Institution
University of Luxembourg
Education•Luxembourg, Luxembourg•
About: University of Luxembourg is a education organization based out in Luxembourg, Luxembourg. It is known for research contribution in the topics: Context (language use) & Computer science. The organization has 4744 authors who have published 22175 publications receiving 381824 citations.
Papers published on a yearly basis
Papers
More filters
••
TL;DR: A taxonomy of ICOs is provided to increase understanding of their many forms, analyze the various regulatory challenges they pose, and suggest the steps regulators should consider in response.
Abstract: Initial coin offerings typically use blockchain technology to offer tokens that confer various rights in return, most often, for cryptocurrency. They can be seen as a conjunction of crowdfunding and blockchain. Based on a database of over 1000 ICO white papers, we provide a taxonomy of ICOs to increase understanding of their many forms, analyze the various regulatory challenges they pose, and suggest the first steps regulators should consider in response. As our database shows, ICOs are a global phenomenon and the global ICO market is much larger than generally thought, with overall ICO subscriptions estimated to exceed 75 billion USD as at the end of June 2. The US ICO market is significant, but the US doesn’t dominate this market, by any means. Furthermore, many ICOs are offered on the basis of utterly inadequate disclosure of information; more than half the ICO white papers are either silent on the initiators or backers or do not provide contact details, and an even greater share do not elaborate on the applicable law, segregation or pooling of client funds, and the existence of an external auditor. Accordingly, the decision to invest in them often cannot be the outcome of a rational calculus. Hallmarks of a classic speculative bubble are present. At the same time, ICOs provide a new, innovative and potentially important vehicle for raising funds to support innovative ideas and ventures, with the potential for aspects of their underlying structure to have an important impact on fundraising systems and structures in future.
157 citations
••
TL;DR: In this paper, the authors revisited the impact of skilled emigration on human capital accumulation using new panel data covering 147 countries during the period 1975-2000 and derived testable predictions from a stylized theoretical model and test them in dynamic regression models.
157 citations
••
TL;DR: In this article, the authors review the recent literature across various disciplines on the effects of climate change on migration, and explore the impact of migration on migration in the context of climate adaptation.
Abstract: Migration is one response to climatic stress and shocks. In this article we review the recent literature across various disciplines on the effects of climate change on migration. We explore...
157 citations
••
01 Oct 2019TL;DR: In this paper, the authors present evidence derived from representative survey data from Switzerland that is consistent with this view, finding that increased investment in digitalization is associated with increased employment of high skilled workers and reduced employment of low-skilled workers, with a slightly positive net effect.
Abstract: With the process of digitalization now in full swing, many are wondering how the adoption of new technologies influences job creation and destruction. Much hinges upon the specific tasks that machines take on and how many new tasks are created through the adoption of new digital technologies. Some argue that most tasks that are at risk of automation are those performed by rather low- to medium-skilled employees, while most new tasks that emerge from the adoption of digital technologies complement high-skilled labor. We present evidence derived from representative survey data from Switzerland that is consistent with this view. Specifically, we find that increased investment in digitalization is associated with increased employment of high-skilled workers and reduced employment of low-skilled workers, with a slightly positive net effect. The main effects are almost entirely driven by firms that employ machine-based digital technologies, e.g. robots, 3D printing or the Internet of Things. We do not find any significant employment effects when non-machine-based digital technologies are considered, e.g. ERP, e-commerce or cooperation support systems.
157 citations
••
TL;DR: The dependence of the twisting on the volume fraction was related to the increase in the magnitude of the repulsive interactions between the charged rods as the average separation distance decreases.
Abstract: The packing of cellulose nanocrystals (CNC) in the anisotropic chiral nematic phase has been investigated over a wide concentration range by small-angle X-ray scattering (SAXS) and laser diffraction. The average separation distance between the CNCs and the average pitch of the chiral nematic phase have been determined over the entire isotropic-anisotropic biphasic region. The average separation distances range from 51 nm, at the onset of the anisotropic phase formation, to 25 nm above 6 vol % (fully liquid crystalline phase) whereas the average pitch varies from ≈15 μm down to ≈2 μm as ϕ increases from 2.5 up to 6.5 vol %. Using the cholesteric order, we determine that the twist angle between neighboring CNCs increases from about 1° up to 4° as ϕ increases from 2.5 up to 6.5 vol %. The dependence of the twisting on the volume fraction was related to the increase in the magnitude of the repulsive interactions between the charged rods as the average separation distance decreases.
156 citations
Authors
Showing all 4893 results
Name | H-index | Papers | Citations |
---|---|---|---|
Jun Wang | 166 | 1093 | 141621 |
Leroy Hood | 158 | 853 | 128452 |
Andreas Heinz | 108 | 1078 | 45002 |
Philippe Dubois | 101 | 1098 | 48086 |
John W. Berry | 97 | 351 | 52470 |
Michael Müller | 91 | 333 | 26237 |
Bart Preneel | 82 | 844 | 25572 |
Bjorn Ottersten | 81 | 1058 | 28359 |
Sander Kersten | 79 | 246 | 23985 |
Alexandre Tkatchenko | 77 | 271 | 26863 |
Rudi Balling | 75 | 238 | 19529 |
Lionel C. Briand | 75 | 380 | 24519 |
Min Wang | 72 | 716 | 19197 |
Stephen H. Friend | 70 | 184 | 53422 |
Ekhard K. H. Salje | 70 | 581 | 19938 |