867 resultados para OTP (one-time password)
Resumo:
The measurement of broadband ultrasonic attenuation (BUA) in cancellous bone at the calcaneus for the assessment of osteoporosis was first described within this journal 25 years ago. It was recognized in 2006 by Universities UK as being one of the ‘100 discoveries and developments in UK Universities that have changed the world’ over the past 50 years. In 2008, the UK's Department of Health also recognized BUA assessment of osteoporosis in a publication highlighting 11 projects that have contributed to ‘60 years of NHS research benefiting patients’. The BUA technique has been extensively clinically validated and is utilized worldwide, with at least seven commercial systems currently providing calcaneal BUA measurement. However, there is still no fundamental understanding of the dependence of BUA upon the material and structural properties of cancellous bone. This review aims to provide an ‘engineering in medicine’ perspective and proposes a new paradigm based upon phase cancellation due to variation in propagation transit time across the receive transducer face to explain the non-linear relationship between BUA and bone volume fraction in cancellous bone.
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The high morbidity and mortality associated with atherosclerotic coronary vascular disease (CVD) and its complications are being lessened by the increased knowledge of risk factors, effective preventative measures and proven therapeutic interventions. However, significant CVD morbidity remains and sudden cardiac death continues to be a presenting feature for some subsequently diagnosed with CVD. Coronary vascular disease is also the leading cause of anaesthesia related complications. Stress electrocardiography/exercise testing is predictive of 10 year risk of CVD events and the cardiovascular variables used to score this test are monitored peri-operatively. Similar physiological time-series datasets are being subjected to data mining methods for the prediction of medical diagnoses and outcomes. This study aims to find predictors of CVD using anaesthesia time-series data and patient risk factor data. Several pre-processing and predictive data mining methods are applied to this data. Physiological time-series data related to anaesthetic procedures are subjected to pre-processing methods for removal of outliers, calculation of moving averages as well as data summarisation and data abstraction methods. Feature selection methods of both wrapper and filter types are applied to derived physiological time-series variable sets alone and to the same variables combined with risk factor variables. The ability of these methods to identify subsets of highly correlated but non-redundant variables is assessed. The major dataset is derived from the entire anaesthesia population and subsets of this population are considered to be at increased anaesthesia risk based on their need for more intensive monitoring (invasive haemodynamic monitoring and additional ECG leads). Because of the unbalanced class distribution in the data, majority class under-sampling and Kappa statistic together with misclassification rate and area under the ROC curve (AUC) are used for evaluation of models generated using different prediction algorithms. The performance based on models derived from feature reduced datasets reveal the filter method, Cfs subset evaluation, to be most consistently effective although Consistency derived subsets tended to slightly increased accuracy but markedly increased complexity. The use of misclassification rate (MR) for model performance evaluation is influenced by class distribution. This could be eliminated by consideration of the AUC or Kappa statistic as well by evaluation of subsets with under-sampled majority class. The noise and outlier removal pre-processing methods produced models with MR ranging from 10.69 to 12.62 with the lowest value being for data from which both outliers and noise were removed (MR 10.69). For the raw time-series dataset, MR is 12.34. Feature selection results in reduction in MR to 9.8 to 10.16 with time segmented summary data (dataset F) MR being 9.8 and raw time-series summary data (dataset A) being 9.92. However, for all time-series only based datasets, the complexity is high. For most pre-processing methods, Cfs could identify a subset of correlated and non-redundant variables from the time-series alone datasets but models derived from these subsets are of one leaf only. MR values are consistent with class distribution in the subset folds evaluated in the n-cross validation method. For models based on Cfs selected time-series derived and risk factor (RF) variables, the MR ranges from 8.83 to 10.36 with dataset RF_A (raw time-series data and RF) being 8.85 and dataset RF_F (time segmented time-series variables and RF) being 9.09. The models based on counts of outliers and counts of data points outside normal range (Dataset RF_E) and derived variables based on time series transformed using Symbolic Aggregate Approximation (SAX) with associated time-series pattern cluster membership (Dataset RF_ G) perform the least well with MR of 10.25 and 10.36 respectively. For coronary vascular