906 resultados para time-interval-unit


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2000 Mathematics Subject Classification: 26C05, 26C10, 30A12, 30D15, 42A05, 42C05.

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Occupational therapists and other health professionals are faced with the challenge of helping parents cope with the birth of their preterm infant and fostering parent-infant bonding and attachment. Kangaroo care, or skin to skin contact, has the potential to minimize the delay in the parent-infant attachment process and facilitate more normal infant growth and development. The present study investigated the impact of parent participation in a hospital-based kangaroo care program on time spent with their preterm infant in the NICU. Fourteen parents with preterm infants in the NICU participated in the study. The results indicated that parents who participated in the kangaroo care program spent significantly more time with their infant than the parents who did not participate in the program (p $<$.022). In addition, parents in the kangaroo care group visited their infant more frequently than the control group (p $<$.037). However, the mean time with baby per day did not show a significant difference between the groups (p $<$.194). This information may assist occupational therapists in developing family-centered early intervention programs beginning in the NICU. ^

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A new method for estimating the time to colonization of Methicillin-resistant Staphylococcus Aureus (MRSA) patients is developed in this paper. The time to colonization of MRSA is modelled using a Bayesian smoothing approach for the hazard function. There are two prior models discussed in this paper: the first difference prior and the second difference prior. The second difference prior model gives smoother estimates of the hazard functions and, when applied to data from an intensive care unit (ICU), clearly shows increasing hazard up to day 13, then a decreasing hazard. The results clearly demonstrate that the hazard is not constant and provide a useful quantification of the effect of length of stay on the risk of MRSA colonization which provides useful insight.

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In Semester 1 2007, a Monitoring Student Engagement study, conducted as part of the Enhancing Transition at Queensland University of Technology (ET@QUT) Project and extending earlier work in the Project by Arora (2006), aimed at mapping the processes and resources used at that time to identify, monitor and manage students in their first year who were at risk of leaving QUT (Shaw, 2007). This identified a lack of documentation of the processes and resources used and revealed an ad-hoc rather than holistic and systematic approach to monitoring student engagement. One of Shaw’s recommendations was to: “To introduce a centralised case management approach to student engagement” (p. 14). That provided the genesis for the Student Success Project that is being reported on here. The aim of the Student Success Project is to trial, evaluate and ultimately establish holistic and systematic ways of helping students who appear to be at-risk of failing or withdrawing from a unit to persist and succeed. Students are profiled as being at-risk if they are absent from more than 2 tutorials in a row without contacting their tutor or if they fail to submit their first assignment. A Project Officer makes personal contact with these students to suggest ways they can get further assistance depending on their situation.

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This paper presents a model to estimate travel time using cumulative plots. Three different cases considered are i) case-Det, for only detector data; ii) case-DetSig, for detector data and signal controller data and iii) case-DetSigSFR: for detector data, signal controller data and saturation flow rate. The performance of the model for different detection intervals is evaluated. It is observed that detection interval is not critical if signal timings are available. Comparable accuracy can be obtained from larger detection interval with signal timings or from shorter detection interval without signal timings. The performance for case-DetSig and for case-DetSigSFR is consistent with accuracy generally more than 95% whereas, case-Det is highly sensitive to the signal phases in the detection interval and its performance is uncertain if detection interval is integral multiple of signal cycles.

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Professional prac− tice guidelines for endoscope reprocessing re− commend reprocessing endoscopes between each case and proper storage following repro− cessing after the last case of the list. There is lim− ited empirical evidence to support the efficacy of endoscope reprocessing prior to use in the first case of the day; however, internationally, many guidelines continue to recommend this practice. The aim of this study is to estimate a safe shelf life for flexible endoscopes in a high−turnover gastroenterology unit. Materials and methods: In a prospective obser− vational study, all flexible endoscopes in active service during the 3−week study period were mi− crobiologically sampled prior to reprocessing be− fore the first case of the day (n = 200). The main outcome variables were culture status, organism cultured, and shelf life. Results: Among the total number of useable samples (n = 194), the overall contamination rate was 15.5 %, with a pathogenic contamination rate of 0.5 %. Mean time between last case one day and reprocessing before the first case on the next day (that is, shelf life) was 37.62 h (SD 36.47). Median shelf life was 18.8 h (range 5.27± 165.35 h). The most frequently identified organ− ism was coagulase−negative Staphylococcus, an environmental nonpathogenic organism. Conclusions: When processed according to es− tablished guidelines, flexible endoscopes remain free from pathogenic organisms between last case and next day first case use. Significant re− ductions in the expenditure of time and resources on reprocessing endoscopes have the potential to reduce the restraints experienced by high−turnover endoscopy units and improve ser− vice delivery.

