879 resultados para Effort intensity


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Features analysis is an important task which can significantly affect the performance of automatic bacteria colony picking. Unstructured environments also affect the automatic colony screening. This paper presents a novel approach for adaptive colony segmentation in unstructured environments by treating the detected peaks of intensity histograms as a morphological feature of images. In order to avoid disturbing peaks, an entropy based mean shift filter is introduced to smooth images as a preprocessing step. The relevance and importance of these features can be determined in an improved support vector machine classifier using unascertained least square estimation. Experimental results show that the proposed unascertained least square support vector machine (ULSSVM) has better recognition accuracy than the other state-of-the-art techniques, and its training process takes less time than most of the traditional approaches presented in this paper.

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Biological invasions, nutrient enrichment and ocean warming are known to threaten biodiversity and ecosystem functioning. The independent effects of these ecological stressors are well studied, however, we lack understanding of their cumulative effects, which may be additive, antagonistic or synergistic. For example, the impacts of biological invasions are often determined by environmental context, which suggests that the effects of invasive species may vary with other stressors such as pollution or climate change. This study examined the effects of an invasive seaweed (Sargassum muticum) on the structure and functioning of a benthic marine assemblage and tested explicitly whether these effects varied with nutrient enrichment and ocean warming. Overall, the presence of Sargassum muticum increased assemblage productivity rates and warming altered algal assemblage structure, which was characterised by a decrease in kelp and an increase in ephemeral green algae. The effects of Sargassum muticum on total algal biomass accumulation, however, varied with nutrient enrichment and warming producing antagonistic cumulative effects on total algal biomass accumulation. These findings show that the nature of stressor interactions may vary with stressor intensity and among response variables, which leads to less predictable consequences for the structure and functioning of communities.

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Congenital anomalies (CA) are the paradigm example of rare diseases liable to primary prevention actions due to the multifactorial etiology of many of them, involving a number of environmental factors together with genetic predispositions. Yet despite the preventive potential, lack of attention to an integrated preventive strategy has led to the prevalence of CA remaining relatively stable in recent decades. The 2 European projects, EUROCAT and EUROPLAN, have joined efforts to provide the first science-based and comprehensive set of recommendations for the primary prevention of CA in the European Union. The resulting EUROCAT-EUROPLAN 'Recommendations on Policies to Be Considered for the Primary Prevention of Congenital Anomalies in National Plans and Strategies on Rare Diseases' were issued in 2012 and endorsed by EUCERD (European Union Committee of Experts on Rare Diseases) in 2013. The recommendations exploit interdisciplinary expertise encompassing drugs, diet, lifestyles, maternal health status, and the environment. The recommendations include evidence-based actions aimed at reducing risk factors and at increasing protective factors and behaviors at both individual and population level. Moreover, consideration is given to topics specifically related to CA (e.g. folate status, teratogens) as well as of broad public health impact (e.g. obesity, smoking) which call for specific attention to their relevance in the pre- and periconceptional period. The recommendations, reported entirely in this paper, are a comprehensive tool to implement primary prevention into national policies on rare diseases in Europe.

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Opacity is a property of many plasmas. It is normally expected that if an emission line in a plasma becomes optically thick, then its intensity ratio to that of another transition that remains optically thin should decrease. However, radiative transfer calculations undertaken both by ourselves and others predict that under certain conditions the intensity ratio of an optically thick to an optically thin line can show an increase over the optically thin value, indicating an enhancement in the former. These conditions include the geometry of the emitting plasma and its orientation to the observer. A similar effect can take place between lines of differing optical depths. While previous observational studies have focused on stellar point sources, here we investigate the spatially resolved solar atmosphere using measurements of the I(1032 Å)/I(1038 Å) intensity ratio of O VI in several regions obtained with the Solar Ultraviolet Measurements of Emitted Radiation instrument on board the Solar and Heliospheric Observatory satellite. We find several I(1032 Å)/I(1038 Å) ratios observed on the disk to be significantly larger than the optically thin value of 2.0, providing the first detection (to our knowledge) of intensity enhancement in the ratio arising from opacity effects in the solar atmosphere. The agreement between observation and theory is excellent and confirms that the O VI emission originates from a slab-like geometry in the solar atmosphere, rather than from cylindrical structures.

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ABSTRACT BODY: To resolve outstanding questions on heating of coronal loops, we study intensity fluctuations in inter-moss portions of active region core loops as observed with AIA/SDO. The 94Å fluctuations (Figure 1) have structure on timescales shorter than radiative and conductive cooling times. Each of several strong 94Å brightenings is followed after ~8 min by a broader peak in the cooler 335Å emission. This indicates that we see emission from the hot component of the 94Å contribution function. No hotter contributions appear, and we conclude that the 94Å intensity can be used as a proxy for energy injection into the loop plasma. The probability density function of the observed 94Å intensity has 'heavy tails' that approach zero more slowly than the tails of a normal distribution. Hence, large fluctuations dominate the behavior of the system. The resulting 'intermittence' is associated with power-law or exponential scaling of the related variables, and these in turn are associated with turbulent phenomena. The intensity plots in Figure 1 resemble multifractal time series, which are common to various forms of turbulent energy dissipation. In these systems a single fractal dimension is insufficient to describe the dynamics and instead there is a spectrum of fractal dimensions that quantify the self-similar properties. Figure 2 shows the multifractal spectrum from our data to be invariant over timescales from 24 s to 6.4 min. We compare these results to outputs from theoretical energy dissipation models based on MHD turbulence, and in some cases we find substantial agreement, in terms of intermittence, multifractality and scale invariance. Figure 1. Time traces of 94A intensity in the inter-moss portions of four AR core loops. Figure 2. Multifractal spectra showing timescale invariance. The four cases of Figure 1 are included.

