885 resultados para Live observation


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Enveloped virus release is driven by poorly understood proteins that are functional analogs of the coat protein assemblies that mediate intracellular vesicle trafficking. We used differential electron density mapping to detect membrane integration by membrane-bending proteins from five virus families. This demonstrates that virus matrix proteins replace an unexpectedly large portion of the lipid content of the inner membrane face, a generalized feature likely to play a role in reshaping cellular membranes.

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Beckett’s sparse and minimalist pieces have continuously addressed the nature and characteristics of the media for which they were written. What does it mean when a work written specifically for television is transposed to the stage, as film director Atom Egoyan did in his 2006 version of Beckett’s Eh Joe? This article will focus on the implications of such a transposition and discuss how Egoyan’s version reveals the haptic interface present in the original piece, between body and technology, between the flesh and “spirit made light” of the electronic broadcast.

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Remote sensing observations often have correlated errors, but the correlations are typically ignored in data assimilation for numerical weather prediction. The assumption of zero correlations is often used with data thinning methods, resulting in a loss of information. As operational centres move towards higher-resolution forecasting, there is a requirement to retain data providing detail on appropriate scales. Thus an alternative approach to dealing with observation error correlations is needed. In this article, we consider several approaches to approximating observation error correlation matrices: diagonal approximations, eigendecomposition approximations and Markov matrices. These approximations are applied in incremental variational assimilation experiments with a 1-D shallow water model using synthetic observations. Our experiments quantify analysis accuracy in comparison with a reference or ‘truth’ trajectory, as well as with analyses using the ‘true’ observation error covariance matrix. We show that it is often better to include an approximate correlation structure in the observation error covariance matrix than to incorrectly assume error independence. Furthermore, by choosing a suitable matrix approximation, it is feasible and computationally cheap to include error correlation structure in a variational data assimilation algorithm.

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Aim Earth observation (EO) products are a valuable alternative to spectral vegetation indices. We discuss the availability of EO products for analysing patterns in macroecology, particularly related to vegetation, on a range of spatial and temporal scales. Location Global. Methods We discuss four groups of EO products: land cover/cover change, vegetation structure and ecosystem productivity, fire detection, and digital elevation models. We address important practical issues arising from their use, such as assumptions underlying product generation, product accuracy and product transferability between spatial scales. We investigate the potential of EO products for analysing terrestrial ecosystems. Results Land cover, productivity and fire products are generated from long-term data using standardized algorithms to improve reliability in detecting change of land surfaces. Their global coverage renders them useful for macroecology. Their spatial resolution (e.g. GLOBCOVER vegetation, 300 m; MODIS vegetation and fire, ≥ 500 m; ASTER digital elevation, 30 m) can be a limiting factor. Canopy structure and productivity products are based on physical approaches and thus are independent of biome-specific calibrations. Active fire locations are provided in near-real time, while burnt area products show actual area burnt by fire. EO products can be assimilated into ecosystem models, and their validation information can be employed to calculate uncertainties during subsequent modelling. Main conclusions Owing to their global coverage and long-term continuity, EO end products can significantly advance the field of macroecology. EO products allow analyses of spatial biodiversity, seasonal dynamics of biomass and productivity, and consequences of disturbances on regional to global scales. Remaining drawbacks include inter-operability between products from different sensors and accuracy issues due to differences between assumptions and models underlying the generation of different EO products. Our review explains the nature of EO products and how they relate to particular ecological variables across scales to encourage their wider use in ecological applications.

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The optimal utilisation of hyper-spectral satellite observations in numerical weather prediction is often inhibited by incorrectly assuming independent interchannel observation errors. However, in order to represent these observation-error covariance structures, an accurate knowledge of the true variances and correlations is needed. This structure is likely to vary with observation type and assimilation system. The work in this article presents the initial results for the estimation of IASI interchannel observation-error correlations when the data are processed in the Met Office one-dimensional (1D-Var) and four-dimensional (4D-Var) variational assimilation systems. The method used to calculate the observation errors is a post-analysis diagnostic which utilises the background and analysis departures from the two systems. The results show significant differences in the source and structure of the observation errors when processed in the two different assimilation systems, but also highlight some common features. When the observations are processed in 1D-Var, the diagnosed error variances are approximately half the size of the error variances used in the current operational system and are very close in size to the instrument noise, suggesting that this is the main source of error. The errors contain no consistent correlations, with the exception of a handful of spectrally close channels. When the observations are processed in 4D-Var, we again find that the observation errors are being overestimated operationally, but the overestimation is significantly larger for many channels. In contrast to 1D-Var, the diagnosed error variances are often larger than the instrument noise in 4D-Var. It is postulated that horizontal errors of representation, not seen in 1D-Var, are a significant contributor to the overall error here. Finally, observation errors diagnosed from 4D-Var are found to contain strong, consistent correlation structures for channels sensitive to water vapour and surface properties.

