937 resultados para passenger trains
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In Arabidopsis thaliana (Arabidopsis), DICER-LIKE1 (DCL1) functions together with the double-stranded RNA binding protein (dsRBP), DRB1, to process microRNAs (miRNAs) from their precursor transcripts prior to their transfer to the RNA-induced silencing complex (RISC). miRNA-loaded RISC directs RNA silencing of cognate mRNAs via ARGONAUTE1 (AGO1)-catalyzed cleavage. Short interefering RNAs (siRNAs) are processed from viral-derived or transgene-encoded molecules of doublestranded RNA (dsRNA) by the DCL/dsRBP partnership, DCL4/DRB4, and are also loaded to AGO1-catalyzed RISC for cleavage of complementary mRNAs. Here, we use an artificial miRNA (amiRNA) technology, transiently expressed in Nicotiana benthamiana, to produce a series of amiRNA duplexes with differing intermolecular thermostabilities at the 5′ end of duplex strands. Analyses of amiRNA duplex strand accumulation and target transcript expression revealed that strand selection (amiRNA and amiRNA*) is directed by asymmetric thermostability of the duplex termini. The duplex strand possessing a lower 59 thermostability was preferentially retained by RISC to guide mRNA cleavage of the corresponding target transgene. In addition, analysis of endogenous miRNA duplex strand accumulation in Arabidopsis drb1 and drb2345 mutant plants revealed that DRB1 dictates strand selection, presumably by directional loading of the miRNA duplex onto RISC for passenger strand degradation. Bioinformatic and Northern blot analyses of DCL4/DRB4-dependent small RNAs (miRNAs and siRNAs) revealed that small RNAs produced by this DCL/dsRBP combination do not conform to the same terminal thermostability rules as those governing DCL1/DRB1-processed miRNAs. This suggests that small RNA processing in the DCL1/DRB1-directed miRNA and DCL4/DRB4-directed sRNA biogenesis pathways operates via different mechanisms.
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In plants, double-stranded RNA (dsRNA) is an effective trigger of RNA silencing, and several classes of endogenous small RNA (sRNA), processed from dsRNA substrates by DICER-like (DCL) endonucleases, are essential in controlling gene expression. One such sRNA class, the microRNAs (miRNAs) control the expression of closely related genes to regulate all aspects of plant development, including the determination of leaf shape, leaf polarity, flowering time, and floral identity. A single miRNA sRNA silencing signal is processed from a long precursor transcript of nonprotein-coding RNA, termed the primary miRNA (pri-miRNA). A region of the pri-miRNA is partially self-complementary allowing the transcript to fold back onto itself to form a stem-loop structure of imperfectly dsRNA. Artificial miRNA (amiRNA) technology uses endogenous pri-miRNAs, in which the miRNA and miRNA*(passenger strand of the miRNA duplex) sequences have been replaced with corresponding amiRNA/ amiRNA*sequences that direct highly efficient RNA silencing of the targeted gene. Here, we describe the rules for amiRNA design, as well as outline the PCR and bacterial cloning procedures involved in the construction of an amiRNA plant expression vector to control target gene expression in Arabidopsis thaliana. © 2014 Springer Science+Business Media New York.
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The signal processing techniques developed for the diagnostics of mechanical components operating in stationary conditions are often not applicable or are affected by a loss of effectiveness when applied to signals measured in transient conditions. In this chapter, an original signal processing tool is developed exploiting some data-adaptive techniques such as Empirical Mode Decomposition, Minimum Entropy Deconvolution and the analytical approach of the Hilbert transform. The tool has been developed to detect localized faults on bearings of traction systems of high speed trains and it is more effective to detect a fault in non-stationary conditions than signal processing tools based on envelope analysis or spectral kurtosis, which represent until now the landmark for bearings diagnostics.