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Purpose: Television viewing time, independent of leisure-time physical activity, has cross-sectional relationships with the metabolic syndrome and its individual components. We examined whether baseline and five-year changes in self-reported television viewing time are associated with changes in continuous biomarkers of cardio-metabolic risk (waist circumference, triglycerides, high density lipoprotein cholesterol, systolic and diastolic blood pressure, fasting plasma glucose; and a clustered cardio-metabolic risk score) in Australian adults. Methods: AusDiab is a prospective, population-based cohort study with biological, behavioral, and demographic measures collected in 1999–2000 and 2004–2005. Non-institutionalized adults aged ≥ 25 years were measured at baseline (11,247; 55% of those completing an initial household interview); 6,400 took part in the five-year follow-up biomedical examination, and 3,846 met the inclusion criteria for this analysis. Multiple linear regression analysis was used and unstandardized B coefficients (95% CI) are provided. Results: Baseline television viewing time (10 hours/week unit) was not significantly associated with change in any of the biomarkers of cardio-metabolic risk. Increases in television viewing time over five years (10 hours/week unit) were associated with increases in: waist circumference (cm) (men: 0.43 (0.08, 0.78), P = 0.02; women: 0.68 (0.30, 1.05), P <0.001), diastolic blood pressure (mmHg) (women: 0.47 (0.02, 0.92), P = 0.04), and the clustered cardio-metabolic risk score (women: 0.03 (0.01, 0.05), P = 0.007). These associations were independent of baseline television viewing time and baseline and change in physical activity and other potential confounders. Conclusion: These findings indicate that an increase in television viewing time is associated with adverse cardio-metabolic biomarker changes. Further prospective studies using objective measures of several sedentary behaviors are required to confirm causality of the associations found.

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This paper presents the preliminary results in establishing a strategy for predicting Zenith Tropospheric Delay (ZTD) and relative ZTD (rZTD) between Continuous Operating Reference Stations (CORS) in near real-time. It is anticipated that the predicted ZTD or rZTD can assist the network-based Real-Time Kinematic (RTK) performance over long inter-station distances, ultimately, enabling a cost effective method of delivering precise positioning services to sparsely populated regional areas, such as Queensland. This research firstly investigates two ZTD solutions: 1) the post-processed IGS ZTD solution and 2) the near Real-Time ZTD solution. The near Real-Time solution is obtained through the GNSS processing software package (Bernese) that has been deployed for this project. The predictability of the near Real-Time Bernese solution is analyzed and compared to the post-processed IGS solution where it acts as the benchmark solution. The predictability analyses were conducted with various prediction time of 15, 30, 45, and 60 minutes to determine the error with respect to timeliness. The predictability of ZTD and relative ZTD is determined (or characterized) by using the previously estimated ZTD as the predicted ZTD of current epoch. This research has shown that both the ZTD and relative ZTD predicted errors are random in nature; the STD grows from a few millimeters to sub-centimeters while the predicted delay interval ranges from 15 to 60 minutes. Additionally, the RZTD predictability shows very little dependency on the length of tested baselines of up to 1000 kilometers. Finally, the comparison of near Real-Time Bernese solution with IGS solution has shown a slight degradation in the prediction accuracy. The less accurate NRT solution has an STD error of 1cm within the delay of 50 minutes. However, some larger errors of up to 10cm are observed.

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Aims: To describe a local data linkage project to match hospital data with the Australian Institute of Health and Welfare (AIHW) National Death Index (NDI) to assess longterm outcomes of intensive care unit patients. Methods: Data were obtained from hospital intensive care and cardiac surgery databases on all patients aged 18 years and over admitted to either of two intensive care units at a tertiary-referral hospital between 1 January 1994 and 31 December 2005. Date of death was obtained from the AIHW NDI by probabilistic software matching, in addition to manual checking through hospital databases and other sources. Survival was calculated from time of ICU admission, with a censoring date of 14 February 2007. Data for patients with multiple hospital admissions requiring intensive care were analysed only from the first admission. Summary and descriptive statistics were used for preliminary data analysis. Kaplan-Meier survival analysis was used to analyse factors determining long-term survival. Results: During the study period, 21 415 unique patients had 22 552 hospital admissions that included an ICU admission; 19 058 surgical procedures were performed with a total of 20 092 ICU admissions. There were 4936 deaths. Median follow-up was 6.2 years, totalling 134 203 patient years. The casemix was predominantly cardiac surgery (80%), followed by cardiac medical (6%), and other medical (4%). The unadjusted survival at 1, 5 and 10 years was 97%, 84% and 70%, respectively. The 1-year survival ranged from 97% for cardiac surgery to 36% for cardiac arrest. An APACHE II score was available for 16 877 patients. In those discharged alive from hospital, the 1, 5 and 10-year survival varied with discharge location. Conclusions: ICU-based linkage projects are feasible to determine long-term outcomes of ICU patients

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This paper presents a model for estimation of average travel time and its variability on signalized urban networks using cumulative plots. The plots are generated based on the availability of data: a) case-D, for detector data only; b) case-DS, for detector data and signal timings; and c) case-DSS, for detector data, signal timings and saturation flow rate. The performance of the model for different degrees of saturation and different detector detection intervals is consistent for case-DSS and case-DS whereas, for case-D the performance is inconsistent. The sensitivity analysis of the model for case-D indicates that it is sensitive to detection interval and signal timings within the interval. When detection interval is integral multiple of signal cycle then it has low accuracy and low reliability. Whereas, for detection interval around 1.5 times signal cycle both accuracy and reliability are high.

