40 research outputs found

    Segmentation of Loops from Coronal EUV Images

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    We present a procedure which extracts bright loop features from solar EUV images. In terms of image intensities, these features are elongated ridge-like intensity maxima. To discriminate the maxima, we need information about the spatial derivatives of the image intensity. Commonly, the derivative estimates are strongly affected by image noise. We therefore use a regularized estimation of the derivative which is then used to interpolate a discrete vector field of ridge points ``ridgels'' which are positioned on the ridge center and have the intrinsic orientation of the local ridge direction. A scheme is proposed to connect ridgels to smooth, spline-represented curves which fit the observed loops. Finally, a half-automated user interface allows one to merge or split, eliminate or select loop fits obtained form the above procedure. In this paper we apply our tool to one of the first EUV images observed by the SECCHI instrument onboard the recently launched STEREO spacecraft. We compare the extracted loops with projected field lines computed from almost-simultaneously-taken magnetograms measured by the SOHO/MDI Doppler imager. The field lines were calculated using a linear force-free field model. This comparison allows one to verify faint and spurious loop connections produced by our segmentation tool and it also helps to prove the quality of the magnetic-field model where well-identified loop structures comply with field-line projections. We also discuss further potential applications of our tool such as loop oscillations and stereoscopy.Comment: 13 pages, 9 figures, Solar Physics, online firs

    Overstory influences on light attenuation patterns and understory plant community diversity and composition in southern boreal forests of Quebec

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    We have characterized overstory light transmission, understory light levels, and plant communities in mixedwood boreal forests of northwestern Quebec with the objective of understanding how overstory light transmission interacts with composition and time since disturbance to influence the diversity and composition of understory vegetation, and, in turn, the further attenuation of light to the forest floor by the understory. Overstory light transmission differed among three forest types (aspen, mixed deciduous-conifer, and old cedar-dominated), with old forests having higher proportions of high light levels than aspen and mixed forests, which were characterized by intermediate light levels. The composition of the understory plant communities in old forests showed the weakest correlation to overstory light transmission, although those forests had the largest range of light transmission. The strongest correlation between characteristics of overstory light transmission and understory communities was found in aspen forests. Species diversity indices were consistently higher in aspen forests but showed weak relationships with overstory light transmission. Light attenuation by the understory vegetation and total height of the understory vegetation were strongly and positively related to overstory light transmission but not forest type. Therefore, light transmission through the overstory influenced the structure and function of understory plants more than their diversity and composition. This is likely due to the strong effect of the upper understory layers, which tend to homogenize light levels at the forest floor regardless of forest type. The understory plant community acts as a filter, thereby reducing light levels at the forest floor to uniformly low levels

    Faixas normais de nutrientes em cana-de-açúcar pelos métodos ChM, DRIS e CND e nível crítico pela distribuição normal reduzida

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    Existem diversos métodos para a interpretação da diagnose foliar; o nível crítico ou as faixas de suficiência descritas na literatura são os mais utilizados. Porém, o uso de métodos de determinação de faixas normais de nutrientes que contemplam regiões específicas (localidades) aumenta a eficiência da interpretação. O objetivo deste trabalho foi determinar as faixas normais de nutrientes para a cultura da cana-de-açúcar, mediante a utilização dos métodos Chance Matemática (ChM), Sistema Integrado de Diagnose e Recomendação (DRIS) e Diagnose da Composição Nutricional (CND), além do Nível Crítico determinado pelo método de distribuição normal reduzida. O trabalho foi realizado tomando-se como base dados relativos a teores de nutrientes em amostras foliares e de produtividade de lavouras comerciais de cana-de-açúcar, localizadas no município de Campos de Goytacazes, RJ. Com o método da ChM, foram obtidas faixas de suficiência semelhantes aos métodos DRIS e CND, para N, Ca, S e Mn, enquanto para P, K, Mg, Cu e Zn os valores obtidos pela ChM foram superiores. A utilização dos métodos ChM, DRIS e CND, em lavouras comerciais de cana-de-açúcar em geral, possibilitou a obtenção de menor amplitude da faixa normal dos nutrientes, em comparação com os valores alcançados pelos métodos nível crítico e faixa de suficiência

