592 resultados para Speed Detection.


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Background Rapid diagnostic tests (RDTs) for detection of Plasmodium falciparum infection that target P. falciparum histidine-rich protein 2 (PfHRP2), a protein that circulates in the blood of patients infected with this species of malaria, are widely used to guide case management. Understanding determinants of PfHRP2 availability in circulation is therefore essential to understanding the performance of PfHRP2-detecting RDTs. Methods The possibility that pre-formed host anti-PfHRP2 antibodies may block target antigen detection, thereby causing false negative test results was investigated in this study. Results Anti-PfHRP2 antibodies were detected in 19/75 (25%) of plasma samples collected from patients with acute malaria from Cambodia, Nigeria and the Philippines, as well as in 3/28 (10.7%) asymptomatic Solomon Islands residents. Pre-incubation of plasma samples from subjects with high-titre anti-PfHRP2 antibodies with soluble PfHRP2 blocked the detection of the target antigen on two of the three brands of RDTs tested, leading to false negative results. Pre-incubation of the plasma with intact parasitized erythrocytes resulted in a reduction of band intensity at the highest parasite density, and a reduction of lower detection threshold by ten-fold on all three brands of RDTs tested. Conclusions These observations indicate possible reduced sensitivity for diagnosis of P. falciparum malaria using PfHRP2-detecting RDTs among people with high levels of specific antibodies and low density infection, as well as possible interference with tests configured to detect soluble PfHRP2 in saliva or urine samples. Further investigations are required to assess the impact of pre-formed anti-PfHRP2 antibodies on RDT performance in different transmission settings.

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We compare three alternative methods for eliciting retrospective confidence in the context of a simple perceptual task: the Simple Confidence Rating (a direct report on a numerical scale), the Quadratic Scoring Rule (a post-wagering procedure), and the Matching Probability (MP; a generalization of the no-loss gambling method). We systematically compare the results obtained with these three rules to the theoretical confidence levels that can be inferred from performance in the perceptual task using Signal Detection Theory (SDT). We find that the MP provides better results in that respect. We conclude that MP is particularly well suited for studies of confidence that use SDT as a theoretical framework.

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In current bridge management systems (BMSs), load and speed restrictions are applied on unhealthy bridges to keep the structure safe and serviceable for as long as possible. But the question is, whether applying these restrictions will always decrease the internal forces in critical components of the bridge and enhance the safety of the unhealthy bridges. To find the answer, this paper for the first time in literature, looks into the design aspects through studying the changes in demand by capacity ratios of the critical components of a bridge under the train loads. For this purpose, a structural model of a simply supported bridge, whose dynamic behaviour is similar to a group of real railway bridges, is developed. Demand by capacity ratios of the critical components of the bridge are calculated, to identify their sensitivity to increase of speed and magnitude of live load. The outcomes of this study are very significant as they show that, on the contrary to what is expected, by applying restriction on speed, the demand by capacity ratio of components may increase and make the bridge unsafe for carrying live load. Suggestions are made to solve the problem.

