Contributions in Merlin

In dieser Arbeit wird das von Piotroski (2000) geschaffene Scoring Modell « F Score » , rend auf Kennzahlen, für Value Aktien am Schweizer Aktienmarkt untersucht. Im ersten Teil erfolgt eine theoretische Analyse, welche zum Schluss kommt, dass die von Piotroski doku- mentierte Üb errendite aus der Inkongruenz zwischen der Einschätzung durch die Investoren und dem Fundamentalwert resultiert. In der empirischen Analyse im zweiten Teil wird der F Score auf dem Schweizer Markt nach Vorbild dem Piotroskis angewendet. Dabei vermochte der F Sc ore Gewinner von Verliererakti en zu unterscheiden . Das Portfolio mit den aktien konnte eine um 6.82% höhere jährliche Rendite als der SPI erzielen, wies jedoch im Vergleich zu weiteren Value Konstruktionen keine bessere Performance auf. Die Überrendite zeigte dabei keine Signifikanz. Im dritten Teil wurde der F Score schrittweise durch den Ein- bezug weiterer Kennzahlen und Marktdaten modifiziert. Dabei wurden auch weitere Bewer- tungskennzahlen miteinbezogen. Schliesslich erfolgte eine Gewichtung durch Equal Risk Con- tribution. Schrittweise konnten die Renditen gesteigert werden, während die Risiko Masse san ken. So konnten verschiedene Portfolios signifikante Überrenditen aufweisen.

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In an environment that is plagued by distrust and intransparency, such as the used car market, blockchain-based certified vehicle data offers a compelling solution to these issues. One particular manifestation of such blockchain-based car data is the cardossier project. While previous research has examined the possibilities and effects of cardossier data, the role of commercial used car dealers has been largely unexplored. Thus, this work is dedicated to the role of used car dealers in a market with cardossier data. Through a design science approach, the role of dealers was incorporated into an existing experimental online market game. Subsequently, the developed software artifact was used for a market simulation experiment. The results thereof are a conceptual abstraction of used car dealers into the domain of an experimental market game, the implementation of said abstraction as well as insights into the effects of blockchain-based certified car data onto a used car market environment, that contains not only sellers and buyers but also dealers.

In the aftermath of shocking workplace scandals, people are often baffled when individuals within the organization were aware of clear-cut wrongdoing yet did not inform authorities. The current research suggests that moral concern for the suffering that a transgressor might face if a crime were reported is an under-recognized, powerful force that shapes whistleblowing in organizations, particularly when transgressors are fellow members of a highly entitative group (i.e., a group that is perceived as highly unified). Two experiments show that group entitativity heightens concern about possible consequences that the transgressor would face if a crime were to be reported, and that this concern reduces the likelihood of reporting wrongdoing in organizations to authorities. Further, the studies identify a mechanism through which concern about the transgressor is heightened in highly entitative groups: potential reporters perceive that the transgressor felt remorse for their crime. Thus, when fellow members of highly entitative organizations commit crimes, people are more likely to imagine that these transgressors felt anxiety or guilt about their actions, and this prompts greater concern for transgressors in ways that encourage people to let them “off the hook.” We discuss the implications of these findings for how reporting to authorities can be encouraged within highly entitative organizations.

Negative symptoms in schizophrenia are conceptualised as loading onto two factors: amotivation and diminished expression, which relate to different behavioural and neural markers. This distinction has proven useful for understanding the cognitive, motivational and neural mechanisms involved in negative symptoms, and for the development of treatments. Recently, it has been advocated that an even finer distinction into five subdomains is needed to understand the mechanisms underlying negative symptoms, and to prevent masking specific treatment and intervention effects. However, it is currently unclear whether such a fine-grained approach offers additional insights grounded in theory. In the present work, we focused on the factor amotivation, which has been shown to selectively correlate with the propensity to discount rewards in the face of effort and with the activity in the ventral striatum during reward anticipation. In a reanalysis of these studies we explored whether subdomains of amotivation – avolition, asociality, anhedonia – showed preferential correlation with these previously identified behavioural and neural markers. We show that for both behavioural and neural markers, a fine-grained model with the three subdomains did not better explain the data than a model with the amotivation factor only. Moreover, none of the three subdomains correlated significantly more or less with the behavioural or neural markers. Thus, no additional information was gained on amotivation in schizophrenia by selectively looking at its three subdomains. Consequently, the two-factor solution currently remains a valid option for the study of negative symptoms and further research is needed for behavioural and neural validation of the five-factor model.

Objective To investigate whether varied or repeated b-values provide better diffusion MRI data for discriminating cortical areas with a data-driven approach. Methods Data were acquired from three volunteers at 1.5T with b-values of 800, 1400, 2000 s/mm$^{2}$ along 64 diffusion-encoding directions. The diffusion signal was sampled from gray matter in seven regions of interest (ROIs). Rotational invariants of the local diffusion profile were extracted as features that characterize local tissue properties. Random forest classification experiments assessed whether classification accuracy improved when data with multiple b-values were used over repeated acquisition of the same (1400 s/mm$^{2}$) b-value to compare all possible pairs of the seven ROIs. Three data sets from the Human Connectome Project were subjected to similar processing and analysis pipelines in eight ROIs. Results Three different b-values showed an average improvement in correct classification rates of 5.6% and 4.6%, respectively, in the local and HCP data over repeated measurements of the same b-value. The improvement in correct classification rate reached as high as 16% for individual binary classification experiments between two ROIs. Often using only two of the available three b-values were adequate to make such an improvement in classification rates. Conclusion Acquisitions with varying b-values are more suitable for discriminating cortical areas.

Bitcoin ist nichts für schwache Nerven. Der Kurs explodierte im April auf über 60 000 $ – seitdem ist er um gut ein Drittel abgesackt. Ist der Kursrückgang der Beginn des Platzens einer riesigen Blase? Könnten Regulierer der Kryptowährung den Garaus machen?

"Blackout" is a novel by Marc Elsberg. It is about a Europe-wide blackout caused by a hacker attack on the power grid. The book impressively illustrates the consequences of a prolonged blackout, some of which are unimaginable for people who are not familiar with the topic. With the success of the fictional book Blackout, the topic of the vulnerability of the power grid and its consequences for society and the environment were brought to a wider audience. This paper validates the attack on the power grid from a technical perspective and discusses whether a similar attack could in fact lead to a Europe-wide blackout of the magnitude described. We distinguish between two types of effects that occur when the grid is attacked, immediate effects and consequences. If an attacker remotely cuts off the power of several households by hacking their smart meters, the immediate effect is that the hacked households no longer have power. A consequence is the instability of the power grid that may follow the immediate effect due to the fact that the generation and consumption of power are not in line anymore. Consequences form chains of effects which can be described by the metaphor of "domino effect". A blackout can reach out to places where nothing was attacked because the power grid as a whole collapses, which causes other infrastructures such as the telecommunications system, the traffic system and food supply chains to collapse. This paper mainly focuses on the validation of the immediate effects described in "Blackout".