279 research outputs found

    Resolving the productivity paradox of digitalised production

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    [EN] Although Industry 4.0 and other initiatives predict widespread adoption of digitalised technology on the factory floor, few companies use new digitalised production technology holistically in their ecosystems; in practical implementation, companies often decide against digitalisation for financial reasons. This is due to a paradox (akin to the so called “productivity paradox”) caused by the complexity of value creation and value delivery within digitalised production. This article analyses and synthesises cross-disciplinary research using a grounded theory model, thus offering valuable insights for businesses considering investing in digitalised production. A qualitative model and an associated toolbox (complete with tools for practical application by business leaders and decision-makers) are presented to address organisational uncertainty and leadership disconnect that often contribute to the paradoxical gap between digital strategy and operational implementation.Dold, L.; Speck, C. (2021). Resolving the productivity paradox of digitalised production. International Journal of Production Management and Engineering. 9(2):65-80. https://doi.org/10.4995/ijpme.2021.15058OJS658092Al-Debei, Mutaz M.; Avison, David (2010): Developing a unified framework of the business model concept. In Euro-pean Journal of Information Systems 19 (3), pp. 359-376. https://doi.org/10.1057/ejis.2010.21Andulkar, Mayur; Le, Duc Tho; Berger, Ulrich (2018): A multi-case study on Industry 4.0 for SME's in Brandenburg, Germany. Proceedings of the 51st Hawaii International Conference on System Sciences. Hawaii, 2018. https://doi.org/10.24251/HICSS.2018.574Arnold, Christian; Kiel, Daniel; Voight, Kai-Ingo (2017): Innovative Business Models for the Industrial Internet of Things. In Berg Huettenmaenn Monatsh 162 (9), pp. 371-381. https://doi.org/10.1007/s00501-017-0667-7Arnold, Christian; Voight, Kai-Ingo (2017): Ecosystem Effects of the Industrial Internet of Things on Manufacturing Companies. In Acta INFOLOGICA 1 (2), pp. 99-108.Berghaus, Sabine (2018): The Fuzzy Front End of Digital Transformation. Activities and Approaches for Initiating Organizational Change Strategies. UniversitĂ€t St. Gallen. Available online at https://www1.unisg.ch/www/edis.nsf/SysLkpByIdentifier/4704/$FILE/dis4704.pdf.Berghaus, Sabine; Back, Andrea; Kaltenrieder, Bramwell. (2017): Digital Maturity & Transformation Report 2017. ZĂŒrich: Crosswalk AG,. In Veröffentlichung zur Studie der UniversitĂ€t St. Gallen in Kooperation mit Crosswalk. St. Gallen, March 2017.Bouwman, Harry; Nikou, Shahrokh; Molina-Castillo, Francisco J.; Reuver, Mark de (2018): The impact of digitaliza-tion on business models. In Digital Policy, Regulation and Governance 20 (2), pp. 105-124. https://doi.org/10.1108/DPRG-07-2017-0039Buchholz, Birgit; Ferdinand, Jan-Peter; Gieschen, Jan-Hinrich; Seidel, Uwe (2017): Digitalisierung industrieller Wertschöpfung. Eine Studie im Rahmen der Begleitforschung zum Technologieprogramm AUTONOMIK fĂŒr In-dustrie 4.0 des Bundesministeriums fĂŒr Wirtschaft und Energie. Berlin: iit-Institut fĂŒr Innovation und Technik der VDI/VDE Innovation + Technik GmbH.BurggrĂ€f, Peter; Dannapfel, Matthias; Voet, Hanno; Bök, Patrick-Benjamin; Uelpenich, JĂ©rĂŽme; Hoppe, Julian (2017): Digital Transformation