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We review the theory and observations related to the "superhump" precession of eccentric accretion discs in close binary systems. We agree with earlier work, although for different reasons, that the discrepancy between observation and dynamical theory implies that the effect of pressure in the disc cannot be neglected. We extend earlier work that investigates this effect to include the correct expression for the radius at which resonant orbits occur. Using analytic expressions for the accretion disc structure, we derive a relationship between the period excess and mass ratio with the pressure effects included. This is compared to the observed data, recently derived results for detailed integration of the disc equations and the equivalent empirically derived relations and used to predict values for the mass ratio based on measured values of the period excess for 88 systems.

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A candidate live vaccine for avian pathogenic Escherichia coli (APEC) was constructed from a virulent field APEC O78 strain by mutation of the aroA gene. The mutant was highly similar to the parent wild-type strain in respect of colony morphology, motility, growth in suspension, hemagglutination, Congo Red binding, HEp-2 cell adhesion, and the elaboration of surface antigens type 1 fimbriae and flagella, although production of curli fimbriae was reduced marginally. The mutant proved avirulent when inoculated into 1-day-old chicks by spray application and when presented again in the drinking water at 7 days of age. Chickens and turkeys vaccinated with an O78 aroA mutant were protected against a challenge at 6 wk of age by virulent APEC strains.

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Live bacterial cells (LBC) are administered orally as attenuated vaccines, to deliver biopharmaceutical agents, and as probiotics to improve gastrointestinal health. However, LBC present unique formulation challenges and must survive gastrointestinal antimicrobial defenses including gastric acid after administration. We present a simple new formulation concept, termed Polymer Film Laminate (PFL). LBC are ambient dried onto cast acid-resistant enteric polymer films that are then laminated together to produce a solid oral dosage form. LBC of a model live bacterial vaccine and a probiotic were dried directly onto a cast film of enteric polymer. The effectiveness at protecting dried cells in a simulated gastric fluid (pH 2.0) depended on the composition of enteric polymer film used, with a blend of ethylcellulose plus Eudragit L100 55 providing greater protection from acid than Eudragit alone. However, although PFL made from blended polymers films completely released low molecular weight dye into intestinal conditions (pH 7.0), they failed to release LBC. In contrast, PFL made from Eudragit alone successfully protected dried probiotic or vaccine LBC from simulated gastric fluid for 2h, and subsequently released all viable cells within 60min of transfer into simulated intestinal fluid. Release kinetics could be controlled by modifying the lamination method.

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Data assimilation methods which avoid the assumption of Gaussian error statistics are being developed for geoscience applications. We investigate how the relaxation of the Gaussian assumption affects the impact observations have within the assimilation process. The effect of non-Gaussian observation error (described by the likelihood) is compared to previously published work studying the effect of a non-Gaussian prior. The observation impact is measured in three ways: the sensitivity of the analysis to the observations, the mutual information, and the relative entropy. These three measures have all been studied in the case of Gaussian data assimilation and, in this case, have a known analytical form. It is shown that the analysis sensitivity can also be derived analytically when at least one of the prior or likelihood is Gaussian. This derivation shows an interesting asymmetry in the relationship between analysis sensitivity and analysis error covariance when the two different sources of non-Gaussian structure are considered (likelihood vs. prior). This is illustrated for a simple scalar case and used to infer the effect of the non-Gaussian structure on mutual information and relative entropy, which are more natural choices of metric in non-Gaussian data assimilation. It is concluded that approximating non-Gaussian error distributions as Gaussian can give significantly erroneous estimates of observation impact. The degree of the error depends not only on the nature of the non-Gaussian structure, but also on the metric used to measure the observation impact and the source of the non-Gaussian structure.

