ERAWATCH country reports 2011: Austria

The main objective of the ERAWATCH Annual Country Reports is to characterise and assess the performance of national research systems and related policies in a structured manner that is comparable across countries. EW Country Reports 2011 identify the structural challenges faced by national innovation systems. They further analyse and assess the ability of the policy mix in place to consistently and efficiently tackle these challenges. The annex of the reports gives an overview of the latest national policy efforts towards the enhancement of European Research Area and further assess their efficiency to achieve the targets. These reports were originally produced in November - December 2011, focusing on policy developments over the previous twelve months. The reports were produced by the ERAWATCH Network under contract to JRC-IPTS. The analytical framework and the structure of the reports have been developed by the Institute for Prospective Technological Studies of the Joint Research Centre (JRC-IPTS) and Directorate General for Research and Innovation with contributions from ERAWATCH Network Asbl.JRC.J.2-Knowledge for Growt

RIO Country Report 2017: Austria

The R&I Observatory country report 2017 provides a brief analysis of the R&I system covering the economic context, main actors, funding trends & human resources, policies to address R&I challenges, and R&I in national and regional smart specialisation strategies. Data is from Eurostat, unless otherwise referenced and is correct as at January 2018. Data used from other international sources is also correct to that date. The report provides a state-of-play and analysis of the national level R&I system and its challenges, to support the European Semester.JRC.B.7-Knowledge for Finance, Innovation and Growt

Technologische und organisatorische Kompetenz österreichischer Zulieferbetriebe. Eine empirische Untersuchung am Beispiel der Maschinen- und Stahlbauindustrie sowie der Elektro- und Elektronikindustrie

Series: Discussion Papers of the Institute for Economic Geography and GIScienc

PCSIM: A Parallel Simulation Environment for Neural Circuits Fully Integrated with Python

The Parallel Circuit SIMulator (PCSIM) is a software package for simulation of neural circuits. It is primarily designed for distributed simulation of large scale networks of spiking point neurons. Although its computational core is written in C++, PCSIM's primary interface is implemented in the Python programming language, which is a powerful programming environment and allows the user to easily integrate the neural circuit simulator with data analysis and visualization tools to manage the full neural modeling life cycle. The main focus of this paper is to describe PCSIM's full integration into Python and the benefits thereof. In particular we will investigate how the automatically generated bidirectional interface and PCSIM's object-oriented modular framework enable the user to adopt a hybrid modeling approach: using and extending PCSIM's functionality either employing pure Python or C++ and thus combining the advantages of both worlds. Furthermore, we describe several supplementary PCSIM packages written in pure Python and tailored towards setting up and analyzing neural simulations

Compensating Inhomogeneities of Neuromorphic VLSI Devices Via Short-Term Synaptic Plasticity

Recent developments in neuromorphic hardware engineering make mixed-signal VLSI neural network models promising candidates for neuroscientific research tools and massively parallel computing devices, especially for tasks which exhaust the computing power of software simulations. Still, like all analog hardware systems, neuromorphic models suffer from a constricted configurability and production-related fluctuations of device characteristics. Since also future systems, involving ever-smaller structures, will inevitably exhibit such inhomogeneities on the unit level, self-regulation properties become a crucial requirement for their successful operation. By applying a cortically inspired self-adjusting network architecture, we show that the activity of generic spiking neural networks emulated on a neuromorphic hardware system can be kept within a biologically realistic firing regime and gain a remarkable robustness against transistor-level variations. As a first approach of this kind in engineering practice, the short-term synaptic depression and facilitation mechanisms implemented within an analog VLSI model of I&F neurons are functionally utilized for the purpose of network level stabilization. We present experimental data acquired both from the hardware model and from comparative software simulations which prove the applicability of the employed paradigm to neuromorphic VLSI devices

Working Document: Towards a vision for research, technology and innovation cooperation between Russia and the EU, its Member States and Associated States

This Working Document outlines development perspectives for cooperation in research, technology and innovation (RTI) between the EU, its Member States (MS), countries associated to the EU’s FP7 (AC), and Russia. The Working Document has been prepared in the framework of the ERA.Net RUS project and is based on a comprehensive foresight exercise implemented over the years 2010-2013 and on analysis of ongoing RTI cooperation. In-depth discussions among the ERA.Net RUS and ERA.Net RUS Plus consortiums and Funding Parties, and in the frame of expert workshops with policy makers and analysts provided essential input. Furthermore, results of other related projects (such as BILAT-RUS, BILAT-RUS Advanced, ACCESSRU, etc.) have been studied. The paper proposes a vision on enhancing the cooperation between EU MS/AC and Russia overall, as well as a specific follow-up vision for the ERA.Net RUS and ERA.Net RUS Plus projects.JRC.J.2-Knowledge for Growt

Emotion and memory: Event-related potential indices predictive for subsequent successful memory depend on the emotional mood state.

The present research investigated the influencesof emotional mood states on cognitive processes and neural circuits during long-term memory encoding using event-related potentials (ERPs). We assessed whether the subsequent memory effect (SME), an electrophysiological index of successful memory encoding, varies as a function of participants’ current mood state. ERPs were recorded while participants in good or bad mood states were presented with words that had to be memorized for subsequent recall. In contrast to participants in bad mood, participants in good mood most frequently applied elaborative encoding styles. At the neurophysiological level, ERP analyses showed that potentials to subsequently recalled words were more positive than to forgotten words at central electrodes in the time interval of 500-650 ms after stimulus onset (SME). At fronto-central electrodes, a polarity-reversed SME was obtained. The strongest modulations of the SME by participants’ mood state were obtained at fronto-temporal electrodes. These differences in the scalp topography of the SME suggest that successful recall relies on partially separable neural circuits for good and bad mood states. The results are consistent with theoretical accounts of the interface between emotion and cognition that propose mood-dependent cognitive styles

Austrian Research and Technology Report 2023

Der Forschungs- und Technologiebericht ist der Lagebericht über die aus Bundesmitteln geförderte Forschung, Technologie und Innovation in Österreich und wird im Auftrag des Bundesministeriums für Bildung, Wissenschaft und Forschung (BMBWF) in Einvernehmen mit dem Bundesministerium für Klimaschutz, Umwelt, Energie, Mobilität, Innovation und Technologie (BMK) sowie dem Bundesministerium für Arbeit und Wirtschaft (BMAW) erstellt. Der vorliegende Bericht steht im Zeichen eines komplexen Wandels auf unterschiedlichen Ebenen, einerseits getrieben durch multiple Krisen, die nicht nur das Innovationsverhalten von Unternehmen und wissenschaftlichen Akteurinnen und Akteuren verändern, sondern auch veränderte Rahmenbedingungen mit sich bringen. Die Twin Transition ist allgegenwärtig. Im vorliegenden Bericht wird mit dem Schwerpunktthema der Fokus auf die Grüne Transformation in Forschung und Wirtschaft gelegt. Abstrac