of Lean Production. Systematic Approach for the Determination of Digitally Pervasive Val-ue Chains. In World Academy of Science, Engineering and Technology, International Journal of Social, Behavioral, Educational, Economic, Business and Industrial Engineering 11 (10), 2462-2471.Burmeister, Christian; Luettgens, Dirk; Piller, Frank T. (2016): Business Model Innovation for Industrie 4.0. Why the 'Industrial Internet' Mandates a New Perspective. In Die UnternehmensfĂŒhrung ; RWTH-TIM Working Paper 70 (2), pp. 124-152. https://doi.org/10.2139/ssrn.2571033Cañas, HĂ©ctor; Mula, Josefa; DĂ­az-Madroñero, Manuel; Campuzano-BolarĂ­n, Francisco (2021): Implementing Industry 4.0 principles. In Computers & Industrial Engineering 158 (1), p. 107379. https://doi.org/10.1016/j.cie.2021.107379Charmaz, Kathy (2014): Constructing grounded theory. 2nd edition. Los Angeles, London, New Delhi, Singapore, Washington DC: SAGE.Chesbrough, Henry (2010): Business model innovation: opportunities and barriers. Opportunities and Barriers. In Long range planning 43 (2-3), pp. 354-363. https://doi.org/10.1016/j.lrp.2009.07.010Chesbrough, Henry; Rosenbloom, Richard S. (2002): The role of the business model in capturing value from innova-tion: evidence from Xerox Corporation's technology spin‐off companies. In Industrial and corporate change 11 (3), pp. 529-555. https://doi.org/10.1093/icc/11.3.529Cottyn, Johannes; Stockman, Kurt; Hendrik, van Landeghem (2008): The Complementarity of Lean Thinking and the ISA 95 Standard. WBF 2008. WBF. Barcelona, November 2008. Available online at http://hdl.handle.net/1854/LU-524679.Dold, Luzian (2020): Beurteilung von Investitionen in die digitalisierte Produktion. Eine Mixed-Method-Studie zur moderierenden Wirkung von Nutzenkonstrukten aus GeschĂ€ftsmodellen an der LĂŒcke zwischen digitaler Strategie und operativen Prozessen. Dissertation. Middlesex University, London.Dold, Luzian (2021): A Value Centred Paradigm to Moderate the Digital Transformation of Manufacturing. In Adv. J Social Sci. 8 (1), pp. 86-95. DOI: 10.21467/ajss.8.1.86-95.Döring, Nicola; Bortz, JĂŒrgen (2016): Forschungsmethoden und Evaluation in den Sozial- und Humanwissenschaften. With assistance of Sandra Pöschl. 5. vollstĂ€ndig ĂŒberarbeitete, aktualisierte und erweiterte Auflage. Berlin, Heidel-berg: Springer (Springer-Lehrbuch). https://doi.org/10.1007/978-3-642-41089-5Dorst, Wolfgang (2016): Implementation Strategy Industrie 4.0. Report on the results of the Industrie 4.0 Platform. With assistance of W. Dorst, C. Glohr, T. Hahn, U. Loewen, Rosen, R. Schiemann, T., F. Vollmar et al. Edited by BITKOM e.V., VDMA e.V., ZVEI e.V. Berlin, Frankfurt am Main.Eruvankai, Saju; Muthukrishnan, Murugesan; Mysore, Anantharamaiah Kumar (2017): Accelerating IIOT Adoption with OPC UA. In INTERNETWORKING INDONESIA 9 (1), pp. 3-8. Available online at http://www.internetworkingindonesia.org/Issues/Vol9-No1-2017/iij_vol9_no1_2017_eruvankai.pdf.Fleisch, Elgar; Weinberger, Markus; Wortmann, Ass Felix; Wortmann, Felix (2014): GeschĂ€ftsmodelle im Internet der Dinge. In HMD Praxis der Wirtschaftsinformatik 51 (6), pp. 812-826. https://doi.org/10.1365/s40702-014-0083-3Geissbauer, Reinhard; Schrauf Stefan; Koch Volkmar; Kuge Simon (2014): Industry 4.0 : Opportunities and Challenges of the Industrial Internet. Edited by Pricewaterhousecooper Aktiengesellschaft. MĂŒnchen.Gibbons, Paul M.; Burgess, Stuart C. (2010): Introducing OEE as a