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For certain observing types, such as those that are remotely sensed, the observation errors are correlated and these correlations are state- and time-dependent. In this work, we develop a method for diagnosing and incorporating spatially correlated and time-dependent observation error in an ensemble data assimilation system. The method combines an ensemble transform Kalman filter with a method that uses statistical averages of background and analysis innovations to provide an estimate of the observation error covariance matrix. To evaluate the performance of the method, we perform identical twin experiments using the Lorenz ’96 and Kuramoto-Sivashinsky models. Using our approach, a good approximation to the true observation error covariance can be recovered in cases where the initial estimate of the error covariance is incorrect. Spatial observation error covariances where the length scale of the true covariance changes slowly in time can also be captured. We find that using the estimated correlated observation error in the assimilation improves the analysis.

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Many human behaviours and pathologies have been attributed to the putative mirror neuron system, a neural system that is active during both the observation and execution of actions. While there are now a very large number of papers on the mirror neuron system, variations in the methods and analyses employed by researchers mean that the basic characteristics of the mirror response are not clear. This review focuses on three important aspects of the mirror response, as measured by modulations in corticospinal excitability: (1) muscle specificity, (2) direction, and (3) timing of modulation. We focus mainly on electromyographic (EMG) data gathered following single-pulse transcranial magnetic stimulation (TMS), because this method provides precise information regarding these three aspects of the response. Data from paired-pulse TMS paradigms and peripheral nerve stimulation (PNS) are also considered when we discuss the possible mechanisms underlying the mirror response. In this systematic review of the literature, we examine the findings of 85 TMS and PNS studies of the human mirror response, and consider the limitations and advantages of the different methodological approaches these have adopted in relation to discrepancies between their findings. We conclude by proposing a testable model of how action observation modulates corticospinal excitability in humans. Specifically, we propose that action observation elicits an early, non-specific facilitation of corticospinal excitability (at around 90 ms from action onset), followed by a later modulation of activity specific to the muscles involved in the observed action (from around 200 ms). Testing this model will greatly advance our understanding of the mirror mechanism and provide a more stable grounding on which to base inferences about its role in human behaviour.

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The analysis step of the (ensemble) Kalman filter is optimal when (1) the distribution of the background is Gaussian, (2) state variables and observations are related via a linear operator, and (3) the observational error is of additive nature and has Gaussian distribution. When these conditions are largely violated, a pre-processing step known as Gaussian anamorphosis (GA) can be applied. The objective of this procedure is to obtain state variables and observations that better fulfil the Gaussianity conditions in some sense. In this work we analyse GA from a joint perspective, paying attention to the effects of transformations in the joint state variable/observation space. First, we study transformations for state variables and observations that are independent from each other. Then, we introduce a targeted joint transformation with the objective to obtain joint Gaussianity in the transformed space. We focus primarily in the univariate case, and briefly comment on the multivariate one. A key point of this paper is that, when (1)-(3) are violated, using the analysis step of the EnKF will not recover the exact posterior density in spite of any transformations one may perform. These transformations, however, provide approximations of different quality to the Bayesian solution of the problem. Using an example in which the Bayesian posterior can be analytically computed, we assess the quality of the analysis distributions generated after applying the EnKF analysis step in conjunction with different GA options. The value of the targeted joint transformation is particularly clear for the case when the prior is Gaussian, the marginal density for the observations is close to Gaussian, and the likelihood is a Gaussian mixture.

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We present a novel but simple enteric coated sphere formulation containing probiotic bacteria (Lactobacillus casei). Oral delivery of live bacterial cells (LBC) requires live cells to survive firstly manufacturing processes and secondly GI microbicidal defenses including gastric acid. We incorporated live L. casei directly in the granulation liquid, followed by granulation, extrusion, spheronization, drying and spray coating to produce dried live probiotic spheres. A blend of MCC, calcium-crosslinked alginate, and lactose was developed that gave improved live cell survival during manufacturing, and gave excellent protection from gastric acid plus rapid release in intestinal conditions. No significant loss of viability was observed in all steps except drying, which resulted in approximately 1 log loss of viable cells. Eudragit coating was used to protect dried live cells from acid, and microcrystalline cellulose (MCC) was combined with sodium alginate to achieve efficient sphere disintegration leading to rapid and complete bacterial cell release in intestinal conditions. Viability and release of L. casei was evaluated in vitro in simulated GI conditions. Uncoated spheres gave partial acid protection, but enteric coated spheres effectively protected dried probiotic LBC from acid for 2 h, and subsequently released all viable cells within 1h of transfer into simulated intestinal fluid.