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Die Rechtsfolgen einer fehlgeschlagenen Anteilsabtretung stellen ein rechtspraktisches Problem des GmbH-Rechts dar, dessen Lösungswege üblicherweise im Schuldrecht gesucht werden. Der Anwendung der schuldrechtlichen Rechtsinstitute im Rahmen des § 16 Abs. 1 GmbHG geht die Frage voran, ob das durch die Legitimationswirkung charakterisierte Auseinanderfallen von Herrschaftsrecht und Herrschaftsmöglichkeit zur Anwendung des Eigentümer-Besitzer-Verhältnisses führen kann. Der Übertragbarkeit der drei Komponenten der Vindikationslage – Sache, Eigentum, Besitz – und deren Interdependenzen auf die durch die Legitimationswirkung hervorgerufene Situation widmet sich diese Arbeit. Im Wege des systematischen Vergleichs der Rechtsbeziehungen weist der Autor eine Vergleichbarkeit nach und schlägt eine analoge Anwendung des Eigentümer-Besitzer-Verhältnisses vor. Im Mittelpunkt stehen die Rechtsgegenständlichkeit der Mitgliedschaft und die Ausdehnung des Besitzbegriffs auf unkörperliche Rechtsprodukte.
Recent years have seen a considerable broadening of the ambitions in urban sustainability policy-making. With its Sustainable Development Goal (SDG) 11 Making cities and human settlements inclusive, safe, resilient and sustainable, the 2030 Agenda stresses the critical role of cities in achieving sustainable development. In the context of SDG17 on partnerships, emphasis is also placed on the role of researchers and other scientific actors as change agents in the sustainability transformation. Against this backdrop, this article sheds light on different pathways through which science can contribute to urban sustainability. In particular, we discern four forms of science-policy-society interactions as key vectors: 1. sharing knowledge and providing scientific input to urban sustainability policy-making; 2. implementing transformative research projects; 3. contributing to local capacity building; and 4. self-governing towards sustainability. The pathways of influence are illustrated with empirical examples, and their interlinkages and limitations are discussed. We contend that there are numerous opportunities for actors from the field of sustainability science to engage with political and societal actors to enhance sustainable development at the local level.
The Author as Researcher
(2019)
This article proposes a new perspective on avant-garde travel writing through the lens of scientific field work, investigating these new writing techniques in Boris Pil’niak’s expedition prose. In the 1920s, the researching writer represents a hidden, but influential counterpart to the widely propagated figure of the working writer. While the author as producer combines word and deed in an operative act, the author as researcher investigates the production of knowledge. This entails revising the centrality of facts. Literature as artistic research subverts factography by going beyond the horizons of veristic data registration to include uncharted realms and vague possibilities. This exploration leads to specific genres: the author as researcher tries his hand at a kind of laboratory text, a prolific genre at the intersection of testing equipment, recording media, and hypothetical thought. Not confined to a sterile lab, avant-garde writer-researchers, as members of research expeditions, oscillate between their home writing desks and the remote depths of the emerging USSR. At the same time, they explore writing practices situated between data acquisition, sampling, fact-finding, observation and recording.
Signals for 2 degrees C
(2019)
The targets of the Paris Agreement make it necessary to redirect finance flows towards sustainable, low-carbon infrastructures and technologies. Currently, the potential of institutional investors to help finance this transition is widely discussed. Thus, this paper takes a closer look at influence factors for green investment decisions of large European insurance companies. With a mix of qualitative and quantitative methods, the importance of policy, market and civil society signals is evaluated. In summary, respondents favor measures that promote green investment, such as feed-in tariffs or adjustments of capital charges for green assets, over ones that make carbon-intensive investments less attractive, such as the phase-out of fossil fuel subsidies or a carbon price. While investors currently see a low impact of the carbon price, they rank a substantial reform as an important signal for the future. Respondents also emphasize that policy signals have to be coherent and credible to coordinate expectations.
