Modelling of networked measuring systems -- from white-box models to data based approaches

Mathematical modelling is at the core of metrology as it transforms raw measured data into useful measurement results. A model captures the relationship between the measurand and all relevant quantities on which the measurand depends, and is used to design measuring systems, analyse measured data, make inferences and predictions, and is the basis for evaluating measurement uncertainties. Traditional modelling approaches are typically analytical, for example, based on principles of physics. But with the increasing use of digital technologies, large sensor networks and powerful computing hardware, these traditional approaches are being replaced more and more by data-driven methods. This paradigm shift holds true in particular for the digital future of measurement in all spheres of our lives and the environment, where data provided by large and complex interconnected systems of sensors are to be analysed. Additionally, there is a requirement for existing guidelines and standards in metrology to take the paradigm shift into account. In this paper we lay the foundation for the development from traditional to data-driven modelling approaches. We identify key aspects from traditional modelling approaches and discuss their transformation to data-driven modelling

Implementing systems medicine within healthcare

Comentari editorialThe cause of a complex disease cannot be pinpointed to a single origin; rather, a highly complex network of many factors that interact on different levels over time and space is disturbed. This complexity requires novel approaches to diagnosis, treatment, and prevention. To foster the necessary shift to a pro-active systems medicine, proof-of-concept studies are needed. Here, we highlight several systems approaches that have been shown to work within the field of respiratory medicine, and we propose the next steps for broader implementation

Probing spin helical surfaces states in topological HgTe nanowires

Nanowires with helical surface states represent key prerequisites for observing and exploiting phase-coherent topological conductance phenomena, such as spin-momentum locked quantum transport or topological superconductivity. We demonstrate in a joint experimental and theoretical study that gated nanowires fabricated from high-mobility strained HgTe, known as a bulk topological insulator, indeed preserve the topological nature of the surface states, that moreover extend phase-coherently across the entire wire geometry. The phase-coherence lengths are enhanced up to 5μm when tuning the wires into the bulk gap, so as to single out topological transport. The nanowires exhibit distinct conductance oscillations, both as a function of the flux due to an axial magnetic field and of a gate voltage. The observed h/e-periodic Aharonov-Bohm-type modulations indicate surface-mediated quasiballistic transport. Furthermore, an in-depth analysis of the scaling of the observed gate-dependent conductance oscillations reveals the topological nature of these surface states. To this end we combined numerical tight-binding calculations of the quantum magnetoconductance with simulations of the electrostatics, accounting for the gate-induced inhomogeneous charge carrier densities around the wires. We find that helical transport prevails even for strongly inhomogeneous gating and is governed by flux-sensitive high-angular momentum surface states that extend around the entire wire circumference

“A very orderly retreat”: Democratic transition in East Germany, 1989-90

East Germany's 1989-90 democratisation is among the best known of East European transitions, but does not lend itself to comparative analysis, due to the singular way in which political reform and democratic consolidation were subsumed by Germany's unification process. Yet aspects of East Germany's democratisation have proved amenable to comparative approaches. This article reviews the comparative literature that refers to East Germany, and finds a schism between those who designate East Germany's transition “regime collapse” and others who contend that it exemplifies “transition through extrication”. It inquires into the merits of each position and finds in favour of the latter. Drawing on primary and secondary literature, as well as archival and interview sources, it portrays a communist elite that was, to a large extent, prepared to adapt to changing circumstances and capable of learning from “reference states” such as Poland. Although East Germany was the Soviet state in which the positions of existing elites were most threatened by democratic transition, here too a surprising number succeeded in maintaining their position while filing across the bridge to market society. A concluding section outlines the alchemy through which their bureaucratic power was transmuted into property and influence in the “new Germany”

Maternal education and cognitive development in 15 European very-preterm birth cohorts from the RECAP Preterm platform

Background: Studies are sparse and inconclusive about the association between maternal education and cognitive development among children born very preterm (VPT). Although this association is well established in the general population, questions remain about its magnitude among children born VPT whose risks of medical and developmental complications are high. We investigated the association of maternal education with cognitive outcomes in European VPT birth cohorts. Methods: We used harmonized aggregated data from 15 population-based cohorts of children born at = 37 weeks of GA) were available in eight cohorts. Maternal education was classified as: low (primary/lower secondary); medium (upper secondary/short tertiary); high (bachelor's/higher). Pooled standardized mean differences (SMDs) in cognitive scores were estimated (reference: high educational level) for children assessed at ages 2-3, 4-7 and 8-15 years. Results: The study included 10 145 VPT children from 12 cohorts at 2-3 years, 8829 from 12 cohorts at 4-7 years and 1865 children from 6 cohorts at 8-15 years. Children whose mothers had low, compared with high, educational attainment scored lower on cognitive measures [pooled unadjusted SMDs: 2-3 years = -0.32 (95% confidence intervals: -0.43 to -0.21); 4-7 years = -0.57 (-0.67; -0.47); 8-15 years = -0.54 (-0.72; -0.37)]. Analyses by GA subgroups (= 27 weeks) in children without severe neonatal morbidity and term controls yielded similar results. Conclusions: Across diverse settings and regardless of the degree of prematurity, low maternal education was associated with lower cognition.Peer reviewe