938 resultados para Biometric recognition system
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In vertebrate species, the innate immune system down-regulates protein translation in response to viral infection through the action of the double-stranded RNA (dsRNA)-activated protein kinase (PKR). In some teleost species another protein kinase, Z-DNA-dependent protein kinase (PKZ), plays a similar role but instead of dsRNA binding domains, PKZ has Zα domains. These domains recognize the left-handed conformer of dsDNA and dsRNA known as Z-DNA/Z-RNA. Cyprinid herpesvirus 3 infects common and koi carp, which have PKZ, and encodes the ORF112 protein that itself bears a Zα domain, a putative competitive inhibitor of PKZ. Here we present the crystal structure of ORF112-Zα in complex with an 18-bp CpG DNA repeat, at 1.5 Å. We demonstrate that the bound DNA is in the left-handed conformation and identify key interactions for the specificity of ORF112. Localization of ORF112 protein in stress granules induced in Cyprinid herpesvirus 3-infected fish cells suggests a functional behavior similar to that of Zα domains of the interferon-regulated, nucleic acid surveillance proteins ADAR1 and DAI.
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Mode of access: Internet.
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Bibliography: p. 39-41.
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Thesis (Ph.D.)--University of Washington, 2016-06
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Although the importance of CD4(+) T cell responses to human cytonnegalovirus (HCMV) has recently been recognized in transplant and immunosuppressed patients, the precise specificity and nature of this response has remained largely unresolved. In the present study we have isolated CD4(+) CTL which recognize epitopes from HCMV glycoproteins gB and gH in association with two different HLA-DR antigens, DRA1*0101/DRB1*0701 (DR7) and DRA1*0101/DRB1*1101 (DR11). Comparison of amino acid sequences of HICMV isolates revealed that the gB and gH epitope sequences recognized by human CD4(+) T cells were not only conserved in clinical isolates from HCMV but also in CMV isolates from higher primates (chimpanzee, rhesus and baboon). Interestingly, these epitope sequences from chimpanzee, rhesus and baboon CMV are efficiently recognized by human CD4(+) CTL. More importantly, we show that gB-specific T cells from humans can also efficiently lyse pepticle-sensitized Patr-DR7(+) cells from chimpanzees. These findings suggest that conserved gB and gH epitopes should be considered while designing a prophylactic vaccine against HCMV. In addition, they also provide a functional basis for the conservation of MHC class 11 lineages between humans and Old World primates and open the possibility for the use of such primate models in vaccine development against HCMV.
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MHC class I molecules generally present peptides of 8-10 aa long, forming an extended coil in the HLA cleft. Although longer peptides can also bind to class I molecules, they tend to bulge from the cleft and it is not known whether the TCR repertoire has sufficient plasticity to recognize these determinants during the antiviral CTL response. In this study, we show that unrelated individuals infected with EBV generate a significant CTL response directed toward an HLA-B*3501-restricted, 11-mer epitope from the BZLF1 Ag. The 11-mer determinant adopts a highly bulged conformation with seven of the peptide side chains being solvent-exposed and available for TCR interaction. Such a complex potentially creates a structural challenge for TCR corecognition of both HLA-B*3501 and the peptide Ag. Surprisingly, unrelated B*3501 donors recognizing the 11-mer use identical or closely related alpha beta TCR sequences that share particular CDR3 motifs. Within the small number of dominant CTL clonotypes observed, each has discrete fine specificity for the exposed-side chain residues of the peptide. The data show that bulged viral peptides are indeed immunogenic but suggest that the highly constrained TCR repertoire reflects a limit to TCR diversity when responding to some unusual MHC peptide ligands.
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Different DNA motifs are required for optimal stimulation Of mouse and human immune cells by CpG oligode-oxynucleotides (ODN). These species differences presumably reflect sequence differences in TLR9, the CPG DNA receptor. In this study, we show that this sequence specificity is restricted to phosphorothioate (PS)-modified ODN and is not observed when a natural phosphodiester backbone is used. Thus, human and mouse cells have not evolved to recognize different CpG motifs in natural DNA. Nonoptimal PS-ODN (i.e., mouse CpG motif on human cells and vice versa) gave delayed and less sustained phosphorylation of p38 AWK than optimal motifs. When the CpG dinucleotide was inverted to GC In each ODN some residual activity of the PS-ODN was retained in a species-specific, TLR-9-dependent manner. Thus, TLR9 may he responsible for mediating many published CpG-independent responses to PS-ODN.
