Heuristic methods for the analysis of a queuing system describing emergency medical service deployed along a highway

Consideration is given to a queueing model that describes the deployment of emergency medical service along a highway. Two heuristic methods are proposed for the approximate evaluation of stationary loss probability and utilization of ambulance cars. The high accuracy of these methods is demonstrated by several examples. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 3, pp. 84–99, May–June 2006.     

一种高精度超声测距方法的研究

本文介绍了一种基于超声波循环反射测量原理的高精度超声测距方法 ,并给出了以单片机为核心的测距系统的组成 .本测量法克服了多次反射法中对回波脉冲个数的限制 ,经温度补偿后测量精度得到了明显改善 .     

Automation for High-throughput Identification and Picking of GFP Expressing Colonies

Green fluorescent protein (GFP) has many applications as a marker in living cells, and has become widely used as a reporter gene in microbial, plant and animal cells. Screening microbial colonies for GFP expression enables various types of assays (e.g. for secretory mutations). However, this is laborious, non-quantitative and potentially hazardous to the operator (due to UV illumination) when performed manually. In order to address this the GloPix robot was developed. The imaging system discriminates between colonies based on the level of fluorescence activity and the picking function automatically transfers cells to microplate wells. Measuring fluorescent activity allows quantitation of fluorescent tag concentration/expression.     

An improved approach to application-specific power electronicseducation-switch characterization and modeling

An integrated power electronics curriculum has been implemented in the Department of Electrical and Computer Engineering at the University of Illinois, Chicago. This paper describes the development of a set of hands-on laboratory experiments to accompany classroom lectures. Content is based on switching converter topologies and commercial power semiconductor devices. Unlike most experiments, which focus on circuit- or control-level characteristics, our approach emphasizes the circuit-device-load interactions. The concept presented is innovative in that it creates a 3×3 matrix of experiment variation-devices, circuits-control, and machines-loads-with one set of hardware. The lab development is ongoing with future experiments to address three-phase converters and motor control applications. Experiment content is described, as well as the means by which the material has been integrated within the course sequence. Lab station construction and safety issues are also addressed. The experiments require hands-on measurement and circuit connection and complement the established course elements of theory and computer-based circuit modeling. Laboratory experiments and computer simulations collectively provide quantitative evidence of mixed circuit and device optimization     

Variability of Stress in Alumina Corrosion Layers Formed in Thermal-Barrier Coatings

Residual stress distributions have been measured and mapped usingphotoluminescence, piezo spectroscopy in thermally grown alumina oxides(TGO) formed on platinum-aluminide bond coats with thermal-barrier coatings(TBC) of thickness 0, 3, and 200 m. When there is a 3-m TBC or noTBC, the residual stress varies substantially with position and the meanstress is much lower than expected from simple thermoelastic, plane-stressanalysis. This is partly explained by the stress being relaxed by surfaceroughness, but stress mapping indicates that local fracture hasoccurred. The stress in the TGO formed under 200 m TBCs appear muchmore uniform and the mean value is approximately equal to the estimatedthermoelastic plane stress. This could be due to the extra constraintimposed by the TBC. The luminescence line width is much greater forspecimens with 200-m TBC and is too large to be explained by varyingmacroscopic stresses due to interface roughness. The effects of oxidationtime and reactive-element additions to the substrate at the level of30 ppm, on the residual stress, are relatively minor over the rangesexplored in these experiments.     

Pacing strategies during a cycling time trial with simulated headwinds and tailwinds

