-Christoph Markschies: Geleitwort -Ulrich Päßler: Christian Gottfried Ehrenberg: Lebensbilder eines Naturforschers -Mathias Grote: „Aus dem Kleinen bauen sich die Welten“ – Christian Gottfried Ehrenbergs ökologische Mikrobiologie avant la lettre -Anne Greenwood MacKinney: Die Inszenierung naturforschender Gelehrsamkeit beim Sammeln: Christian Gottfried Ehrenbergs und Wilhelm Hemprichs nordafrikanische Forschungsreise (1820 – 1825) -Ulrich Päßler: Reisen im Nahen Osten. Zeichnungen -Ulrich Päßler: Christian Gottfried Ehrenberg und die Biogeographie: Die russisch-sibirische Reise mit Alexander von Humboldt (1829) -Ulrich Päßler: Russisch-Sibirische Reise. Zeichnungen -Wolf-Henning Kusber, Regine Jahn: Christian Gottfried Ehrenbergs Zeichnungen: Eine frühe wissenschaftliche Dokumentation mikroskopischer Organismen -Ferdinand Damaschun: Christian Gottfried Ehrenberg und die Entwicklung der Mikroskop-Technik im 19. Jahrhundert -Ulrich Päßler: Die Reise ins Kleinste der Natur. Zeichnungen -Katrin Böhme: Das große Ganze: Christian Gottfried Ehrenberg und die Gesellschaft Naturforschender Freunde zu Berlin

Currently, a transformation of our technical world into a networked technical world where besides the embedded systems with their interaction with the physical world the interconnection of these nodes in the cyber world becomes a reality can be observed. In parallel nowadays there is a strong trend to employ artificial intelligence techniques and in particular machine learning to make software behave smart. Often cyber-physical systems must be self-adaptive at the level of the individual systems to operate as elements in open, dynamic, and deviating overall structures and to adapt to open and dynamic contexts while being developed, operated, evolved, and governed independently. In this presentation, we will first discuss the envisioned future scenarios for cyber-physical systems with an emphasis on the synergies networking can offer and then characterize which challenges for the design, production, and operation of these systems result. We will then discuss to what extent our current capabilities, in particular concerning software engineering match these challenges and where substantial improvements for the software engineering are crucial. In today's software engineering for embedded systems models are used to plan systems upfront to maximize envisioned properties on the one hand and minimize cost on the other hand. When applying the same ideas to software for smart cyber-physical systems, it soon turned out that for these systems often somehow more subtle links between the involved models and the requirements, users, and environment exist. Self-adaptation and runtime models have been advocated as concepts to covers the demands that result from these subtler links. Lately, both trends have been brought together more thoroughly by the notion of self-aware computing systems. We will review the underlying causes, discuss some our work in this direction, and outline related open challenges and potential for future approaches to software engineering for smart cyber-physical systems.

Background: Dynamic balance keeps the vertical projection of the center of mass within the base of support while walking. Dynamic balance tests are used to predict the risks of falls and eventual falls. The psychometric properties of most dynamic balance tests are unsatisfactory and do not comprise an actual loss of balance while walking. Objectives: Using beam walking distance as a measure of dynamic balance, the BEAM consortium will determine the psychometric properties, lifespan and patient reference values, the relationship with selected “dynamic balance tests,” and the accuracy of beam walking distance to predict falls. Methods: This cross-sectional observational study will examine healthy adults in 7 decades (n = 432) at 4 centers. Center 5 will examine patients (n = 100) diagnosed with Parkinson’s disease, multiple sclerosis, stroke, and balance disorders. In test 1, all participants will be measured for demographics, medical history, muscle strength, gait, static balance, dynamic balance using beam walking under single (beam walking only) and dual task conditions (beam walking while concurrently performing an arithmetic task), and several cognitive functions. Patients and healthy participants age 50 years or older will be additionally measured for fear of falling, history of falls, miniBESTest, functional reach on a force platform, timed up and go, and reactive balance. All participants age 50 years or older will be recalled to report fear of falling and fall history 6 and 12 months after test 1. In test 2, seven to ten days after test 1, healthy young adults and age 50 years or older (n = 40) will be retested for reliability of beam walking performance. Conclusion: We expect to find that beam walking performance vis-à-vis the traditionally used balance outcomes predicts more accurately fall risks and falls. Clinical Trial Registration Number: NCT03532984.