214 resultados para H5 full bridge modulation
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This study proposes a full Bayes (FB) hierarchical modeling approach in traffic crash hotspot identification. The FB approach is able to account for all uncertainties associated with crash risk and various risk factors by estimating a posterior distribution of the site safety on which various ranking criteria could be based. Moreover, by use of hierarchical model specification, FB approach is able to flexibly take into account various heterogeneities of crash occurrence due to spatiotemporal effects on traffic safety. Using Singapore intersection crash data(1997-2006), an empirical evaluate was conducted to compare the proposed FB approach to the state-of-the-art approaches. Results show that the Bayesian hierarchical models with accommodation for site specific effect and serial correlation have better goodness-of-fit than non hierarchical models. Furthermore, all model-based approaches perform significantly better in safety ranking than the naive approach using raw crash count. The FB hierarchical models were found to significantly outperform the standard EB approach in correctly identifying hotspots.
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We present experimental and theoretical results of the intensity dependence of residual amplitude modulation (RAM) production in electro-optic phase modulators. By utilizing the anisotropy of the medium, we show that RAM has a photorefractive origin.
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4D simulation, building information modeling, virtual construction, computer simulation and virtual prototyping are emerging topics in the building construction industry. These techniques not only relate to the buildings themselves, but can also be applied to other forms of construction, including bridges. Since bridge construction is a complex process involving multiple types of plant and equipment, applying such virtual methods benefits the understanding of all parties in construction practice. This paper describes the relationship between temporary platforms, plant and equipment resources and a proposed-built model in the construction planning and use of Virtual Prototyping Simulation (VPS) to implement different construction scenarios in order to help planners identify an optimal construction plan. A case study demonstrates the use of VPS integrated with temporary platform design and plant and equipment-resource allocation to generate different construction scenarios.
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The serviceability and safety of bridges are crucial to people’s daily lives and to the national economy. Every effort should be taken to make sure that bridges function safely and properly as any damage or fault during the service life can lead to transport paralysis, catastrophic loss of property or even casualties. Nonetheless, aggressive environmental conditions, ever-increasing and changing traffic loads and aging can all contribute to bridge deterioration. With often constrained budget, it is of significance to identify bridges and bridge elements that should be given higher priority for maintenance, rehabilitation or replacement, and to select optimal strategy. Bridge health prediction is an essential underpinning science to bridge maintenance optimization, since the effectiveness of optimal maintenance decision is largely dependent on the forecasting accuracy of bridge health performance. The current approaches for bridge health prediction can be categorised into two groups: condition ratings based and structural reliability based. A comprehensive literature review has revealed the following limitations of the current modelling approaches: (1) it is not evident in literature to date that any integrated approaches exist for modelling both serviceability and safety aspects so that both performance criteria can be evaluated coherently; (2) complex system modelling approaches have not been successfully applied to bridge deterioration modelling though a bridge is a complex system composed of many inter-related bridge elements; (3) multiple bridge deterioration factors, such as deterioration dependencies among different bridge elements, observed information, maintenance actions and environmental effects have not been considered jointly; (4) the existing approaches are lacking in Bayesian updating ability to incorporate a variety of event information; (5) the assumption of series and/or parallel relationship for bridge level reliability is always held in all structural reliability estimation of bridge systems. To address the deficiencies listed above, this research proposes three novel models based on the Dynamic Object Oriented Bayesian Networks (DOOBNs) approach. Model I aims to address bridge deterioration in serviceability using condition ratings as the health index. The bridge deterioration is represented in a hierarchical relationship, in accordance with the physical structure, so that the contribution of each bridge element to bridge deterioration can be tracked. A discrete-time Markov process is employed to model deterioration of bridge elements over time. In Model II, bridge deterioration in terms of safety is addressed. The structural reliability of bridge systems is estimated from bridge elements to the entire bridge. By means of conditional probability tables (CPTs), not only series-parallel relationship but also complex probabilistic relationship in bridge systems can be effectively modelled. The structural reliability of each bridge element is evaluated from its limit state functions, considering the probability distributions of resistance and applied load. Both Models I and II are designed in three steps: modelling consideration, DOOBN development and parameters estimation. Model III integrates Models I and II to address bridge health performance in both serviceability and safety aspects jointly. The modelling of bridge ratings is modified so that every basic modelling unit denotes one physical bridge element. According to the specific materials used, the integration of condition ratings and structural reliability is implemented through critical failure modes. Three case studies have been conducted to validate the proposed models, respectively. Carefully selected data and knowledge from bridge experts, the National Bridge Inventory (NBI) and existing literature were utilised for model validation. In addition, event information was generated using simulation to demonstrate the Bayesian updating ability of the proposed models. The prediction results of condition ratings and structural reliability were presented and interpreted for basic bridge elements and the whole bridge system. The results obtained from Model II were compared with the ones obtained from traditional structural reliability methods. Overall, the prediction results demonstrate the feasibility of the proposed modelling approach for bridge health prediction and underpin the assertion that the three models can be used separately or integrated and are more effective than the current bridge deterioration modelling approaches. The primary contribution of this work is to enhance the knowledge in the field of bridge health prediction, where more comprehensive health performance in both serviceability and safety aspects are addressed jointly. The proposed models, characterised by probabilistic representation of bridge deterioration in hierarchical ways, demonstrated the effectiveness and pledge of DOOBNs approach to bridge health management. Additionally, the proposed models have significant potential for bridge maintenance optimization. Working together with advanced monitoring and inspection techniques, and a comprehensive bridge inventory, the proposed models can be used by bridge practitioners to achieve increased serviceability and safety as well as maintenance cost effectiveness.
