Johannes Kepler University of Linz

About: Johannes Kepler University of Linz is a education organization based out in Linz, Oberösterreich, Austria. It is known for research contribution in the topics: Computer science & Thin film. The organization has 6605 authors who have published 19243 publications receiving 385667 citations.

Exploring the role of ICT on household behavioural energy efficiency to mitigate global warming

Abstract: With the advent of ICT in the energy system, new possibilities to inform and influence residential electricity consumption become available. We explore the potential of ICT-based interventions in households to decrease electricity usage, improve energy efficiency and thus contribute to reducing GHG (greenhouse gas) emissions from this sector. Based on a literature review on the subject, we suggest that ICT can affect some of the main behaviour-influencing factors, and discuss the causal avenues by which these effects can take hold. Our review finds that ICT-based effects on consumer behaviour can reduce household final electricity consumption by 0–5%. These and other findings from the literature are used to define parameter values, which reflect the efficacy of ICT at changing household energy usage patterns, and ultimately decreasing GHG emissions from the electricity sector. A quantitative analysis of the potential for ICT to contribute to reaching the 1.5 °C target in the context of the European Union (EU) energy sector is performed. It is found that ICT-based interventions in household energy use could contribute between 0.23% and 3.3% of the EU CO2e reduction target from the energy sector that would keep warming under 1.5 °C, corresponding to 4.5–64.7 mio. tCO2e abated per year.

madmom: a new Python Audio and Music Signal Processing Library

Abstract: In this paper, we present madmom, an open-source audio processing and music information retrieval (MIR) library written in Python. madmom features a concise, NumPy-compatible, object oriented design with simple calling conventions and sensible default values for all parameters, which facilitates fast prototyping of MIR applications. Prototypes can be seamlessly converted into callable processing pipelines through madmom's concept of Processors, callable objects that run transparently on multiple cores. Processors can also be serialised, saved, and re-run to allow results to be easily reproduced anywhere. Apart from low-level audio processing, madmom puts emphasis on musically meaningful high-level features. Many of these incorporate machine learning techniques and madmom provides a module that implements some in MIR commonly used methods such as hidden Markov models and neural networks. Additionally, madmom comes with several state-of-the-art MIR algorithms for onset detection, beat, downbeat and meter tracking, tempo estimation, and piano transcription. These can easily be incorporated into bigger MIR systems or run as stand-alone programs.

Tunable 3D/2D magnetism in the (MnBi2Te4)(Bi2Te3)m topological insulators family

Abstract: This work is supported by Saint Petersburg State University project for scientific investigations (ID No. 51126254, https://spin.lab.spbu.ru) and Russian Science Foundation (Grant no. 18-12-00062 in part of the photoemission measurements and 18-12-00169 in part of calculations of topological invariants, investigation of dependence of the electronic spectra on SOC strength, and tight-binding band structure calculations). Russian Foundation for Basic Research (Grant nos. 20-32-70179 and 18-52-06009) and Science Development Foundation under the President of the Republic of Azerbaijan (Grant no. EIF-BGM-4-RFTF-1/2017-21/04/1-M-02) are acknowledged. We also acknowledge the support by the Basque Departamento de Educacion, UPV/EHU (Grant no. IT-756-13), Spanish Ministerio de Ciencia e Innovacion (Grant no. PID2019-103910GB-I00), the Fundamental Research Program of the State Academies of Sciences (line of research III.23.2.9) and Tomsk State University competitiveness improvement program (project no. 8.1.01.2018). I.P.R. acknowledge support from Ministry of Education and Science of the Russian Federation (State Task No. 0721-2020-0033) (tight-binding calculations). The calculations were performed in Donostia International Physics Center and in the Research park of St. Petersburg State University Computing Center (http://cc.spbu.ru).

Understanding photosynthetic light-harvesting: a bottom up theoretical approach

Abstract: We discuss a bottom up approach for modeling photosynthetic light-harvesting Methods are reviewed for a full structure-based parameterization of the Hamiltonian of pigment–protein complexes (PPCs) These parameters comprise (i) the local transition energies of the pigments in their binding sites in the protein, the site energies; (ii) the couplings between optical transitions of the pigments, the excitonic couplings; and (iii) the spectral density characterizing the dynamic modulation of pigment transition energies and excitonic couplings by protein vibrations Starting with quantum mechanics perturbation theory, we provide a microscopic foundation for the standard PPC Hamiltonian and relate the expressions obtained for its matrix elements to quantities that can be calculated with classical molecular mechanics/electrostatics approaches including the whole PPC in atomic detail and using charge and transition densities obtained with quantum chemical calculations on the isolated building blocks of the PPC In the second part of this perspective, the Hamiltonian is utilized to describe the quantum dynamics of excitons Situations are discussed that differ in the relative strength of excitonic and exciton-vibrational coupling The predictive power of the approaches is demonstrated in application to different PPCs, and challenges for future work are outlined