913 resultados para Weak Localization


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The purpose of the current research project is to design a successful in-situ hybridization to identify regions within the brains of honeybees where DWV replicates. The localization of the virus in the brains of the bees can draw a connection between CCDand DWV.In conclusion, these results demonstrate that in bees infected with DWV the virus replicates actively in very important regions of the brain, including neuropils that are responsible for vision and olfaction. This means that the virus could adversely affect the vision and olfaction of the honeybees making it difficult for bees to behave normally.

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To determine the subcellular localization of the tegument proteins pp65, pp71, pp150, and pp28 as fusions to one of several fluorescent proteins. Since these tegument proteins play pivotal roles in several stages of the viral life cycle, knowledge of where and the mechanism of how these proteins localize upon release could result in a better understanding of their function during a lytic infection as well as assist in the development of an effective, novel antiviral treatment.

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Apis mellifera L., the European honeybee, is a crucial pollinator of many important agricultural crops in the United States. Recently, honeybee colonies have been affected by Colony Collapse Disorder (CCD), a disorder in which the colony fails due to the disappearance of a key functional group of worker bees. Though no direct causalrelationship has been confirmed, hives that experience CCD have been shown to have a high incidence of Deformed Wing Virus (DWV), a common honeybee virus. While the genome sequence and gene-order of DWV has been analyzed fairly recently, few other studies have been performed to understand the molecular characterization of the virus.Since little is known about where DWV proteins localize in infected host cells, the objective of this project was to determine the subcellular localization of two of the important non-structural proteins that are encoded in the DWV genome. This project focused on the protein 3C, an autocatalytic protease which cleaves itself from a longer polyprotein and helps to cut all of the other proteins apart from one another so that they can become functional, and 3D, the RNA-dependent RNA polymerase (RdRp) which is critical for replication of the virus because it copies the viral genome. By tagging nested constructs containing these two proteins and tracking where they localized in living cells, this study aimed to better understand the replication of DWV and to elicit possible targetsfor further research on how to control the virus. Since DWV is a picorna-like virus, distantly related to human viruses such as polio, and picornavirus non-structural proteins aggregate at cellular membranes during viral replication, the major hypothesis was that the 3C and 3CD proteins would localize at cellular organelle membranes as well. Using confocal microscopy, both proteins were found to localize in the cytoplasm, but the 3CDprotein was found to be mostly diffuse cytoplasmic, and the 3C protein was found to localize more specifically on membranous structures just outside of the nucleus.

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Complete resection of grade II gliomas might prolong survival but is not always possible. The goal of the study was to evaluate the location of unexpected grade II gliomas remnants after assumed complete removal with intraoperative (iop) MRI and to assess the reason for their non-detection.

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External beam proton radiation therapy has been used since 1975 to treat choroidal melanoma. For tumor location determination during proton radiation treatment, surgical tantalum clips are registered with image data. This report introduces the intraoperative application of an opto-electronic navigation system to determine with high precision the position of the tantalum markers and their spatial relationship to the tumor and anatomical landmarks. The application of the technique in the first 4 patients is described.

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Localization is information of fundamental importance to carry out various tasks in the mobile robotic area. The exact degree of precision required in the localization depends on the nature of the task. The GPS provides global position estimation but is restricted to outdoor environments and has an inherent imprecision of a few meters. In indoor spaces, other sensors like lasers and cameras are commonly used for position estimation, but these require landmarks (or maps) in the environment and a fair amount of computation to process complex algorithms. These sensors also have a limited field of vision. Currently, Wireless Networks (WN) are widely available in indoor environments and can allow efficient global localization that requires relatively low computing resources. However, the inherent instability in the wireless signal prevents it from being used for very accurate position estimation. The growth in the number of Access Points (AP) increases the overlap signals areas and this could be a useful means of improving the precision of the localization. In this paper we evaluate the impact of the number of Access Points in mobile nodes localization using Artificial Neural Networks (ANN). We use three to eight APs as a source signal and show how the ANNs learn and generalize the data. Added to this, we evaluate the robustness of the ANNs and evaluate a heuristic to try to decrease the error in the localization. In order to validate our approach several ANNs topologies have been evaluated in experimental tests that were conducted with a mobile node in an indoor space.