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While strengthened partnerships between University and Schools have been proposed in recent reviews of teacher education (House of Representative Standing Committee on Education and Vocational Training, 2007; Caldwell & Sutton, 2010; Donaldson, 2010), there is a need to understand the benefits and challenges for participants of these partnerships. The Teacher Education Centre of Excellence (TECE) in this study is a preservice teacher preparation partnership between a Queensland University, Queensland Department of Education, Training and Employment (DETE) and an Education Queensland school. It was established in response to a mandated reform within the Improving Teacher Quality National Partnership Agreement (Department of Education Employment and Workplace Relations, 2011). High-achieving Bachelor of Education preservice teachers apply to be part of the 18-month program in the third year of their four-year Education degree. These preservice teachers experience mentoring in partner schools in addition to course work designed and delivered by a DETE appointed Head of Mentoring and a university academic. On completion of the program, graduates will be appointed to South West Queensland rural and remote Education Queensland schools. This paper analyses participant perspectives from the first phase of this partnership in particular identifying the benefits and challenges experienced by the preservice teachers and the leaders of the program from the participating institutions. A sociocultural theoretical perspective (Wenger, 1998) informed the analysis examining how preservice teachers experience a sense of becoming a professional teacher within a specific employment context. Data from interviews with 6 pre-service teachers and 8 program leaders were analysed inductively through coding of interview records. Findings indicate the importance of strong relationships and opportunity for reciprocal learning through ongoing professional conversations as contexts for preservice teachers to develop an identity as an emerging professional. This research has significance for the ongoing development of this partnership as well as informing the principles for the design of future similar partnerships.
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The present research examined the effects of occupational stress in psychiatric nursing on employee well!being using the full Job Strain Model.The Job Strain Model was assessed for its ability to predict employee well!being in terms of job satisfaction and mental health. The original Job Strain Model was expanded to include social support based on previous research concerning the impact of social support on well!being[ In the present study\ both work support and non-work were assessed for their contribution to wellbeing.The results of this study indicate that the full Job Strain Model can be used to significantly predict job satisfaction and mental health in this sample of Australian psychiatric nurses. Furthermore social support was shown to be an important component of the Job Strain Model.
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When wheels pass over insulated rail joints (IRJs) a vertical impact force is generated. The ability to measure the impact force is valuable as the force signature helps understand the behaviour of the IRJs, in particular their potential for failure. The impact forces are thought to be one of the main factors that cause damage to the IRJ and track components. Study of the deterioration mechanism helps finding new methods to improve the service life of IRJs in track. In this research, the strain-gage-based wheel load detector, for the first time, is employed to measure the wheel–rail contact-impact force at an IRJ in a heavy haul rail line. In this technique, the strain gages are installed within the IRJ assembly without disturbing the structural integrity of IRJ and arranged in a full wheatstone bridge to form a wheel load detector. The instrumented IRJ is first tested and calibrated in the lab and then installed in the field. For comparison purposes, a reference rail section is also instrumented with the same strain gage pattern as the IRJ. In this paper the measurement technique, the process of instrumentation, and tests as well as some typical data obtained from the field and the inferences are presented.
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We analyzed mesopic rod and S-cone interactions in terms of their contributions to the blue-yellow opponent pathway. Stimuli were generated using a 4-primary colorimeter. Mixed rod and S-cone modulation thresholds (constant L-, M-cone excitation) were measured as a function of their phase difference. Modulation amplitude was equated using threshold units and contrast ratios. This study identified three interaction types: (1) A linear and antagonistic rod:S-cone interaction, (2) probability summation (3) and a previously unidentified mutual nonlinear reinforcement. Linear rod:S-cone interactions occur within the blue-yellow opponent pathway. Probability summation involves signaling by different post-receptoral pathways. The origin of the nonlinear reinforcement is possibly at the photoreceptors.