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With marine biodiversity conservation the primary goal for reserve planning initiatives, a site's conservation potential is typically evaluated on the basis of the biological and physical features it contains. By comparison, socio-economic information is seldom a formal consideration of the reserve system design problem and generally limited to an assessment of threats, vulnerability or compatibility with surrounding uses. This is perhaps surprising given broad recognition that the success of reserve establishment is highly dependent on widespread stakeholder and community support. Using information on the spatial distribution and intensity of commercial rock lobster catch in South Australia, we demonstrate the capacity of mathematical reserve selection procedures to integrate socio-economic and biophysical information for marine reserve system design. Analyses of trade-offs highlight the opportunities to design representative, efficient and practical marine reserve systems that minimise potential loss to commercial users. We found that the objective of minimising the areal extent of the reserve system was barely compromised by incorporating economic design constraints. With a small increase in area (< 3%) and boundary length (< 10%), the economic impact of marine reserves on the commercial rock lobster fishery was reduced by more than a third. We considered also how a reserve planner might prioritise conservation areas using information on a planning units selection frequency. We found that selection frequencies alone were not a reliable guide for the selection of marine reserve systems, but could be used with approaches such as summed irreplaceability to direct conservation effort for efficient marine reserve design.
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This paper describes the real time global vision system for the robot soccer team the RoboRoos. It has a highly optimised pipeline that includes thresholding, segmenting, colour normalising, object recognition and perspective and lens correction. It has a fast ‘paint’ colour calibration system that can calibrate in any face of the YUV or HSI cube. It also autonomously selects both an appropriate camera gain and colour gains robot regions across the field to achieve colour uniformity. Camera geometry calibration is performed automatically from selection of keypoints on the field. The system acheives a position accuracy of better than 15mm over a 4m × 5.5m field, and orientation accuracy to within 1°. It processes 614 × 480 pixels at 60Hz on a 2.0GHz Pentium 4 microprocessor.
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A major impediment to developing real-time computer vision systems has been the computational power and level of skill required to process video streams in real-time. This has meant that many researchers have either analysed video streams off-line or used expensive dedicated hardware acceleration techniques. Recent software and hardware developments have greatly eased the development burden of realtime image analysis leading to the development of portable systems using cheap PC hardware and software exploiting the Multimedia Extension (MMX) instruction set of the Intel Pentium chip. This paper describes the implementation of a computationally efficient computer vision system for recognizing hand gestures using efficient coding and MMX-acceleration to achieve real-time performance on low cost hardware.
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This paper presents an innovative approach for signature verification and forgery detection based on fuzzy modeling. The signature image is binarized and resized to a fixed size window and is then thinned. The thinned image is then partitioned into a fixed number of eight sub-images called boxes. This partition is done using the horizontal density approximation approach. Each sub-image is then further resized and again partitioned into twelve further sub-images using the uniform partitioning approach. The features of consideration are normalized vector angle (α) from each box. Each feature extracted from sample signatures gives rise to a fuzzy set. Since the choice of a proper fuzzification function is crucial for verification, we have devised a new fuzzification function with structural parameters, which is able to adapt to the variations in fuzzy sets. This function is employed to develop a complete forgery detection and verification system.
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Probabilistic robotics most often applied to the problem of simultaneous localisation and mapping (SLAM), requires measures of uncertainty to accompany observations of the environment. This paper describes how uncertainty can be characterised for a vision system that locates coloured landmarks in a typical laboratory environment. The paper describes a model of the uncertainty in segmentation, the internal cameral model and the mounting of the camera on the robot. It explains the implementation of the system on a laboratory robot, and provides experimental results that show the coherence of the uncertainty model.
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Recovering position from sensor information is an important problem in mobile robotics, known as localisation. Localisation requires a map or some other description of the environment to provide the robot with a context to interpret sensor data. The mobile robot system under discussion is using an artificial neural representation of position. Building a geometrical map of the environment with a single camera and artificial neural networks is difficult. Instead it would be simpler to learn position as a function of the visual input. Usually when learning images, an intermediate representation is employed. An appropriate starting point for biologically plausible image representation is the complex cells of the visual cortex, which have invariance properties that appear useful for localisation. The effectiveness for localisation of two different complex cell models are evaluated. Finally the ability of a simple neural network with single shot learning to recognise these representations and localise a robot is examined.