A new Miconia (Melastomatacaeae) from Bolivia, with remarks on angular-branched species in the Andes

A new species of Melastomataceae frorm Bolivia is described, illustrated and placed in a phenetic context within Miconia, a genus of 1000 species and about 2000 published names. Miconia quadrialata is readily distinguished from its Congeners by two-colored leaves and sharply four-angular and winged branchlets. A search for quadrangular-branched miconias revealed that 12 of 15 such species (in four sections), including the new species, occur in cloud forest in the Andes, raising the question of the adaptive significance of quadrangular branchlets

Scientific visualisation of complex interdependencies in hospitals

The IFM is on a quest to find ways to manage the complexity of hospital processes from different perspectives. An interdisciplinary project was conducted using scientific visualisation to support this goal. The findings indicated that there is a lot more involved than simply devising methods to illustrate the multiple variable context and the hypothetical data situation

The value of scientific knowledge dissemination for scientists:A value capture perspective

Scientific knowledge dissemination is necessary to collaboratively develop solutions to today’s challenges among scientific, public, and commercial actors. Building on this, recent concepts (e.g., Third Mission) discuss the role and value of different dissemination mechanisms for increasing societal impact. However, the value individual scientists receive in exchange for disseminating knowledge differs across these mechanisms, which, consequently, affects their selection. So far, value capture mechanisms have mainly been described as appropriating monetary rewards in exchange for scientists’ knowledge (e.g., patenting). However, most knowledge dissemination activities in science do not directly result in capturing monetary value (e.g., social engagement). By taking a value capture perspective, this article conceptualizes and explores how individual scientists capture value from disseminating their knowledge. Results from our qualitative study indicate that scientists’ value capture consists of a measureable objective part (e.g., career promotion) and a still unconsidered subjective part (e.g., social recognition), which is perceived as valuable due to scientists’ needs. By advancing our understanding of value capture in science, scientists’ selection of dissemination mechanisms can be incentivized to increase both the value captured by themselves and society. Hence, policy makers and university managers can contribute to overcoming institutional and ecosystem barriers and foster scientists’ engagement with society

FictionalAssert and Implicatures

In this paper, we present interdisciplinary work of linguists and literary scholars on the emergence of implicatures in fictional, here particularly lyrical texts. By systematically analysing a small corpus of poems by Emily Dickinson, John Donne, and other poets not discussed here, we show that, due to specific characteristics of the text type, an additional effect of pragmatic interpretation occurs that we call apparent flouting: in poetry, the pragmatic interpretation of the text is achieved in a more complex way than in non-fictional discourse. It requires a speech act operator that is different from Assert (Krifka 1995), which applies to the text as a whole and does not assert its actual truth. Because the pragmatic interpretation of poetry is more complex, cases of ambiguity that put forward several possible readings, for example, are not resolved right away. Rather, all possible readings contribute to the overall meaning of the poem