Editorial
(2019)
A Fuzzy Rule-Based Model for Remote Monitoring of Preterm in the Intensive Care Unit of Hospitals
(2019)
The use of Remote patient monitoring (RPM) systems to monitor critically ill patients in the Intensive Care Unit (ICU) has enabled quality and real-time healthcare management. Fuzzy logic as an approach to designing RPM systems provides a means for encapsulating the subjective decision-making process of medical experts in an algorithm suitable for computer implementation. In this paper, a remote monitoring system for preterm in neonatal ICU incubators is modeled and simulated. The model was designed with 4 input variables (body temperature, heart rate, respiratory rate, and oxygen level saturation), and 1 output variable (action performed represented as ACT). ACT decides whether-an alert is generated or not and also determines the message displayed when a notification is required. ACT classifies the clinical priority of the monitored preterm into 5 different fields: code blue, code red, code yellow, code green, and-code black. The model was simulated using a fuzzy logic toolbox of MATLAB R2015A. About 216 IF_THEN rules were formulated to monitor the inputs data fed into the model. The performance of the model was evaluated using-the confusion matrix to determine the model’s accuracy, precision, sensitivity, specificity, and false alarm rate. The-experimental results obtained shows that the fuzzy-based system is capable of producing satisfactory results when used for monitoring and classifying the clinical statuses of neonates in ICU incubators.
To what extent has the European Union (EU) had a benign or retarding effect on what its member states would have undertaken in the absence of EU climate policies during 2008–2012? A measurement tool for the EU policy’s effect is developed and shows a benign average EU effect with considerable variation across countries. The EU’s policy effectiveness vis-à-vis its member states is explained by the EU’s non-compliance mechanism, the degree of usage of the Kyoto flexible mechanisms, and national pre-Kyoto emission reduction goals. Time-series cross-sectional analyses show that the EU’s non-compliance mechanism has no effect, while the ex-ante plans for using Kyoto flexible mechanisms and/or the ambitious pre-Kyoto emission reduction targets allow member states to escape constraints imposed by EU climate policy.
Network science is driven by the question which properties large real-world networks have and how we can exploit them algorithmically. In the past few years, hyperbolic graphs have emerged as a very promising model for scale-free networks. The connection between hyperbolic geometry and complex networks gives insights in both directions: (1) Hyperbolic geometry forms the basis of a natural and explanatory model for real-world networks. Hyperbolic random graphs are obtained by choosing random points in the hyperbolic plane and connecting pairs of points that are geometrically close. The resulting networks share many structural properties for example with online social networks like Facebook or Twitter. They are thus well suited for algorithmic analyses in a more realistic setting. (2) Starting with a real-world network, hyperbolic geometry is well-suited for metric embeddings. The vertices of a network can be mapped to points in this geometry, such that geometric distances are similar to graph distances. Such embeddings have a variety of algorithmic applications ranging from approximations based on efficient geometric algorithms to greedy routing solely using hyperbolic coordinates for navigation decisions.
JavaScript is the most popular programming language for web applications. Static analysis of JavaScript applications is highly challenging due to its dynamic language constructs and event-driven asynchronous executions, which also give rise to many security-related bugs. Several static analysis tools to detect such bugs exist, however, research has not yet reported much on the precision and scalability trade-off of these analyzers. As a further obstacle, JavaScript programs structured in Node. js modules need to be collected for analysis, but existing bundlers are either specific to their respective analysis tools or not particularly suitable for static analysis.
Mobile operating systems, such as Google's Android, have become a fixed part of our daily lives and are entrusted with a plethora of private information. Congruously, their data protection mechanisms have been improved steadily over the last decade and, in particular, for Android, the research community has explored various enhancements and extensions to the access control model. However, the vast majority of those solutions has been concerned with controlling the access to data, but equally important is the question of how to control the flow of data once released. Ignoring control over the dissemination of data between applications or between components of the same app, opens the door for attacks, such as permission re-delegation or privacy-violating third-party libraries. Controlling information flows is a long-standing problem, and one of the most recent and practical-oriented approaches to information flow control is secure multi-execution.
