The role of instrument compliance in normal force measurements of polymer melts

Schweizer et al. [J Rheol 48(6):1345-1363, 2004] showed nonlinear step shear rate data for a polystyrene melt (M w=200kg/mol, M w/M n=1.06, T=175°C). For different rheometers, cone angles, and sample sizes, the delayed normal force rise observed therein relative to a compliance-free reference N 1 (from a thermodynamically consistent reptation model) is shown to depend on rheometer compliance characterized by the instrument stiffness K A. K A can be obtained from mapping N 1 on the measured N 1,meas. or directly from mechanical contact measurement with a mismatch of 20-30%. The ranking of the stiffnesses found is K A(RMS 800)>K A(MCR 300)>K A(ARES LR2). Once K A is known, N 1,meas.-data can be corrected by solving the ill-posed Volterra equation involved in it. The correction shown for experiments with the 0.15-rad cone angle gives very good results. The characteristic decay time of the normal force after cessation of flow scales linearly with the axial response time t a calculated from K A, cone angle, and sample radius. The torque decay time is practically independent of t

Dividing the ICO Jungle: Extracting and Evaluating Design Archetypes

The sale of blockchain-based digital tokens as a novel funding mechanism, referred to as initial coin offerings (ICO), has grown exponentially, resulting in $12bn raised globally during the first half of 2018. Due to the novelty of the phenomenon, the concept is not yet entirely understood. Existing research provides first insights into ICO endeavors and design only. To date, comprehensive and in-depth analyses of ICO design archetypes to better understand prevailing ICO characteristics are missing. We bridge this gap by enriching an existing ICO taxonomy and applying a cluster analysis to identify predominant ICO archetypes. As a result, we identify five ICO design archetypes: the average ICO, the liberal ICO, the visionary ICO, the compliant ICO, and the native ICO. We thereby contribute to a comprehensive and in-depth understanding of the ICO phenomenon and its implications. Further, we offer practitioners tangible design suggestions for future ICOs

PDPK: A Framework to Synthesise Process Data and Corresponding Procedural Knowledge for Manufacturing

Procedural knowledge describes how to accomplish tasks and mitigate problems. Such knowledge is commonly held by domain experts, e.g. operators in manufacturing who adjust parameters to achieve quality targets. To the best of our knowledge, no real-world datasets containing process data and corresponding procedural knowledge are publicly available, possibly due to corporate apprehensions regarding the loss of knowledge advances. Therefore, we provide a framework to generate synthetic datasets that can be adapted to different domains. The design choices are inspired by two real-world datasets of procedural knowledge we have access to. Apart from containing representations of procedural knowledge in Resource Description Framework (RDF)-compliant knowledge graphs, the framework simulates parametrisation processes and provides consistent process data. We compare established embedding methods on the resulting knowledge graphs, detailing which out-of-the-box methods have the potential to represent procedural knowledge. This provides a baseline which can be used to increase the comparability of future work. Furthermore, we validate the overall characteristics of a synthesised dataset by comparing the results to those achievable on a real-world dataset. The framework and evaluation code, as well as the dataset used in the evaluation, are available open source

DON’T SLIP ON THE ICO – A TAXONOMY FOR A BLOCKCHAIN-ENABLED FORM OF CROWDFUNDING

Blockchain is rapidly evolving and there is an increasing interest in the technology in both practice and academia. Recently, a blockchain use case called Initial Coin Offering (ICO) draws a lot of attention. ICO is a novel form of crowdfunding that utilizes blockchain tokens to allow for truly peer-to-peer investments. Although, more than 4.5 billion USD have been invested via ICOs, the phenomenon is poorly understood. Scientific research lacks a structured classification of ICOs to provide further insights into their characteristics. We bridge this gap by developing a taxonomy based on real-world ICO cases, related literature, and expert interviews. Further, we derive and discuss prevailing ICO archetypes. Our findings contribute to theory development in the field of ICOs by enriching the descriptive knowledge, identifying design options, deriving ICO archetypes, and laying the foundation for further research. Additionally, our research provides several benefits for practitioners. Our proposed taxonomy illustrates that there is no one-size-fits-all model of ICOs and might support the decision-making process of start-ups, investors and regulators. The proposed ICO archetypes indicate how common ICOs are designed and thus might serves as best practices. Finally, our analysis indicates that ICOs represent a valid alter-native to traditional crowdfunding approaches

