scispace - formally typeset
Search or ask a question
Institution

University of St Andrews

EducationSt Andrews, Fife, United Kingdom
About: University of St Andrews is a education organization based out in St Andrews, Fife, United Kingdom. It is known for research contribution in the topics: Population & Laser. The organization has 16260 authors who have published 43364 publications receiving 1636072 citations. The organization is also known as: St Andrews University & University of St. Andrews.
Topics: Population, Laser, Planet, Galaxy, Stars


Papers
More filters
Journal ArticleDOI
TL;DR: It is demonstrated that bottlenose dolphins extract identity information from signature whistles even after all voice features have been removed from the signal, ensuring that dolphins are the only animals other than humans that have been shown to transmit identity information independent of the caller's voice or location.
Abstract: Bottlenose dolphins (Tursiops truncatus) develop individually distinctive signature whistles that they use to maintain group cohesion. Unlike the development of identification signals in most other species, signature whistle development is strongly influenced by vocal learning. This learning ability is maintained throughout life, and dolphins frequently copy each other's whistles in the wild. It has been hypothesized that signature whistles can be used as referential signals among conspecifics, because captive bottlenose dolphins can be trained to use novel, learned signals to label objects. For this labeling to occur, signature whistles would have to convey identity information independent of the caller's voice features. However, experimental proof for this hypothesis has been lacking. This study demonstrates that bottlenose dolphins extract identity information from signature whistles even after all voice features have been removed from the signal. Thus, dolphins are the only animals other than humans that have been shown to transmit identity information independent of the caller's voice or location.

321 citations

Journal ArticleDOI
TL;DR: In this paper, the authors studied the behavior of coronal jets, which are the source of significant mass and energy input to the upper solar atmosphere and the solar wind, and provided critical insight for understanding the larger, more complex drivers of the solar activity.
Abstract: Coronal jets represent important manifestations of ubiquitous solar transients, which may be the source of significant mass and energy input to the upper solar atmosphere and the solar wind. While the energy involved in a jet-like event is smaller than that of "nominal" solar flares and coronal mass ejections (CMEs), jets share many common properties with these phenomena, in particular, the explosive magnetically driven dynamics. Studies of jets could, therefore, provide critical insight for understanding the larger, more complex drivers of the solar activity. On the other side of the size-spectrum, the study of jets could also supply important clues on the physics of transients close or at the limit of the current spatial resolution such as spicules. Furthermore, jet phenomena may hint to basic process for heating the corona and accelerating the solar wind; consequently their study gives us the opportunity to attack a broad range of solar-heliospheric problems.

321 citations

Book ChapterDOI
12 Jun 2011
TL;DR: NextPlace is presented, a novel approach to location prediction based on nonlinear time series analysis of the arrival and residence times of users in relevant places that achieves higher performance compared to other predictors and also more stability over time.
Abstract: Accurate and fine-grained prediction of future user location and geographical profile has interesting and promising applications including targeted content service, advertisement dissemination for mobile users, and recreational social networking tools for smart-phones. Existing techniques based on linear and probabilistic models are not able to provide accurate prediction of the location patterns from a spatio-temporal perspective, especially for long-term estimation. More specifically, they are able to only forecast the next location of a user, but not his/her arrival time and residence time, i.e., the interval of time spent in that location. Moreover, these techniques are often based on prediction models that are not able to extend predictions further in the future. In this paper we present NextPlace, a novel approach to location prediction based on nonlinear time series analysis of the arrival and residence times of users in relevant places. NextPlace focuses on the predictability of single users when they visit their most important places, rather than on the transitions between different locations. We report about our evaluation using four different datasets and we compare our forecasting results to those obtained by means of the prediction techniques proposed in the literature. We show how we achieve higher performance compared to other predictors and also more stability over time, with an overall prediction precision of up to 90% and a performance increment of at least 50% with respect to the state of the art.

320 citations

Journal ArticleDOI
TL;DR: A comprehensive overview of the current understanding of potential exoplanet biosignatures, including gaseous, surface, and temporal signatures, can be found in this article, with a focus on recent advances in assessing biosignature plausibility.
Abstract: In the coming years and decades, advanced space- and ground-based observatories will allow an unprecedented opportunity to probe the atmospheres and surfaces of potentially habitable exoplanets for signatures of life. Life on Earth, through its gaseous products and reflectance and scattering properties, has left its fingerprint on the spectrum of our planet. Aided by the universality of the laws of physics and chemistry, we turn to Earth's biosphere, both in the present and through geologic time, for analog signatures that will aid in the search for life elsewhere. Considering the insights gained from modern and ancient Earth, and the broader array of hypothetical exoplanet possibilities, we have compiled a comprehensive overview of our current understanding of potential exoplanet biosignatures, including gaseous, surface, and temporal biosignatures. We additionally survey biogenic spectral features that are well known in the specialist literature but have not yet been robustly vetted in the context of exoplanet biosignatures. We briefly review advances in assessing biosignature plausibility, including novel methods for determining chemical disequilibrium from remotely obtainable data and assessment tools for determining the minimum biomass required to maintain short-lived biogenic gases as atmospheric signatures. We focus particularly on advances made since the seminal review by Des Marais et al. The purpose of this work is not to propose new biosignature strategies, a goal left to companion articles in this series, but to review the current literature, draw meaningful connections between seemingly disparate areas, and clear the way for a path forward.

320 citations


Authors

Showing all 16531 results

NameH-indexPapersCitations
Yi Chen2174342293080
Paul M. Thompson1832271146736
Ian J. Deary1661795114161
Dongyuan Zhao160872106451
Mark J. Smyth15371388783
Harry Campbell150897115457
William J. Sutherland14896694423
Thomas J. Smith1401775113919
John A. Peacock140565125416
Jean-Marie Tarascon136853137673
David A. Jackson136109568352
Ian Ford13467885769
Timothy J. Mitchison13340466418
Will J. Percival12947387752
David P. Lane12956890787
Network Information
Related Institutions (5)
University of Oxford
258.1K papers, 12.9M citations

94% related

University of Cambridge
282.2K papers, 14.4M citations

94% related

University of Edinburgh
151.6K papers, 6.6M citations

93% related

University of Manchester
168K papers, 6.4M citations

93% related

University College London
210.6K papers, 9.8M citations

93% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023127
2022387
20211,998
20201,996
20192,059
20181,946