1000 resultados para IDENTIFICATION


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The brochure is to contribute to the overall goal of stimulating the adaptation of pro-poor agri-food systems innovations to improve food security and sustainable natural resource management among rural poor farmers. The paper seeks to identify and exploit opportunities for expanding market access for minor crops and NRM products. The minor crops studied included cow pea, sorghum, groundnut, sweet potato and yam.

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The paper provides key for the identification of the East African marine fishes. Just like in most determination keys this one is based on the "either-or" principle, i.e. there is a single alternatIve at each point. A specimen either fits all the characters recorded, or fails to conform to one or more characters and you should then proceed to the next number, keeping this up until the fish to be identified does fit all the characters.

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We present a novel framework for identifying and tracking dominant agents in groups. Our proposed approach relies on a causality detection scheme that is capable of ranking agents with respect to their contribution in shaping the system's collective behaviour based exclusively on the agents' observed trajectories. Further, the reasoning paradigm is made robust to multiple emissions and clutter by employing a class of recently introduced Markov chain Monte Carlo-based group tracking methods. Examples are provided that demonstrate the strong potential of the proposed scheme in identifying actual leaders in swarms of interacting agents and moving crowds. © 2011 IEEE.

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When a thin rectangular plate is restrained on the two long edges and free on the remaining edges, the equivalent stiffness of the restraining joints can be identified by the order of the natural frequencies obtained using the free response of the plate at a single location. This work presents a method to identify the equivalent stiffness of the restraining joints, being represented as simply supporting the plate but elastically restraining it in rotation. An integral transform is used to map the autospectrum of the free response from the frequency domain to the stiffness domain in order to identify the equivalent torsional stiffness of the restrained edges of the plate and also the order of natural frequencies. The kernel of the integral transform is built interpolating data from a finite element model of the plate. The method introduced in this paper can also be applied to plates or shells with different shapes and boundary conditions. © 2011 Elsevier Ltd. All rights reserved.

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We identified a new class of human immunodeficiency virus type 1 (HIV-1) recombinants (00CN-HH069 and 00CN-HH086) in which further recombination occurred between two established circulating recombinant forms (CRFs). These two isolates were found among 57 HIV-1 samples from a cohort of injecting drug users in eastern Yunnan Province of China. Informative-site analysis in conjunction with bootscanning plots and exploratory tree analysis revealed that these two strains were closely related mosaics comprised of CRF07_BC and CRF08_BC, which are found in China. The genotype screening based on gag-reverse transcriptase sequences if 57 samples from eastern Yunnan identified 47 CRF08_BC specimens (82.5%), 5 CRF07_BC specimens (8.8%), and 3 additional specimens with the novel recombinant structure. These new "second-generation" recombinants thus constitute a substantial proportion (5 of 57; 8.8%) of HIV-1 strains in this population and may belong to a new but yet-undefined class of CRF. This might be the first example of CRFs recombining with each other, leading to the evolution of second-generation inter-CRF recombinants.

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In our studies, 88 human mRNA samples were collected from the Integrated Sequence-Structure database and then the dynamic process in co-transcriptional mRNA folding was simulated using the RNAstructure version 4.1 program. Through statistical analyses of the frequencies of occurrence of hairpins, a group of special folding structures-the 'common hairpins'-were identified. These 'common hairpins' have lower energies and occur in all the subsequent folding units that formed in the dynamic folding process. By applying the formulas (1)-(4) of the 'common hairpins' statistical model, 163 'common hairpins' were found, to make up about 7% of the total of 2286 hairpins. Classified studies further show that the 'common hairpins' that were studied may oscillate in the dynamic folding process. However, the hairpin loops of the 'common hairpins' and stems proximal to those 'common hairpins' loops maintain topologically stable structures, while other loops and stems distal to the 'common hairpins' loops are shown to be alterable structures. Strikingly, further studies indicate that the stable structures of these 'common hairpins' may have unbeknown effects on controlling the formation of protein structures in the translation process (unpublished results). (c) 2005 Elsevier B.V. All rights reserved.