measure of lean Six Sigma capability. In Lean Six Sigma Journal 1 (2), pp. 134-156. https://doi.org/10.1108/20401461011049511Grebe, Michael; RĂŒssmann, Michael,Leyh Michael; Franke, Roman (2019): HOW DIGITAL CHAMPIONS INVEST. Edited by Boston Consulting Group. MĂŒnchen. Available online at http://image-src.bcg.com/Images/BCG-How-Digital-Champions-Invest-June-2019_tcm15-223286.pdf, checked on 1/6/2020.GĂŒrdĂŒr, Didem; El-khoury, Jad; Törngren, Martin (2019): Digitalizing Swedish industry. What is next? In Computers in Industry 105 (1), pp. 153-163. https://doi.org/10.1016/j.compind.2018.12.011Henssen, Robert; Schleipen, Miriam (2014): Interoperability between OPC UA and AutomationML. In Procedia CIRP 25, pp. 297-304. https://doi.org/10.1016/j.procir.2014.10.042Hopp, Wallace J.; Spearman, Mark L. (2004): To Pull or Not to Pull. What Is the Question? In Manufacturing & Ser-vice Operations Management 6 (2), pp. 133-148. https://doi.org/10.1287/msom.1030.0028Imtiaz, Jahanzaib; Jasperneite, JĂŒrgen (2013): Scalability of OPC-UA down to the chip level enables "Internet of Things". In IEEE intelligent Systems, pp. 500-505. https://doi.org/10.1109/INDIN.2013.6622935Industrial Value Chain Initiative (2018): Industrial Value Chain Reference Architecture -Next. Strategic implementation framework of industrial value chain for connected industries. Edited by Industrial Value Chain Initiative. Monozu-kuri Nippon Conference c/o. Tokyo.Jesse, Norbert (2016): Internet of Things and Big Data - The Disruption of the Value Chain and the Rise of New Soft-ware Ecosystems. In IFAC-PapersOnLine 49 (29), pp. 275-282. https://doi.org/10.1016/j.ifacol.2016.11.079JĂŒttemann, Gerd (Ed.) (1989): Qualitative Forschung in der Psychologie. Grundfragen, Verfahrensweisen, Anwen-dungsfelder. 2. Aufl. Heidelberg: Asanger.Kagermann, Henning; Anderl, Reiner; Gausemeier, JĂŒrgen; Schuh, GĂŒnther; Wahlster Wolfgang (2016): Industrie 4.0 im globalen Kontext. Strategien der Zusammenarbeit mit internationalen Partnern. Acatech Studie. MĂŒnchen: Her-bert Utz Verlag.Kagermann, Henning; Wahlster, Wolfgang; Helbig, Johannes (2013): Umsetzungsempfehlungen fĂŒr das Zukunftspro-jekt Industrie 4.0. Abschlussbericht des Arbeitskreises Industrie 4.0. Edited by Prof. Dr. Henning Kagermann. For-schungsunion Wirtschaft und Wissenschaft, Arbeitskreis Industrie 4.0. Frankfurt am Main.Kagermann, Henning; Wahlster, Wolfgang; Lukas, Wolf-Dieter (2011): Industrie 4.0 : Mit dem Internet der Dinge auf dem Weg zur 4. Industriellen Revolution. In VDI Nachrichten 2011, 4/1/2011 (13).Kiel, Daniel; MĂŒller, Julian; Arnold, Christian; Voight, Kai-Ingo (2017): Sustainable Industrial Value Creation. Benefits and Challenges of Industry 4.0. In International Journal of Innovation Management (ijim) 21 (8), pp. 1-34. https://doi.org/10.1142/S1363919617400151Koch, Arno (2016): OEE fĂŒr das Produktionsteam. Das vollstĂ€ndige OEE-Benutzerhandbuch - oder wie Sie die ver-borgene Maschine entdecken. 