94 resultados para Simultaneous interpreting


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Magnetic resonance imaging (MRI) offers the opportunity to study biological tissues and processes in a non-disruptive manner. The technique shows promise for the study of the load-bearing performance (consolidation) of articular cartilage and changes in articular cartilage accompanying osteoarthritis. Consolidation of articular cartilage involves the recording of two transient characteristics: the change over time of strain and the hydrostatic excess pore pressure (HEPP). MRI study of cartilage consolidation under mechanical load is limited by difficulties in measuring the HEPP in the presence of the strong magnetic fields associated with the MRI technique. Here we describe the use of MRI to image and characterize bovine articular cartilage deforming under load in an MRI compatible consolidometer while monitoring pressure with a Fabry-Perot interferometer-based fiber-optic pressure transducer.

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Multiple copies of expression cassettes driven by the Trichoderma reesei xylanase 2 (xyn2) and cellobiohydrolase 2 (cbh2) promoters were introduced into the recombinant T. reesei EC-21 generated to express a thermostable Dictyoglomus thermophilum xylanase (XynB) under the egl2 promoter for further improvement of the enzyme yield. The transformants were screened based on increased XynB activity only. Multiple promoter transformant MPP-4 expressing the xynB gene under all the three promoters was found to be the highest producer of XynB, giving a 65% increase in yield compared to the parental single-promoter recombinant EC-21. The multiple-promoter transformant strains harboured six to nine copies of the xynB gene. Amongst the three promoters, egl2 seemed to have the strongest effect on XynB expression. The shotgun approach we used proved to be effective for rapid enhancement of protein expression using three promoters active at the near-neutral pH of the cultivation medium.

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In Australia, as in many western education systems over the last two decades, discourses of accountability and performativity have reshaped education policy that has in turn reorganised the work of school leaders and teachers. One of the effects of this reorganisation is increased attention to the production, analysis and display of student achievement data. In this paper we examine in detail a sequence of the production and reading of literacy assessment data in a small Catholic school. Our analysis uses institutional ethnography’s concept of the ‘active text’, the text as occurring in a specific place and time even as it is articulated to social relations beyond its immediate context. Through this process we learn from those involved how their everyday work brings into being formalised, textually authorised processes in a local site that ensure the school meets accountability requirements while enabling teachers to resist standardisation of literacy teaching and assessment.

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We investigated memories of room-sized spatial layouts learned by sequentially or simultaneously viewing objects from a stationary position. In three experiments, sequential viewing (one or two objects at a time) yielded subsequent memory performance that was equivalent or superior to simultaneous viewing of all objects, even though sequential viewing lacked direct access to the entire layout. This finding was replicated by replacing sequential viewing with directed viewing in which all objects were presented simultaneously and participants’ attention was externally focused on each object sequentially, indicating that the advantage of sequential viewing over simultaneous viewing may have originated from focal attention to individual object locations. These results suggest that memory representation of object-to-object relations can be constructed efficiently by encoding each object location separately, when those locations are defined within a single spatial reference system. These findings highlight the importance of considering object presentation procedures when studying spatial learning mechanisms.

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Multiscale numerical modeling of the species balance and transport in the ionized gas phase and on the nanostructured solid surface complemented by the heat exchange model is used to demonstrate the possibility of minimizing the Gibbs-Thompson effect in low-temperature, low-pressure chemically active plasma-assisted growth of uniform arrays of very thin Si nanowires, impossible otherwise. It is shown that plasma-specific effects drastically shorten and decrease the dispersion of the incubation times for the nucleation of nanowires on non-uniform Au catalyst nanoparticle arrays. The fast nucleation makes it possible to avoid a common problem of small catalyst nanoparticle burying by amorphous silicon. These results explain a multitude of experimental observations on chemically active plasma-assisted Si nanowire growth and can be used for the synthesis of a range of inorganic nanowires for environmental, biomedical, energy conversion, and optoelectronic applications.

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It is shown that the simultaneous saturation of Ni nanoparticles used as catalyst for vertically aligned carbon nanotube and nanocone arrays can be improved in low-temperature plasma- or ion-assisted processes compared with neutral gas-based routes. The results of hybrid multiscale numerical simulations of the catalyst nanoarrays (particle sizes of 2 and 10 nm) saturation with carbon show the possibility of reducing the difference in catalyst incubation times for smallest and largest catalyst particles by up to a factor of 2. This approach is generic and provides process conditions for simultaneous nucleation and growth of uniform arrays of vertically aligned nanostructures. © 2008 American Institute of Physics.

