417 resultados para Semi-direct product
Resumo:
The nucleotide sequence of DNA complementary to rice ragged stunt oryzavirus (RRSV) genome segment 8 (S8) of an isolate from Thailand was determined. RRSV S8 is 1 914 bp in size and contains a single large open reading frame (ORF) spanning nucleotides 23 to 1 810 which is capable of encoding a protein of M(r) 67 348. The N-terminal amino acid sequence of a ~43K virion polypeptide matched to that inferred for an internal region of the S8 coding sequence. These data suggest that the 43K protein is encoded by S8 and is derived by a proteolytic cleavage. Predicted polypeptide sizes from this possible cleavage of S8 protein are 26K and 42K. Polyclonal antibodies raised against a maltose binding protein (MBP)-S8 fusion polypeptide (expressed in Escherichia coli) recognised four RRSV particle associated polypeptides of M(r) 67K, 46K, 43K and 26K and all except the 26K polypeptide were also highly immunoreactive to polyclonal antibodies raised against purified RRSV particles. Cleavage of the MBP-S8 fusion polypeptide with protease Factor X produced the expected 40K MBP and two polypeptides of apparent M(r) 46K and 26K. Antibodies to purified RRSV particles reacted strongly with the intact fusion protein and the 46K cleavage product but weakly to the 26K product. Furthermore, in vitro transcription and translation of the S8 coding region revealed a post-translational self cleavage of the 67K polypeptide to 46K and 26K products. These data indicate that S8 encodes a structural polypeptide, the majority of which is auto- catalytically cleaved to 26K and 46K proteins. The data also suggest that the 26K protein is the self cleaving protease and that the 46K product is further processed or undergoes stable conformational changes to a ~43K major capsid protein.
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Near-infrared spectroscopy (NIRS) calibrations were developed for the discrimination of Chinese hawthorn (Crataegus pinnatifida Bge. var. major) fruit from three geographical regions as well as for the estimation of the total sugar, total acid, total phenolic content, and total antioxidant activity. Principal component analysis (PCA) was used for the discrimination of the fruit on the basis of their geographical origin. Three pattern recognition methods, linear discriminant analysis, partial least-squares-discriminant analysis, and back-propagation artificial neural networks, were applied to classify and compare these samples. Furthermore, three multivariate calibration models based on the first derivative NIR spectroscopy, partial least-squares regression, back-propagation artificial neural networks, and least-squares-support vector machines, were constructed for quantitative analysis of the four analytes, total sugar, total acid, total phenolic content, and total antioxidant activity, and validated by prediction data sets.
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This research investigates users' anticipation of their future experiences with interactive products to support design for experience in the early stages of product development. This research generates new knowledge of anticipated user experience (AUX), which reveals users' tendency to perceive the pragmatic quality of products as the main determinant of their positive future experiences. The AUX Framework has been an important outcome of this study. The exploration of the components of this framework allows a better prediction and understanding of users' underlying needs and potential usage contexts valuable for the early design phases.
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Efficient and effective feature detection and representation is an important consideration when processing videos, and a large number of applications such as motion analysis, 3D scene understanding, tracking etc. depend on this. Amongst several feature description methods, local features are becoming increasingly popular for representing videos because of their simplicity and efficiency. While they achieve state-of-the-art performance with low computational complexity, their performance is still too limited for real world applications. Furthermore, rapid increases in the uptake of mobile devices has increased the demand for algorithms that can run with reduced memory and computational requirements. In this paper we propose a semi binary based feature detectordescriptor based on the BRISK detector, which can detect and represent videos with significantly reduced computational requirements, while achieving comparable performance to the state of the art spatio-temporal feature descriptors. First, the BRISK feature detector is applied on a frame by frame basis to detect interest points, then the detected key points are compared against consecutive frames for significant motion. Key points with significant motion are encoded with the BRISK descriptor in the spatial domain and Motion Boundary Histogram in the temporal domain. This descriptor is not only lightweight but also has lower memory requirements because of the binary nature of the BRISK descriptor, allowing the possibility of applications using hand held devices.We evaluate the combination of detectordescriptor performance in the context of action classification with a standard, popular bag-of-features with SVM framework. Experiments are carried out on two popular datasets with varying complexity and we demonstrate comparable performance with other descriptors with reduced computational complexity.
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A new method for the direct aryl iodination of isoindolines and isoindoline nitroxides which utilizes periodic acid and potassium iodide in sulfuric acid is presented. Di-iodo functionalized tetramethyl and tetraethyl isoindolines and a di-iodo tetramethyl isoindoline nitroxide were prepared in high yield (70-82%). The analogous mono-iodo species were afforded in modest yield (34-48%). Iodinated nitrones were also obtained from a tetraethyl isoindoline nitroxide.