disease prediction, nearest neighbour (NNge) and the support vector machine based method, SMO, have the highest MR of 10.1 and 10.28 while logistic regression (LR) and the decision tree (DT) method, J48, have MR of 8.85 and 9.0 respectively. DT rules are most comprehensible and clinically relevant. The predictive accuracy increase achieved by addition of risk factor variables to time-series variable based models is significant. The addition of time-series derived variables to models based on risk factor variables alone is associated with a trend to improved performance. Data mining of feature reduced, anaesthesia time-series variables together with risk factor variables can produce compact and moderately accurate models able to predict coronary vascular disease. Decision tree analysis of time-series data combined with risk factor variables yields rules which are more accurate than models based on time-series data alone. The limited additional value provided by electrocardiographic variables when compared to use of risk factors alone is similar to recent suggestions that exercise electrocardiography (exECG) under standardised conditions has limited additional diagnostic value over risk factor analysis and symptom pattern. The effect of the pre-processing used in this study had limited effect when time-series variables and risk factor variables are used as model input. In the absence of risk factor input, the use of time-series variables after outlier removal and time series variables based on physiological variable values’ being outside the accepted normal range is associated with some improvement in model performance.
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This paper presents a methodology for estimation of average travel time on signalized urban networks by integrating cumulative plots and probe data. This integration aims to reduce the relative deviations in the cumulative plots due to midlink sources and sinks. During undersaturated traffic conditions, the concept of a virtual probe is introduced, and therefore, accurate travel time can be obtained when a real probe is unavailable. For oversaturated traffic conditions, only one probe per travel time estimation interval—360 s or 3% of vehicles traversing the link as a probe—has the potential to provide accurate travel time.
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Staphylococcus aureus is a common pathogen that causes a variety of infections including soft tissue infections, impetigo, septicemia toxic shock and scalded skin syndrome. Traditionally, Methicillin-Resistant Staphylococcus aureus (MRSA) was considered a Hospital-Acquired (HA) infection. It is now recognised that the frequency of infections with MRSA is increasing in the community, and that these infections are not originating from hospital environments. A 2007 report by the Centers for Disease Control and Prevention (CDC) stated that Staphylococcus aureus is the most important cause of serious and fatal infections in the USA. Community-Acquired MRSA (CA-MRSA) are genetically diverse and distinct, meaning they are able to be identified and tracked by way of genotyping. Genotyping of MRSA using Single nucleotide polymorphisms (SNPs) is a rapid and robust method for monitoring MRSA, specifically ST93 (Queensland Clone) dissemination in the community. It has been shown that a large proportion of CA-MRSA infections in Queensland and New South Wales are caused by ST93. The rationale for this project was that SNP analysis of MLST genes is a rapid and cost-effective method for genotyping and monitoring MRSA dissemination in the community. In this study, 16 different sequence types (ST) were identified with 41% of isolates identified as ST93 making it the predominate clone. Males and Females were infected equally with an average patient age of 45yrs. Phenotypically, all of the ST93 had an identical antimicrobial resistance pattern. They were resistant to the β-lactams – Penicillin, Flu(di)cloxacillin and Cephalothin but sensitive to all other antibiotics tested. Virulence factors play an important role in allowing S. aureus to cause disease by way of colonising, replication and damage to the host. One virulence factor of particular interest is the toxin Panton-Valentine leukocidin (PVL), which is composed of two separate proteins encoded by two adjacent genes. PVL positive CA-MRSA are shown to cause recurrent, chronic or severe skin and soft tissue infections. As a result, it is important that PVL positive CA-MRSA is genotyped and tracked. Especially now that CA-MRSA infections are more prevalent than HA-MRSA infections and are now deemed endemic in Australia. 98% of all isolates in this study tested positive for the PVL toxin gene. This study showed that PVL is present in many different community based ST, not just ST93, which were all PVL positive. With this toxin becoming entrenched in CA-MRSA, genotyping would provide more accurate data and a way of tracking the dissemination. PVL gene can be sub-typed using an allele-specific Real-Time PCR (RT-PCR) followed by High resolution meltanalysis. This allows the identification of PVL subtypes within the CA-MRSA population and allow the tracking of these clones in the community.
