT effects than more implicit measures of empathy such as that used in Study 2. If these assumptions are confirmed, one could infer that OT effects on empathic responses are more pronounced in men than women, and that any such effect is best studied using more implicit measures of empathy rather than explicit self-report measures.

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Invasive plants can have different effects of ecosystem functioning and on the provision of ecosystem services, from strongly deleterious impacts to positive effects. The nature and intensity of such effects will depend on the service and ecosystem being considered, but also on features of life strategies of invaders that influence their invasiveness as well as their influence of key processes of receiving ecosystems. To address the combined effect of these various factors we developed a robust and efficient methodological framework that allows to identify areas of possible conflict between ecosystem services and alien invasive plants, considering interactions between landscape invasibility and species invasiveness. Our framework combines the statistical robustness of multi-model inference, efficient techniques to map ecosystem services, and life strategies as a functional link between invasion, functional changes and potential provision of services by invaded ecosystems. The framework was applied to a test region in Portugal, for which we could successfully predict the current patterns of plant invasion, of ecosystem service provision, and finally of probable conflict (expressing concern for negative impacts, and value for positive impacts on services) between alien species richness (total and per plant life strategy) and the potential provision of selected services. Potential conflicts were identified for all combinations of plant strategy and ecosystem service, with an emphasis for those concerning conflicts with carbon sequestration, water regulation and wood production. Lower levels of conflict were obtained between invasive plant strategies and the habitat for biodiversity supporting service. The added value of the proposed framework in the context of landscape management and planning is discussed in perspective of anticipation of conflicts, mitigation of negative impacts, and potentiation of positive effects of plant invasions on ecosystems and their services.

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Introduction: Non-invasive brain imaging techniques often contrast experimental conditions across a cohort of participants, obfuscating distinctions in individual performance and brain mechanisms that are better characterised by the inter-trial variability. To overcome such limitations, we developed topographic analysis methods for single-trial EEG data [1]. So far this was typically based on time-frequency analysis of single-electrode data or single independent components. The method's efficacy is demonstrated for event-related responses to environmental sounds, hitherto studied at an average event-related potential (ERP) level. Methods: Nine healthy subjects participated to the experiment. Auditory meaningful sounds of common objects were used for a target detection task [2]. On each block, subjects were asked to discriminate target sounds, which were living or man-made auditory objects. Continuous 64-channel EEG was acquired during the task. Two datasets were considered for each subject including single-trial of the two conditions, living and man-made. The analysis comprised two steps. In the first part, a mixture of Gaussians analysis [3] provided representative topographies for each subject. In the second step, conditional probabilities for each Gaussian provided statistical inference on the structure of these topographies across trials, time, and experimental conditions. Similar analysis was conducted at group-level. Results: Results show that the occurrence of each map is structured in time and consistent across trials both at the single-subject and at group level. Conducting separate analyses of ERPs at single-subject and group levels, we could quantify the consistency of identified topographies and their time course of activation within and across participants as well as experimental conditions. A general agreement was found with previous analysis at average ERP level. Conclusions: This novel approach to single-trial analysis promises to have impact on several domains. In clinical research, it gives the possibility to statistically evaluate single-subject data, an essential tool for analysing patients with specific deficits and impairments and their deviation from normative standards. In cognitive neuroscience, it provides a novel tool for understanding behaviour and brain activity interdependencies at both single-subject and at group levels. In basic neurophysiology, it provides a new representation of ERPs and promises to cast light on the mechanisms of its generation and inter-individual variability.

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The dispersal process, by which individuals or other dispersing agents such as gametes or seeds move from birthplace to a new settlement locality, has important consequences for the dynamics of genes, individuals, and species. Many of the questions addressed by ecology and evolutionary biology require a good understanding of species' dispersal patterns. Much effort has thus been devoted to overcoming the difficulties associated with dispersal measurement. In this context, genetic tools have long been the focus of intensive research, providing a great variety of potential solutions to measuring dispersal. This methodological diversity is reviewed here to help (molecular) ecologists find their way toward dispersal inference and interpretation and to stimulate further developments.

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The role of land cover change as a significant component of global change has become increasingly recognized in recent decades. Large databases measuring land cover change, and the data which can potentially be used to explain the observed changes, are also becoming more commonly available. When developing statistical models to investigate observed changes, it is important to be aware that the chosen sampling strategy and modelling techniques can influence results. We present a comparison of three sampling strategies and two forms of grouped logistic regression models (multinomial and ordinal) in the investigation of patterns of successional change after agricultural land abandonment in Switzerland. Results indicated that both ordinal and nominal transitional change occurs in the landscape and that the use of different sampling regimes and modelling techniques as investigative tools yield different results. Synthesis and applications. Our multimodel inference identified successfully a set of consistently selected indicators of land cover change, which can be used to predict further change, including annual average temperature, the number of already overgrown neighbouring areas of land and distance to historically destructive avalanche sites. This allows for more reliable decision making and planning with respect to landscape management. Although both model approaches gave similar results, ordinal regression yielded more parsimonious models that identified the important predictors of land cover change more efficiently. Thus, this approach is favourable where land cover change pattern can be interpreted as an ordinal process. Otherwise, multinomial logistic regression is a viable alternative.

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Spatial econometrics has been criticized by some economists because some model specifications have been driven by data-analytic considerations rather than having a firm foundation in economic theory. In particular this applies to the so-called W matrix, which is integral to the structure of endogenous and exogenous spatial lags, and to spatial error processes, and which are almost the sine qua non of spatial econometrics. Moreover it has been suggested that the significance of a spatially lagged dependent variable involving W may be misleading, since it may be simply picking up the effects of omitted spatially dependent variables, incorrectly suggesting the existence of a spillover mechanism. In this paper we review the theoretical and empirical rationale for network dependence and spatial externalities as embodied in spatially lagged variables, arguing that failing to acknowledge their presence at least leads to biased inference, can be a cause of inconsistent estimation, and leads to an incorrect understanding of true causal processes.

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In multilevel modelling, interest in modeling the nested structure of hierarchical data has been accompanied by increasing attention to different forms of spatial interactions across different levels of the hierarchy. Neglecting such interactions is likely to create problems of inference, which typically assumes independence. In this paper we review approaches to multilevel modelling with spatial effects, and attempt to connect the two literatures, discussing the advantages and limitations of various approaches.