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Product Lifecycle Management (PLM) systems are widely used in the manufacturing industry. A core feature of such systems is to provide support for versioning of product data. As workflow functionality is increasingly used in PLM systems, the possibility emerges that the versioning transitions for product objects as encapsulated in process models do not comply with the valid version control policies mandated in the objects’ actual lifecycles. In this paper we propose a solution to tackle the (non-)compliance issues between processes and object version control policies. We formally define the notion of compliance between these two artifacts in product lifecycle management and then develop a compliance checking method which employs a well-established workflow analysis technique. This forms the basis of a tool which offers automated support to the proposed approach. By applying the approach to a collection of real-life specifications in a main PLM system, we demonstrate the practical applicability of our solution to the field.
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A focused library based on the marine natural products polyandrocarpamines A (1) and B (2) has been designed and synthesised using parallel solution-phase chemistry. In silico physicochemical property calculations were performed on synthetic candidates in order to optimise the library for drug discovery and chemical biology. A library of ten 2-aminoimidazolone products (3–12) was prepared by coupling glycocyamidine and a variety of aldehydes using a one-step stereoselective aldol condensation reaction under microwave conditions. All analogues were characterised by NMR, UV, IR and MS. The library was evaluated for cytotoxicity towards the prostate cancer cell lines, LNCaP, PC-3 and 22Rv1.
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Different reputation models are used in the web in order to generate reputation values for products using uses' review data. Most of the current reputation models use review ratings and neglect users' textual reviews, because it is more difficult to process. However, we argue that the overall reputation score for an item does not reflect the actual reputation for all of its features. And that's why the use of users' textual reviews is necessary. In our work we introduce a new reputation model that defines a new aggregation method for users' extracted opinions about products' features from users' text. Our model uses features ontology in order to define general features and sub-features of a product. It also reflects the frequencies of positive and negative opinions. We provide a case study to show how our results compare with other reputation models.
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In recent years, the Web 2.0 has provided considerable facilities for people to create, share and exchange information and ideas. Upon this, the user generated content, such as reviews, has exploded. Such data provide a rich source to exploit in order to identify the information associated with specific reviewed items. Opinion mining has been widely used to identify the significant features of items (e.g., cameras) based upon user reviews. Feature extraction is the most critical step to identify useful information from texts. Most existing approaches only find individual features about a product without revealing the structural relationships between the features which usually exist. In this paper, we propose an approach to extract features and feature relationships, represented as a tree structure called feature taxonomy, based on frequent patterns and associations between patterns derived from user reviews. The generated feature taxonomy profiles the product at multiple levels and provides more detailed information about the product. Our experiment results based on some popularly used review datasets show that our proposed approach is able to capture the product features and relations effectively.
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The traditional structural design procedure, especially for the large-scale and complex structures, is time consuming and inefficient. This is due primarily to the fact that the traditional design takes the second-order effects indirectly by virtue of design specifications for every member instead of system analysis for a whole structure. Consequently, the complicated and tedious design procedures are inevitably necessary to consider the second-order effects for the member level in design specification. They are twofold in general: 1) Flexural buckling due to P-d effect, i.e. effective length. 2) Sway effect due to P-D effect, i.e. magnification factor. In this study, a new system design concept based on the second-order elastic analysis is presented, in which the second-order effects are taken into account directly in the system analysis, and also to avoid the tedious member-by-member stability check. The plastic design on the basis of this integrated method of direct approach is ignored in this paper for simplicity and clarity, as the only emphasis is placed on the difference between the second-order elastic limit-state design and present system design approach. A practical design example, a 57m-span dome steel skylight structure, is used to demonstrate the efficiency and effectiveness of the proposed approach. This skylight structure is also designed by the traditional design approach BS5950-2000 for comparison on which the emphasis of aforementioned P-d and P-D effects is placed.
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Background Globally, alcohol-related injuries cause millions of deaths and huge economic loss each year . The incidence of facial (jawbone) fractures in the Northern Territory of Australia is second only to Greenland, due to a strong involvement of alcohol in its aetiology, and high levels of alcohol consumption. The highest incidences of alcohol-related trauma in the Territory are observed amongst patients in the Maxillofacial Surgery Unit of the Royal Darwin Hospital. Accordingly, this project aims to introduce screening and brief interventions into this unit, with the aims of changing health service provider practice, improving access to care, and improving patient outcomes. Methods Establishment of Project Governance: The project governance team includes a project manager, project leader, an Indigenous Reference Group (IRG) and an Expert Reference Group (ERG). Development of a best practice pathway: PACT project researchers collaborate with clinical staff to develop a best practice pathway suited to the setting of the surgical unit. The pathway provides clear guidelines for screening, assessment, intervention and referral. Implementation: The developed pathway is introduced to the unit through staff training workshops and associate resources and adapted in response to staff feedback. Evaluation: File audits, post workshop questionnaires and semi-structured interviews are administered. Discussion This project allows direct transfer of research findings into clinical practice and can inform future hospital-based injury prevention strategies.