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The World Health Organization identifies road trauma as a major public health issue in every country; most notably among low-to-middle income countries. More than 90% of all road fatalities occur in these countries, although they have only 48% of all registered vehicles [1]. Unprecedented focus has been placed on reducing the global road trauma burden through the United Nations Decade of Action for Road Safety (2011-2020). China is rapidly transitioning from a nation of bicycle riders and pedestrians to one where car ownership and use is increasing. This transition presents important public health, mobility, and safety challenges. Rapid motorisation has resulted in an increased road trauma burden, shouldered disproportionately among the population. Vulnerable road users (bicyclists, pedestrians, and motorcyclists) are of particular concern, representing 70% of all road-related fatalities [1]. Furthermore, those at greatest risk of sustaining a crash-related disability are: male, older, less educated, and earning a lower income [2] and residing in urban areas [3], with higher fatality rates in north-western poorer provinces [3]. Speeding is a key factor in road crashes in China [1, 4] and is one of two risk factors targeted in the Bloomberg Philanthropies-funded Global Road Safety Program operating in two Chinese cities over five year [5] to which the first author has provided expert advice. However, little evidence exists to help understand the factors underpinning speeding behaviour. Previous research conducted by the authors in Beijing and Hangzhou explored personal, social, and legal factors relating to speeding to assist in better understanding the motivations for non-compliance with speed limits. Qualitative and quantitative research findings indicated that speeding is relatively common, including self-reported travel speeds of greater than 30 km/hour above posted speed limits [6], and that the road safety laws and enforcement practices may, in some circumstances, contribute to this [7]. Normative factors were also evident; the role of friends, family members and driving instructors were influential. Additionally, using social networks to attempt to avoid detection and penalty was reported, thereby potentially reinforcing community perceptions that speeding is acceptable [8, 9]. The authors established strong collaborative links with the Chinese Academy of Sciences and Zhejiang Police College to conduct this research. The first author has worked in both institutions for extended time periods and recognises that research must include an understanding of culturally-relevant issues if road safety is to improve in China. Future collaborations to assist in enhancing our understanding of such issues are welcomed. References [1] World Health Organization. (2009). Global status report on road safety: Time for action; Geneva. [2] Chen, H., Du, W., & Li, N. (2013). The socioeconomic inequality in traffic-related disability among Chinese adults: the application of concentration index. Accident Analysis & Prevention, 55(101-106). [3] Wang, S. Y., Li, Y. H., Chi, G. B., Xiao, S. Y., Ozanne-Smith, J., Stevenson, M., & Phillips, M. (2008). Injury-related fatalities in China: an under-recognised public-health problem. The Lancet (British edition), 372(9651), 1765-1773. [4] He, J., King, M. J., Watson, B., Rakotonirainy, A., & Fleiter, J. J. (2013). Speed enforcement in China: National, provincial and city initiatives and their success. Accident Analysis & Prevention, 50, 282-288. [5] Bhalla, K., Li, Q., Duan, L., Wang, Y., Bishai, D., & Hyder, A. A. (2013). The prevalence of speeding and drink driving in two cities in China: a mid project evaluation of ongoing road safety interventions. Injury, 44, 49-56. doi:10.1016/S0020-1383(13)70213-4. [6] Fleiter, J. J., Watson, B., & Lennon, A. (2013). Awareness of risky behaviour among Chinese drivers. Peer-reviewed paper presented at 23rd Canadian Multidisciplinary Road Safety Conference, Montréal, Québec. [7] Fleiter, J. J., Watson, B., Lennon, A., King, M. J., & Shi, K. (2009). Speeding in Australia and China: A comparison of the influence of legal sanctions and enforcement practices on car drivers. Peer-reviewd paper presented at Australasian Road Safety Research Policing Education Conference, Sydney. [8] Fleiter, J. J., Watson, B., Lennon, A., King, M. J., & Shi, K. (2011). Social influences on drivers in China. Journal of the Australasian College of Road Safety, 22(2), 29-36. [9] Fleiter, J. J., Watson, B., Guan, M. Q., Ding, J. Y., & Xu, C. (2013). Characteristics of Chinese Drivers Attending a Mandatory Training Course Following Licence Suspension. Peer-reviewed paper presented at Road Safety on Four Continents, Beijing, China.

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Aerial hawking bats use intense echolocation calls to search for insect prey. Their calls have evolved into the most intense airborne animal vocalisations. Yet our knowledge about call intensities in the field is restricted to a small number of species. We describe a novel stereo videogrammetry method used to study flight and echolocation behaviour, and to measure call source levels of the aerial hawking bat Eptesicus bottae (Vespertilionidae). Bats flew close to their predicted minimum power speed. Source level increased with call duration; the loudest call of E. bottae was at 133 dB peSPL. The calculated maximum detection distance for large flying objects (e.g. large prey, conspecifics) was up to 21 m. The corresponding maximum echo delay is almost exactly the duration of one wing beat in E. bottae and this also is its preferred pulse interval. These results, obtained by using videogrammetry to track bats in the field, corroborate earlier findings from other species from acoustic tracking methods.

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Many species of bat use ultrasonic frequency modulated (FM) pulses to measure the distance to objects by timing the emission and reception of each pulse. Echolocation is mainly used in flight. Since the flight speed of bats often exceeds 1% of the speed of sound, Doppler effects will lead to compression of the time between emission and reception as well as an elevation of the echo frequencies, resulting in a distortion of the perceived range. This paper describes the consequences of these Doppler effects on the ranging performance of bats using different pulse designs. The consequences of Doppler effects on ranging performance described in this paper assume bats to have a very accurate ranging resolution, which is feasible with a filterbank receiver. By modeling two receiver types, it was first established that the effects of Doppler compression are virtually independent of the receiver type. Then, used a cross-correlation model was used to investigate the effect of flight speed on Doppler tolerance and range–Doppler coupling separately. This paper further shows how pulse duration, bandwidth, function type, and harmonics influence Doppler tolerance and range–Doppler coupling. The influence of each signal parameter is illustrated using calls of several bat species. It is argued that range–Doppler coupling is a significant source of error in bat echolocation, and various strategies bats could employ to deal with this problem, including the use of range rate information are discussed.