Resumo:
In order to examine time allocation patterns within household-level trip-chaining, simultaneous doubly-censored Tobit models are applied to model time-use behavior within the context of household activity participation. Using the entire sample and a sub-sample of worker households from Tucson's Household Travel Survey, two sets of models are developed to better understand the phenomena of trip-chaining behavior among five types of households: single non-worker households, single worker households, couple non-worker households, couple one-worker households, and couple two-worker households. Durations of out-of-home subsistence, maintenance, and discretionary activities within trip chains are examined. Factors found to be associated with trip-chaining behavior include intra-household interactions with the household types and their structure and household head attributes.
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Fuzzy logic has been applied to control traffic at road junctions. A simple controller with one fixed rule-set is inadequate to minimise delays when traffic flow rate is time-varying and likely to span a wide range. To achieve better control, fuzzy rules adapted to the current traffic conditions are used.
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This paper discusses a new paradigm of real-time simulation of power systems in which equipment can be interfaced with a real-time digital simulator. In this scheme, one part of a power system can be simulated by using a real-time simulator; while the other part is implemeneted as a physical system. The only interface of the physical system with the computer-based simulator is through data-acquisition system. The physical system is driven by a voltage-source converter (VSC)that mimics the power system simulated in the real-time simulator. In this papar, the VSC operates in a voltage-control mode to track the point of common coupling voltage signal supplied by the digital simulator. This type of splitting a network in two parts and running a real-time simulation with a physical system in parallel is called a power network in loop here. this opens up the possibility of study of interconnection o f one or several distributed generators to a complex power network. The proposed implementation is verified through simulation studies using PSCAD/EMTDC and through hardware implementation on a TMS320G2812 DSP.
Resumo:
For quite some time, debate has raged about what the human race can and should do with its knowledge of genetics. We are now nearly 60 years removed from the work of Watson and Crick who determined the structure of deoxyribonucleic acid (DNA), yet our opinions as how best to employ scientific knowledge of the human genome, remain as diverse and polarised as ever. Human judgment is often shaped and coloured by popular media and culture, so it should come as no surprise that box office movies such as Gattaca (1997) continue to play a role in informing public opinion on genetics. In order to perform well at the box office, movies such as Gattaca take great liberty in sensationalising (and even distorting) the implications that may result from genetic screening and testing. If the public’s opinion on human genetics is strongly derived from the box office and popular media, then it is no wonder that the discourse on human genetics is couched in the polar parlances of future utopias or future dystopias. When legislating in an area like genetic discrimination in the workforce, we must be mindful of not overplaying the causal link between genetic predisposition towards a disability and an employee’s ability to perform the inherent requirements of their job. Genetic information is ultimately about people, it is not about genes. Genetic discrimination is ultimately about actions, it is not about the intrinsic value of genetic information.
