We describe a calculator for the decision threshold and detection limit, a tool intended for gamma-ray spectrometry. The tool is an Excel file composed of several sheets, containing procedures for ...calculating the decision thresholds and detection limits under various assumptions. It is publicly available at https://f2.ijs.si/en/laboratories/lmr/calculator. The input data for the calculations are peak-analysis results, usually listed in peak-analysis reports (peak energies, FWHMs, peak areas and their uncertainties). Besides these quantities, data on the total number of counts in the peak region and the numbers of counts in the peaked background (if present) and their uncertainties are needed for the calculation. The calculation procedures implemented in the Excel sheets make it possible to calculate the decision thresholds and detection limits from peak data obtained using the region-of-interest method and the least-squares method. With the least-squares method it is possible to calculate the decision thresholds and detection limits for both isolated and overlapping peaks. An additional sheet enables the calculation of decision thresholds and detection limits for multi-gamma-ray emitters. We show that, in general, the indications corresponding to the decision threshold depend on the observed value of the indication and that those calculated with the region-of-interest method do not depend on it, except through the width of the peak region.
•The dependencies of the characteristic limits on the input parameters are discussed.•The uncertainty of the continuous background determines the characteristic limits.•In case of the ROI method they depend on the peak area only through the peak width.•In case of the LSQ method they depend on the peak area through its uncertainty.•Overlapping peaks share common background what increases the characteristic limits.
A metrologically consistent procedure for assessing the detection limits of activity measurements for gamma-ray emitters with high-resolution spectrometers using the LSQ method is described and ...tested. As the input to the assessment, besides the measured contents of the spectral channels, the results of the peak analysis, i.e., the indication and its uncertainty, are used. The unfolding of the spectral region of interest into its components corresponding to the peak representing the indication and its background allows us to take into account the uncertainty budget, describing the uncertainty of the indication and the shape of the corresponding peak, making possible to include these sources of uncertainty in the calculation of the decision threshold. To assess the detection limit, the variance of the indication is calculated as a function of the indication itself, while considering the relative uncertainty of the conversion factor. The variance of the indication observed is approximated by a polynomial of the second order of the indication, thus making it possible to calculate the detection limit analytically. The method was tested on measured spectra using the empirically determined spectral shape of the peak representing the indication. It was shown how the empirically determined shape of an isolated and expressive peak close to the peak representing the indication can be used in the calculation of the decision threshold and how the presence of a peak overlapping with the peak representing the indication affects the decision threshold and the detection limit. It is explained that besides the counting statistics, the sources of uncertainty due to the shape of the peak representing indication also contribute to the decision threshold. However, to the increase of the detection limit over the decision threshold, besides the counting statistic, only the uncertainty of the conversion factor contributes. It is shown that in the presence of the indication, the decision threshold and the detection limit can be used to quantify the comparison between the observed value and the true value of the measurand with a predetermined quantity value in terms of the probabilities of making errors of the first and second kind. The application of the decision thresholds and detection limits to a conformity assessment is proposed.
•The calculation of the detection limit is generalized to any measured quantity value.•The peak analysis results are used to assess the decision threshold and the detection limit.•The LSQ method is used to calculate the uncertainty to assess the decision threshold.•The indication to assess the detection limit is calculated analytically.•The decision threshold and the detection limit increase with the indication.
The method of calculation of the decision threshold with the Least Squares Method, described in the standard ISO 11929, is presented for the case when the sources of peaked background contribute to ...the peak holding the indication. The decision threshold is calculated from spectral data corresponding to the indication zero; therefore, the observed indication must be removed from the spectrum. When the peaked background is present, the indication completely overlaps with the peaked background, so it can't be unfolded directly. Therefore, two steps are needed in the calculation: the unfolding of the peak, housing the indication, from the continuous background and the possible overlapping peaks, and separating of the indication from the peaked background using the background data obtained from separate calculations and measurements. In this article it is shown that the method of least squares is flexible enough to accommodate all sources of uncertainty into the uncertainty matrix of input quantities. Its derivation is presented in detail and the calculation of the indication corresponding to the decision threshold is described. As a proof of the concept an example of calculating the number of counts corresponding to the decision threshold as a function of the indication is presented. The method of calculation and the results of the calculation are briefly discussed.
•The decision threshold is calculated with LSQ method.•The uncertainty matrix is constructed for the peaked background.•The design matrix comprises the indication and the total background.•An example of the calculation is presented.•It is shown that the decision threshold increases with the indication.
The count rate in the peak of a gamma-ray spectrum at 2223 keV was measured over a period of 25 years. The peak is produced by neutron capture on hydrogen, a constituent of the spectrometer's shield. ...Since the neutrons are produced by cosmic rays, the count rate in the peak is correlated with the solar activity via the interaction between the solar wind and the cosmic rays. The correlation between the total daily number of sunspots, as a measure of the solar activity, and the count rate in the peak was investigated as a function of the time shift between the time dependence of the count rate in the peak and the time dependence of the total daily number of sunspots. Variations of the correlation coefficient as a function of the shift are discussed in terms of phenomena occurring on the surface of the Sun. The variations indicate a long-term correlation, corresponding to the 11-year solar cycle, and a short-term correlation, corresponding to the sunspots.