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The present invention relates to genetically modified cells that are capable of optimal transgene expression by co-expressing a silencing suppressor whilst at the same time are also capable of silencing a gene, such as a naturally occurring gene of the cell. The present invention also relates to methods of producing the modified cells, as well as relates to processes for obtaining a genetically modified cell with a desired property.

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This paper presents a novel method to rank map hypotheses by the quality of localization they afford. The highest ranked hypothesis at any moment becomes the active representation that is used to guide the robot to its goal location. A single static representation is insufficient for navigation in dynamic environments where paths can be blocked periodically, a common scenario which poses significant challenges for typical planners. In our approach we simultaneously rank multiple map hypotheses by the influence that localization in each of them has on locally accurate odometry. This is done online for the current locally accurate window by formulating a factor graph of odometry relaxed by localization constraints. Comparison of the resulting perturbed odometry of each hypothesis with the original odometry yields a score that can be used to rank map hypotheses by their utility. We deploy the proposed approach on a real robot navigating a structurally noisy office environment. The configuration of the environment is physically altered outside the robots sensory horizon during navigation tasks to demonstrate the proposed approach of hypothesis selection.

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This article assesses the extent to which the recently formulated Chinese concept of “Responsible Protection” (RP) offers a valuable contribution to the normative debate over R2P’s third pillar following the controversy over military intervention in Libya. While RP draws heavily on previous proposals such as the original 2001 ICISS report and Brazil’s “Responsibility while Protecting” (RwP), by amalgamating and re-packaging these earlier ideas in a more restrictive form the initiative represents a new and distinctive interpretation of R2P. However, some aspects of RP are framed too narrowly to provide workable guidelines for determining the permissibility of military intervention for civilian protection purposes, and should therefore be clarified and refined. Nevertheless, the Chinese proposal remains significant because it offers important insights into Beijing’s current stance on R2P. More broadly, China’s RP and Brazil’s RwP initiatives illustrate the growing willingness of rising, non-Western powers to assert their own normative preferences on sovereignty, intervention and global governance.

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For robots operating in outdoor environments, a number of factors, including weather, time of day, rough terrain, high speeds, and hardware limitations, make performing vision-based simultaneous localization and mapping with current techniques infeasible due to factors such as image blur and/or underexposure, especially on smaller platforms and low-cost hardware. In this paper, we present novel visual place-recognition and odometry techniques that address the challenges posed by low lighting, perceptual change, and low-cost cameras. Our primary contribution is a novel two-step algorithm that combines fast low-resolution whole image matching with a higher-resolution patch-verification step, as well as image saliency methods that simultaneously improve performance and decrease computing time. The algorithms are demonstrated using consumer cameras mounted on a small vehicle in a mixed urban and vegetated environment and a car traversing highway and suburban streets, at different times of day and night and in various weather conditions. The algorithms achieve reliable mapping over the course of a day, both when incrementally incorporating new visual scenes from different times of day into an existing map, and when using a static map comprising visual scenes captured at only one point in time. Using the two-step place-recognition process, we demonstrate for the first time single-image, error-free place recognition at recall rates above 50% across a day-night dataset without prior training or utilization of image sequences. This place-recognition performance enables topologically correct mapping across day-night cycles.

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Competing events are common in medical research. Ignoring them in the statistical analysis can easily lead to flawed results and conclusions. This article uses a real dataset and a simple simulation to show how standard analysis fails and how such data should be analysed

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Quantifying the impact of biochemical compounds on collective cell spreading is an essential element of drug design, with various applications including developing treatments for chronic wounds and cancer. Scratch assays are a technically simple and inexpensive method used to study collective cell spreading; however, most previous interpretations of scratch assays are qualitative and do not provide estimates of the cell diffusivity, D, or the cell proliferation rate,l. Estimating D and l is important for investigating the efficacy of a potential treatment and provides insight into the mechanism through which the potential treatment acts. While a few methods for estimating D and l have been proposed, these previous methods lead to point estimates of D and l, and provide no insight into the uncertainty in these estimates. Here, we compare various types of information that can be extracted from images of a scratch assay, and quantify D and l using discrete computational simulations and approximate Bayesian computation. We show that it is possible to robustly recover estimates of D and l from synthetic data, as well as a new set of experimental data. For the first time, our approach also provides a method to estimate the uncertainty in our estimates of D and l. We anticipate that our approach can be generalized to deal with more realistic experimental scenarios in which we are interested in estimating D and l, as well as additional relevant parameters such as the strength of cell-to-cell adhesion or the strength of cell-to-substrate adhesion.