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The concept of an injective affine embedding of the quantum states into a set of classical states, i.e., into the set of the probability measures on some measurable space, as well as its relation to statistically complete observables is revisited, and its limitation in view of a classical reformulation of the statistical scheme of quantum mechanics is discussed. In particular, on the basis of a theorem concerning a non-denseness property of a set of coexistent effects, it is shown that an injective classical embedding of the quantum states cannot be supplemented by an at least approximate classical description of the quantum mechanical effects. As an alternative approach, the concept of quasi-probability representations of quantum mechanics is considered.
Sleep scoring is a necessary and time-consuming task in sleep studies. In animal models (such as mice) or in humans, automating this tedious process promises to facilitate long-term studies and to promote sleep biology as a data-driven f ield. We introduce a deep neural network model that is able to predict different states of consciousness (Wake, Non-REM, REM) in mice from EEG and EMG recordings with excellent scoring results for out-of-sample data. Predictions are made on epochs of 4 seconds length, and epochs are classified as artifactfree or not. The model architecture draws on recent advances in deep learning and in convolutional neural networks research. In contrast to previous approaches towards automated sleep scoring, our model does not rely on manually defined features of the data but learns predictive features automatically. We expect deep learning models like ours to become widely applied in different fields, automating many repetitive cognitive tasks that were previously difficult to tackle.
Urban farming is an innovative and sustainable way of food production and is becoming more and more important in smart city and quarter concepts. It also enables the production of certain foods in places where they usually dare not produced, such as production of fish or shrimps in large cities far away from the coast. Unfortunately, it is not always possible to show students such concepts and systems in real life as part of courses: visits of such industry plants are sometimes not possible because of distance or are permitted by the operator for hygienic reasons. In order to give the students the opportunity of getting into contact with such an urban farming system and its complex operation, an industrial urban farming plant was set up on a significantly smaller scale. Therefore, all needed technical components like water aeriation, biological and mechanical filtration or water circulation have been replaced either by aquarium components or by self-designed parts also using a 3D-printer. Students from different courses like mechanical engineering, smart building engineering, biology, electrical engineering, automation technology and civil engineering were involved in this project. This “miniature industrial plant” was also able to start operation and has now been running for two years successfully. Due to Corona pandemic, home office and remote online lectures, the automation of this miniature plant should be brought to a higher level in future for providing a good control over the system and water quality remotely. The aim of giving the student a chance to get to know the operation of an urban farming plant was very well achieved and the students had lots of fun in “playing” and learning with it in a realistic way.
Der Temperaturanstieg der vergangenen Jahrzehnte war in Gebirgsregionen besonders ausgeprägt. Sollte sich dieser Temperaturtrend im 21. Jahrhundert fortsetzen, dann dürf-ten sich auch die Häufigkeit und Intensität von Niederschlä-gen und Trockenperioden verändern, was die Waldwirtschaft vor grosse Herausforderungen stellen wird. Trockenheit ist ein entscheidender Faktor für die Waldökosysteme der inner-alpinen Täler, wo seit Jahren trockenheitsbedingtes Baum-sterben festgestellt wird. Der vorliegende Beitrag hat zum Ziel, die Sensitivität der verschiedenen Waldökosysteme ge-genüber Klimawandel und alternative, teilweise extreme Bewirtschaftungsvarianten in der Region Visp zu testen. Me-thodische Ansätze wie Monitoring, Feldexperimente und dy-namische Modellierung wurden kombiniert, und es wurden verschiedene Ökosystemleistungen berücksichtigt, so Holz-produktion, Schutz vor Naturgefahren, Kohlenstoffspeiche-rung und Aspekte der Biodiversität. Die Resultate deuten da-rauf hin, dass auf den Trockenstandorten der Tieflagen die einheimischen Baumarten an ihre physiologischen Grenzen stossen und längerfristig über alternative Baumarten nach-gedacht werden sollte. In den mittleren Lagen dürften Tro-ckenheit und Schadinsekten wie die Borkenkäfer die zukünf-tige Waldentwicklung steuern. In den Hochlagen hingegen werden sich die Wälder ausdehnen und besser wachsen als heute. Alle untersuchten Ökosystemleistungen werden ge-bietsweise starken Veränderungen unterworfen sein. Die dis-kutierten Bewirtschaftungsvarianten scheinen dazu geeignet, die Wasserverfügbarkeit der Bestände, hauptsächlich in tief-eren Lagen, zu erhöhen und dadurch die Widerstandskraft der Bäume gegenüber Trockenperioden vorübergehend zu stärken. Es ist aber davon ausgehen, dass nur verhältnismäs-sig starke Eingriffe wesentliche Effekte erzielen können. Die Verknüpfung von Umweltmonitoring, Feldexperimenten und Modellierung unter Miteinbezug von Ökosystemleistungen ist vielversprechend, da sie eine differenzierte Abschätzung des zukünftigen Landschaftswandels und seiner Effekte auf die Waldleistungen ermöglicht.