The 2016 Revision of ISO 1 – Standard Reference Temperature for the Specification of Geometrical and Dimensional Properties

This paper discusses the changes in the 2016 (third edition) of International Standard ISO 1. While the value of the standard reference temperature remains unchanged at 20 °C, the important definitions for the “reference temperature” and “standard reference temperature,” absent in prior editions, are now defined, with the latter exclusively reserved for the assignment of the internationally agreed upon temperature of 20 °C. The scope of the revised Standard has been carefully refined and made more explicit. This, together with other clarifications and improvements, has eliminated the ambiguities associated with specifications at non-standard reference temperatures and allows, if needed, different reference temperatures to be associated with different properties of a workpiece. The relationship between ISO 1 and dimensional measurements is also discussed and clarified. In this paper, we discuss the motivation for these changes and present several issues debated during the revision process for the benefit of future standards committees that might study this topic

Semigroups of distributions with linear Jacobi parameters

We show that a convolution semigroup of measures has Jacobi parameters polynomial in the convolution parameter $t$ if and only if the measures come from the Meixner class. Moreover, we prove the parallel result, in a more explicit way, for the free convolution and the free Meixner class. We then construct the class of measures satisfying the same property for the two-state free convolution. This class of two-state free convolution semigroups has not been considered explicitly before. We show that it also has Meixner-type properties. Specifically, it contains the analogs of the normal, Poisson, and binomial distributions, has a Laha-Lukacs-type characterization, and is related to the $q=0$ case of quadratic harnesses.Comment: v3: the article is merged back together with arXiv:1003.4025. A significant revision following suggestions by the referee. 2 pdf figure

Quantification of silver nanoparticle uptake and distribution within individual human macrophages by FIB/SEM slice and view

Background Quantification of nanoparticle (NP) uptake in cells or tissues is very important for safety assessment. Often, electron microscopy based approaches are used for this purpose, which allow imaging at very high resolution. However, precise quantification of NP numbers in cells and tissues remains challenging. The aim of this study was to present a novel approach, that combines precise quantification of NPs in individual cells together with high resolution imaging of their intracellular distribution based on focused ion beam/ scanning electron microscopy (FIB/SEM) slice and view approaches. Results We quantified cellular uptake of 75 nm diameter citrate stabilized silver NPs (Ag 75 Cit) into an individual human macrophage derived from monocytic THP-1 cells using a FIB/SEM slice and view approach. Cells were treated with 10 μg/ml for 24 h. We investigated a single cell and found in total 3138 ± 722 silver NPs inside this cell. Most of the silver NPs were located in large agglomerates, only a few were found in clusters of fewer than five NPs. Furthermore, we cross-checked our results by using inductively coupled plasma mass spectrometry and could confirm the FIB/SEM results. Conclusions Our approach based on FIB/SEM slice and view is currently the only one that allows the quantification of the absolute dose of silver NPs in individual cells and at the same time to assess their intracellular distribution at high resolution. We therefore propose to use FIB/SEM slice and view to systematically analyse the cellular uptake of various NPs as a function of size, concentration and incubation time.TU Berlin, Open-Access-Mittel - 201

The implementation of the Gaussian filter for dimensional metrology: basics, algorithms and C code

The Gaussian filter is set to remain of enduring importance in metrology. This publication deals with the digital implementation of the Gaussian filter and the estimation of the occurring errors. Guidance is given on how to keep these errors as small as possible. In addition algorithms for the implementation of the Gaussian filter are given