Rechtliche Aspekte des Einsatzes von KI und Robotik in Medizin und Pflege

Die rasanten Entwicklungen im Bereich der Künstlichen Intelligenz und Robotik stellen nicht nur die Ethik, sondern auch das Recht vor neue Herausforderungen, gerade im Bereich der Medizin und Pflege. Grundsätzlich hat der Einsatz von KI dabei das Potenzial, sowohl die Heilbehandlungen als auch den adäquaten Umgang im Rahmen der Pflege zu erleichtern, wenn nicht sogar zu verbessern. Verwaltungsaufgaben, die Überwachung von Vitalfunktionen und deren Parameter sowie die Untersuchung von Gewebeproben etwa könnten autonom ablaufen. In Diagnostik und Therapie können Systeme die behandelnde Ärztin unterstützen. Intelligente Betten ermöglichen eine Frühmobilisierung der Patient:innen bei gleichzeitig geringerem Personalaufwand. Gleichwohl birgt der Einsatz der Systeme rechtliche Herausforderungen. So besteht das Risiko einer Verletzung der beteiligten Personen. Im Gegensatz zu herkömmlichen Technologien „leidet“ KI unter der „Black-Box-Problematik“: Die von den Systemen generierten Ergebnisse sind nicht mehr vollständig vorhersehbar und nachvollziehbar. Der Einsatz birgt unbekannte und unkalkulierbare Risiken, was sich insbesondere auf die zivilrechtliche Haftung und strafrechtliche Verantwortung auswirkt. Wem die Entscheidungen der Systeme normativ zuzurechnen sind, ist eine Kernfrage des juristischen Diskurses. Die aus praktikabilitätsgründen naheliegende Wahl, dem letztentscheidenden Menschen das Verhalten eines KI-Systems zuzurechnen, überzeugt nicht in allen Fällen, sondern degradiert ihn häufig zum symbolischen Haftungsknecht und legt ihm einseitig die Risiken der Technologien auf. Weiterhin ergeben sich im Bereich der Medizin und Pflege Fragen hinsichtlich der Zulassung von KI-Systemen, da die Maschinen während der Nutzung weiterlernen und so ihren strukturellen Aufbau kontinuierlich verändern. Es ist daher angebracht, sich frühzeitig mit dem Konfliktpotential aus ethischer und rechtlicher Sicht auseinander zu setzen, um einer potenziellen gesellschaftlichen Angst vor derartigen Systemen vorzubeugen und einen praxisgerechten Handlungsrahmen zu schaffen.Definition of the problem: Rapid developments in the field of artificial intelligence (AI) and robotics pose new challenges not only to ethics but also to law, especially in the field of medicine and nursing. In principle, the use of AI has the potential to facilitate, if not improve, both curative treatments and adequate handling in the context of care. Administrative tasks, the monitoring of vital functions and their parameters, and the examination of tissue samples, for example, could run autonomously. In diagnostics and therapy, such systems can support the attending physician. Intelligent beds make it possible to mobilize patients early while at the same time reducing the need for personnel. Nevertheless, the use of these systems poses legal challenges. For example, there is a risk of injury to the people involved. Unlike conventional technologies, AI “suffers” from the “black box problem”: the results generated by the systems are no longer fully predictable and comprehensible. Its use entails unknown and incalculable risks, with particular implications for civil liability and criminal responsibility. Arguments: To whom the decisions of the systems are normatively attributable is a core question of legal discourse. The obvious choice, for reasons of practicability, of attributing the behaviour of an AI system to the human being who makes the final decisions is not convincing in all cases, but often degrades the human being to a symbolic “liability servant” and imposes the risks of the technologies on the human being in a one-sided manner. Furthermore, in the field of medicine and care, questions arise regarding the approval of AI systems, since the machines continue to learn during use and thus continuously change their structural design. Since the systems require any amount of reliable data for training and later use—especially through further learning—adequate handling of personal data is also necessary with regard to data protection law in the area of care and medicine. Conclusions: It is therefore advisable to address the potential for conflict from an ethical and legal perspective at an early stage in order to prevent a potential social fear of such systems and to create a practical framework for action. Orientation towards the guiding principle of “meaningful human control” offers the potential to solve these challenges

Strategic Research and Innovation Agenda for Organic Food and Farming

TP Organics is the European Technology Platform for organic food and farming, and for low-input agriculture. Established in 2008, it brings together small and medium-sized enterprises, larger companies, farmers, researchers, consumers and civil society organisations involved in the organic value chain from production, input and supply, to food processing, marketing and consumption. It identifies research and innovation needs and communicates them to policy-makers. The aim is to leverage the organic sector’s contribution to sustainable farming and food production. Since 2013, TP Organics is officially recognised by the European Commission as one of 40 European Technology Platforms (ETPs). TP Organics published its first Strategic Research Agenda in 2009. This proved very successful, as about a third of the research questions identified gained funding through the 7th Framework Programme for Research and Development (FP7) of the EU, or through transnational research programmes (ERA-Nets) and national research projects. With the end of the 7th Framework Programme and the start of the new EU Framework Programme for Research and Innovation, Horizon 2020, TP Organics decided to revise its research agenda. This new Strategic Research and Innovation Agenda is the product of an intensive participatory process, which lasted for a year and a half and benefited from three consultations