Resumo:
Aims: Driving Under the Influence (DUI) enforcement can be a broad screening mechanism for alcohol and other drug problems. The current response to DUI is focused on using mechanical means to prevent inebriated persons from driving, with little attention the underlying substance abuse problems. ---------- Methods: This is a secondary analysis of an administrative dataset of over 345,000 individuals who entered Texas substance abuse treatment between 2005 and 2008. Of these, 36,372 were either on DUI probation, referred to treatment by probation, or had a DUI arrest in the past year. The DUI offenders were compared on demographic characteristics, substance use patterns, and levels of impairment with those who were not DUI offenders and first DUI offenders were compared with those with more than one past-year offense. T tests and chi square tests were used to determine significance. ---------- Results: DUI offenders were more likely to be employed, to have a problem with alcohol, to report more past-year arrests for any offense, to be older, and to have used alcohol and drugs longer than the non-DUI clients who reported higher ASI scores and were more likely to use daily. Those with one past-year DUI arrest were more likely to have problems with drugs other than alcohol and were less impaired than those with two or more arrests based on their ASI scores and daily use. Non-DUI clients reported higher levels of mood disorders than DUIs but there was no difference in their diagnosis of anxiety. Similar findings were found between those with one or multiple DUI arrests. ----------Conclusion: Although first-time DUIs were not as impaired as non-DUI clients, their levels of impairment were sufficient to cause treatment. Screening and brief intervention at arrest for all DUI offenders and treatment in combination with abstinence monitoring could decrease future recidivism.
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Background: The 2003 Bureau of Labor Statistics American Time Use Survey (ATUS) contains 438 distinct primary activity variables that can be analyzed with regard to how time is spent by Americans. The Compendium of Physical Activities is used to code physical activities derived from various surveys, logs, diaries, etc to facilitate comparison of coded intensity levels across studies. ------ ----- Methods: This paper describes the methods, challenges, and rationale for linking Compendium estimates of physical activity intensity (METs, metabolic equivalents) with all activities reported in the 2003 ATUS. ----- ----- Results: The assigned ATUS intensity levels are not intended to compute the energy costs of physical activity in individuals. Instead, they are intended to be used to identify time spent in activities broadly classified by type and intensity. This function will complement public health surveillance systems and aid in policy and health-promotion activities. For example, at least one of the future projects of this process is the descriptive epidemiology of time spent in common physical activity intensity categories. ----- ----- Conclusions: The process of metabolic coding of the ATUS by linking it with the Compendium of Physical Activities can make important contributions to our understanding of Americans’ time spent in health-related physical activity.
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The aim of this project was to implement a just-in-time hints help system into a real time strategy (RTS) computer game that would deliver information to the user at the time that it would be of the most benefit. The goal of this help system is to improve the user’s learning in terms of their rate of learning, retention and avoidance of stagnation. The first stage of this project was implementing a computer game to incorporate four different types of skill that the user must acquire, namely motor, perceptual, declarative knowledge and strategic. Subsequently, the just-in-time hints help system was incorporated into the game to assess the user’s knowledge and deliver hints accordingly. The final stage of the project was to test the effectiveness of this help system by conducting two phases of testing. The goal of this testing was to demonstrate an increase in the user’s assessment of the helpfulness of the system from phase one to phase two. The results of this testing showed that there was no significant difference in the user’s responses in the two phases. However, when the results were analysed with respect to several categories of hints that were identified, it became apparent that patterns in the data were beginning to emerge. The conclusions of the project were that further testing with a larger sample size would be required to provide more reliable results and that factors such as the user’s skill level and different types of goals should be taken into account.
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We treat two related moving boundary problems. The first is the ill-posed Stefan problem for melting a superheated solid in one Cartesian coordinate. Mathematically, this is the same problem as that for freezing a supercooled liquid, with applications to crystal growth. By applying a front-fixing technique with finite differences, we reproduce existing numerical results in the literature, concentrating on solutions that break down in finite time. This sort of finite-time blow-up is characterised by the speed of the moving boundary becoming unbounded in the blow-up limit. The second problem, which is an extension of the first, is proposed to simulate aspects of a particular two-phase Stefan problem with surface tension. We study this novel moving boundary problem numerically, and provide results that support the hypothesis that it exhibits a similar type of finite-time blow-up as the more complicated two-phase problem. The results are unusual in the sense that it appears the addition of surface tension transforms a well-posed problem into an ill-posed one.