The aims of this study were to examine the effects of one self-selected and two enforced pacing strategies (constant and variable power output) on cycling performance during a time trial in which variable wind conditions were simulated. Seven male cyclists rode their own bicycles on a Computrainer cycle ergometer, which was programmed to simulate a 16.1 km time trial on a flat course with a 8.05 km h(-1) headwind in the first half of the race and a 8.05 km h(-1) tailwind in the second half of the race. Subjects rode an initial time trial (ITT) at a self-selected pace to the best of their ability. The mean power output from this trial was then used to calculate the pacing strategies in the subsequent two trials: Constant (C)--riders rode the whole time trial at this mean power output; and Variable (V)--riders rode the first headwind section at a power output 5% higher than the mean and then reduced the power output in the last 8.05 km so that the mean power output was the same as in the initial time trial and in trial C. Power output, heart rate and ratings of perceived exertion (RPE) were recorded every 1.61 km. Finish times, 8.05 km split times and blood lactate levels, pre- and post-exercise (to calculate delta lactate), were also recorded in each trial. In the ITT, riders chose a mean +/- SD power output of 267 +/- 56 W in the first 1.61 km which was 14% higher than the overall race mean +/- SD of 235 +/- 41 W. Power outputs then dropped to below the race mean after the first few kilometres. Mean +/- SD finish times in the C and V time trials were 1661 +/- 130 and 1659 +/- 135 s, respectively. These were significantly faster than the 1671 +/- 131 s recorded in the initial time trial (p = 0.009), even though overall mean power outputs were similar (234 - 235 W) between all trials (p = 0.26). Overall mean RPE and delta lactate were lowest in trial V (p < 0.05). Perceived exertion showed a pacing strategy by race split interaction (p < 0.0001), but it was not increased significantly during the first 8.05 km of the V condition when power outputs were 5% higher than in condition C. Heart rate showed no main effect of pacing strategy (p = 0.80) and the interaction between strategy and race split did not reach statistical significance (p = 0.07). These results suggest that in a 16.1 km time trial with equal 8.05 km headwind and tailwind sections, riders habitually set off too fast in the first few kilometres and will benefit (10 s improvement) from a constant pacing strategy and, to a slightly greater degree (12 s improvement), from a variable (5% +/- mean) pacing strategy in line with the variations in wind direction during the race. Riders should choose a constant power when external conditions are constant, but when there are hilly or variable wind sections in the race, a variable power strategy should be planned. This strategy would be best monitored with 'power-measuring devices' rather than heart rate or subjective feelings as the sensitivity of these variables to small but meaningful changes in power during a race is low.     

Statistical methods for assessing measurement error (reliability) in variables relevant to sports medicine

Minimal measurement error (reliability) during the collection of interval- and ratio-type data is critically important to sports medicine research. The main components of measurement error are systematic bias (e.g. general learning or fatigue effects on the tests) and random error due to biological or mechanical variation. Both error components should be meaningfully quantified for the sports physician to relate the described error to judgements regarding 'analytical goals' (the requirements of the measurement tool for effective practical use) rather than the statistical significance of any reliability indicators. Methods based on correlation coefficients and regression provide an indication of 'relative reliability'. Since these methods are highly influenced by the range of measured values, researchers should be cautious in: (i) concluding acceptable relative reliability even if a correlation is above 0.9; (ii) extrapolating the results of a test-retest correlation to a new sample of individuals involved in an experiment; and (iii) comparing test-retest correlations between different reliability studies. Methods used to describe 'absolute reliability' include the standard error of measurements (SEM), coefficient of variation (CV) and limits of agreement (LOA). These statistics are more appropriate for comparing reliability between different measurement tools in different studies. They can be used in multiple retest studies from ANOVA procedures, help predict the magnitude of a 'real' change in individual athletes and be employed to estimate statistical power for a repeated-measures experiment. These methods vary considerably in the way they are calculated and their use also assumes the presence (CV) or absence (SEM) of heteroscedasticity. Most methods of calculating SEM and CV represent approximately 68% of the error that is actually present in the repeated measurements for the 'average' individual in the sample. LOA represent the test-retest differences for 95% of a population. The associated Bland-Altman plot shows the measurement error schematically and helps to identify the presence of heteroscedasticity. If there is evidence of heteroscedasticity or non-normality, one should logarithmically transform the data and quote the bias and random error as ratios. This allows simple comparisons of reliability across different measurement tools. It is recommended that sports clinicians and researchers should cite and interpret a number of statistical methods for assessing reliability. We encourage the inclusion of the LOA method, especially the exploration of heteroscedasticity that is inherent in this analysis. We also stress the importance of relating the results of any reliability statistic to 'analytical goals' in sports medicine.     

Head trauma: CT scan interpretation by radiology residents versus staff radiologists

The determination of diagnostic features in recorded heart sounds was investigated with Carpentier-Edwards (CE) bioprosthetic valves. Morphological features, extracted using the Choi-Williams distribution, achieved between 96 and 61% correct classification. The time-scale wavelet-transform feature set achieved 100% correct classification with native valve populations, and 87% with the CE replacements.