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Recent developments in modeling driver steering control with preview are reviewed. While some validation with experimental data has been presented, the rigorous application of formal system identification methods has not yet been attempted. This paper describes a steering controller based on linear model-predictive control. An indirect identification method that minimizes steering angle prediction error is developed. Special attention is given to filtering the prediction error so as to avoid identification bias that arises from the closed-loop operation of the driver-vehicle system. The identification procedure is applied to data collected from 14 test drivers performing double lane change maneuvers in an instrumented vehicle. It is found that the identification procedure successfully finds parameter values for the model that give small prediction errors. The procedure is also able to distinguish between the different steering strategies adopted by the test drivers. © 2006 IEEE.

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The capability to automatically identify shapes, objects and materials from the image content through direct and indirect methodologies has enabled the development of several civil engineering related applications that assist in the design, construction and maintenance of construction projects. Examples include surface cracks detection, assessment of fire-damaged mortar, fatigue evaluation of asphalt mixes, aggregate shape measurements, velocimentry, vehicles detection, pore size distribution in geotextiles, damage detection and others. This capability is a product of the technological breakthroughs in the area of Image and Video Processing that has allowed for the development of a large number of digital imaging applications in all industries ranging from the well established medical diagnostic tools (magnetic resonance imaging, spectroscopy and nuclear medical imaging) to image searching mechanisms (image matching, content based image retrieval). Content based image retrieval techniques can also assist in the automated recognition of materials in construction site images and thus enable the development of reliable methods for image classification and retrieval. The amount of original imaging information produced yearly in the construction industry during the last decade has experienced a tremendous growth. Digital cameras and image databases are gradually replacing traditional photography while owners demand complete site photograph logs and engineers store thousands of images for each project to use in a number of construction management tasks. However, construction companies tend to store images without following any standardized indexing protocols, thus making the manual searching and retrieval a tedious and time-consuming effort. Alternatively, material and object identification techniques can be used for the development of automated, content based, construction site image retrieval methodology. These methods can utilize automatic material or object based indexing to remove the user from the time-consuming and tedious manual classification process. In this paper, a novel material identification methodology is presented. This method utilizes content based image retrieval concepts to match known material samples with material clusters within the image content. The results demonstrate the suitability of this methodology for construction site image retrieval purposes and reveal the capability of existing image processing technologies to accurately identify a wealth of materials from construction site images.

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Campylobacter jejuni is a leading cause of human diarrheal illness in the world, and research on it has benefitted greatly by the completion of several genome sequences and the development of molecular biology tools. However, many hurdles remain for a full understanding of this unique bacterial pathogen. One of the most commonly used strains for genetic work with C. jejuni is NCTC11168. While this strain is readily transformable with DNA for genomic recombination, transformation with plasmids is problematic. In this study, we have identified a determinant of this to be cj1051c, predicted to encode a restriction-modification type IIG enzyme. Knockout mutagenesis of this gene resulted in a strain with a 1,000-fold-enhanced transformation efficiency with a plasmid purified from a C. jejuni host. Additionally, this mutation conferred the ability to be transformed by plasmids isolated from an Escherichia coli host. Sequence analysis suggested a high level of variability of the specificity domain between strains and that this gene may be subject to phase variation. We provide evidence that cj1051c is active in NCTC11168 and behaves as expected for a type IIG enzyme. The identification of this determinant provides a greater understanding of the molecular biology of C. jejuni as well as a tool for plasmid work with strain NCTC11168. © 2012, American Society for Microbiology.

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In geotechnical engineering, soil classification is an essential component in the design process. Field methods such as the cone penetration test (CPT) can be used as less expensive and faster alternatives to sample retrieval and testing. Unfortunately, current soil classification charts based on CPT data and laboratory measurements are too generic, and may not provide an accurate prediction of the soil type. A probabilistic approach is proposed here to update and modify soil identification charts based on site-specific CPT data. The probability that a soil is correctly classified is also estimated. The updated identification chart can be used for a more accurate prediction of the classification of the soil, and can account for prior information available before conducting the tests, site-specific data, and measurement errors. As an illustration, the proposed approach is implemented using CPT data from the Treporti Test Site (TTS) near Venice (Italy) and the National Geotechnical Experimentation Sites (NGES) at Texas A&M University. The applicability of the site-specific chart for other sites in Venice Lagoon is assessed using data from the Malamocco test site, approximately 20 km from TTS.