Bivariate confidence probability plots as a method to test the accuracy and variability of microbiological measures

IntroductionIn an interlaboratory calibration analysis to validate a methodology that will be proposed as a European standard for domestic laundry disinfection, tests were carried out to detect if there are different behaviors in the measurements regarding accuracies and variabilities. Interlaboratory tests using different doses of disinfectant and microorganisms were carried out. ISO 5725-2 and ISO 13528 form the basis of validations of quantitative methods, providing validation specifications for interlaboratory studies. However, a need for a simple graphical method to detect interlaboratory differences in accuracy and variability was observed.ObjectivesThe general goal of this work is to present a new exploratory methodology, graphical and easy to interpret, that can determine the accuracy and variability (precision) of a variable, and compare it to the methodology applied in ISO 5725-2 and ISO 13528.MethodsWe used confidence probability plots of the multivariate Student’s t-distribution to observe the accuracy and variability of microbiological measures carried out by different laboratories during a ring trial exercise. A function in R was built for this purpose: Miriam.analysis.ellipse(Y, factor_a, eel.plot = “ t-Student”). The different observations of accuracy and variability are represented in the ellipses. If any of the points are outside the ellipse with 95% confidence, we can assume a deviation in accuracy and / or variability.ResultsTwo examples are provided with real microbiological data (logarithmic unit reductions (LR) for Pseudomonas aeruginosa, Escherichia coli, Staphilococcus aureus, Enterococcus hirae, Candida albicans and microbial counts in water (WW)). The proposed new method allowed us to detect possible deviations in the WWMEA variable and we believe it has future application for the rapid control of microbiological measures.

Island-arc augite-bytownite-labradoritic dacites of the Kara-Dag, Crimea

Island-arc calc-alcaline dacites (66,7% of SiO2, 3,4% of Na2O, 1,9% of K2O) compose a subvolcanic body among tuffs, andesites and trachyandesites in the east of the Kara-Dag volcanic massif of the Rocky Crimea. The unique features of dacites is abundance of plagioclase phenocrysts (the central zone is bytownite Ca75–72Na24–27K0,5–1; the intermediate and external zones is labradorite Ca67–52Na32–47K1) and low-Ti augite (augite Ca43–41Mg41–38Fe16–21 with 1–2% of Al2O3 composes the core; the intermediate and external zones is augite Ca43–41Mg41–38Fe16–21 with 1–2% Al2O3). Titanomagnetite, ilmenite and apatite form intergrowths with augite. Lowmagnesian titanomagnetite is enriched with manganese (up to 4,5 wt.% MnO) and zinc (up to 1,6% of ZnO); it contains from 39 to 28% of ulvospinel minal. Ilmenite, poor in Mn, contains from 10 to 25 mol.% of hematite minal that demonstrates the crystallization with the raised fO2, in other words, the water saturation of fusion. Apatite is poor in Sr, Ce and S. The trend with standard accumulation of fluorine from chlorine-hydroxyl-fluorapatite up to fluorapatite is shown. Plagioclase microlites — labradorite Ca52–50Na46–48K2–3 composes the cementing mass of rhyolitic composition (77,3% SiO2, 3,3% Na2O, 2,5% K2O) with quartz, small amounts of andesine Ca49–46Na49–52K2–3, oligoclase Ca27Na68K5 and anorthoclase in interstitions. The speciality of the described dacites is plagioclase wealth in anorthite component, what is typical for island-arc volcanites. The crystallization temperature of augite is ~1050–950 ᵒC. The crystallization temperature of associated titanomagnetite and ilmenite of early origin is ~900 ᵒC, fO2 exceed by 1 logarithmic unit the QFM buffer, their late origin crystallization temperature is ~880 ᵒC, fO2 exceed by 2 logarithmic units the QFM buffer.

Cycling injuries in London: the impact of motor vehicle and cycle volumes, and road characteristics including speed limits

Cycling injury risk is an important topic, but few studies explore cycling risk in relation to exposure. This is largely because of a lack of exposure data, in other words how much cycling is done at different locations. This paper helps to fill this gap. It reports a case-control study of cycling injuries in London in 2013-2014, using modelled cyclist flow data alongside datasets covering some characteristics of the London route network. A multilevel binary logistic regression model is used to investigate factors associated with injury risk, comparing injury sites with control sites selected using the modelled flow data. Findings provide support for ‘safety in numbers’: for each increase of a natural logarithmic unit (2.71828) in cycling flows, an 18% decrease in injury odds was found. Conversely, increased motor traffic volume is associated with higher odds of cycling injury, with one logarithmic unit increase associated with a 31% increase in injury odds. Twenty-mile per hour compared with 30mph speed limits were associated with 21% lower injury odds. Residential streets were associated with reduced injury odds, and junctions with substantially higher injury odds. Bus lanes do not affect injury odds once other factors are controlled for. These data suggest that speed limits of 20mph may reduce cycling injury risk, as may motor traffic reduction. Further, building cycle routes that generate new cycle trips should generate ‘safety in numbers’ benefits.

The Unit Symbol for the Logarithmic Scale of Radar Reflectivity Factors

This note argues that the proper symbol for the logarithmic unit of radar reflectivity factor is dBz. The basis for this contention lies in both customary engineering practice and the international standard for unit symbols.

Interactions leading to colour opponency in ganglion cells of the turtle retina

In the turtle retina, colour-dependent photoresponses could be recorded intracellularly from ganglion cells receiving only bipolar cell input. Thus, the mechanism for colour discrimination by these ganglion cells (type A) is contained in the outer plexiform layer of the retina and depends on interaction between horizontal and cone cells. Ganglion cells receiving an additional amacrine input (type B) are not influenced by colour, and have about 0.7 logarithmic unit lower absolute sensitivity to peak wavelength than have type A ganglion cells.

Calcium-binding constants of trypsin and trypsinogen. A reassessment

The Ca2+-binding constants for trypsin and trypsinogen have been reassessed by using enzyme that has been purified by affinity chromatography and measuring the distribution of 45Ca2+ between the protein and a cation exchanger. The pKCa2+ value of 4.5 for the high-affinity site on trypsin was 1 logarithmic unit greater than that previously reported.