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Using low-energy electron-diffraction (LEED) formalism, we demonstrate theoretically that LEED I-V spectra are characterized mainly by short-range order. We also show experimentally that diffuse LEED (DLEED) I-V spectra can be accurately measured from a disordered system using a video-LEED system even at very low coverage. These spectra demonstrate that experimental DLEED I-V spectra from disordered systems may be used to determine local structures. As an example, it is shown that experimental DLEED I-V spectra from K/Co {1010BAR} at potassium coverages of 0.07, 0.1, and 0.13 monolayer closely resemble calculated and experimental LEED I-V spectra for a well-ordered Co{1010BAR}-c(2X2)-K superstructure, leading to the conclusion that at low coverages, potassium atoms are located in the fourfold-hollow sites and that there is no large bond-length change with coverage.

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Background: We examined whether higher effort-reward imbalance (ERI) and lower job control are associated with exit from the labour market. 

Methods: There were 1263 participants aged 50-74 years from the English Longitudinal Study on Ageing with data on working status and work-related psychosocial factors at baseline (wave 2; 2004-2005), and working status at follow-up (wave 5; 2010-2011). Psychosocial factors at work were assessed using a short validated version of ERI and job control. An allostatic load index was formed using 13 biological parameters. Depressive symptoms were measured using the Center for Epidemiologic Studies Depression Scale. Exit from the labour market was defined as not working in the labour market when 61 years old or younger in 2010-2011. 

Results: Higher ERI OR=1.62 (95% CI 1.01 to 2.61, p=0.048) predicted exit from the labour market independent of age, sex, education, occupational class, allostatic load and depression. Job control OR=0.60 (95% CI 0.42 to 0.85, p=0.004) was associated with exit from the labour market independent of age, sex, education, occupation and depression. The association of higher effort OR=1.32 (95% CI 1.01 to 1.73, p=0.045) with exit from the labour market was independent of age, sex and depression but attenuated to non-significance when additionally controlling for socioeconomic measures. Reward was not related to exit from the labour market. 

Conclusions: Stressful work conditions can be a risk for exiting the labour market before the age of 61 years. Neither socioeconomic position nor allostatic load and depressive symptoms seem to explain this association.

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Efficient identification and follow-up of astronomical transients is hindered by the need for humans to manually select promising candidates from data streams that contain many false positives. These artefacts arise in the difference images that are produced by most major ground-based time-domain surveys with large format CCD cameras. This dependence on humans to reject bogus detections is unsustainable for next generation all-sky surveys and significant effort is now being invested to solve the problem computationally. In this paper, we explore a simple machine learning approach to real-bogus classification by constructing a training set from the image data of similar to 32 000 real astrophysical transients and bogus detections from the Pan-STARRS1 Medium Deep Survey. We derive our feature representation from the pixel intensity values of a 20 x 20 pixel stamp around the centre of the candidates. This differs from previous work in that it works directly on the pixels rather than catalogued domain knowledge for feature design or selection. Three machine learning algorithms are trained (artificial neural networks, support vector machines and random forests) and their performances are tested on a held-out subset of 25 per cent of the training data. We find the best results from the random forest classifier and demonstrate that by accepting a false positive rate of 1 per cent, the classifier initially suggests a missed detection rate of around 10 per cent. However, we also find that a combination of bright star variability, nuclear transients and uncertainty in human labelling means that our best estimate of the missed detection rate is approximately 6 per cent.

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This article examines the influence on the engineering design process of the primary objective of validation, whether it is proving a model, a technology or a product. Through the examination of a number of stiffened panel case studies, the relationships between simulation, validation, design and the final product are established and discussed. The work demonstrates the complex interactions between the original (or anticipated) design model, the analysis model, the validation activities and the product in service. The outcome shows clearly some unintended consequences. High fidelity validation test simulations require a different set of detailed parameters to accurately capture behaviour. By doing so, there is a divergence from the original computer-aided design model, intrinsically limiting the value of the validation with respect to the product. This work represents a shift from the traditional perspective of encapsulating and controlling errors between simulation and experimental test to consideration of the wider design-test process. Specifically, it is a reflection on the implications of how models are built and validated, and the effect on results and understanding of structural behaviour. This article then identifies key checkpoints in the design process and how these should be used to update the computer-aided design system parameters for a design. This work strikes at a fundamental challenge in understanding the interaction between design, certification and operation of any complex system.