879 resultados para Median Filtering


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Background Length of hospital stay (LOS) is a surrogate marker for patients' well-being during hospital treatment and is associated with health care costs. Identifying pretreatment factors associated with LOS in surgical patients may enable early intervention in order to reduce postoperative LOS. Methods This cohort study enrolled 157 patients with suspected or proven gynecological cancer at a tertiary cancer centre (2004-2006). Before commencing treatment, the scored Patient Generated - Subjective Global Assessment (PG-SGA) measuring nutritional status and the Functional Assessment of Cancer Therapy-General (FACT-G) scale measuring quality of life (QOL) were completed. Clinical and demographic patient characteristics were prospectively obtained. Patients were grouped into those with prolonged LOS if their hospital stay was greater than the median LOS and those with average or below average LOS. Results Patients' mean age was 58 years (SD 14 years). Preoperatively, 81 (52%) patients presented with suspected benign disease/pelvic mass, 23 (15%) with suspected advanced ovarian cancer, 36 (23%) patients with suspected endometrial and 17 (11%) with cervical cancer, respectively. In univariate models prolonged LOS was associated with low serum albumin or hemoglobin, malnutrition (PG-SGA score and PG-SGA group B or C), low pretreatment FACT-G score, and suspected diagnosis of cancer. In multivariable models, PG-SGA group B or C, FACT-G score and suspected diagnosis of advanced ovarian cancer independently predicted LOS. Conclusions Malnutrition, low quality of life scores and being diagnosed with advanced ovarian cancer are the major determinants of prolonged LOS amongst gynecological cancer patients. Interventions addressing malnutrition and poor QOL may decrease LOS in gynecological cancer patients.

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The aim of this paper is to explore a new approach to obtain better traffic demand (Origin-Destination, OD matrices) for dense urban networks. From reviewing existing methods, from static to dynamic OD matrix evaluation, possible deficiencies in the approach could be identified: traffic assignment details for complex urban network and lacks in dynamic approach. To improve the global process of traffic demand estimation, this paper is focussing on a new methodology to determine dynamic OD matrices for urban areas characterized by complex route choice situation and high level of traffic controls. An iterative bi-level approach will be used, the Lower level (traffic assignment) problem will determine, dynamically, the utilisation of the network by vehicles using heuristic data from mesoscopic traffic simulator and the Upper level (matrix adjustment) problem will proceed to an OD estimation using optimization Kalman filtering technique. In this way, a full dynamic and continuous estimation of the final OD matrix could be obtained. First results of the proposed approach and remarks are presented.

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Background The purpose of this study was to provide a detailed evaluation of adherence to nutrition supplements by patients with a lower limb fracture. Methods These descriptive data are from 49 nutritionally“ at-risk” patients aged 70+ years admitted to the hospital after a fall-related lower limb fracture and allocated to receive supplementation as part of a randomized, controlled trial. Supplementation commenced on day 7 and continued for 42 days. Prescribed volumes aimed to meet 45% of individually estimated theoretical energy requirements to meet the shortfall between literature estimates of energy intake and requirements. The supplement was administered by nursing staff on medication rounds in the acute or residential care settings and supervised through thrice-weekly home visits postdischarge. Results Median daily percent of the prescribed volume of nutrition supplement consumed averaged over the 42 days was 67% (interquartile range [IQR], 31–89, n = 49). There was no difference in adherence for gender, accommodation, cognition, or whether the supplement was self-administered or supervised. Twenty-three participants took some supplement every day, and a further 12 missed <5 days. For these 35 “nonrefusers,” adherence was 82% (IQR, 65–93), and they lost on average 0.7% (SD, 4.0%) of baseline weight over the 6 weeks of supplementation compared with a loss of 5.5% (SD, 5.4%) in the “refusers” (n = 14, 29%), p = .003. Conclusions We achieved better volume and energy consumption than previous studies of hip fracture patients but still failed to meet target supplement volumes prescribed to meet 45% of theoretical energy requirements. Clinicians should consider alternative methods of feeding such as a nasogastric tube, particularly in those patients where adherence to oral nutrition supplements is poor and dietary intake alone is insufficient to meet estimated energy requirements.

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In order to estimate the safety impact of roadway interventions engineers need to collect, analyze, and interpret the results of carefully implemented data collection efforts. The intent of these studies is to develop Accident Modification Factors (AMF's), which are used to predict the safety impact of various road safety features at other locations or in upon future enhancements. Models are typically estimated to estimate AMF's for total crashes, but can and should be estimated for crash outcomes as well. This paper first describes data collected with the intent estimate AMF's for rural intersections in the state of Georgia within the United Sates. Modeling results of crash prediction models for the crash outcomes: angle, head-on, rear-end, sideswipe (same direction and opposite direction) and pedestrian-involved crashes are then presented and discussed. The analysis reveals that factors such as the Annual Average Daily Traffic (AADT), the presence of turning lanes, and the number of driveways have a positive association with each type of crash, while the median width and the presence of lighting are negatively associated with crashes. The model covariates are related to crash outcome in different ways, suggesting that crash outcomes are associated with different pre-crash conditions.