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Background During a global influenza pandemic, the vaccine requirements of developing countries can surpass their supply capabilities, if these exist at all, compelling them to rely on developed countries for stocks that may not be available in time. There is thus a need for developing countries in general to produce their own pandemic and possibly seasonal influenza vaccines. Here we describe the development of a plant-based platform for producing influenza vaccines locally, in South Africa. Plant-produced influenza vaccine candidates are quicker to develop and potentially cheaper than egg-produced influenza vaccines, and their production can be rapidly upscaled. In this study, we investigated the feasibility of producing a vaccine to the highly pathogenic avian influenza A subtype H5N1 virus, the most generally virulent influenza virus identified to date. Two variants of the haemagglutinin (HA) surface glycoprotein gene were synthesised for optimum expression in plants: these were the full-length HA gene (H5) and a truncated form lacking the transmembrane domain (H5tr). The genes were cloned into a panel of Agrobacterium tumefaciens binary plant expression vectors in order to test HA accumulation in different cell compartments. The constructs were transiently expressed in tobacco by means of agroinfiltration. Stable transgenic tobacco plants were also generated to provide seed for stable storage of the material as a pre-pandemic strategy. Results For both transient and transgenic expression systems the highest accumulation of full-length H5 protein occurred in the apoplastic spaces, while the highest accumulation of H5tr was in the endoplasmic reticulum. The H5 proteins were produced at relatively high concentrations in both systems. Following partial purification, haemagglutination and haemagglutination inhibition tests indicated that the conformation of the plant-produced HA variants was correct and the proteins were functional. The immunisation of chickens and mice with the candidate vaccines elicited HA-specific antibody responses. Conclusions We managed, after synthesis of two versions of a single gene, to produce by transient and transgenic expression in plants, two variants of a highly pathogenic avian influenza virus HA protein which could have vaccine potential. This is a proof of principle of the potential of plant-produced influenza vaccines as a feasible pandemic response strategy for South Africa and other developing countries.
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A high-throughput method of isolating and cloning geminivirus genomes from dried plant material, by combining an Extract-n-Amp™-based DNA isolation technique with rolling circle amplification (RCA) of viral DNA, is presented. Using this method an attempt was made to isolate and clone full geminivirus genomes/genome components from 102 plant samples, including dried leaves stored at room temperature for between 6 months and 10 years, with an average hands-on-time to RCA-ready DNA of 15 min per 20 samples. While storage of dried leaves for up to 6 months did not appreciably decrease cloning success rates relative to those achieved with fresh samples, efficiency of the method decreased with increasing storage time. However, it was still possible to clone virus genomes from 47% of 10-year-old samples. To illustrate the utility of this simple method for high-throughput geminivirus diversity studies, six Maize streak virus genomes, an Abutilon mosaic virus DNA-B component and the DNA-A component of a previously unidentified New Word begomovirus species were fully sequenced. Genomic clones of the 69 other viruses were verified as such by end sequencing. This method should be extremely useful for the study of any circular DNA plant viruses with genome component lengths smaller than the maximum size amplifiable by RCA. © 2008 Elsevier B.V. All rights reserved.
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The civil liability provisions relating to the assessment of damages for past and future economic loss have abrogated the common law principle of full compensation by imposing restrictions on the damages award, most commonly by a “three times average weekly earnings” cap. This consideration of the impact of those provisions is informed by a case study of the Supreme Court of Victoria Court of Appeal decision, Tuohey v Freemasons Hospital (Tuohey) , which addressed the construction and arithmetic operation of the Victorian cap for high income earners. While conclusions as to operation of the cap outside of Victoria can be drawn from Tuohey, a number of issues await judicial determination. These issues, which include the impact of the damages caps on the calculation of damages for economic loss in the circumstances of fluctuating income; vicissitudes; contributory negligence; claims per quod servitum amisit; and claims by dependants, are identified and potential resolutions discussed.
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This paper develops and applies a multi-criteria procedure, incorporating changes in natural frequencies, modal flexibility and the modal strain energy, for damage detection in slab-on-girder bridges. The proposed procedure is first validated through experimental testing of a model bridge. Numerically simulated modal data obtained through finite element analyses are then used to evaluate the vibration parameters before and after damage and used as the indices for assessment of the state of structural health. The procedure is illustrated by its application to full scale slab-on-girder bridges under different damage scenarios involving single and multiple damages on the deck and girders.