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Institution

University of Bath

EducationBath, Bath and North East Somerset, United Kingdom
About: University of Bath is a education organization based out in Bath, Bath and North East Somerset, United Kingdom. It is known for research contribution in the topics: Population & Photonic-crystal fiber. The organization has 15830 authors who have published 39608 publications receiving 1358769 citations. The organization is also known as: Bath University.


Papers
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Journal ArticleDOI
TL;DR: In this article, the authors examine and evaluate methods and assumptions used by the economic studies and compare ex-ante models and forecasts with the ex-post approach to improve the information available to policy makers and potential future hosts of Summer Olympics and other mega-events.
Abstract: As the Summer Olympics are growing with larger media coverage and sponsorship, host cities have started to attach great importance to the tourism and other likely economic effects that occur by staging such a special event As a result, a number of studies have been conducted to consider the various economic implications on the hosts This paper examines and evaluates methods and assumptions used by the economic studies It also compares ex-ante models and forecasts with the ex-post approach The aim is to improve the information available to policy makers and potential future hosts of Summer Olympics and other mega-events Copyright © 2003 John Wiley & Sons, Ltd

326 citations

Journal ArticleDOI
TL;DR: There was a significant negative relationship between the resulting density of Serratia marcescens and the number of symbiotic gut bacterial species present, and this outcome is consistent with the predictions of community ecology theory that species-rich communities are more resistant to invasion than species-poor communities.
Abstract: Diversity-invasibility relationships were explored in the novel context of the colonization resistance provided by gut bacteria of the desert locust Schistocerca gregaria against pathogenic bacteria. Germ-free insects were associated with various combinations of one to three species of locust gut bacteria and then fed an inoculum of the pathogenic bacterium Serratia marcescens. There was a significant negative relationship between the resulting density of Serratia marcescens and the number of symbiotic gut bacterial species present. Likewise there was a significant inverse relationship between community diversity and the proportion of locusts that harboured Serratia. Host mortality was not negatively correlated with resistance to gut-invasion by Serratia marcescens, although there were significantly more deaths among pathogen fed germ-free insects than tri-associated gnotobiotes. The outcome is consistent with the predictions of community ecology theory that species-rich communities are more resistant to invasion than species-poor communities.

324 citations

Journal ArticleDOI
TL;DR: An approach is implemented to assess the goodness of fit of the model using the ancestry “palettes” estimated by CHROMOPAINTER and apply it to both simulated data and real case studies, allowing a richer and more robust analysis of recent demographic history.
Abstract: Genetic clustering algorithms, implemented in programs such as STRUCTURE and ADMIXTURE, have been used extensively in the characterisation of individuals and populations based on genetic data. A successful example is the reconstruction of the genetic history of African Americans as a product of recent admixture between highly differentiated populations. Histories can also be reconstructed using the same procedure for groups that do not have admixture in their recent history, where recent genetic drift is strong or that deviate in other ways from the underlying inference model. Unfortunately, such histories can be misleading. We have implemented an approach, badMIXTURE, to assess the goodness of fit of the model using the ancestry “palettes” estimated by CHROMOPAINTER and apply it to both simulated data and real case studies. Combining these complementary analyses with additional methods that are designed to test specific hypotheses allows a richer and more robust analysis of recent demographic history.

324 citations

Journal ArticleDOI
TL;DR: In this paper, the synthesis, structures and properties of mixed-component metal-organic frameworks (MC-MOFs) are described, and some of the potential benefits in functionality that these materials have are highlighted.
Abstract: Mixed-component metal–organic frameworks (MC-MOFs) are metal–organic frameworks that have different linkers or metals with the same structural role. Many of these mixed-ligand or mixed-metal MOFs are solid solutions, in which the proportions of the ligands or metals can be adjusted or even controlled. These MC-MOFs can be prepared directly, using more than one metal or ligand in the synthesis, or formed by post-synthetic modification. A second class of MC-MOFs have core–shell structures, and these can be prepared through epitaxial growth of one MOF on the surface of another or post-synthetic modification of the crystal surfaces. This review describes the syntheses, structures and properties of mixed-ligand, mixed-metal and core–shell MOFs, and highlights some of the potential benefits in functionality that these materials have.

324 citations

Journal ArticleDOI
TL;DR: This paper aims to illustrate with practical, real-world scenarios and examples from the literature the different GIS methods and uses to improve community health and healthcare practices, and to discuss challenges and problems currently hindering the wide-scale adoption of GIS across the NHS.
Abstract: The term "Geographic Information Systems" (GIS) has been added to MeSH in 2003, a step reflecting the importance and growing use of GIS in health and healthcare research and practices. GIS have much more to offer than the obvious digital cartography (map) functions. From a community health perspective, GIS could potentially act as powerful evidence-based practice tools for early problem detection and solving. When properly used, GIS can: inform and educate (professionals and the public); empower decision-making at all levels; help in planning and tweaking clinically and cost-effective actions, in predicting outcomes before making any financial commitments and ascribing priorities in a climate of finite resources; change practices; and continually monitor and analyse changes, as well as sentinel events. Yet despite all these potentials for GIS, they remain under-utilised in the UK National Health Service (NHS). This paper has the following objectives: (1) to illustrate with practical, real-world scenarios and examples from the literature the different GIS methods and uses to improve community health and healthcare practices, e.g., for improving hospital bed availability, in community health and bioterrorism surveillance services, and in the latest SARS outbreak; (2) to discuss challenges and problems currently hindering the wide-scale adoption of GIS across the NHS; and (3) to identify the most important requirements and ingredients for addressing these challenges, and realising GIS potential within the NHS, guided by related initiatives worldwide. The ultimate goal is to illuminate the road towards implementing a comprehensive national, multi-agency spatio-temporal health information infrastructure functioning proactively in real time. The concepts and principles presented in this paper can be also applied in other countries, and on regional (e.g., European Union) and global levels.

324 citations


Authors

Showing all 16056 results

NameH-indexPapersCitations
Michael Grätzel2481423303599
Brenda W.J.H. Penninx1701139119082
Amartya Sen149689141907
Gilbert Laporte12873062608
Andre K. Geim125445206833
Matthew Jones125116196909
Benoît Roux12049362215
Stephen Mann12066955008
Bruno S. Frey11990065368
Raymond A. Dwek11860352259
David Cutts11477864215
John Campbell107115056067
David Chandler10742452396
Peter H.R. Green10684360113
Huajian Gao10566746748
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202386
2022404
20212,474
20202,371
20192,144
20181,972