HOW DO LARGE STAKES INFLUENCE BITCOIN PERFORMANCE? EVIDENCE FROM THE MT.GOX LIQUIDATION CASE

Bitcoin as the first and still most important decentralized cryptocurrency has gained wide popu-larity due to the steep rise of its price during the second half of 2017. Because of its digital na-ture, Bitcoin cannot be valuated exclusively with fundamental approaches, which is why factors such as investor sentiment have become a common alternative to capture its performance. In this work, we studied whether and how the sale of Bitcoins from the insolvency assets of Mt.Gox, which represent about 1.1% of the current global total, relates to Bitcoin price movements. We used social media sentiment analysis of Twitter data to examine how investors are influenced in their decision to buy or sell Bitcoin when confronted with the trade actions of Nobuaki Koba-yashi, the trustee in charge of the Mt.Gox case. We built a vector error correction model to ana-lyze the long-run relationship between cointegrated variables. Our analysis confirms the posi-tive association of Bitcoin performance with positive Twitter sentiment and tweet volume and the negative association with negative sentiment. We further found empirical evidence that Mt.Gox selloff events have a lasting negative impact on the Bitcoin price and that we can measure this effect by Twitter sentiment and tweet volume

Tarzan and chain: exploring the ICO jungle and evaluating design archetypes

The phenomenon of a blockchain use case called initial coin offering (ICO) is drawing increasing attention as a novel funding mechanism. ICO is a crowdfunding type that utilizes blockchain tokens to allow for truly peer-to-peer investments. Although more than \$7bn has been raised globally via ICOs as at 2018, the concept and its implications are not yet entirely understood. The research lags behind in providing in-depth analyses of ICO designs and their long-term success. We address this research gap by developing an ICO taxonomy, applying a cluster analysis to identify prevailing ICO archetypes, and providing an outlook on the token value market performance for individual archetypes. We identify five ICO design archetypes and display their secondary market development from both a short-term and a long-term perspective. We contribute to an in-depth understanding of ICOs and their implications. Further, we offer practitioners tangible design and success indications for future ICOs

Don't Slip on the Initial Coin Offering (ICO) : A Taxonomy for a Blockchain-enabled Form of Crowdfunding

Blockchain is rapidly evolving and there is an increasing interest in the technology in both prac-tice and academia. Recently, a blockchain use case called Initial Coin Offering (ICO) draws a lot of attention. ICO is a novel form of crowdfunding that utilizes blockchain tokens to allow for tru-ly peer-to-peer investments. Although, more than 4.5 billion USD have been invested via ICOs, the phenomenon is poorly understood. Scientific research lacks a structured classification of ICOs to provide further insights into their characteristics. We bridge this gap by developing a taxonomy based on real-world ICO cases, related literature, and expert interviews. Further, we derive and discuss prevailing ICO archetypes. Our findings contribute to theory development in the field of ICOs by enriching the descriptive knowledge, identifying design options, deriving ICO archetypes, and laying the foundation for further research. Additionally, our research pro-vides several benefits for practitioners. Our proposed taxonomy illustrates that there is no one-size-fits-all model of ICOs and might support the decision-making process of start-ups, investors and regulators. The proposed ICO archetypes indicate how common ICOs are designed and thus might serves as best practices. Finally, our analysis indicates that ICOs represent a valid alter-native to traditional crowdfunding approaches

Symmetric dithiodigalactoside: strategic combination of binding studies and detection of selectivity between a plant toxin and human lectins

Thioglycosides offer the advantage over O-glycosides to be resistant to hydrolysis. Based on initial evidence of this recognition ability for glycosyldisulfides by screening dynamic combinatorial libraries, we have now systematically studied dithiodigalactoside on a plant toxin (Viscum album agglutinin) and five human lectins (adhesion/growth-regulatory galectins with medical relevance e.g. in tumor progression and spread). Inhibition assays with surface-presented neoglycoprotein and in solution monitored by saturation transfer difference NMR spectroscopy, flanked by epitope mapping, as well as isothermal titration calorimetry revealed binding properties to VAA (Ka: 1560 ± 20 M-1). They were reflected by the structural model and the affinity on the level of toxin-exposed cells. In comparison, galectins were considerably less reactive, with intrafamily grading down to very minor reactivity for tandem-repeat-type galectins, as quantitated by radioassays for both domains of galectin-4. Model building indicated contact formation to be restricted to only one galactose moiety, in contrast to thiodigalactoside. The tested lycosyldisulfide exhibits selectivity between the plant toxin and the tested human lectins, and also between these proteins. Therefore, glycosyldisulfides have potential as chemical platform for inhibitor design

Solution-based Innovation : A Method for Emerging Technology Use Case Development

Interest in blockchain is growing rapidly and at a global scale. The potential to disrupt various industries is attributed to the emerging blockchain technology. Organizations and institutions have thus begun to examine the emerging the technology and its impact on their businesses. However, researchers and practitioners still lack a systematic approach to understand the po-tential of blockchain and to develop convincing use cases. We addressed this research gap by applying an action design research approach and situational method engineering to propose a method for the development of blockchain technology use cases. Following this approach, we iteratively evaluate and further develop the proposed method through application in four distinct industries. In a next research step, we now focus on a broader context and evaluate if our existing use case development method is applicable for other emerging technologies than blockchain. By doing so, we seek to broaden our evaluation, generalize our method, and support practitioners and researchers in better leveraging the opportunities of continuous digital transformation