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Recent modelling of socio-economic costs by the Australian railway industry in 2010 has estimated the cost of level crossing accidents to exceed AU$116 million annually. To better understand causal factors that contribute to these accidents, the Cooperative Research Centre for Rail Innovation is running a project entitled Baseline Level Crossing Video. The project aims to improve the recording of level crossing safety data by developing an intelligent system capable of detecting near-miss incidents and capturing quantitative data around these incidents. To detect near-miss events at railway level crossings a video analytics module is being developed to analyse video footage obtained from forward-facing cameras installed on trains. This paper presents a vision base approach for the detection of these near-miss events. The video analytics module is comprised of object detectors and a rail detection algorithm, allowing the distance between a detected object and the rail to be determined. An existing publicly available Histograms of Oriented Gradients (HOG) based object detector algorithm is used to detect various types of vehicles in each video frame. As vehicles are usually seen from a sideway view from the cabin’s perspective, the results of the vehicle detector are verified using an algorithm that can detect the wheels of each detected vehicle. Rail detection is facilitated using a projective transformation of the video, such that the forward-facing view becomes a bird’s eye view. Line Segment Detector is employed as the feature extractor and a sliding window approach is developed to track a pair of rails. Localisation of the vehicles is done by projecting the results of the vehicle and rail detectors on the ground plane allowing the distance between the vehicle and rail to be calculated. The resultant vehicle positions and distance are logged to a database for further analysis. We present preliminary results regarding the performance of a prototype video analytics module on a data set of videos containing more than 30 different railway level crossings. The video data is captured from a journey of a train that has passed through these level crossings.
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This project advances the current understanding of intraurban rail passengers and their travel experiences to help rail industry leaders tailor policy approaches to fit specific, relevant segments of their target population. Using a Q-sorting technique and cluster analysis, preliminary research identified five perspectives occurring in a small sample of rail passengers who varied in their frequency and location of rail travel as well as certain sociodemographic characteristics. Revealed perspectives (named to capture the gist of their content) included "Rail travel is about the destination, not the journey"; "Despite challenges, public transport is still the best option"; "Rail travel is fine"; "Rail travel? So far, so good"; and "Bad taste for rail travel." This paper discusses each of the perspectives in detail and considers them in relation to tailored policy implications. An overarching finding from this study is that improving railway travel access requires attention to physical, psychological, financial, and social facets of accessibility. For example, designing waiting areas to be more socially functional and comfortable has the potential to increase ridership by addressing social forms of access, decreasing perceived wait times, and making time at the station feel like time well spent. Even at this preliminary stage, the Q-sorting technique promises to provide a valuable, holistic, albeit fine-grained, analysis of passenger attitudes and experiences that will assist industry efforts in increasing ridership.
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Transition zones between bridge decks and rail tracks suffer early failure due to poor interaction between rail vehicles and sudden changes of stiffness. This has been an ongoing problem to rail industry and yet still no systematic studies appear to have been taken to maintain a gradually smoothening transmission of forces between the bridge and its approach. Differential settlement between the bridge deck and rail track in the transition zone is the fundamental issue, which negatively impacts the rail industry by causing passenger discomfort, early damage to infrastructure and vehicle components, speed reduction, and frequent maintenance cycles. Identification of mechanism of the track degradation and factors affecting is imperative to design any mitigation method for reducing track degradation rate at the bridge transition zone. Unfortunately this issue is still not well understood, after conducting a numbers of reviews to evaluate the key causes, and introducing a wide range of mitigation techniques. In this study, a comprehensive analysis of the available literature has been carried out to develop either a novel design framework or a mitigation technique for the bridge transition zone. This paper addresses three critical questions in relation to the track degradation at transition zone: (1) what are the causes of bridge transition track degradation?; (2) what are the available mitigation techniques in reducing the track degradation rate?; (3) what are the factors affecting on poor performance of the existing mitigation techniques?. It is found that the absence of soil-water response, dynamic loading response, and behaviour of geotechnical characteristics under long-term conditions in existing track transition design frameworks critically influence on the failures of existing mitigation techniques. This paper also evaluates some of the existing design frameworks to identify how each design framework addresses the track degradation at the bridge transition zone.
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Whole System Design is increasingly being seen as one of the most cost effective ways to both increase the productivity and reduce the negative environmental impacts of an engineered system. A focus on design is critical, as the output from this stage of the project locks-in most of the economic and environmental performance of the designed system throughout its life, which can span from a few years to many decades. Indeed, it is now widely acknowledged that all designers – particularly engineers, architects and industrial designers – need to be able to understand and implement a whole system design approach. This book provides a clear design methodology, based on leading efforts in the field, and is supported by worked examples that demonstrate how advances in energy, materials and water productivity can be achieved through applying an integrated approach to sustainable engineering. Chapters 1–5 outline the approach and explain how it can be implemented to enhance the established Systems Engineering framework. Chapters 6–10 demonstrate, through detailed worked examples, the application of the approach to industrial pumping systems, passenger vehicles, electronics and computer systems, temperature control of buildings, and domestic water systems.
