An investigation of the relation between cooperation and the innovative success of German regions

Concepts like regional innovation systems, innovative milieu, and learning regions emphasize the positive contribution of intra-regional cooperation to firmsÕ innovation performance. Despite substantial numbers of case studies, the quantitative empirical evidence for this claim is thin. Using data on the co-application and co- invention of patents for 270 German labor market regions the study shows that intra- regional cooperation intensity and regional innovation efficiency are associated. In contrast to the negative influence of inter-regional cooperation, medium levels of intra-regional cooperation stimulate regional innovation efficiency.regional innovation efficiency, cooperation intensity, collaboration, regional cooperation

Contaminated by war : A brief history of sea-dumping of munitions

Munitions introduced to the sea during military activities, including naval combat and mine warfare represent only a fraction of military material present in seas and oceans. Huge amounts of obsolete conventional munitions and chemical munitions were dumped to the sea until 1975, when London convention put a stop of sea dumping. Such munitions are a threat for maritime workers, but also for environment. Corroding shells release toxic degradation products to sediments and bottom water, and unlike other contaminants, they cannot be reduced by land measures. Only removal of source can reduce the contamination. Much work has been done in the last decade, and mechanisms of toxicity and bioaccumulation are being recognized, as well as transport and spreading mechanisms. The full assessment of the risk associated with munitions now depends on broad application of developed techniques

Potassium self-diffusion in a K-rich single-crystal alkali feldspar

The paper reports potassium diffusion measurements performed on gem-quality single-crystal alkali feldspar in the temperature range from $1169$ to 1021 \, \mbox{K}. Natural sanidine from Volkesfeld, Germany was implanted with \mbox{}^{43}\mbox{K} at the ISOLDE/CERN radioactive ion-beam facility normal to the (001) crystallographic plane. Diffusion coefficients are well described by the Arrhenius equation with an activation energy of 2.4 \, \mbox{eV} and a pre-exponential factor of 5\times10^{-6} \, \mbox{m}^{2}/\mbox{s}, which is more than three orders of magnitude lower than the \mbox{}^{22}\mbox{Na} diffusivity in the same feldspar and the same crystallographic direction. State-of-the-art considerations including ionic conductivity data on the same crystal and Monte Carlo simulations of diffusion in random binary alloy structures point to a correlated motion of K and Na through the interstitialcy mechanism

Understanding the Business Value: Towards a Taxonomy of Industrial Use Scenarios enabled by Cyber-Physical Systems in the Equipment Manufacturing Industry

The trend of digitalization provides new opportunities for industrial equipment manufactures as sensor technology and ubiquitous connectivity become part of the equipment. In particular, cyber-physical systems (CPSs) enable digital innovation for the industrial product and service business by improving operational efficiencies, facilitating innovative hybrid business models, and fuelling servitization in manufacturing. Despite the new opportunities, so far no research has been conducted to investigate and classify configurations and affordances of this new technology. To gain both a broad and in-depth understanding of use scenarios and added-value of CPSs for the service business in the equipment industry, a multi-method approach is chosen: a systematic literature review as well as case study research are conducted. Grounded in existing literature and based on empirical data of 45 use scenarios, we propose a taxonomy to classify use scenarios enabled by CPSs in the equipment industry. This work contributes to the theoretical body of knowledge by proposing a taxonomy of use scenarios enabled by CPSs. The taxonomy can be (1) leveraged to categorize use scenarios of CPSs in the equipment manufacturing industry and (2) used as a framework for further research. Practitioners can use the taxonomy to classify and compare use scenarios as well as identify business model archetypes

Micro simulated moving bed chromatography-mass spectrometry as a continuous on-line process analytical tool