In this paper, we present Ariel, the design and implementation of an IFC architecture for Android based on the secure multi-execution of apps. Ariel demonstrably extends Android's system with support for executing multiple instances of apps, and it is equipped with a policy lattice derived from the protection levels of Android's permissions as well as an I/O scheduler to achieve control over data flows between application instances. We demonstrate how secure multi-execution with Ariel can help to mitigate two prominent attacks on Android, permission re-delegations and malicious advertisement libraries.
Internet connectivity of cloud services is of exceptional importance for both their providers and consumers. This article demonstrates the outlines of a method for measuring cloud-service connectivity at the internet protocol level from a client's perspective. For this, we actively collect connectivity data via traceroute measurements from PlanetLab to several major cloud services. Furthermore, we construct graph models from the collected data, and analyse the connectivity of the services based on important graph-based measures. Then, random and targeted node removal attacks are simulated, and the corresponding vulnerability of cloud services is evaluated. Our results indicate that cloud service hosts are, on average, much better connected than average hosts. However, when interconnecting nodes are removed in a targeted manner, cloud connectivity is dramatically reduced.
Detect me if you can
(2019)
Spam Bots have become a threat to online social networks with their malicious behavior, posting misinformation messages and influencing online platforms to fulfill their motives. As spam bots have become more advanced over time, creating algorithms to identify bots remains an open challenge. Learning low-dimensional embeddings for nodes in graph structured data has proven to be useful in various domains. In this paper, we propose a model based on graph convolutional neural networks (GCNN) for spam bot detection. Our hypothesis is that to better detect spam bots, in addition to defining a features set, the social graph must also be taken into consideration. GCNNs are able to leverage both the features of a node and aggregate the features of a node’s neighborhood. We compare our approach, with two methods that work solely on a features set and on the structure of the graph. To our knowledge, this work is the first attempt of using graph convolutional neural networks in spam bot detection.
Emotions are a complex concept and they are present in our everyday life. Persons on the autism spectrum are said to have difficulties in social interactions, showing deficits in emotion recognition in comparison to neurotypically developed persons. But social-emotional skills are believed to be positively augmented by training. A new adaptive social cognition training tool “E.V.A.” is introduced which teaches emotion recognition from face, voice and body language. One cross-sectional and one longitudinal study with adult neurotypical and autistic participants were conducted. The aim of the cross-sectional study was to characterize the two groups and see if differences in their social-emotional skills exist. The longitudinal study, on the other hand, aimed for detecting possible training effects following training with the new training tool. In addition, in both studies usability assessments were conducted to investigate the perceived usability of the new tool for neurotypical as well as autistic participants. Differences were found between autistic and neurotypical participants in their social-emotional and emotion recognition abilities. Training effects for neurotypical participants in an emotion recognition task were found after two weeks of home training. Similar perceived usability was found for the neurotypical and autistic participants. The current findings suggest that persons with ASC do not have a general deficit in emotion recognition, but are in need for more time to correctly recognize emotions. In addition, findings suggest that training emotion recognition abilities is possible. Further studies are needed to verify if the training effects found for neurotypical participants also manifest in a larger ASC sample.
The aim of this paper is to discuss Nicolai Hartmann’s conception of personhood as developed in his philosophy of spiritual being. Many contemporary accounts of personhood are systematically focused on rational phenomena as self-consciousness or practical reasoning, which are understood as ‘conditions of personhood’. Apart from having some technical problems, those accounts limit our self-under-standing as persons on distinct rational properties and often fail to consider the sociocultural aspects of the personal situation. Nicolai Hartmann — although respecting the role of reason — understands personhood particularly as participation in a shared spiritual sphere called Objektiver Geist (objective spirit), which includes various intersubjective phenomena as languages, religion, moral, arts, and the
sciences. Being part of this sphere seems to be more fundamental than having distinct rational properties, which requests a spiritual frame to be exerted. Further it is shown that Hartmann’s ontology of person also includes a notion of being affected by the existential weight of situations and other person’s actions — an idea often maintained by phenomenological positions. By regarding rational, intersubjective and affective aspects, Hartmann’s philosophy of person succeeds in offering a broad articulation of our self-understanding and may also be seen as providing a background to understand certain phenomena that are part of the personal situation.
Strafrecht, Besonderer Teil
(2021)