3., korrigierte Auflage. Herrieden: CETPM Publishing (Operational Excellence, Nr. 5).Legrenzi, Christopher (2017): THE DIGITAL PARADOX. INFORMATION, INFORMATICS, AND INFOR-MATION SYSTEM. In ISM Journal of International Business, pp. 35-42.Lerch, Christian; JĂ€ger, Angela; Maloca, Spomenka (2017): Wie digital ist Deutschlands Industrie wirklich. Arbeit und ProduktivitĂ€t in der digitalen Produktion. In Mitteilungen aus der ISI-Erhebung Modernisierung der Produktion, Ausgabe 71.Leyh, Christian; Bley, Katja (2016): Digitalisierung. Chance oder Risiko fĂŒr den deutschen Mittelstand? - Eine Studie ausgewĂ€hlter Unternehmen. In HMD 53 (1), pp. 29-41. https://doi.org/10.1365/s40702-015-0197-2Lin, Shi-Wan; Crawford, Mark; Mellor, Stephen (2017): The Industrial Internet of Things Volume G1: Reference Architecture. Version 1.80. Needham, MA. In Industrial Internet Consortium (IIC) Tech. Rep.Magruk, Andrzej (2016): Uncertainty in the Sphere of the Industry 4.0 - Potential Areas to Research. In Business, Management & Education/Verslas, Vadyba ir Studijos 14 (2), pp. 275-291. https://doi.org/10.3846/bme.2016.332Maier, W.; Weber, M. (2013): Management von Big-Data-Projekten. Leitfaden. Berlin: Bundesverband Information-swirtschaft,Telekommunikation und neue Medien e. V.Maklan, Stan; Peppard, Joe; Klaus, Philipp (2015): Show me the money. In European Journal of Marketing 49 (3/4), pp. 561-595. https://doi.org/10.1108/EJM-08-2013-0411Mayring, Philipp (2008): EinfĂŒhrung in die qualititative Sozialforschung. Eine Anleitung zu qualitativem Denken. 5. Aufl. Weinheim, Basel: Beltz (Beltz Studium).Obermaier, Robert (2019): Industrie 4.0 und Digitale Transformation als unternehmerische Gestaltungsaufgabe. In Robert Obermaier (Ed.): Handbuch Industrie 4.0 und Digitale Transformation. Betriebswirtschaftliche, technische und rechtliche Herausforderungen. 1st ed. 2019. Wiesbaden: Springer Fachmedien Wiesbaden, pp. 3-46. https://doi.org/10.1007/978-3-658-24576-4_1Obermaier, Robert; Schweikl, Stefan (2019): Zur Bedeutung von Solows Paradoxon. Empirische Evidenz und ihre Übertragbarkeit auf Digitalisierungsinvestitionen in einer Industrie 4.0. In Robert Obermaier (Ed.): Handbuch In-dustrie 4.0 und Digitale Transformation. Betriebswirtschaftliche, technische und rechtliche Herausforderungen. 1st ed. 2019. Wiesbaden: Springer Fachmedien Wiesbaden, pp. 529-564. https://doi.org/10.1007/978-3-658-24576-4_22Osterwalder, Alexander (2004): The business model ontology: A proposition in a design science approach. Disserti-ation. Universite de Lausanne, Lausanne. Ecole des Hautes Etudes Commerciales. Available online at https://doc.rero.ch/record/4210/files/1_these_Osterwalder.pdf.Osterwalder, Alexander; Pigneur, Yves (2010): Business model generation: a handbook for visionaries, game changers, and challengers. Hoboken: John Wiley & Sons.Palm, Florian; GrĂŒner, Sten; Pfrommer, Julius; Graube, Markus; Urbas, Leon (2014): open62541-der offene OPC UA Stack. In Onlinepublikation des Fraunhofer IOSB, Lehrstuhl Prozessleittechnik der RWTH Aachen; TU Dresden, Professur fĂŒr Prozessleitechnik,Porter, Michael E. (2010): Wettbewerbsvorteile. Spitzenleistungen erreichen und behaupten. 7. durchgesehene Auflage Auflage. Frankfurt, New York: Campus.Porter, Michael E.; Heppelmann, James E. (2014): How smart, connected products are transforming competition. In Harvard business review 92 (11), pp. 64-88.Rachinger, Michael; Rauter, Romana; MĂŒller, Christiana; Vorraber, Wolfgang; Schirgi, Eva (2019): Digitalization and its influence on business model innovation. In Journal of Manufacturing Technology Management 30 (8), pp. 1143-1160. https://doi.org/10.1108/JMTM-01-2018-0020Remane, Gerrit; Hanelt, Andre; Wiesboeck, Florian; Kolbe, Lutz M. (2017): Digital maturity in traditional industries - an exploratory analysis. Twenty-Fifth European Conference on Information Systems (ECIS),. GuimarĂŁes,Portugal, 