Continuous manufacturing is becoming increasingly important in the (bio-)pharmaceutical industry, as more product can be produced in less time and at lower costs. In this context, there is a need for powerful continuous analytical tools. Many established off-line analytical methods, such as mass spectrometry (MS), are hardly considered for process analytical technology (PAT) applications in biopharmaceutical processes, as they are limited to at-line analysis due to the required sample preparation and the associated complexity, although they would provide a suitable technique for the assessment of a wide range of quality attributes. In this study, we investigated the applicability of a recently developed micro simulated moving bed chromatography system (µSMB) for continuous on-line sample preparation for MS. As a test case, we demonstrate the continuous on-line MS measurement of a protein solution (myoglobin) containing Tris buffer, which interferes with ESI-MS measurements, by continuously exchanging this buffer with a volatile ammonium acetate buffer suitable for MS measurements. The integration of the µSMB significantly increases MS sensitivity by removing over 98% of the buffer substances. Thus, this study demonstrates the feasibility of on-line µSMB-MS, providing a versatile PAT tool by combining the detection power of MS for various product attributes with all the advantages of continuous on-line analytics

Geometric Deep Learning for Autonomous Driving: Unlocking the Power of Graph Neural Networks With CommonRoad-Geometric

Heterogeneous graphs offer powerful data representations for traffic, given their ability to model the complex interaction effects among a varying number of traffic participants and the underlying road infrastructure. With the recent advent of graph neural networks (GNNs) as the accompanying deep learning framework, the graph structure can be efficiently leveraged for various machine learning applications such as trajectory prediction. As a first of its kind, our proposed Python framework offers an easy-to-use and fully customizable data processing pipeline to extract standardized graph datasets from traffic scenarios. Providing a platform for GNN-based autonomous driving research, it improves comparability between approaches and allows researchers to focus on model implementation instead of dataset curation.Comment: Presented at IV 202

ScenarioTools Real-Time Play-Out for Test Sequence Validation in an Automotive Case Study

In many areas, such as automotive, healthcare, or production, we find software-intensive systems with complex real-time requirements. To efficiently ensure the quality of these systems, engineers require automated tools for the validation of the requirements throughout the development. This, however, requires that the requirements are specified in an analyzable way. We propose modeling the specification using Modal Sequence Diagrams (MSDs), which express what a system may, must, or must not do in certain situations. MSDs can be executed via the play-out algorithm to investigate the behavior emerging from the interplay of multiple scenarios; we can also test if traces of the final product satisfy all scenarios. In this paper, we present the first tool supporting the play-out of MSDs with real-time constraints. As a case study, we modeled the requirements on gear shifts in an upcoming standard on vehicle testing and use our tool to validate externally generated gear shift sequences

Uptake and absorption of fluoranthene from spiked microplastics into the digestive gland tissues of blue mussels, Mytilus edulis L.

The present work intended to investigate the fate of contaminant-loaded microplastics if ingested by benthic filter feeder Mytilus edulis under laboratory conditions. In the course of a 7-day experiment the mussels were exposed to PVC microplastics in a size range >40 mm, in doses of 2000 particles L_1 (11.56 mg L_1). Particles were either virgin or loaded with one of four different nominal concentrations of the polycyclic aromatic hydrocarbon (PAH) fluoranthene (500, 125, 31.25 and 7.8125 mg g_1). Verification of fluoranthene concentrations on the particles provided evidence of the high absorptive capacity of PVC for this PAH, indicating that comparable particles may serve as considerable accumulation sites for high concentrations of hydrophobic contaminants in the aquatic environment. Analysis of digestive gland tissues via polarised light microscopy revealed the occurrence of particles and particle aggregates within stomach and intestines of all mussels treated with microplastics, thus making the xenobiotic bioavailable. Results of contaminant analysis in mussel tissues via equilibrium sampling point to a considerable capability of microplastics for the accumulation of hydrophobic contaminants from the environment and their potential to act as vehicles for the transport of theses contaminants into organismal tissues. of fluoranthene concentrations on the particles provided evidence of the high absorptive capacity of PVC for this PAH, indicating that comparable particles may serve as considerable accumulation sites for high concentrations of hydrophobic contaminants in the aquatic environment. Analysis of digestive gland tissues via polarised light microscopy revealed the occurrence of particles and particle aggregates within stomach and intestines of all mussels treated with microplastics, thus making the xenobiotic bioavailable. Results of contaminant analysis in mussel tissues via equilibrium sampling point to a considerable capability of microplastics for the accumulation of hydrophobic contaminants from the environment and their potential to act as vehicles for the transport of theses contaminants into organismal tissues. © 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY licens