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MapReduce is a computation model for processing large data sets in parallel on large clusters of machines, in a reliable, fault-tolerant manner. A MapReduce computation is broken down into a number of map tasks and reduce tasks, which are performed by so called mappers and reducers, respectively. The placement of the mappers and reducers on the machines directly affects the performance and cost of the MapReduce computation in cloud computing. From the computational point of view, the mappers/reducers placement problem is a generation of the classical bin packing problem, which is NP-complete. Thus, in this paper we propose a new heuristic algorithm for the mappers/reducers placement problem in cloud computing and evaluate it by comparing with other several heuristics on solution quality and computation time by solving a set of test problems with various characteristics. The computational results show that our heuristic algorithm is much more efficient than the other heuristics and it can obtain a better solution in a reasonable time. Furthermore, we verify the effectiveness of our heuristic algorithm by comparing the mapper/reducer placement for a benchmark problem generated by our heuristic algorithm with a conventional mapper/reducer placement which puts a fixed number of mapper/reducer on each machine. The comparison results show that the computation using our mapper/reducer placement is much cheaper than the computation using the conventional placement while still satisfying the computation deadline.
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Nitrogen-doped TiO2 nanofibres of anatase and TiO2(B) phases were synthesised by a reaction between titanate nanofibres of a layered structure and gaseous NH3 at 400–700 °C, following a different mechanism than that for the direct nitrogen doping from TiO2. The surface of the N-doped TiO2 nanofibres can be tuned by facial calcination in air to remove the surface-bonded N species, whereas the core remains N doped. N-Doped TiO2 nanofibres, only after calcination in air, became effective photocatalysts for the decomposition of sulforhodamine B under visible-light irradiation. The surface-oxidised surface layer was proven to be very effective for organic molecule adsorption, and the activation of oxygen molecules, whereas the remaining N-doped interior of the fibres strongly absorbed visible light, resulting in the generation of electrons and holes. The N-doped nanofibres were also used as supports of gold nanoparticle (Au NP) photocatalysts for visible-light-driven hydroamination of phenylacetylene with aniline. Phenylacetylene was activated on the N-doped surface of the nanofibres and aniline on the Au NPs. The Au NPs adsorbed on N-doped TiO2(B) nanofibres exhibited much better conversion (80 % of phenylacetylene) than when adsorbed on undoped fibres (46 %) at 40 °C and 95 % of the product is the desired imine. The surface N species can prevent the adsorption of O2 that is unfavourable for the hydroamination reaction, and thus, improve the photocatalytic activity. Removal of the surface N species resulted in a sharp decrease of the photocatalytic activity. These photocatalysts are feasible for practical applications, because they can be easily dispersed into solution and separated from a liquid by filtration, sedimentation or centrifugation due to their fibril morphology.
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As planners work to create more sustainable and liveable urban environments, a priority is to transition away from prioritising the automobile and towards enhancing the pedestrian experience. Thus, this research explores the experience of pedestrian accessibility in inner-urban higher-density Brisbane in Australia, drawing on findings from semi-structured in-depth interviews with 24 residents and over 100 hours of public place observations in three case-study neighbourhoods. The interviews took place in residents homes and explored their experience of higher density living and their neighbourhood, whilst observations were recorded through a combination of methods including photographs, sketch maps, recordings and field journals. Observation locations included retail and commercial space, roads, parkland and open space, with multiple observations at each location. A thematic analysis identified common themes in both interviews and the observations, with this paper focusing on residents’ lived experience in urban built environments. This analysis revealed that pedestrian accessibility is linked to access to local amenities and direct routes, aesthetics, sense of community, ownership of space and safety. In particular, observations revealed how pedestrian accessibility and route-taking works with, against or in spite of the design features of urban environments, as well as the importance of the social use of the built environment. Residents spoke about although walking quick and preferred for local amenities, the decision to walk was moderated by factors such as time of day and perceived safety. Measures to ensure and improve the pedestrian accessibility of urban areas needs to take into account the propensity for people to prefer and improvise direct routes (often to the detriment of traffic safety considerations), the importance of ongoing maintenance and upgrading of walking infrastructure and the importance of aesthetically pleasing and safe walking environments. By combining interviews and observations, this research highlights the current dominance of the automobile culture in Brisbane and the layers of meaning, experiences and complexity hidden within the pedestrian experience.
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Past approaches adopted by scholars in comparing international news have tended to concentrate on political and economic perspectives, while the role that culture plays in determining news has been somewhat neglected until recently. This article examines the role of culture in the development of journalistic practices and how a value systems approach can be applied to understanding journalism practices across cultures. Specifically, the article compares German and Anglo-American journalism practices with a view to locating differences between these traditions. The study demonstrates that using value systems as developed by Dutch anthropologist Geert Hofstede can be immensely useful in comparing the differences between the two traditions, as well as in understanding how journalists in these traditions report about the world.