Author Index
In: A Current Bibliography on African Affairs, Band 50, Heft 4, S. 345-353
ISSN: 2376-6662
In: A Current Bibliography on African Affairs, Band 50, Heft 4, S. 345-353
ISSN: 2376-6662
In: A Current Bibliography on African Affairs, Band 51, Heft 1, S. 66-76
ISSN: 2376-6662
In: A Current Bibliography on African Affairs, Band 51, Heft 2, S. 164-173
ISSN: 2376-6662
In: A Current Bibliography on African Affairs, Band 50, Heft 3, S. 252-261
ISSN: 2376-6662
This title is endorsed by Cambridge Assessment International Education to support the full syllabus for examination from 2020. Reinforce learning and deepen understanding of the key concepts covered in the latest syllabus; an ideal course companion or homework book for use throughout the course. - Develop and strengthen skills and knowledge with a wealth of additional exercises that perfectly supplement the Student's Book. - Build confidence with extra practice for each lesson to ensure that a topic is thoroughly understood before moving on. - Build a strong understanding of the main events of the course and the confidence to know how to use this knowledge. - Keep track of students' work with ready-to-go write-in exercises. - Save time with all answers available in the Online Teacher's Guide
In: Review of Pacific Basin Financial Markets and Policies, Band 21, Heft 4, S. 1899001
ISSN: 1793-6705
In: International political science abstracts: IPSA, Band 68, Heft 6, S. 895-936
ISSN: 1751-9292
Michael Lewis is a New York Times bestselling author who has written more than a dozen books on subjects ranging from politics to Wall Street. His recently released book, "Fifth Risk," explores mismanagement in federal government. His other books include "The Big Short," "Moneyball" and "The Blind Side" - all of which were made into movies. Another, "Liar's Poker," was based partly on his experience as a bond salesman at Salomon Brothers. Lewis is a sharp observer of politics, finance and the evolution of American culture, combining keen insight with a sharp sense of humor. He is a columnist for Bloomberg News and a contributing writer to Vanity Fair. His articles have also appeared in The New York Times Magazine, The New Yorker and Sports Illustrated.
BASE
In: Civil wars, Band 20, Heft 3, S. 451-453
ISSN: 1743-968X
In: Proceedings of the 27th ACM Conference on Information and Knowledge Management, S. 803-812
In this work, we address the problem of blocking in the context of author name disambiguation. We describe a framework that formalizes different ways of name-matching to determine which names could potentially refer to the same author. We focus on name variations that follow from specifying a name with different completeness (i.e. full first name or only initial). We extend this framework by a simple way to define traditional, new and custom blocking schemes. Then, we evaluate different old and new schemes in the Web of Science. In this context we define and compare a new type of blocking schemes. Based on these results, we discuss the question whether name-matching can be used in blocking evaluation as a replacement of annotated author identifiers. Finally, we argue that blocking can have a strong impact on the application and evaluation of author disambiguation.
Viroporins are viral proteins with ion channel (IC) activity that play an important role in several processes, including virus replication and pathogenesis. While many coronaviruses (CoVs) encode two viroporins, severe acute respiratory syndrome CoV (SARS-CoV) encodes three: proteins 3a, E, and 8a. Additionally, proteins 3a and E have a PDZ-binding motif (PBM), which can potentially bind over 400 cellular proteins which contain a PDZ domain, making them potentially important for the control of cell function. In the present work, a comparative study of the functional motifs included within the SARS-CoV viroporins was performed, mostly focusing on the roles of the IC and PBM of E and 3a proteins. ; This work was supported by grants from the Government of Spain (BIO2013-42869-R and BIO2016-75549-R AEI/FEDER, UE), the European Zoonotic Anticipation and Preparedness Initiative (ZAPI) (IMI_JU_115760), and the U.S. National Institutes of Health (NIH) (0258-3413/HHSN266200700010C awarded to L.E., 2P01AI060699 awarded to L.E. and S.P., and R01 AI129269 awarded to S.P.). V.M.A. and M.Q.M. are grateful for the support of the Government of Spain (FIS2013-40473-P and FIS2016-75257-P AEI/FEDER, UE) and Universitat Jaume I (P1.1B2015-28). C.C.R. received a contract from Fundación La Caixa.
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In: PS: political science & politics, Band 51, Heft 4, S. 866-869
ISSN: 1537-5935
In: 14th Greenhouse Gas Control Technologies Conference Melbourne 21-26 October 2018 (GHGT-14)
SSRN
Working paper
In: Feminist Legal Studies
Through a commentary on the enriching experience of receiving feedback through the Brewing Legal Times author-meets-reader session in February 2018, this piece reflects on the intellectual generosity and scholarly labour that makes such sessions an important form of academic social reproduction.
A standard feature of the contemporary internet landscape is the ability for people to comment on published content and to interact with other individuals, discussing the issues at hand and engaging with each other in debate. In this thesis, I describe a method for the automatic detection of author stances in online forums with respect to discussions on divisive, polarizing social issues, such as gun control and marriage equality {--} a task which is often unproblematic for human readers of the discourse. The research investigates the linguistic and rhetorical devices used by discussion participants to express their topic stance in the context of multi-party, multi-threaded discourse. Along the way, I address necessary sub-tasks in the author stance detection problem, such as the classification of the topic stance of an individual contribution to the discourse, and the assessment of the level of agreement or disagreement between adjacent posts {--} which is crucial, given the highly interactive nature of this genre. I also identify features that provide evidence of an author's topic stance from the very structure of the discourse, without any information at all from the text of the comments posted. The final model is a collective classifier that is able to synthesize all of the stance indicators provided by these different sources, deal with the inconsistencies in this information that may arise, and arrive at a single prediction of the topic stance for every participant in the discussion. The model has many applications in industry and public life, including more tailored newsfeeds, social network suggestions, and use in political fundraising or advocacy campaigns.
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