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In 1984, the International Agency for Research on Cancer determined that working in the primary aluminium production process was associated with exposure to certain polycyclic aromatic hydrocarbons (PAHs) that are probably carcinogenic to humans. Key sources of PAH exposure within the occupational environment of a prebake aluminium smelter are processes associated with use of coal-tar pitch. Despite the potential for exposure via inhalation, ingestion and dermal adsorption, to date occupational exposure limits exist only for airborne contaminants. This study, based at a prebake aluminium smelter in Queensland, Australia, compares exposures of workers who came in contact with PAHs from coal-tar pitch in the smelter’s anode plant (n = 69) and cell-reconstruction area (n = 28), and a non-production control group (n = 17). Literature relevant to PAH exposures in industry and methods of monitoring and assessing occupational hazards associated with these compounds are reviewed, and methods relevant to PAH exposure are discussed in the context of the study site. The study utilises air monitoring of PAHs to quantify exposure via the inhalation route and biological monitoring of 1-hydroxypyrene (1-OHP) in urine of workers to assess total body burden from all routes of entry. Exposures determined for similar exposure groups, sampled over three years, are compared with published occupational PAH exposure limits and/or guidelines. Results of paired personal air monitoring samples and samples collected for 1-OHP in urine monitoring do not correlate. Predictive ability of the benzene-soluble fraction (BSF) in personal air monitoring in relation to the 1-OHP levels in urine is poor (adjusted R2 < 1%) even after adjustment for potential confounders of smoking status and use of personal protective equipment. For static air BSF levels in the anode plant, the median was 0.023 mg/m3 (range 0.002–0.250), almost twice as high as in the cell-reconstruction area (median = 0.013 mg/m3, range 0.003–0.154). In contrast, median BSF personal exposure in the anode plant was 0.036 mg/m3 (range 0.003–0.563), significantly lower than the median measured in the reconstruction area (0.054 mg/m3, range 0.003–0.371) (p = 0.041). The observation that median 1-OHP levels in urine were significantly higher in the anode plant than in the reconstruction area (6.62 µmol/mol creatinine, range 0.09–33.44 and 0.17 µmol/mol creatinine, range 0.001–2.47, respectively) parallels the static air measurements of BSF rather than the personal air monitoring results (p < 0.001). Results of air measurements and biological monitoring show that tasks associated with paste mixing and anode forming in the forming area of the anode plant resulted in higher PAH exposure than tasks in the non-forming areas; median 1-OHP levels in urine from workers in the forming area (14.20 µmol/mol creatinine, range 2.02–33.44) were almost four times higher than those obtained from workers in the non-forming area (4.11 µmol/mol creatinine, range 0.09–26.99; p < 0.001). Results justify use of biological monitoring as an important adjunct to existing measures of PAH exposure in the aluminium industry. Although monitoring of 1-OHP in urine may not be an accurate measure of biological effect on an individual, it is a better indicator of total PAH exposure than BSF in air. In January 2005, interim study results prompted a plant management decision to modify control measures to reduce skin exposure. Comparison of 1-OHP in urine from workers pre- and post-modifications showed substantial downward trends. Exposure via the dermal route was identified as a contributor to overall dose. Reduction in 1-OHP urine concentrations achieved by reducing skin exposure demonstrate the importance of exposure via this alternative pathway. Finally, control measures are recommended to ameliorate risk associated with PAH exposure in the primary aluminium production process, and suggestions for future research include development of methods capable of more specifically monitoring carcinogenic constituents of PAH mixtures, such as benzo[a]pyrene.

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Machine vision represents a particularly attractive solution for sensing and detecting potential collision-course targets due to the relatively low cost, size, weight, and power requirements of the sensors involved. This paper describes the development of detection algorithms and the evaluation of a real-time flight ready hardware implementation of a vision-based collision detection system suitable for fixed-wing small/medium size UAS. In particular, this paper demonstrates the use of Hidden Markov filter to track and estimate the elevation (β) and bearing (α) of the target, compares several candidate graphic processing hardware choices, and proposes an image based visual servoing approach to achieve collision avoidance

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An algorithm based on the concept of combining Kalman filter and Least Error Square (LES) techniques is proposed in this paper. The algorithm is intended to estimate signal attributes like amplitude, frequency and phase angle in the online mode. This technique can be used in protection relays, digital AVRs, DGs, DSTATCOMs, FACTS and other power electronics applications. The Kalman filter is modified to operate on a fictitious input signal and provides precise estimation results insensitive to noise and other disturbances. At the same time, the LES system has been arranged to operate in critical transient cases to compensate the delay and inaccuracy identified because of the response of the standard Kalman filter. Practical considerations such as the effect of noise, higher order harmonics, and computational issues of the algorithm are considered and tested in the paper. Several computer simulations and a laboratory test are presented to highlight the usefulness of the proposed method. Simulation results show that the proposed technique can simultaneously estimate the signal attributes, even if it is highly distorted due to the presence of non-linear loads and noise.

