905 resultados para Replicated Microarray Experiments


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Why it is easier to cut with even the sharpest knife when 'pressing down and sliding' than when merely 'pressing down alone' is explained. A variety of cases of cutting where the blade and workpiece have different relative motions is analysed and it is shown that the greater the 'slice/push ratio' xi given by ( blade speed parallel to the cutting edge/blade speed perpendicular to the cutting edge), the lower the cutting forces. However, friction limits the reductions attainable at the highest.. The analysis is applied to the geometry of a wheel cutting device (delicatessan slicer) and experiments with a cheddar cheese and a salami using such an instrumented device confirm the general predictions. (C) 2004 Kluwer Academic Publishers.

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Neoglycolipid technology is the basis of a microarray platform for assigning oligosaccharide ligands for carbohydrate-binding proteins. The strategy for generating the neoglycolipid probes by reductive amination results in ring opening of the core monosaccharides. This often limits applicability to short-chain saccharides, although the majority of recognition motifs are satisfactorily presented with neoglycolipids of longer oligosaccharides. Here, we describe neoglycolipids prepared by oxime ligation. We provide evidence from NMR studies that a significant proportion of the oxime-linked core monosaccharide is in the ring-closed form, and this form selectively interacts with a carbohydrate-binding protein. By microarray analyses we demonstrate the effective presentation with oxime-linked neoglycolipids of (1) Lewis(x) trisaccharide to antibodies to Lewisx, (2) sialyllactose analogs to the sialic acid-binding receptors, siglecs, and (3) N-glycans to a plant lectin that requires an intact N-acetylglucosamine core.

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Skill and risk taking are argued to be independent and to require different remedial programs. However, it is possible to contend that skill-based training could be associated with an increase, a decrease, or no change in risk taking behavior. In 3 experiments, the authors examined the influence of a skill-based training program (hazard perception) on the risk taking behavior of car drivers (using video-based driving simulations). Experiment 1 demonstrated a decrease in risk taking for novice drivers. In Experiment 2, the authors examined the possibilities that the skills training might operate through either a nonspecific reduction in risk taking or a specific improvement in hazard perception. Evidence supported the latter. These findings were replicated in a more ecological context in Experiment 3, which compared advanced and nonadvanced police drivers.

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In three experiments, the authors investigated the impression-formation process resulting from the perception of familiar or unfamiliar social category combinations. In Experiment 1, participants were asked to generate attributes associated with either a familiar or unfamiliar social category conjunction. Compared to familiar combinations, the authors found that when the conjunction was unfamiliar, participants formed their impression less from the individual constituent categories and relatively more from novel emergent attributes. In Experiment 2 the authors replicated this effect using alternative experimental materials. In Experiment 3, the effect generalized to additional (orthogonally combined) gender and occupation categories. The implications of these findings for understanding the processes involved in the conjunction of social categories, and the formation of new stereotypes, are discussed.

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Three experiments investigated the influence of implicit memory for familiar brand names on consumer choice. Priming was measured using modified preference judgment tasks that comprised both brand consideration and choice components. Experiment 1 used a 'complex choice task' where consideration and choice stages were characterized as acting in sequence. Experiment 2 explored a different formulation whereby consideration and choice were assumed to act in parallel, Both experiments demonstrated that priming had an influence on brand consideration but not on final or preferred choice. Finally, Experiment 3 replicated and extended these findings under more realistic conditions where participants actually received some of the products that they selected. Overall, the experiments suggested that for many decisions involving the consideration of familiar brands prior to choice, previous exposure to brand names can increase the likelihood that they will enter the consumers' consideration set. However, the advantage does not appear to extend to choice itself. Copyright (C) 2004 John Wiley Sons, Ltd.

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This paper presents results to indicate the potential applications of a direct connection between the human nervous system and a computer network. Actual experimental results obtained from a human subject study are given, with emphasis placed on the direct interaction between the human nervous system and possible extra-sensory input. An brief overview of the general state of neural implants is given, as well as a range of application areas considered. An overall view is also taken as to what may be possible with implant technology as a general purpose human-computer interface for the future.

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The Danish Eulerian Model (DEM) is a powerful air pollution model, designed to calculate the concentrations of various dangerous species over a large geographical region (e.g. Europe). It takes into account the main physical and chemical processes between these species, the actual meteorological conditions, emissions, etc.. This is a huge computational task and requires significant resources of storage and CPU time. Parallel computing is essential for the efficient practical use of the model. Some efficient parallel versions of the model were created over the past several years. A suitable parallel version of DEM by using the Message Passing Interface library (AIPI) was implemented on two powerful supercomputers of the EPCC - Edinburgh, available via the HPC-Europa programme for transnational access to research infrastructures in EC: a Sun Fire E15K and an IBM HPCx cluster. Although the implementation is in principal, the same for both supercomputers, few modifications had to be done for successful porting of the code on the IBM HPCx cluster. Performance analysis and parallel optimization was done next. Results from bench marking experiments will be presented in this paper. Another set of experiments was carried out in order to investigate the sensitivity of the model to variation of some chemical rate constants in the chemical submodel. Certain modifications of the code were necessary to be done in accordance with this task. The obtained results will be used for further sensitivity analysis Studies by using Monte Carlo simulation.

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Large scale air pollution models are powerful tools, designed to meet the increasing demand in different environmental studies. The atmosphere is the most dynamic component of the environment, where the pollutants can be moved quickly on far distnce. Therefore the air pollution modeling must be done in a large computational domain. Moreover, all relevant physical, chemical and photochemical processes must be taken into account. In such complex models operator splitting is very often applied in order to achieve sufficient accuracy as well as efficiency of the numerical solution. The Danish Eulerian Model (DEM) is one of the most advanced such models. Its space domain (4800 × 4800 km) covers Europe, most of the Mediterian and neighboring parts of Asia and the Atlantic Ocean. Efficient parallelization is crucial for the performance and practical capabilities of this huge computational model. Different splitting schemes, based on the main processes mentioned above, have been implemented and tested with respect to accuracy and performance in the new version of DEM. Some numerical results of these experiments are presented in this paper.

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In this paper results are shown to indicate the efficacy of a direct connection between the human nervous system and a computer network. Experimental results obtained thus far from a study lasting for over 3 months are presented, with particular emphasis placed on the direct interaction between the human nervous system and a piece of wearable technology. An overview of the present state of neural implants is given, as well as a range of application areas considered thus far. A view is also taken as to what may be possible with implant technology as a general purpose human-computer interface for the future.

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The associative sequence learning model proposes that the development of the mirror system depends on the same mechanisms of associative learning that mediate Pavlovian and instrumental conditioning. To test this model, two experiments used the reduction of automatic imitation through incompatible sensorimotor training to assess whether mirror system plasticity is sensitive to contingency (i.e., the extent to which activation of one representation predicts activation of another). In Experiment 1, residual automatic imitation was measured following incompatible training in which the action stimulus was a perfect predictor of the response (contingent) or not at all predictive of the response (noncontingent). A contingency effect was observed: There was less automatic imitation indicative of more learning in the contingent group. Experiment 2 replicated this contingency effect and showed that, as predicted by associative learning theory, it can be abolished by signaling trials in which the response occurs in the absence of an action stimulus. These findings support the view that mirror system development depends on associative learning and indicate that this learning is not purely Hebbian. If this is correct, associative learning theory could be used to explain, predict, and intervene in mirror system development.

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