•The solar activity and the background of a gamma-ray spectrometer were correlated.•The total daily number of sunspots and the peak count rate at 2223 keV were examined.•The long-term correlation corresponding to the 11-year solar cycle was observed.•A short-term correlation with the number of sunspots was detected as well.•The speed of the solar wind was assessed from the time dependence of the correlation.
We show that in gamma-ray spectrometric measurements the decision threshold depends on the observed value of the measurand. Since the decision threshold is intended to describe the sensitivity of the ...measurement, this dependence restricts its application to measurements where the indication is not expressive. To extend the direct applicability of the decision threshold to expressive indications in gamma-ray spectrometric measurements, where mainly the Region-of-Interest method is used to evaluate the isolated peaks, a recalculation of the decision thresholds to the peak widths corresponding to the inexpressive peaks is proposed. For the Least-Squares method, where the dependence of the decision threshold on the value of the measurand originates in the non-zero value of the correlation coefficient between the indication and the background, no recalculation is possible. Instead, we can only make a drastic simplification of the calculation, resulting in underestimated decision thresholds.
Time Windows Based Dynamic Routing in Multi-AGV Systems Smolic-Rocak, N.; Bogdan, S.; Kovacic, Z. ...
IEEE transactions on automation science and engineering,
2010-Jan., 2010, 2010-01-00, 20100101, Letnik:
7, Številka:
1
Journal Article
This paper presents a dynamic routing method for supervisory control of multiple automated guided vehicles (AGVs) that are traveling within a layout of a given warehouse. In dynamic routing a ...calculated path particularly depends on the number of currently active AGVs' missions and their priorities. In order to solve the shortest path problem dynamically, the proposed routing method uses time windows in a vector form. For each mission requested by the supervisor, predefined candidate paths are checked if they are feasible. The feasibility of a particular path is evaluated by insertion of appropriate time windows and by performing the windows overlapping tests. The use of time windows makes the algorithm apt for other scheduling and routing problems. Presented simulation results demonstrate efficiency of the proposed dynamic routing. The proposed method has been successfully implemented in the industrial environment in a form of a multiple AGV control system.
An account is given on the value of the correlation coefficient between the number of counts in a peak in a gamma-ray spectrum and the number of counts in the background, where the peak resides. It ...is supposed that the decomposition of the spectrum in the peak and in the background is performed by using the Least Squares method. The values of the correlation coefficient were determined empirically from measurements of gamma-ray spectra under repeatable conditions and from analyses of these spectra using four different kinds of peak-analysis software. These values were compared to the a-priori values, obtained from the Least Squares method.
•The number of counts in the peak and the continuous background are correlated.•The value of the correlation coefficient is empirically determined.•The value depends on the width of the fitted region.•In case of short widths of the fitted region it tends to unity.
Deciding on “termination of resuscitation” (TOR) is a dilemma for any physician facing cardiac arrest. Due to the lack of evidence-based criteria and scarcity of the existing guidelines, crucial ...arbitration to interrupt resuscitation remains at the practitioner’s discretion.
Evaluate with a quantitative method the existence of a physician internal bias to terminate resuscitation.
We extracted data concerning OHCAs managed between January 2013 and September 2021 from the RéAC registry. We conducted a statistical analysis using generalized linear mixed models to model the binary TOR decision. Utstein data were used as fixed effect terms and a random effect term to model physicians personal bias towards TOR.
5,144 OHCAs involving 173 physicians were included. The cohort’s average age was 69 (SD 18) and was composed of 62% of women. Median no-flow and low-flow times were respectively 6 (IQR 0,12) and 18 (IQR 10,26) minutes. Our analysis showed a significant (p < 0.001) physician effect on TOR decision.
Odds ratio for the “doctor effect” was 2.48 2.13–2.94 for a doctor one SD above the mean, lower than that of dependency for activities of daily living (41.18 24.69–65.50), an age of more than 85 years (38.60 28.67–51.08), but higher than that of oncologic, cardiovascular, respiratory disease or no-flow duration between 10 to 20 minutes (1.60 1.26–2.00).
We demonstrate the existence of individual physician biases in their decision about TOR. The impact of this bias is greater than that of a no-flow duration lasting ten to twenty minutes. Our results plead in favor developing tools and guidelines to guide physicians in their decision.
Invasive infections by fungal pathogens cause more deaths than malaria worldwide. We found the ergoline compound NGx04 in an antifungal screen, with selectivity over mammalian cells. High-resolution ...chemogenomics identified the lipid transfer protein Sec14p as the target of NGx04 and compound-resistant mutations in Sec14p define compound-target interactions in the substrate binding pocket of the protein. Beyond its essential lipid transfer function in a variety of pathogenic fungi, Sec14p is also involved in secretion of virulence determinants essential for the pathogenicity of fungi such as Cryptococcus neoformans, making Sec14p an attractive antifungal target. Consistent with this dual function, we demonstrate that NGx04 inhibits the growth of two clinical isolates of C. neoformans and that NGx04-related compounds have equal and even higher potency against C. neoformans. Furthermore NGx04 analogues showed fungicidal activity against a fluconazole resistant C. neoformans strain. In summary, we present genetic evidence that NGx04 inhibits fungal Sec14p and initial data supporting NGx04 as a novel antifungal starting point.
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