2017.Rese, Mario; Meier, Horst; Gesing, Judith; Boßlau, Mario (2013): An ontology of business models for industrial prod-uct-service systems. In Yoshiki Shimomura, Koji Kimita (Eds.): The Philosopher's Stone for Sustainability. Pro-ceedings of the 4th CIRP International Conference on Industrial Product-Service Systems, Tokyo, Japan, Novem-ber 8th - 9th, 2012. Heidelberg: Springer (Lecture Notes in Production Engineering), pp. 191-196. https://doi.org/10.1007/978-3-642-32847-3_32Sauer, Olaf (2014): Information Technology for the Factory of the Future - State of the Art and Need for Action. In Procedia CIRP 25, pp. 293-296. https://doi.org/10.1016/j.procir.2014.10.041Schmenner, Roger W. (2015): The Pursuit of Productivity. In Production and Operations Management 24 (2), pp. 341-350. https://doi.org/10.1111/poms.12230Schuh, G.; Anderl, R.; Dumitrescu, R.; Hompel, M. ten; KrĂŒger, A. (Eds.) (2020): Industrie 4.0 Maturity Index. Man-aging the Digital Transformation of Companies - UPDATE 2020 - (acatech STUDY). MUNICH: Herbert Utz Verlag.Schuh, GĂŒnther; Reuter, Christina; Hauptvogel, Annika; Dölle, Christian (2015): Hypotheses for a Theory of Produc-tion in the Context of Industrie 4.0. In : Advances in Production Technology: Springer, pp. 11-23. Available online at https://link.springer.com/10.1007/978-3-319-12304-2_2 https://doi.org/10.1007/978-3-319-12304-2_2Skilton, Mark; Gordon, Penelope; Harding, Chris (2010): Building return on investment from cloud computing. Cloud Business Artifacts Project, Cloud Computing Work Group, The Open Group. Edited by The Open Group. Burling-ton, MA.Solow, R. M. (1987): We'd better watch out. In New York Times Book Review 36.Strauss, Anselm; Corbin, Juliet (2010): Grounded theory. Grundlagen qualitativer Sozialforschung. UnverĂ€nd. Nachdr. der letzten Aufl. Weinheim: Beltz.Tantik, Erdal; Anderl, Reiner (2016): Industrie 4.0. Using Cyber-physical Systems for Value-stream Based Production Evaluation. In Procedia CIRP 57, pp. 207-212. https://doi.org/10.1016/j.procir.2016.11.036Veile, Johannes; Kiel, Daniel; Voight, Kai-Ingo; MĂŒller, Julian Marius (2019): Lessons learned from Industry 4.0 implementation in the German manufacturing industry. In Journal of Manufacturing Technology Management (ahead-of-print). https://doi.org/10.1108/JMTM-08-2018-0270Witzel, Andreas (2000): Das problemzentrierte Interview. In Forum Qualitative Sozialforschung / Forum: Qualitative Social Research 1 (1). https://doi.org/10.1016/j.lrp.2015.04.001YlipÀÀ, Torbjörn; Skoogh, Anders; Bokrantz, Jon; Gopalakrishnan, Maheshwaran (2017): Identification of maintenance improvement potential using OEE assessment. In International Journal of Productivity and Performance Manage-ment 66 (1), pp. 126-143. https://doi.org/10.1108/IJPPM-01-2016-0028Zennaro, Ilenia; Battini, Daria; Sgarbossa, Fabio; Persona, Alessandro; Marchi, Rosario de; van der Wiele, Ton (2018): Micro Downtime - Data Collection, Analysis and Impact on OEE in Bottling Lines The San Benedetto Case Study. In Int J Qual & Reliability Mgmt 17 (9), p. 0. https://doi.org/10.1108/IJQRM-11-2016-0202Zott, Christoph; Amit, Raphael; Massa, Lorenzo (2011): The Business model: Recent Developments and Future Re-search. In Journal of management 37 (4), pp. 1019-1042. https://doi.org/10.1177/0149206311406265Zuehlke, Detlef (2010): SmartFactory-Towards a factory-of-things. In Annual Reviews in Control 34 (1), pp. 129-138. https://doi.org/10.1016/j.arcontrol.2010.02.00