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Knowledge of the accuracy of dose calculations in intensity-modulated radiotherapy of the head and neck is essential for clinical confidence in these highly conformal treatments. High dose gradients are frequently placed very close to critical structures, such as the spinal cord, and good coverage of complex shaped nodal target volumes is important for long term-local control. A phantom study is presented comparing the performance of standard clinical pencil-beam and collapsed-cone dose algorithms to Monte Carlo calculation and three-dimensional gel dosimetry measurement. All calculations and measurements are normalized to the median dose in the primary planning target volume, making this a purely relative study. The phantom simulates tissue, air and bone for a typical neck section and is treated using an inverse-planned 5-field IMRT treatment, similar in character to clinically used class solutions. Results indicate that the pencil-beam algorithm fails to correctly model the relative dose distribution surrounding the air cavity, leading to an overestimate of the target coverage. The collapsed-cone and Monte Carlo results are very similar, indicating that the clinical collapsed-cone algorithm is perfectly sufficient for routine clinical use. The gel measurement shows generally good agreement with the collapsed-cone and Monte Carlo calculated dose, particularly in the spinal cord dose and nodal target coverage, thus giving greater confidence in the use of this class solution.

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The phenomenon that married men earn higher average wages than unmarried men, the so-called marriage premium, is well known. However, the robustness of the marriage premium across the wage distribution and the underlying causes of the marriage premium deserve closer scrutiny. Focusing on the entire wage distribution and employing recently developed semi-nonparametric tests for quantile treatment effects, our findings cast doubt on the robustness of the premium. We find that the premium is explained by selection above the median, whereas a positive premium is obtained only at very low wages. We argue that the causal effect at low wages is probably attributable to employer discrimination.

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Safety interventions (e.g., median barriers, photo enforcement) and road features (e.g., median type and width) can influence crash severity, crash frequency, or both. Both dimensions—crash frequency and crash severity—are needed to obtain a full accounting of road safety. Extensive literature and common sense both dictate that crashes are not created equal, with fatalities costing society more than 1,000 times the cost of property damage crashes on average. Despite this glaring disparity, the profession has not unanimously embraced or successfully defended a nonarbitrary severity weighting approach for analyzing safety data and conducting safety analyses. It is argued here that the two dimensions (frequency and severity) are made available by intelligently and reliably weighting crash frequencies and converting all crashes to property-damage-only crash equivalents (PDOEs) by using comprehensive societal unit crash costs. This approach is analogous to calculating axle load equivalents in the prediction of pavement damage: for instance, a 40,000-lb truck causes 4,025 times more stress than does a 4,000-lb car and so simply counting axles is not sufficient. Calculating PDOEs using unit crash costs is the most defensible and nonarbitrary weighting scheme, allows for the simple incorporation of severity and frequency, and leads to crash models that are sensitive to factors that affect crash severity. Moreover, using PDOEs diminishes the errors introduced by underreporting of less severe crashes—an added benefit of the PDOE analysis approach. The method is illustrated with rural road segment data from South Korea (which in practice would develop PDOEs with Korean crash cost data).

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Many studies focused on the development of crash prediction models have resulted in aggregate crash prediction models to quantify the safety effects of geometric, traffic, and environmental factors on the expected number of total, fatal, injury, and/or property damage crashes at specific locations. Crash prediction models focused on predicting different crash types, however, have rarely been developed. Crash type models are useful for at least three reasons. The first is motivated by the need to identify sites that are high risk with respect to specific crash types but that may not be revealed through crash totals. Second, countermeasures are likely to affect only a subset of all crashes—usually called target crashes—and so examination of crash types will lead to improved ability to identify effective countermeasures. Finally, there is a priori reason to believe that different crash types (e.g., rear-end, angle, etc.) are associated with road geometry, the environment, and traffic variables in different ways and as a result justify the estimation of individual predictive models. The objectives of this paper are to (1) demonstrate that different crash types are associated to predictor variables in different ways (as theorized) and (2) show that estimation of crash type models may lead to greater insights regarding crash occurrence and countermeasure effectiveness. This paper first describes the estimation results of crash prediction models for angle, head-on, rear-end, sideswipe (same direction and opposite direction), and pedestrian-involved crash types. Serving as a basis for comparison, a crash prediction model is estimated for total crashes. Based on 837 motor vehicle crashes collected on two-lane rural intersections in the state of Georgia, six prediction models are estimated resulting in two Poisson (P) models and four NB (NB) models. The analysis reveals that factors such as the annual average daily traffic, the presence of turning lanes, and the number of driveways have a positive association with each type of crash, whereas median widths and the presence of lighting are negatively associated. For the best fitting models covariates are related to crash types in different ways, suggesting that crash types are associated with different precrash conditions and that modeling total crash frequency may not be helpful for identifying specific countermeasures.

