DTD level authorization in XML documents with usage control

[Summary]: In recent years an increasing amount of semi-structured data has become important to humans and programs. XML promoted by the World Wide Web Consortium (W3C) is rapidly emerging as the new standard language for semi-structured data representation and exchange on the Internet. XML documents may contain private information that cannot be shared by all user communities. So securing XML data is becoming increasingly important and several approaches have been designed to protect information in a website. However, these approaches typically are used at file system level, rather than for the data in XML documents. Usage control has been considered as the next generation access control model with distinguishing properties of decision continuity. Usage control enables finer-grained control over usage of digital objects than that of traditional access control policies and models. In this paper, we present a usage control model to protect information distributed on the web, which allows the access restrictions directly at DTD-level and XML document-level. Finally, comparisons with related works are analysed

Multi-tensor Completion for Estimating Missing Values in Video Data

Many tensor-based data completion methods aim to solve image and video in-painting problems. But, all methods were only developed for a single dataset. In most of real applications, we can usually obtain more than one dataset to reflect one phenomenon, and all the datasets are mutually related in some sense. Thus one question raised whether such the relationship can improve the performance of data completion or not? In the paper, we proposed a novel and efficient method by exploiting the relationship among datasets for multi-video data completion. Numerical results show that the proposed method significantly improve the performance of video in-painting, particularly in the case of very high missing percentage

Sex differences in acute and chronic experimental pain models

Sex differences in response to noxious stimuli and in the development of chronic pain have been increasingly recognized and studied in humans and laboratory animals. In the clinic, extensive evidence indicates that there are a large number of chronic pain conditions that have higher prevalence in women than in men and some of these conditions, such as migraine and temporomandibular pain disorder, are also affected by the menstrual cycle. The mechanisms for sex differences in pain, particular in chronic pain, are largely unknown. The work presented in this thesis aims to explore mechanisms of sex differences using experimental pain models in rodents. In the first part of the thesis, we explored the role of estrogen receptors and the adenosine A2A receptor in sex differences in pain using genetically modified mice. We observed that in wild-type controls for estrogen receptor α or β knock-outs, females were significantly more sensitive than males to mechanical stimulation under normal condition and after carrageenan-induced inflammation. Such sex differences were eliminated in mice lacking either estrogen receptor α or β. Mechanical hypersensitivity resulting from partial sciatic nerve injury did not however differ between the sexes or between the wild-types and both estrogen receptor knock-outs. These results suggest that estrogen receptors α or β play a role in sex difference in basal mechanical pain threshold and inflammatory hypersensitivity. There was no sex difference in baseline mechanosensitivity in mice lacking the adenosine A2A receptor and wild-type controls. Carrageenan-induced mechanical hypersensitivity was significantly reduced in the A2A receptor knock-outs compared to wild-types. ZM-241,385, a selective A2A receptor antagonist, reduced inflammatory hypersensitivity in wild-type females, but not in males. The selective A2A receptor agonist CGS 21680 produced significantly more hypersensitivity in wild-type female mice than in males. These results suggest that activation of peripheral adenosine A2A receptors contributes to inflammatory hypersensitivity and that this effect is more prominent in females than in males. The second part of the thesis deals with the development of neuropathic pain-like behaviors (allodynia) in rats after spinal cord or infraorbital nerve injury. We observed a significant sex difference (females > males) in the development of mechanical allodynia after spinal cord injury in rats independent of the extent of injury. Increased mechanical hypersensitivity in females was not related to estrous stage at the time of injury. Similarly, after infraorbital nerve injury, female rats developed more persistent local and spread mechanical allodynia which was also not influenced by the estrous stages at the time or after injury. These studies provide further evidence for the presence of sex difference in baseline mechanical pain threshold, inflammatory hypersensitivity and experimental neuropathic pain in rodents. Furthermore, our results showed that estrogen receptors and adenosine A2A receptor may be involved in sex difference in pain sensitivity under normal condition or after inflammation. Finally, although female rats developed more persistent allodynia-like behaviors after spinal cord or infraorbital nerve injury, there appears to be no impact of the estrous cycle on pain development

Deconvolute individual genomes from metagenome sequences through short read clustering.

Metagenome assembly from short next-generation sequencing data is a challenging process due to its large scale and computational complexity. Clustering short reads by species before assembly offers a unique opportunity for parallel downstream assembly of genomes with individualized optimization. However, current read clustering methods suffer either false negative (under-clustering) or false positive (over-clustering) problems. Here we extended our previous read clustering software, SpaRC, by exploiting statistics derived from multiple samples in a dataset to reduce the under-clustering problem. Using synthetic and real-world datasets we demonstrated that this method has the potential to cluster almost all of the short reads from genomes with sufficient sequencing coverage. The improved read clustering in turn leads to improved downstream genome assembly quality