    A top-down view on DNA replication and recombination from 9,000 feet above sea level

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    A report of the Keystone Symposium 'DNA Replication and Recombination' held in Keystone, USA, 27 February to 4 March 2011

    Fluctuations and response in a non-equilibrium micron-sized system

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    The linear response of non-equilibrium systems with Markovian dynamics satisfies a generalized fluctuation-dissipation relation derived from time symmetry and antisymmetry properties of the fluctuations. The relation involves the sum of two correlation functions of the observable of interest: one with the entropy excess and the second with the excess of dynamical activity with respect to the unperturbed process, without recourse to anything but the dynamics of the system. We illustrate this approach in the experimental determination of the linear response of the potential energy of a Brownian particle in a toroidal optical trap. The overdamped particle motion is effectively confined to a circle, undergoing a periodic potential and driven out of equilibrium by a non-conservative force. Independent direct and indirect measurements of the linear response around a non-equilibrium steady state are performed in this simple experimental system. The same ideas are applicable to the measurement of the response of more general non-equilibrium micron-sized systems immersed in Newtonian fluids either in stationary or non-stationary states and possibly including inertial degrees of freedom.Comment: 12 pages, submitted to J. Stat. Mech., revised versio

    The ORC/Cdc6/MCM2-7 complex facilitates MCM2-7 dimerization during prereplicative complex formation.

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    The replicative mini-chromosome-maintenance 2-7 (MCM2-7) helicase is loaded in Saccharomyces cerevisiae and other eukaryotes as a head-to-head double-hexamer around origin DNA. At first, ORC/Cdc6 recruits with the help of Cdt1 a single MCM2-7 hexamer to form an 'initial' ORC/Cdc6/Cdt1/MCM2-7 complex. Then, on ATP hydrolysis and Cdt1 release, the 'initial' complex is transformed into an ORC/Cdc6/MCM2-7 (OCM) complex. However, it remains unclear how the OCM is subsequently converted into a MCM2-7 double-hexamer. Through analysis of MCM2-7 hexamer-interface mutants we discovered a complex competent for MCM2-7 dimerization. We demonstrate that these MCM2-7 mutants arrest during prereplicative complex (pre-RC) assembly after OCM formation, but before MCM2-7 double-hexamer assembly. Remarkably, only the OCM complex, but not the 'initial' ORC/Cdc6/Cdt1/MCM2-7 complex, is competent for MCM2-7 dimerization. The MCM2-7 dimer, in contrast to the MCM2-7 double-hexamer, interacts with ORC/Cdc6 and is salt-sensitive, classifying the arrested complex as a helicase-loading intermediate. Accordingly, we found that overexpression of the mutants cause cell-cycle arrest and dominant lethality. Our work identifies the OCM complex as competent for MCM2-7 dimerization, reveals MCM2-7 dimerization as a limiting step during pre-RC formation and defines critical mechanisms that explain how origins are licensed

    Decentralized Open Platform for Vaccination—A German Example: COVID-19-Vacc

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    The COVID-19 pandemic has massively impacted the health of many people worldwide and poses significant challenges for our social, economic, and political life. Global vaccination should help the world overcome the pandemic and return to a “normal” life. In Germany, the Federal Ministry of Health presented its “National Vaccination Strategy COVID-19”, which describes the primary actors, elements, and activities required for the immunization of the German population. However, the implementation is challenging due to the federal organization of the German state in sixteen federal states. While essential processes such as vaccination rate monitoring and surveillance are planned centrally, the sixteen federal states are responsible for implementing the vaccination strategy in a decentralized manner. Furthermore, the European General Data Protection Regulation (EU-GDPR) imposes strict rules for processing and exchanging personal data. However, Germany is only a case in point. Governmental decisions always need to be implemented by regional and/or local actors, the number of which varies greatly depending on the country. This work addresses these challenges by proposing the COVID-19-Vacc Platform—an open and decentralized digital platform focused on vaccinations as a matter of example. The proposed platform model connects various actors and enables them to involve, conduct, and track the vaccination process while meeting all necessary data protection and security requirements defined by EU-GDPR. Using the DMS Reference Model as the theoretical framework, the blueprint of the COVID-19-Vacc Platform is developed, outlining the platform’s ecosystem structure, its interactions process model, and the service stack, defining how the proposed platform works on the operational level. Our COVID-19-Vacc Platform may help facilitate a fast and EU-GDPR compliant implementation of COVID-19 vaccination strategies. Beyond that, the proposed open and decentralized platform model might facilitate international interconnectivity and therefore the management of emerging global pandemics or other global health-related crisi

    Fabrication technology for high light-extraction ultraviolet thin-film flip-chip (UV TFFC) LEDs grown on SiC