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In studies of germ cell transplantation, measureing tubule diameters and counting cells from different populations using antibodies as markers are very important. Manual measurement of tubule sizes and cell counts is a tedious and sanity grinding work. In this paper, we propose a new boundary weighting based tubule detection method. We first enhance the linear features of the input image and detect the approximate centers of tubules. Next, a boundary weighting transform is applied to the polar transformed image of each tubule region and a circular shortest path is used for the boundary detection. Then, ellipse fitting is carried out for tubule selection and measurement. The algorithm has been tested on a dataset consisting of 20 images, each having about 20 tubules. Experiments show that the detection results of our algorithm are very close to the results obtained manually. © 2013 IEEE.

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This paper proposes a highly reliable fault diagnosis approach for low-speed bearings. The proposed approach first extracts wavelet-based fault features that represent diverse symptoms of multiple low-speed bearing defects. The most useful fault features for diagnosis are then selected by utilizing a genetic algorithm (GA)-based kernel discriminative feature analysis cooperating with one-against-all multicategory support vector machines (OAA MCSVMs). Finally, each support vector machine is individually trained with its own feature vector that includes the most discriminative fault features, offering the highest classification performance. In this study, the effectiveness of the proposed GA-based kernel discriminative feature analysis and the classification ability of individually trained OAA MCSVMs are addressed in terms of average classification accuracy. In addition, the proposedGA- based kernel discriminative feature analysis is compared with four other state-of-the-art feature analysis approaches. Experimental results indicate that the proposed approach is superior to other feature analysis methodologies, yielding an average classification accuracy of 98.06% and 94.49% under rotational speeds of 50 revolutions-per-minute (RPM) and 80 RPM, respectively. Furthermore, the individually trained MCSVMs with their own optimal fault features based on the proposed GA-based kernel discriminative feature analysis outperform the standard OAA MCSVMs, showing an average accuracy of 98.66% and 95.01% for bearings under rotational speeds of 50 RPM and 80 RPM, respectively.

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Evidence is needed for the acceptability and user preferences of receiving skin cancer-related text messages. We prepared 27 questions to evaluate attitudes, satisfaction with program characteristics such as timing and spacing, and overall satisfaction with the Healthy Text program in young adults. Within this randomised controlled trial (age 18-42 years), 546 participants were assigned to one of three Healthy Text message groups; sun protection, skin self-examination, or attention-control. Over a 12-month period, 21 behaviour-specific text messages were sent to each group. Participants’ preferences were compared between the two interventions and control group at the 12-month follow-up telephone interview. In all three groups, participants reported the messages were easy to understand (98%), provided good suggestions or ideas (88%), and were encouraging (86%) and informative (85%) with little difference between the groups. The timing of the texts was received positively (92%); however, some suggestions for frequency or time of day the messages were received from 8% of participants. Participants in the two intervention groups found their messages more informative, and triggering behaviour change compared to control. Text messages about skin cancer prevention and early detection are novel and acceptable to induce behaviour change in young adults.

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Structural damage detection using measured dynamic data for pattern recognition is a promising approach. These pattern recognition techniques utilize artificial neural networks and genetic algorithm to match pattern features. In this study, an artificial neural network–based damage detection method using frequency response functions is presented, which can effectively detect nonlinear damages for a given level of excitation. The main objective of this article is to present a feasible method for structural vibration–based health monitoring, which reduces the dimension of the initial frequency response function data and transforms it into new damage indices and employs artificial neural network method for detecting different levels of nonlinearity using recognized damage patterns from the proposed algorithm. Experimental data of the three-story bookshelf structure at Los Alamos National Laboratory are used to validate the proposed method. Results showed that the levels of nonlinear damages can be identified precisely by the developed artificial neural networks. Moreover, it is identified that artificial neural networks trained with summation frequency response functions give higher precise damage detection results compared to the accuracy of artificial neural networks trained with individual frequency response functions. The proposed method is therefore a promising tool for structural assessment in a real structure because it shows reliable results with experimental data for nonlinear damage detection which renders the frequency response function–based method convenient for structural health monitoring.