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Institution

University College Cork

EducationCork, Ireland
About: University College Cork is a education organization based out in Cork, Ireland. It is known for research contribution in the topics: Population & Context (language use). The organization has 12056 authors who have published 28452 publications receiving 958414 citations. The organization is also known as: Coláiste na hOllscoile Corcaigh & National University of Ireland, Cork.


Papers
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Journal ArticleDOI
TL;DR: This review summarizes each solid-state nanopore fabrication technique reported to date, and compares their advantages and disadvantages, followed by a discussion of approaches used to measure pore size, geometry and surface properties.

208 citations

Journal ArticleDOI
TL;DR: In this paper, the authors developed an atomistic, nearest-neighbor tight-binding Hamiltonian to investigate the electronic structure of dilute bismide alloys of GaP and GaAs and demonstrated that the observed strong variation of the band gap and spin-orbit-splitting energy with Bi composition can be well explained in terms of a BAC interaction between the extended states of the GaAs valence band edge and highly localized Bi-related defect states lying in the band, with the change in ${E}_{g}$ also having a significant contribution from a
Abstract: We develop an atomistic, nearest-neighbor $s{p}^{3}{s}^{*}$ tight-binding Hamiltonian to investigate the electronic structure of dilute bismide alloys of GaP and GaAs. Using this model, we calculate that the incorporation of dilute concentrations of Bi in GaP introduces Bi-related defect states in the band gap, which interact with the host matrix valence band edge via a Bi composition dependent band anticrossing (BAC) interaction. By extending this analysis to GaBi${}_{x}$As${}_{1\ensuremath{-}x}$, we demonstrate that the observed strong variation of the band gap $({E}_{g})$ and spin-orbit-splitting energy $({\ensuremath{\Delta}}_{\text{SO}})$ with Bi composition can be well explained in terms of a BAC interaction between the extended states of the GaAs valence band edge and highly localized Bi-related defect states lying in the valence band, with the change in ${E}_{g}$ also having a significant contribution from a conventional alloy reduction in the conduction band edge energy. Our calculated values of ${E}_{g}$ and ${\ensuremath{\Delta}}_{\text{SO}}$ are in good agreement with experiment throughout the investigated composition range ($x\ensuremath{\le}13$%). In particular, our calculations reproduce the experimentally observed crossover to an ${E}_{g}l{\ensuremath{\Delta}}_{\text{SO}}$ regime at approximately 10.5% Bi composition in bulk GaBi${}_{x}$As${}_{1\ensuremath{-}x}$. Recent x-ray spectroscopy measurements have indicated the presence of Bi pairs and clusters even for Bi compositions as low as 2%. We include a systematic study of different Bi nearest-neighbor environments in the alloy to achieve a quantitative understanding of the effect of Bi pairing and clustering on the GaBi${}_{x}$As${}_{1\ensuremath{-}x}$ electronic structure.

208 citations

Journal ArticleDOI
Patrick F. Fox1, J M Wallace1, S Morgan1, C M Lynch1, E J Niland1, J Tobin1 
TL;DR: In this article, the advantages, limitations, technical feasibility and commercial potential of these methods are discussed and compared, and the principal methods by which this may be achieved are: an elevated ripening temperature, modified starters, exogenous enzymes and cheese slurries.
Abstract: The characteristic aroma, flavour and texture of cheese develop during ripening of the cheese curd through the action of numerous enzymes derived from the cheese milk, the coagulant, starter and non-starter bacteria. Ripening is a slow and consequently an expensive process that is not fully predictable or controllable. Consequently, there are economic and possibly technological incentives to accelerate ripening. The principal methods by which this may be achieved are: an elevated ripening temperature, modified starters, exogenous enzymes and cheese slurries. The advantages, limitations, technical feasibility and commercial potential of these methods are discussed and compared.

208 citations

Journal ArticleDOI
TL;DR: The evolutionary ecology of cognition in wild populations is a rapidly expanding interdisciplinary field providing many opportunities for advancing the understanding of how cognitive abilities have evolved, and how an evolutionary ecological framework, more generally, along with innovative technologies has the potential to revolutionise the study of Cognition in the wild.
Abstract: Cognition is defined as the processes by which animals collect, retain and use information from their environment to guide their behaviour. Thus cognition is essential in a wide range of behaviours, including foraging, avoiding predators and mating. Despite this pivotal role, the evolutionary processes shaping variation in cognitive performance among individuals in wild populations remain very poorly understood. Selection experiments in captivity suggest that cognitive traits can have substantial heritability and can undergo rapid evolution. However only a handful of studies have attempted to explore how cognition influences life-history variation and fitness in the wild, and direct evidence for the action of natural or sexual selection on cognition is still lacking, reasons for which are diverse. Here we review the current literature with a view to: (i) highlighting the key practical and conceptual challenges faced by the field; (ii) describing how to define and measure cognitive traits in natural populations, and suggesting which species, populations and cognitive traits might be examined to greatest effect; emphasis is placed on selecting traits that are linked to functional behaviour; (iii) discussing how to deal with confounding factors such as personality and motivation in field as well as captive studies; (iv) describing how to measure and interpret relationships between cognitive performance, functional behaviour and fitness, offering some suggestions as to when and what kind of selection might be predicted; and (v) showing how an evolutionary ecological framework, more generally, along with innovative technologies has the potential to revolutionise the study of cognition in the wild. We conclude that the evolutionary ecology of cognition in wild populations is a rapidly expanding interdisciplinary field providing many opportunities for advancing the understanding of how cognitive abilities have evolved.

207 citations

Journal ArticleDOI
TL;DR: A possible synthesis of Skinner’s (1957) treatment of verbal behavior with the more recent behavioral interpretation of language known as relational frame theory is suggested.
Abstract: The current article suggests a possible synthesis of Skinner's (1957) treatment of verbal behavior with the more recent behavioral interpretation of language known as relational frame theory. The rationale for attempting to combine these two approaches is first outlined. Subsequently, each of the verbal operants described by Skinner is examined and subjected to a relational frame analysis. In each case, two types of operants are identified; one based on direct contingencies of reinforcement and the other based on arbitrarily applicable relational responding. The latter operants are labeled verbal because they can be distinguished from other forms of social behavior, and they appear to possess the symbolic or referential qualities often ascribed to human language. By applying relational frame theory to Skinner's verbal operants, we aim to contribute towards the development of a modern behavior-analytic research agenda in human language and cognition.

207 citations


Authors

Showing all 12300 results

NameH-indexPapersCitations
Stephen J. O'Brien153106293025
James J. Collins15166989476
J. Wouter Jukema12478561555
John F. Cryan12472358938
Fergus Shanahan11770551963
Timothy G. Dinan11668960561
John M. Starr11669548761
Gordon G. Wallace114126769095
Colin Hill11269354484
Robert Clarke11151290049
Douglas B. Kell11163450335
Thomas Bein10967742800
Steven C. Hayes10645051556
Åke Borg10544453835
Eamonn Martin Quigley10368539585
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202381
2022400
20212,153
20201,927
20191,679
20181,618