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    The light output of deep ultraviolet (UV-C) AlGaN light-emitting diodes (LEDs) is limited due to their poor light extraction efficiency (LEE). To improve the LEE of AlGaN LEDs, we developed a fabrication technology to process AlGaN LEDs grown on SiC into thin-film flip-chip LEDs (TFFC LEDs) with high LEE. This process transfers the AlGaN LED epi onto a new substrate by wafer-to-wafer bonding, and by removing the absorbing SiC substrate with a highly selective SF6 plasma etch that stops at the AlN buffer layer. We optimized the inductively coupled plasma (ICP) SF6 etch parameters to develop a substrate-removal process with high reliability and precise epitaxial control, without creating micromasking defects or degrading the health of the plasma etching system. The SiC etch rate by SF6 plasma was ~46 \mu m/hr at a high RF bias (400 W), and ~7 \mu m/hr at a low RF bias (49 W) with very high etch selectivity between SiC and AlN. The high SF6 etch selectivity between SiC and AlN was essential for removing the SiC substrate and exposing a pristine, smooth AlN surface. We demonstrated the epi-transfer process by fabricating high light extraction TFFC LEDs from AlGaN LEDs grown on SiC. To further enhance the light extraction, the exposed N-face AlN was anisotropically etched in dilute KOH. The LEE of the AlGaN LED improved by ~3X after KOH roughening at room temperature. This AlGaN TFFC LED process establishes a viable path to high external quantum efficiency (EQE) and power conversion efficiency (PCE) UV-C LEDs.Comment: 22 pages, 6 figures. (accepted in Semiconductor Science and Technology, SST-105156.R1 2018

    Seal Rotation Device – an Automated System for documenting Cylinder Seals

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    Cylinder seals are complex artifacts used in many early administrative systems especially in the Near East and Egypt. They are also linked to religious practices and concepts of identity. Several classical methods can be applied to document these objects, like photography, drawing and molding in plaster or plasticine. In addition to more recent methods like structured light scanning, we present an alternative method for 3D data acquisition. By combining existing technologies in a particular way, seals can be documented fast, cost efficiently and safe from a conservation viewpoint. This method developed at the Interdisciplinary Center for Scientific Computing (IWR) at Heidelberg University is a two-step procedure: first several series of images are obtained with a digital reflex camera in an automated way. The seal is mounted between two soft silicone buffers. An Arduino-based control unit rotates the seal using a stepper motor and triggers the camera. In the second step a 3D reconstruction of the seal is computed with the photogrammetric structure-from-motion approach. We will show first results acquired with this method both at the Petrie Museum of Egyptian Archaeology and the British Museum in London

    A conformal approach for the analysis of the non-linear stability of pure radiation cosmologies

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    The conformal Einstein equations for a tracefree (radiation) perfect fluid are derived in terms of the Levi-Civita connection of a conformally rescaled metric. These equations are used to provide a non-linear stability result for de Sitter-like tracefree (radiation) perfect fluid Friedman-Lema\^{\i}tre-Robertson-Walker cosmological models. The solutions thus obtained exist globally towards the future and are future geodesically complete.Comment: 21 page

    The structure of ORC–Cdc6 on an origin DNA reveals the mechanism of ORC activation by the replication initiator Cdc6

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    The Origin Recognition Complex (ORC) binds to sites in chromosomes to specify the location of origins of DNA replication. The S. cerevisiae ORC binds to specific DNA sequences throughout the cell cycle but becomes active only when it binds to the replication initiator Cdc6. It has been unclear at the molecular level how Cdc6 activates ORC, converting it to an active recruiter of the Mcm2-7 hexamer, the core of the replicative helicase. Here we report the cryo-EM structure at 3.3 Å resolution of the yeast ORC–Cdc6 bound to an 85-bp ARS1 origin DNA. The structure reveals that Cdc6 contributes to origin DNA recognition via its winged helix domain (WHD) and its initiator-specific motif. Cdc6 binding rearranges a short α-helix in the Orc1 AAA+ domain and the Orc2 WHD, leading to the activation of the Cdc6 ATPase and the formation of the three sites for the recruitment of Mcm2-7, none of which are present in ORC alone. The results illuminate the molecular mechanism of a critical biochemical step in the licensing of eukaryotic replication origins
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