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The Sound of Success: Investigating Cognitive and Behavioral Effects of Motivational Music in Sports
(2017)
Listening to music before, during, or after sports is a common phenomenon, yet its functions and effects on performance, cognition, and behavior remain to be investigated. Listening to music before, during, or after sports is a common phenomenon, yet its functions and effects on performance, cognition, and behavior remain to be investigated. In this study we present a novel approach to the role of music in sports and exercise that focuses on the notion of musical self-enhancement (Elvers, 2016). We derived the following hypotheses from this framework: listening to motivational music will (i) enhance self-evaluative cognition, (ii) improve performance in a ball game, and (iii) evoke greater risk-taking behavior. To evaluate the hypotheses, we conducted a between-groups experiment (N = 150) testing the effectiveness of both an experimenter playlist and a participant-selected playlist in comparison to a no-music control condition. All participants performed a ball-throwing task developed by Decharms and Davé (1965), consisting of two parts: First, participants threw the ball from fixed distances into a funnel basket. During this task, performance was measured. In the second part, the participants themselves chose distances from the basket, which allowed their risk-taking behavior to be assessed. The results indicate that listening to motivational music led to greater risk taking but did not improve ball-throwing performance. This effect was more pronounced in male participants and among those who listened to their own playlists. Furthermore, self-selected music enhanced state self-esteem in participants who were performing well but not in those who were performing poorly. We also discuss further implications for the notion of musical self-enhancement. // Listening to music before, during, or after sports is a common phenomenon, yet its functions and effects on performance, cognition, and behavior remain to be investigated. In this study we present a novel approach to the role of music in sports and exercise that focuses on the notion of musical self-enhancement (Elvers, 2016). We derived the following hypotheses from this framework: listening to motivational music will (i) enhance self-evaluative cognition, (ii) improve performance in a ball game, and (iii) evoke greater risk-taking behavior. To evaluate the hypotheses, we conducted a between-groups experiment (N = 150) testing the effectiveness of both an experimenter playlist and a participant-selected playlist in comparison to a no-music control condition. All participants performed a ball-throwing task developed by Decharms and Davé (1965), consisting of two parts: First, participants threw the ball from fixed distances into a funnel basket. During this task, performance was measured. In the second part, the participants themselves chose distances from the basket, which allowed their risk-taking behavior to be assessed. The results indicate that listening to motivational music led to greater risk taking but did not improve ball-throwing performance. This effect was more pronounced in male participants and among those who listened to their own playlists. Furthermore, self-selected music enhanced state self-esteem in participants who were performing well but not in those who were performing poorly. We also discuss further implications for the notion of musical self-enhancement.
Die Unified Modeling Language (UML) wird mithilfe eines Profils erweitert, um den Entwurf relationaler Datenbanken zu unterstützen. Elemente von UML wie Vererbung können zur Datenbankmodellierung genutzt werden, und datenbankspezifische Elemente wie beispielweise Indizes lassen sich in UML modellieren. Es wird eine automatisierte Abbildung vom UML-Klassendiagramm zum Datenbankschema erklärt und das Round-Trip-Engineering zwischen UML und einem Datenbankschema dargestellt. Schließlich wird der Nutzen dieser Modellierungsmethode verdeutlicht.
Progressive web applications (PWAs) seem to be the next big thing in the mobile landscape. These are web applications with “super-powers” which are meant to provide the kinds of user experiences previously only native mobile applications could. Therefore they are able to match native applications in their capabilities but still thrive on the reachability of the web. They achieve this by implementing certain characteristics which originate from innovative standards and sophisticated best practices. Conveniently, as it is the web, PWAs are working seamlessly cross-platform. One of the closest things to a PWA so far may be an application created with the NativeScript framework. Such an application is also developed with web technologies yet able to use any native interface directly. This is made possible by using a designated runtime for mediating between JavaScript and the mobile system. Eventually, NativeScript is able to offer a high degree nativity yet also of convenient abstraction during development. This paper is set out to deliver further insight into both approaches by contrasting them based on the characteristics of PWAs. For this purpose, these characteristics are elaborated and adjusted to be applicable to native mobile applications. Hence a reasonable basis for what to expect from a native application is derived. Then NativeScript is assessed on this basis by the means of transferable concepts and technologies as well as a prototypic mobile application. Finally, an informed discussion and conclusion is performed based on the results. The comprehensive characteristics of PWAs resolve previous shortcomings with well thought out concepts and new technologies. These are transferable to native mobile applications to a far extent and may also be put into practice with NativeScript. The framework’s approach may be very well called ingenious, however, in the long run it might fall short of the innovative concept of PWAs. Having said this, it is still able to serve as a practical measure for creating appealing user experiences for multiple systems with arguably little effort. Due to large overlap a transformation between the two application types is a realistic option. Either way, web technologies are far from what they used to be and it is exciting to see how the mobile and web landscape will evolve in the future.
Investing as Random Trial
(2017)
We introduce an investment algorithm for a market of individual securities. The investment algorithm is derived from constraints depending on investment parameters in order to limit the risk and to take into account an individual investor. One constraint is devoted to trading costs. Purchased securities are selected randomly among securities that meet the buy condition, making trading a random trial. Simulations with historical price data are demonstrated for a simple example: The buy condition is evaluated on the basis of the price relationship for two subsequent trading days and the sales condition is defined by holding securities only for one day. A trading expert evaluates the expected return for the investment algorithm with respect to the random selection. Thus, the expert informs precisely on how many market players perform using the same investment algorithm. Its findings are for a parametrized set of buy conditions simultaneously, which makes a trading expert a valuable tool for theorists as well as for practitioners. In our example, the trading expert demonstrated clearly a significant mean reversion effect for a horizon of one day.