Learning to bypass the central bottleneck: Declining automaticity with advancing age.

2010 ◽  
Vol 25 (1) ◽  
pp. 177-192 ◽  
Author(s):  
François Maquestiaux ◽  
Maude Laguë-Beauvais ◽  
Eric Ruthruff ◽  
Alan Hartley ◽  
Louis Bherer
Keyword(s):  
Central Bottleneck

scholarly journals Dynamics of the Central Bottleneck: Dual-Task and Task Uncertainty

PLoS Biology ◽  
2006 ◽  
Vol 4 (7) ◽  
pp. e220 ◽  
Author(s):  
Mariano Sigman ◽  
Stanislas Dehaene
Keyword(s):  
Dual Task ◽  
Task Uncertainty ◽  
Central Bottleneck ◽  
And Task

Mental rotation, memory scanning, and the central bottleneck

1999 ◽  
Vol 62 (1) ◽  
pp. 48-61 ◽  
Author(s):  
Martin Heil ◽  
Karina Wahl ◽  
Michael Herbst
Keyword(s):  
Mental Rotation ◽  
Memory Scanning ◽  
Central Bottleneck

scholarly journals Congestion in a city with a central bottleneck

2012 ◽  
Vol 71 (3) ◽  
pp. 269-277 ◽  
Author(s):  
Mogens Fosgerau ◽  
André de Palma
Keyword(s):  
Central Bottleneck

Through the portal: Effect anticipation in the central bottleneck

2015 ◽  
Vol 160 ◽  
pp. 141-151 ◽  
Author(s):  
Robert Wirth ◽  
Roland Pfister ◽  
Markus Janczyk ◽  
Wilfried Kunde
Keyword(s):  
Central Bottleneck

scholarly journals Semantic micro-contributions with decentralized nanopublication services

2021 ◽  
Vol 7 ◽  
pp. e387
Author(s):  
Tobias Kuhn ◽  
Ruben Taelman ◽  
Vincent Emonet ◽  
Haris Antonatos ◽  
Stian Soiland-Reyes ◽  
...  
Keyword(s):  
Linked Data ◽  
Prior Experience ◽  
Data Publishing ◽  
Efficient Manner ◽  
Heavy Weight ◽  
Weight One ◽  
Central Bottleneck ◽  
User Friendly

While the publication of Linked Data has become increasingly common, the process tends to be a relatively complicated and heavy-weight one. Linked Data is typically published by centralized entities in the form of larger dataset releases, which has the downside that there is a central bottleneck in the form of the organization or individual responsible for the releases. Moreover, certain kinds of data entries, in particular those with subjective or original content, currently do not fit into any existing dataset and are therefore more difficult to publish. To address these problems, we present here an approach to use nanopublications and a decentralized network of services to allow users to directly publish small Linked Data statements through a simple and user-friendly interface, called Nanobench, powered by semantic templates that are themselves published as nanopublications. The published nanopublications are cryptographically verifiable and can be queried through a redundant and decentralized network of services, based on the grlc API generator and a new quad extension of Triple Pattern Fragments. We show here that these two kinds of services are complementary and together allow us to query nanopublications in a reliable and efficient manner. We also show that Nanobench makes it indeed very easy for users to publish Linked Data statements, even for those who have no prior experience in Linked Data publishing.

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