    Simvastatin treatment reduces the cholesterol content of membrane/lipid rafts, implicating the N -methyl-D-aspartate receptor in anxiety: a literature review

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    ABSTRACT Membrane/lipid rafts (MLRs) are plasmalemmal microdomains that are essential for neuronal signaling and synaptic development/stabilization. Inhibitors of 3-hydroxy-3-methylglutaryl-coenzyme-A reductase (statins) can disable the N-methyl-D-aspartate (NMDA) receptor through disruption of MLRs and, in turn, decrease NMDA-mediated anxiety. This hypothesis will contribute to understanding the critical roles of simvastatin in treating anxiety via the NMDA receptor

    Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

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    Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions. Funding: Bill & Melinda Gates Foundation

    Snails on oceanic islands: Testing the general dynamic model of oceanic island biogeography using linear mixed effect models

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    Aim: We collate and analyse data for land snail diversity and endemism, as a means of testing the explanatory power of the general dynamic model of oceanic island biogeography (GDM): a theoretical model linking trends in species immigration, speciation and extinction to a generalized island ontogeny. Location: Eight oceanic archipelagos: Azores, Canaries, Hawaii, Galápagos, Madeira, Samoa, Society, Tristan da Cunha. Methods: Using data obtained from literature sources we examined the power of the GDM through its derivative ATT2 model (i.e. diversity metric = b1 + b2Area + b3Time + b4Time2), in comparison with all the possible simpler models, e.g. including only area or time. The diversity metrics considered were the number of (1) native species, (2) archipelagic endemic species, and (3) single-island endemic species. Models were evaluated using both log-transformed and untransformed diversity data by means of linear mixed effect models. For Hawaii and the Canaries, responses of different major taxonomic groups were also analysed separately. Results: The ATT2 model was always included within the group of best models and, in many cases, was the single-best model and was particularly successful in fitting the log-transformed diversity metrics. In four archipelagos, a hump-shaped relationship with time (island age) is apparent, while the other four archipelagos show a general increase of species richness with island age. In Hawaii and the Canaries outcomes vary between different taxonomic groups. Main conclusions: The GDM is an intentionally simplified representation of environmental and diversity dynamics on oceanic islands, which predicts a simple positive relationship between diversity and island area combined with a humped response to time. We find broad support for the applicability of this model, especially when a full range of island developmental stages is present. However, our results also show that the varied mechanisms of island origins and the differing responses of major taxa should be taken into consideration when interpreting diversity metrics in terms of the GDM. This heterogeneity is reflected in the fact that no single model outperforms all the other models for all datasets analysed. © 2012 Blackwell Publishing Ltd

    Contrasting response to Pleistocene climate change by ground-living and arboreal Mandarina snails from the oceanic Hahajima archipelago

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    While the genetic impact of Pleistocene climate change on temperate species has been well characterized, especially in Europe and North America, an effect on the diversification of species on oceanic islands has been less well studied. This is perhaps a surprising observation given the traditional and continuing contribution of island species (e.g. Darwin's finches, Partula snails, Lord Howe Island palms) to understand speciation. Here, we combine mitochondrial and microsatellite data from the ground-living and arboreal Mandarina snails of the oceanic, subtropical Hahajima archipelago (Ogasawara, colloquially ‘Galápagos of the Orient’) to enable a comparative approach to understand the impact of the Pleistocene glaciations on their phylogeography. Prior work suggested that several narrowly divergent, ground-living species pairs of Mandarina populations on the outlying islands, as well as the low-lying southern and central parts of Hahajima, probably underwent bottlenecks and subsequent expansions during the recent Pleistocene. Here, the most striking finding is that largely arboreal species have deeply divergent, geographically restricted mitochondrial lineages, in contrast to a census size that is at least an order of magnitude lower than ground-living snails. As populations of both types are highly polymorphic at microsatellite loci, the systematic difference at the mitochondrial locus probably indicates a contrasting effect of the Pleistocene climate cycles on the two groups. We speculate that this may have partly come about owing to a reduced efficacy of natural selection on the more greatly structured populations of arboreal snails. If so, then a prediction is that the genome of other snails, or other species with limited mobility, will show a similar response to the Pleistocene climate cycles
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