Aalto University

About: Aalto University is a education organization based out in Espoo, Finland. It is known for research contribution in the topics: Population & Carbon nanotube. The organization has 9969 authors who have published 32648 publications receiving 829626 citations. The organization is also known as: TKK & Aalto-korkeakoulu.

Blockchain Technology in Business and Information Systems Research

Abstract: The blockchain is a distributed ledger technology in the form of a distributed transactional database, secured by cryptography, and governed by a consensus mechanism. A blockchain is essentially a record of digital events. However, it is not ‘‘just a record,’’ since it can also contain socalled smart contracts, which are programs stored on the blockchain that run as implemented without any risk of downtime, censorship, or fraud (Buterin 2014). While blockchain is now seen mostly as the technology enabling cryptocurrencies such as Bitcoin, it will most likely become an even more valuable enabler of economic and social transactions, for instance as a general purpose digital asset ownership record (Lindman et al. 2017). This is because the distributed transaction data and cryptographic logic that lies at the blockchain’s core make it extraordinarily tamper-resistant. The implications of creating a reliable, trustworthy distributed record system, or ledger, may be fundamental to how we organize interpersonal and interorganizational relationships. The global economic system depends on that individuals and organizations trust other entities to create, store, and distribute essential records. For example, banks construct and maintain the financial records, hospitals construct and maintain health records, and universities construct and maintain education records. Often, records central to our health, social, or professional lives are key records either constructed or maintained by third parties. Such third-party record repositories can be vulnerable to corruption by failure in storage systems or human mischief, which could be mitigated by unbiased and incorruptible blockchain-based digital systems (Nærland et al. 2017). The financial sector leads the way in developing blockchain applications and business models; but also companies in industries from shipping and transportation to healthcare and entertainment are actively using blockchain applications to coordinate the movement of products, facilitate the creation of e-health records, and to securely manage original entertainment content. While substantial activity exists in practice, less academic research has examined the implications of blockchain for how we organize contemporary economies, society or organizations. In this special issue, we present early research results that investigate the positive implications of blockchain for modern organizations, specifically in the financial services industry or to manage physical asset ownership. However, the range of potential blockchain applications goes further to cover a multitude of business and social arrangements from tracking shipping containers and pharmaceuticals to recording gambling winnings and marriages based on smart contracts embedded in blockchain applications. Prof. Dr. R. Beck (&) IT University of Copenhagen, Copenhagen, Denmark e-mail: beck@itu.dk

Planck 2018 results - VI. Cosmological parameters (Corrigendum)

Abstract: Author(s): Aghanim, N; Akrami, Y; Ashdown, M; Aumont, J; Baccigalupi, C; Ballardini, M; Banday, AJ; Barreiro, RB; Bartolo, N; Basak, S; Battye, R; Benabed, K; Bernard, JP; Bersanelli, M; Bielewicz, P; Bock, JJ; Bond, JR; Borrill, J; Bouchet, FR; Boulanger, F; Bucher, M; Burigana, C; Butler, RC; Calabrese, E; Cardoso, JF; Carron, J; Challinor, A; Chiang, HC; Chluba, J; Colombo, LPL; Combet, C; Contreras, D; Crill, BP; Cuttaia, F; De Bernardis, P; De Zotti, G; Delabrouille, J; Delouis, JM; DI Valentino, E; DIego, JM; Dore, O; Douspis, M; Ducout, A; Dupac, X; Dusini, S; Efstathiou, G; Elsner, F; Enslin, TA; Eriksen, HK; Fantaye, Y; Farhang, M; Fergusson, J; Fernandez-Cobos, R; Finelli, F; Forastieri, F; Frailis, M; Fraisse, AA; Franceschi, E; Frolov, A; Galeotta, S; Galli, S; Ganga, K; Genova-Santos, RT; Gerbino, M; Ghosh, T; Gonzalez-Nuevo, J; Gorski, KM; Gratton, S; Gruppuso, A; Gudmundsson, JE; Hamann, J; Handley, W; Hansen, FK; Herranz, D; Hildebrandt, SR; Hivon, E; Huang, Z; Jaffe, AH; Jones, WC; Karakci, A; Keihanen, E; Keskitalo, R; Kiiveri, K; Kim, J; Kisner, TS | Abstract: In the original version, the bounds given in Eqs. (87a) and (87b) on the contribution to the early-time optical depth, (15,30), contained a numerical error in deriving the 95th percentile from the Monte Carlo samples. The corrected 95% upper bounds are: τ(15,30) l 0:018 (lowE, flat τ(15, 30), FlexKnot), (1) τ(15, 30) l 0:023 (lowE, flat knot, FlexKnot): (2) These bounds are a factor of 3 larger than the originally reported results. Consequently, the new bounds do not significantly improve upon previous results from Planck data presented in Millea a Bouchet (2018) as was stated, but are instead comparable. Equations (1) and (2) give results that are now similar to those of Heinrich a Hu (2021), who used the same Planck 2018 data to derive a 95% upper bound of 0.020 using the principal component analysis (PCA) model and uniform priors on the PCA mode amplitudes.