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There are several noninvasive techniques for assessing the kinetics of tear film, but no comparative studies have been conducted to evaluate their efficacies. Our aim is to test and compare techniques based on high-speed videokeratoscopy (HSV), dynamic wavefront sensing (DWS), and lateral shearing interferometry (LSI). Algorithms are developed to estimate the tear film build-up time TBLD, and the average tear film surface quality in the stable phase of the interblink interval TFSQAv. Moderate but significant correlations are found between TBLD measured with LSI and DWS based on vertical coma (Pearson's r2=0.34, p<0.01) and higher order rms (r2=0.31, p<0.01), as well as between TFSQAv measured with LSI and HSV (r2=0.35, p<0.01), and between LSI and DWS based on the rms fit error (r2=0.40, p<0.01). No significant correlation is found between HSV and DWS. All three techniques estimate tear film build-up time to be below 2.5 sec, and they achieve a remarkably close median value of 0.7 sec. HSV appears to be the most precise method for measuring tear film surface quality. LSI appears to be the most sensitive method for analyzing tear film build-up.

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Cutaneous cholecalciferol synthesis has not been considered in making recommendations for vitamin D intake. Our objective was to model the effects of sun exposure, vitamin D intake, and skin reflectance (pigmentation) on serum 25-hydroxyvitamin D (25[OH]D) in young adults with a wide range of skin reflectance and sun exposure. Four cohorts of participants (n = 72 total) were studied for 7-8 wk in the fall, winter, spring, and summer in Davis, CA [38.5° N, 121.7° W, Elev. 49 ft (15 m)]. Skin reflectance was measured using a spectrophotometer, vitamin D intake using food records, and sun exposure using polysulfone dosimeter badges. A multiple regression model (R^sup 2^ = 0.55; P < 0.0001) was developed and used to predict the serum 25(OH)D concentration for participants with low [median for African ancestry (AA)] and high [median for European ancestry (EA)] skin reflectance and with low [20th percentile, ~20 min/d, ~18% body surface area (BSA) exposed] and high (80th percentile, ~90 min/d, ~35% BSA exposed) sun exposure, assuming an intake of 200 IU/d (5 ug/d). Predicted serum 25(OH)D concentrations for AA individuals with low and high sun exposure in the winter were 24 and 42 nmol/L and in the summer were 40 and 60 nmol/L. Corresponding values for EA individuals were 35 and 60 nmol/L in the winter and in the summer were 58 and 85 nmol/L. To achieve 25(OH)D ≥75 nmol/L, we estimate that EA individuals with high sun exposure need 1300 IU/d vitamin D intake in the winter and AA individuals with low sun exposure need 2100-3100 IU/d year-round.

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Adversity has the effect of eliciting talents, which, in prosperous circumstances, would have lain dormant. Horace - Roman lyric poet and satirist 65BC – 8 BC This quotation from Horace could well be the chorus to a medley of songs sung by people who face extraordinary adversity and have gained emotional resilience through music making. In this chapter we present three composition ventures that are stories or verses in a new song and whose chorus summarises the nature of the resilience factors present in the narratives. We are aware that words on a page like this can have the effect of filtering out the engaging nature of musical experience and reduce music to a critique or an evaluation of its aesthetic value. This disjuncture between language and the ephemeral, embodied experience is a problem for those who use these creative processes in therapeutic and salutogenic ways (Antonovsky, 1996) for public health. The notion of salutogenic health, put simply, delineates it from therapy in that the processes focus upon wellness rather than therapy. Whilst we include evidence from the fields of community music therapy (Pavlicevic, 2004; Leitschuh et al., 1991), neuroscience (Bittman et al., 2001) and community music (Bartleet et al., 2009) the framework for a salutogenic health outcome in community music is one which seeks to employ music practices and the qualities of music making that provide positive health benefit to communities –to enhance health and well being rather than the “treatment” of disorders. It is essentially a holistic and interdisciplinary study. Therapy and salutogenic health are not mutually exclusive as both depend upon the qualities of music experience to affect change. Collecting, analysing and presenting evidence of change in human behaviour that can be directly attributed to creative music making is a problem of evaluation.