Measuring and Reducing The Travel-Related Carbon Footprint Of Sport Events In The Example Of Meo Rip Curl Portugal Pro 2023

This work explores the ecological dimensions of sporting events, with a primary focus on the MEO Rip Curl Portugal Pro 2023 as a case study. The main aim of this research is to calculate the travel-related carbon footprint of the event’s visitors and to investigate the potential for mitigating their carbon footprint. The research methodology comprises a quantitative survey questionnaire conducted among event attendees. The carbon footprint of various transportation modes was calculated using established emission factors. The study revealed that visitor travel constitutes a significant majority of the event's total carbon footprint. Additionally, it identified the need for enhanced efforts in promoting environmental-friendly transportation options. Finally, an all-encompassing carbon footprint reduction plan was devised to provide event managers with recommendations to mitigate the carbon footprint associated with their events. This work underscores the important role of sports events in environmental education and advocacy. It highlights the importance of measuring, reducing, and mitigating carbon footprints, especially in the context of event visitor travel. The findings emphasise the potential for sports events to adopt more environmental-friendly practices and contribute to global environmental goals. Overall, this research calls for increased awareness and action towards a more eco-conscious sports industry

Anwendung des Kalman-Filters zur Identifikation und Projektion von Zinsstrukturmodellen : Modelltheoretische Grundlagen

Die empirische Identifikation von arbitragefreien Modellen der Zinsstruktur beinhaltet eine spezifische Problematik. Die zentrale die Zinsstruktur treibende Größe ist die Zinsintensität {Rt}. Die Zinsintensität als Grenzwert kurzfristiger Zinssätze ist nun aber keine am Markt beobachtbare Größe, sondern eine latente Variable. Bei den Standardansätzen zur Identifikation von Zinsstrukturmodellen wird daher die Zinsintensität durch einen kurzfristigen Zinssatz, etwa Zinssätzen auf Monatsbasis, approximiert. Diese Vorgehensweise führt notwendigerweise zu Verzerrungen bei der statistischen Identifikation der Prozessparameter. Eine Alternative hierzu bildet der State Space-Ansatz bzw. Kalman-Filter, da dieser explizit die Erfassung latenter Variablen mit stochastischer (linearer) Entwicklungsdynamik erlaubt. Die Verwendung des Kalman-Filters auf die Identifikation von Zinsstrukturmodellen wurde erstmals von PENNACCHI (1991) durchgeführt und hat in jüngerer Zeit verstärkt Beachtung gefunden. Der Kalman-Filter weist dabei eine Reihe von weiteren Vorzügen auf, die ihn – gerade bei höherdimensionalen Modellen – zu einem interessanten und wertvollen generellen Ansatz zur Identifikation von Zinsstrukturmodellen machen: • Durch seine rekursive Struktur ist ein ständiges Update der Prognosen (Projektionen) der Zinsstrukturkurve möglich, sowohl einstufig als auch mehrstufig. • Die rekursive Struktur des Kalman-Filters erlaubt auch in einfacher und direkter Weise die Bestimmung der Likelihood-Funktion als Basis einer Maximum Likelihood-Schätzung. Im ersten Teil der vorliegenden Ausarbeitung soll daher sowohl die allgemeine Systematik des Kalman-Filters als auch dessen Anwendung auf Multifaktormodelle der Zinsstruktur dar- gestellt werden, wobei die Intention nicht die größte mathematische Allgemeinheit und Kürze ist, sondern der Focus auf einer nachvollziehbaren und verständlichen Ausarbeitung liegt. In einem zweiten Teil soll dann die empirische Anwendung der hier entwickelten modelltheoretischen Grundlagen im Vordergrund stehen

Teaching Data Driven Innovation – Facing a Challenge for Higher Education

In the era of digitization, data has become a very important resource for competition. To generate value from these constantly growing amounts of data and to create innovative services and business models based on the data, organizations need to rely on well-trained data scientists and analysts. The required skill set for such experts is complex and challenges higher education in the information systems discipline. Despite some first and promising efforts, there is still a lack of novel teaching approaches for data driven innovation. In this paper we design a morphological box providing a solution space for teaching data driven innovation at universities. For the systematization we analyze the submissions of an academic analytics contest and combine our findings with the existing knowledge base. Furthermore, we present our learnings from two teaching cases and reflect our experiences when applying them in class

The role of quantum effects and nonequilibrium transport coefficients for relativistic heavy ion collisions

Stopping power and thermalization in relativistic heavy ion collisions is investigated employing the quantum molecular dynamics approach. For heavy systems stopping of the incoming nuclei is predicted, independent of the energy. The influence of the quantum effects and their increasing importance at low energies, is demonstrated by inspection of the mean free path of the nucleons and the n-n collision number. Classical models, which neglect these effects, overestimate the stopping and the thermalization as well as the collective flow and squeeze out. The sensitivity of the transverse and longitudinal momentum transfer to the in-medium cross section and to the pressure is investigated

Single-photon emission from Ni-related color centers in CVD diamond

Color centers in diamond are very promising candidates among the possible realizations for practical single-photon sources because of their long-time stable emission at room temperature. The popular nitrogen-vacancy center shows single-photon emission, but within a large, phonon-broadened spectrum (~100nm), which strongly limits its applicability for quantum communication. By contrast, Ni-related centers exhibit narrow emission lines at room temperature. We present investigations on single color centers consisting of Ni and Si created by ion implantation into single crystalline IIa diamond. We use systematic variations of ion doses between 10^8/cm^2 and 10^14/cm^2 and energies between 30keV and 1.8MeV. The Ni-related centers show emission in the near infrared spectral range (~770nm to 787nm) with a small line-width (~3nm FWHM). A measurement of the intensity correlation function proves single-photon emission. Saturation measurements yield a rather high saturation count rate of 77.9 kcounts/s. Polarization dependent measurements indicate the presence of two orthogonal dipoles.Comment: 8 pages, published in conference proceedings of SPIE Photonics Europe 201