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Background: In the last decade, there has been increasing interest in the health effects of sedentary behavior, which is often assessed using self-report sitting-time questions. The aim of this qualitative study was to document older adults’ understanding of sitting-time questions from the International Physical Activity (PA) Questionnaire (IPAQ) and the PA Scale for the Elderly (PASE). Methods: Australian community-dwelling adults aged 65+ years answered the IPAQ and PASE sitting questions in face-to-face semi-structured interviews. IPAQ uses one open-ended question to assess sitting on a weekday in the last 7 days 'at work, at home, while doing coursework and during leisure time'; PASE uses a three-part closed question about daily leisure-time sitting in the last 7 days. Participants expressed their thoughts out loud while answering each question. They were then probed about their responses. Interviews were recorded, transcribed and coded into themes. Results: Mean age of the 28 male and 27 female participants was 73 years (range 65-89). The most frequently reported activity was watching TV. For both questionnaires, many participants had difficulties understanding what activities to report. Some had difficulty understanding what activities should be classified as ‘leisure-time sitting’. Some assumed they were being asked to only report activities provided as examples. Most reported activities they normally do, rather than those performed on a day in the previous week. Participants used a variety of strategies to select ‘a day’ for which they reported their sitting activities and to calculate sitting time on that day. Therefore, many different ways of estimating sitting time were used. Participants had particular difficulty reporting their daily sitting-time when their schedules were not consistent across days. Some participants declared the IPAQ sitting question too difficult to answer. Conclusion: The accuracy of older adults’ self-reported sitting time is questionable given the challenges they have in answering sitting-time questions. Their responses to sitting-time questions may be more accurate if our recommendations for clarifying the sitting domains, providing examples relevant to older adults and suggesting strategies for formulating responses are incorporated. Future quantitative studies should include objective criterion measures to assess validity and reliability of these questions.
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This paper presents channel measurements and weather data collection experiments conducted in a rural environment for an innovative Multi-User-Single-Antenna (MUSA) MIMO-OFDM technology, proposed for rural areas. MUSA MIMO-OFDM uplink channels are established by placing six user terminals (UT) around one access point (AP). Generated terrain profiles and relative received power plots are presented based on the experimental data. According to the relative received signal, MUSA-MIMO-OFDM uplink channels experience temporal fading. Moreover, the correlation between the relative received power and weather variables are presented. Results show that all weather variables exhibit a negative average correlation with received power. Wind speed records the highest average negative correlation coefficient of -0.35. Local maxima of negative correlation, ranging from 0.49 to 0.78, between the weather variables and relative received signals were registered between 5-6 a.m. The highest measured correlation (-0.78) of this time of the day was exhibited by wind speed. These results show the extend of time variation effects experienced by MUSA-MIMO-OFDM channels deployed in rural environments.
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In addition to the well-known health risks associated with lack of physical activity (PA), evidence is emerging about the health risks of sedentary behaviour (sitting). Research about patterns and correlates of sitting and PA in older women is scarce. METHODS: Self-report data from 6,116 women aged 76-81 years were collected as part of the Australian Longitudinal Study on Woman’s Health. Linear regression models were computed to examine whether demographic, social and health factors were associated with sitting and PA. RESULTS: Women who did no PA sat more than women who did any PA (p<0.001). Seven correlates were associated with sitting and PA (p<0.05). Five of these were associated with more sitting and less PA: three health-related (BMI, chronic conditions, anxiety/depression) and two social correlates (caring duties, volunteering). One demographic (being from another English-speaking country) and one social correlate (more social interaction) were associated with more sitting and more PA. Four correlates, two demographic (living in a city; post-high school education), one social (being single), and one health-related correlate (dizziness/loss of balance) were associated with more sitting only. Two other health-related correlates (stiff/painful joints; feet problems) were associated with less PA only. CONCLUSION: Sedentary behaviour and PA are distinct behaviours in older Australian women. Information about the correlates of both behaviours can be used to identify population groups who might benefit from interventions to reduce sedentary behaviour and/or increase PA.