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Background. Volitional risky driving behaviours such as drink- and drug-driving (i.e. substance-impaired driving) and speeding contribute to the overrepresentation of young novice drivers in road crash fatalities, and crash risk is greatest during the first year of independent driving in particular. Aims. To explore the: 1) self-reported compliance of drivers with road rules regarding substance-impaired driving and other risky driving behaviours (e.g., speeding, driving while tired), one year after progression from a Learner to a Provisional (intermediate) licence; and 2) interrelationships between substance-impaired driving and other risky driving behaviours (e.g., crashes, offences, and Police avoidance). Methods. Drivers (n = 1,076; 319 males) aged 18-20 years were surveyed regarding their sociodemographics (age, gender) and self-reported driving behaviours including crashes, offences, Police avoidance, and driving intentions. Results. A relatively small proportion of participants reported driving after taking drugs (6.3% of males, 1.3% of females) and drinking alcohol (18.5% of males, 11.8% of females). In comparison, a considerable proportion of participants reported at least occasionally exceeding speed limits (86.7% of novices), and risky behaviours like driving when tired (83.6% of novices). Substance-impaired driving was associated with avoiding Police, speeding, risky driving intentions, and self-reported crashes and offences. Forty-three percent of respondents who drove after taking drugs also reported alcohol-impaired driving. Discussion and Conclusions. Behaviours of concern include drink driving, speeding, novice driving errors such as misjudging the speed of oncoming vehicles, violations of graduated driver licensing passenger restrictions, driving tired, driving faster if in a bad mood, and active punishment avoidance. Given the interrelationships between the risky driving behaviours, a deeper understanding of influential factors is required to inform targeted and general countermeasure implementation and evaluation during this critical driving period. Notwithstanding this, a combination of enforcement, education, and engineering efforts appear necessary to improve the road safety of the young novice driver, and for the drink-driving young novice driver in particular.
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Validation is an important issue in the development and application of Bayesian Belief Network (BBN) models, especially when the outcome of the model cannot be directly observed. Despite this, few frameworks for validating BBNs have been proposed and fewer have been applied to substantive real-world problems. In this paper we adopt the approach by Pitchforth and Mengersen (2013), which includes nine validation tests that each focus on the structure, discretisation, parameterisation and behaviour of the BBNs included in the case study. We describe the process and result of implementing a validation framework on a model of a real airport terminal system with particular reference to its effectiveness in producing a valid model that can be used and understood by operational decision makers. In applying the proposed validation framework we demonstrate the overall validity of the Inbound Passenger Facilitation Model as well as the effectiveness of the validity framework itself.
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The general aim of designated driver programs is to reduce the level of drink driving by encouraging potential drink drivers to travel with a driver who has abstained from (or at least limited) consuming alcohol. Designated driver programs appear to be quite widespread around the world, however a limited number have been subject to rigorous evaluation. This paper reports results from an outcome evaluation of a designated driver program called ‘Skipper’, which was trialled in a provincial city in Queensland, Australia. The outcome evaluation included surveys three weeks prior to (baseline), four months following (1st follow-up), and 16 months following (2nd follow-up) the commencement of the trial in both the ‘intervention area’ (baseline, n = 202; 1st follow-up, n = 211; 2nd follow-up, n = 200) and a ‘comparison area’(baseline, n = 203; 1st follow-up, n = 199; 2nd follow-up, n = 201); and a comparison of random breath testing and crash data before and after the trial. The survey results indicate that awareness of the program in the intervention area was quite high four months following its introduction and that this was maintained at 16 months. The results also suggest that the ‘Skipper’ program and the related publicity had positive impacts on behaviour with an increase in the proportion of people participating in designated driver as a passenger. It is less clear, however, whether the ‘Skipper’ program impacted on other behaviours of interest, such as drink driving or involvement in alcohol-related crashes. Suggestions for further research and program improvement are discussed as well as limitations of the research.