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This paper investigates the control of a HVDC link, fed from an AC source through a controlled rectifier and feeding an AC line through a controlled inverter. The overall objective is to maintain maximum possible link voltage at the inverter while regulating the link current. In this paper the practical feedback design issues are investigated with a view of obtaining simple, robust designs that are easy to evaluate for safety and operability. The investigations are applicable to back-to-back links used for frequency decoupling and to long DC lines. The design issues discussed include: (i) a review of overall system dynamics to establish the time scale of different feedback loops and to highlight feedback design issues; (ii) the concept of using the inverter firing angle control to regulate link current when the rectifier firing angle controller saturates; and (iii) the design issues for the individual controllers including robust design for varying line conditions and the trade-off between controller complexity and the reduction of nonlinearity and disturbance effects

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Background: A number of epidemiological studies have been conducted to research the adverse effects of air pollution on mortality and morbidity. Hypertension is the most important risk factor for cardiovascular mortality. However, few previous studies have examined the relationship between gaseous air pollution and morbidity for hypertension. ---------- Methods: Daily data on emergency hospital visits (EHVs) for hypertension were collected from the Peking University Third Hospital. Daily data on gaseous air pollutants (sulfur dioxide (SO2) and nitrogen dioxide (NO2)) and particulate matter less than 10 μm in aerodynamic diameter (PM10) were collected from the Beijing Municipal Environmental Monitoring Center. A time-stratified case-crossover design was conducted to evaluate the relationship between urban gaseous air pollution and EHVs for hypertension. Temperature and relative humidity were controlled for. ---------- Results: In the single air pollutant models, a 10 μg/m3 increase in SO2 and NO2 were significantly associated with EHVs for hypertension. The odds ratios (ORs) were 1.037 (95% confidence interval (CI): 1.004-1.071) for SO2 at lag 0 day, and 1.101 (95% CI: 1.038-1.168) for NO2 at lag 3 day. After controlling for PM10, the ORs associated with SO2 and NO2 were 1.025 (95% CI: 0.987-1.065) and 1.114 (95% CI: 1.037-1.195), respectively.---------- Conclusion: Elevated urban gaseous air pollution was associated with increased EHVs for hypertension in Beijing, China.

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Catheter associated urinary tract infections (CAUTI) are a worldwide problem that may lead to increased patient morbidity, cost and mortality.1e3 The literature is divided on whether there are real effects from CAUTI on length of stay or mortality. Platt4 found the costs and mortality risks to be largeyetGraves et al found the opposite.5 A reviewof the published estimates of the extra length of stay showed results between zero and 30 days.6 The differences in estimates may have been caused by the different epidemiological methods applied. Accurately estimating the effects of CAUTI is difficult because it is a time-dependent exposure. This means that standard statistical techniques, such asmatched case-control studies, tend to overestimate the increased hospital stay and mortality risk due to infection. The aim of the study was to estimate excess length of stay andmortality in an intensive care unit (ICU) due to a CAUTI, using a statistical model that accounts for the timing of infection. Data collected from ICU units in lower and middle income countries were used for this analysis.7,8 There has been little research for these settings, hence the need for this paper.

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Operations management is an area concerned with the production of goods and services ensuring that business operations are efficient in utilizing resource and effective to meet customer requirements. It deals with the design and management of products, processes, services and supply chains and considers the acquisition, development, and effective and efficient utilization of resources. Unlike other engineering subjects, content of these units could be very wide and vast. It is therefore necessary to cover the content that is most related to the contemporary industries. It is also necessary to understand what engineering management skills are critical for engineers working in the contemporary organisations. Most of the operations management books contain traditional Operations Management techniques. For example ‘inventory management’ is an important topic in operations management. All OM books deal with effective method of inventory management. However, new trend in OM is Just in time (JIT) delivery or minimization of inventory. It is therefore important to decide whether to emphasise on keeping inventory (as suggested by most books) or minimization of inventory. Similarly, for OM decisions like forecasting, optimization and linear programming most organisations now a day’s use software. Now it is important for us to determine whether some of these software need to be introduced in tutorial/ lab classes. If so, what software? It is established in the Teaching and Learning literature that there must be a strong alignment between unit objectives, assessment and learning activities to engage students in learning. Literature also established that engaging students is vital for learning. However, engineering units (more specifically Operations management) is quite different from other majors. Only alignment between objectives, assessment and learning activities cannot guarantee student engagement. Unit content must be practical oriented and skills to be developed should be those demanded by the industry. Present active learning research, using a multi-method research approach, redesigned the operations management content based on latest developments in Engineering Management area and the necessity of Australian industries. The redesigned unit has significantly helped better student engagement and better learning. It was found that students are engaged in the learning if they find the contents are helpful in developing skills that are necessary in their practical life.