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131.
While bioengineers ask how the shape of diagnostic and therapeutic particles impacts their pharmacological efficiency, biodistribution, and toxicity, microbiologists suggested that morphological adaptations enable pathogens to perhaps evade the immune response. Here, a shape-dependent process is described that limits phagocytosis of filamentous Escherichia coli bacteria by macrophages: successful uptake requires access to one of the terminal bacterial filament poles. By exploiting micropatterned surfaces, we further demonstrate that microenvironmental heterogeneities can slow or inhibit phagocytosis. A comparison to existing literature reveals a common shape-controlled uptake mechanism for both high-aspect ratio filamentous bacteria and engineered particles. 相似文献
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Heike Scheibe 《纺织导报》2005,(10):143-144
通过Autoconer338产品系列,Schlafhorst(赐来福)公司向纺织行业提供了能够高效率卷绕各种规格纱线卷装的成熟、先进技术。而灵活、创新的模块技术为纱线自动络筒工艺提高经济效益奠定了基础。络筒机的主要工作之一是当纱线出现断头,或换纱管,或清纱之后,将两个纱头接在一起.形成一个几乎与正常纱线无区别的接头。这是Schlafhorst公司研发工作的重点之一,因此.该公司一直致力于对纱线捻接工艺的深入研究。 相似文献
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136.
Unsteady scientific data is one of the top challenges in visualization, because a huge amount of information must be displayed. ϵ-machines are an information-theoretic concept; they compress the dynamics in the data set to a finite-state machine, in which nodes represent local flow patterns and edges represent transitions between them. Several enhancements to the fundamental ϵ-machine representation can help users identify interesting time intervals, analyze the evolution of unusual local dynamics, and track features over time. Automatically abstracting information from the original data is a first step toward knowledge-assisted visualization. Successive findings from analysis can help provide subsequent users with knowledge gained in earlier research, resulting in a knowledge-assisted system for the analysis of unsteady-flow features based on information theory. This article is part of a special issue on knowledge-assisted visualization. 相似文献
137.
Georg Kühner Torsten Bluhm Peter Heimann Christine Hennig Hugo Kroiss Alexander Krüger Heike Laqua Marc Lewerentz Josef Maier Heike Riemann Jrg Schacht Anett Spring Andreas Werner Manfred Zilker 《Fusion Engineering and Design》2009,84(7-11):1130-1135
The stellarator W7X is a large complex experiment designed for continuous operation and planned to be operated for about 20 years. Software support is highly demanded for experiment preparation, operation and data analysis which in turn induces serious non-functional requirements on the software quality like, e.g.:
- • high availability, stability, maintainability vs.
- • high flexibility concerning change of functionality, technology, personnel
- • high versatility concerning the scale of system size and performance
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We fabricated a standard sample for a near-field optical microscope using scanning probe lithography. The sample contains a wedged pattern, which allows the measurement of various sizes within one image. The optical resolution of our near-field optical microscope has been evaluated as 40 nm, which was obtained by measuring the narrowest separable gap width of the wedged pattern. Thus a standard sample containing the wedged pattern enables clear evaluation of the resolution. 相似文献
140.
Jänicke H Böttinger M Scheuermann G 《IEEE transactions on visualization and computer graphics》2008,14(6):1459-1466
The visualization and exploration of multivariate data is still a challenging task. Methods either try to visualize all variables simultaneously at each position using glyph-based approaches or use linked views for the interaction between attribute space and physical domain such as brushing of scatterplots. Most visualizations of the attribute space are either difficult to understand or suffer from visual clutter. We propose a transformation of the high-dimensional data in attribute space to 2D that results in a point cloud, called attribute cloud, such that points with similar multivariate attributes are located close to each other. The transformation is based on ideas from multivariate density estimation and manifold learning. The resulting attribute cloud is an easy to understand visualization of multivariate data in two dimensions. We explain several techniques to incorporate additional information into the attribute cloud, that help the user get a better understanding of multivariate data. Using different examples from fluid dynamics and climate simulation, we show how brushing can be used to explore the attribute cloud and find interesting structures in physical space. 相似文献