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Airports accommodate passengers with a range of prior experience, from frequent flyers, to passengers who fly every couple of years, to those who have never flown before. Passengers with varying levels of prior experience may use different visual elements when navigating the airport. Ensuring all passengers can navigate to the processing activities intuitively is important for passengers, airports and airlines. This paper examines how participants with Low, Medium and High airport familiarity navigate through the departures area at an Australian international airport. Three navigation activities are investigated: (i) navigating to the check-in row, (ii) navigating through the Liquids, Aerosols and Gels (LAGs) preparation area before security screening, and; (iii) navigating to either the boarding gate first or to a discretionary activity first, after exiting customs. In the three activities, differences were observed between the familiarity groups. These differences include the use of different information to locate the check-in desk, different actions when navigating through the LAG preparation area, and evidence that Low familiarity passengers have a desire to locate the boarding gate as soon as possible once through customs. This research provides evidence based design reccomendations for airports to benefit from intuitive passenger navigation.
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Passenger experience has become a major factor that influences the success of an airport. In this context, passenger flow simulation has been used in designing and managing airports. However, most passenger flow simulations failed to consider the group dynamics when developing passenger flow models. In this paper, an agent-based model is presented to simulate passenger behaviour at the airport check-in and evacuation process. The simulation results show that the passenger behaviour can have significant influences on the performance and utilisation of services in airport terminals. The model was created using AnyLogic software and its parameters were initialised using recent research data published in the literature.
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This paper presents Sequence Matching Across Route Traversals (SMART); a generally applicable sequence-based place recognition algorithm. SMART provides invariance to changes in illumination and vehicle speed while also providing moderate pose invariance and robustness to environmental aliasing. We evaluate SMART on vehicles travelling at highly variable speeds in two challenging environments; firstly, on an all-terrain vehicle in an off-road, forest track and secondly, using a passenger car traversing an urban environment across day and night. We provide comparative results to the current state-of-the-art SeqSLAM algorithm and investigate the effects of altering SMART’s image matching parameters. Additionally, we conduct an extensive study of the relationship between image sequence length and SMART’s matching performance. Our results show viable place recognition performance in both environments with short 10-metre sequences, and up to 96% recall at 100% precision across extreme day-night cycles when longer image sequences are used.
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Most airports internationally have implemented customer satisfaction programs into their operations to increase non-aeronautical revenues. In the US, taxicabs are an essential airport transport mode given the limited public transport options available. Effective airport taxicab planning can increase airport customer satisfaction levels, as well as facilitate handling increased airport passenger volumes. However, little is known on how US airports have adapted their governance practices from a traditional hierarchical to a network approach in their efforts to undertake airport taxicab planning initiatives since the deregulation of the transportation industry. Data acquired from 51 US hub airports is used to examine their existing taxicab planning practices. The findings offer how US airports can modify governance processes in their airport taxicab planning processes to better support increases in the customer satisfaction levels of airport taxicab patrons.
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Intelligent Transport System (ITS) technology is seen as a cost-effective way to increase the conspicuity of approaching trains and the effectiveness of train warnings at level crossings by providing an in-vehicle warning of an approaching train. The technology is often seen as a potential low-cost alternative to upgrading passive level crossings with traditional active warning systems (flashing lights and boom barriers). ITS platforms provide sensor, localization and dedicated short-range communication (DSRC) technologies to support cooperative applications such as collision avoidance for road vehicles. In recent years, in-vehicle warning systems based on ITS technology have been trialed at numerous locations around Australia, at level crossing sites with active and passive controls. While significant research has been conducted on the benefits of the technology in nominal operating modes, little research has focused on the effects of the failure modes, the human factors implications of unreliable warnings and the technology adoption process from the railway industry’s perspective. Many ITS technology suppliers originate from the road industry and often have limited awareness of the safety assurance requirements, operational requirements and legal obligations of railway operators. This paper aims to raise awareness of these issues and start a discussion on how such technology could be adopted. This paper will describe several ITS implementation cenarios and discuss failure modes, human factors considerations and the impact these scenarios are likely to have in terms of safety, railway safety assurance requirements and the practicability of meeting these requirements. The paper will identify the key obstacles impeding the adoption of ITS systems for the different implementation scenarios and a possible path forward towards the adoption of ITS technology.