Mapping the Territorial Adaptation of Technological Innovation Systems - Trajectories of the Internal Combustion Engine

Besides the rise of sustainable technologies, successful sustainability transitions crucially depend on the phase-out of unsustainable ones. However, the detailed dynamics of declining technological innovation systems (TIS) remain vague. Thus, based on the new TIS life cycle framework, we investigate how the technological dimension of a mature TIS adapts to increasing transformational pressures towards its decline. Considering the internal combustion engine (ICE) as a suitable research case, we measure the technological adaptation as changes in the dominant technological trajectory over time and across TIS territories. Empirically, this is operationalised by a main path analysis in patent citation networks, using 221,700 patents to cover the period from 10 January 1901 until 31 January 2019. Our results not only point to considerable shifts in the direction of technological development over time but also highlight stark differences across the three major car markets. Most notably, in contrast to USA and Japan, where hybrid powertrains have become the dominant alternative powertrains, the dominant trajectory in the EU territory points to an ongoing commitment towards diesel technology. In essence, our results highlight the importance of path dependency and connectivity of the knowledge search process as well as selective forces on the innovation system level, which have been neglected by related empirical studies. Conceptionally, our analysis demonstrates that the technological adaptation process is influenced by specific developments during a time period and heterogenous territorial dynamics within the TIS. Consequently, future TIS studies might consider spatially heterogeneous development cycles as well as possible mechanisms to establish an international trajectory towards sustainability goals

All-electrical measurement of spin injection in a magnetic pp-nn junction diode

Magnetic $p$-$n$ junction diodes are fabricated to investigate spin-polarized electron transport. The injection of spin-polarized electrons in a semiconductor is achieved by driving a current from a ferromagnetic injector (Fe), into a bulk semiconductor ($n$-GaAs) via schottky contact. For detection, a diluted magnetic semiconductor ($p$-GaMnAs) layer is used. Clear magnetoresistance was observed only when a high forward bias was applied across the $p$-$n$ junction.Comment: 4 pages, 4 figure

Fast Neural Representations for Direct Volume Rendering

Despite the potential of neural scene representations to effectively compress 3D scalar fields at high reconstruction quality, the computational complexity of the training and data reconstruction step using scene representation networks limits their use in practical applications. In this paper, we analyze whether scene representation networks can be modified to reduce these limitations and whether such architectures can also be used for temporal reconstruction tasks. We propose a novel design of scene representation networks using GPU tensor cores to integrate the reconstruction seamlessly into on-chip raytracing kernels, and compare the quality and performance of this network to alternative network- and non-network-based compression schemes. The results indicate competitive quality of our design at high compression rates, and significantly faster decoding times and lower memory consumption during data reconstruction. We investigate how density gradients can be computed using the network and show an extension where density, gradient and curvature are predicted jointly. As an alternative to spatial super-resolution approaches for time-varying fields, we propose a solution that builds upon latent-space interpolation to enable random access reconstruction at arbitrary granularity. We summarize our findings in the form of an assessment of the strengths and limitations of scene representation networks \changed{for compression domain volume rendering, and outline future research directions

PinAPL-Py: A comprehensive web-application for the analysis of CRISPR/Cas9 screens.

Large-scale genetic screens using CRISPR/Cas9 technology have emerged as a major tool for functional genomics. With its increased popularity, experimental biologists frequently acquire large sequencing datasets for which they often do not have an easy analysis option. While a few bioinformatic tools have been developed for this purpose, their utility is still hindered either due to limited functionality or the requirement of bioinformatic expertise. To make sequencing data analysis of CRISPR/Cas9 screens more accessible to a wide range of scientists, we developed a Platform-independent Analysis of Pooled Screens using Python (PinAPL-Py), which is operated as an intuitive web-service. PinAPL-Py implements state-of-the-art tools and statistical models, assembled in a comprehensive workflow covering sequence quality control, automated sgRNA sequence extraction, alignment, sgRNA enrichment/depletion analysis and gene ranking. The workflow is set up to use a variety of popular sgRNA libraries as well as custom libraries that can be easily uploaded. Various analysis options are offered, suitable to analyze a large variety of CRISPR/Cas9 screening experiments. Analysis output includes ranked lists of sgRNAs and genes, and publication-ready plots. PinAPL-Py helps to advance genome-wide screening efforts by combining comprehensive functionality with user-friendly implementation. PinAPL-Py is freely accessible at http://pinapl-py.ucsd.edu with instructions and test datasets

Modeling and Checking Business Process Compliance Rules in the Financial Sector

Assuring compliance of business processes with legal and internal regulations is crucial for financial institutions, as non-compliance may lead to severe financial and juridical penalties. To ensure business process compliance, process models have been established as a widely accepted basis for the design, documentation and control of the implementation of business process rules. Accordingly, in this paper, we introduce a semi-automatic business process compliance checking approach based on process models and related models. It relies on graph-based pattern matching, which makes it possible in contrast to existing approaches to define and check any possible type of business rule in any possible type of business process model or even other type of model. The approach is embedded in a design science research methodology

Adaptable Demonstrator Platform for the Simulation of Distributed Agent-Based Automotive Systems

Future autonomous vehicles will no longer have a driver as a fallback solution in case of critical failure scenarios. However, it is costly to add hardware redundancy to achieve a fail-operational behaviour. Here, graceful degradation can be used by repurposing the allocated resources of non-critical applications for safety-critical applications. The degradation problem can be solved as a part of an application mapping problem. As future automotive software will be highly customizable to meet customers\u27 demands, the mapping problem has to be solved for each individual configuration and the architecture has to be adaptable to frequent software changes. Thus, the mapping problem has to be solved at run-time as part of the software platform. In this paper we present an adaptable demonstrator platform consisting of a distributed simulation environment to evaluate such approaches. The platform can be easily configured to evaluate different hardware architectures. We discuss the advantages and limitations of this platform and present an exemplary demonstrator configuration running an agent-based graceful degradation approach