Influence of ground surface characteristics on the mean radiant temperature in urban areas

The effect of variations in land cover on mean radiant surface temperature (Tmrt) is explored through a simple scheme developed within the radiation model SOLWEIG. Outgoing longwave radiation is parameterised using surface temperature observations on a grass and an asphalt surface, whereas outgoing shortwave radiation is modelled through variations in albedo for the different surfaces. The influence of surface materials on Tmrt is small compared to the effects of shadowing. Nevertheless, altering ground surface materials could contribute to a reduction on Tmrt to reduce the radiant load during heat-wave episodes in locations where shadowing is not an option. Evaluation of the new scheme suggests that despite its simplicity it can simulate the outgoing fluxes well, especially during sunny conditions. However, it underestimates at night and in shadowed locations. One grass surface used to develop the parameterisation, with very different characteristics compared to an evaluation grass site, caused Tmrt to be underestimated. The implications of using high resolution (e.g. 15 minutes) temporal forcing data under partly cloudy conditions are demonstrated even for fairly proximal sites

Transplanting the leafy liverwort Herbertus hutchinsiae : A suitable conservation tool to maintain oceanic-montane liverwort-rich heath?

Thanks to the relevant landowners and managers for permission to carry out the experiments, Chris Preston for helping to obtain the liverwort distribution records and the distribution map, Gordon Rothero and Dave Horsfield for advice on choosing experimental sites and Alex Douglas for statistical advice. Juliane Geyer’s help with fieldwork was greatly appreciated. This study was made possible by a NERC PhD studentship and financial support from the Royal Botanic Garden Edinburgh and Scottish Natural Heritage.Peer reviewedPostprin

Chirped pulse Raman amplification in warm plasma: towards controlling saturation

Stimulated Raman backscattering in plasma is potentially an efficient method of amplifying laser pulses to reach exawatt powers because plasma is fully broken down and withstands extremely high electric fields. Plasma also has unique nonlinear optical properties that allow simultaneous compression of optical pulses to ultra-short durations. However, current measured efficiencies are limited to several percent. Here we investigate Raman amplification of short duration seed pulses with different chirp rates using a chirped pump pulse in a preformed plasma waveguide. We identify electron trapping and wavebreaking as the main saturation mechanisms, which lead to spectral broadening and gain saturation when the seed reaches several millijoules for durations of 10's - 100's fs for 250 ps, 800 nm chirped pump pulses. We show that this prevents access to the nonlinear regime and limits the efficiency, and interpret the experimental results using slowly-varying-amplitude, current-averaged particle-in-cell simulations. We also propose methods for achieving higher efficiencies.close0

Mapping data elements to terminological resources for integrating biomedical data sources

BACKGROUND: Data integration is a crucial task in the biomedical domain and integrating data sources is one approach to integrating data. Data elements (DEs) in particular play an important role in data integration. We combine schema- and instance-based approaches to mapping DEs to terminological resources in order to facilitate data sources integration. METHODS: We extracted DEs from eleven disparate biomedical sources. We compared these DEs to concepts and/or terms in biomedical controlled vocabularies and to reference DEs. We also exploited DE values to disambiguate underspecified DEs and to identify additional mappings. RESULTS: 82.5% of the 474 DEs studied are mapped to entries of a terminological resource and 74.7% of the whole set can be associated with reference DEs. Only 6.6% of the DEs had values that could be semantically typed. CONCLUSION: Our study suggests that the integration of biomedical sources can be achieved automatically with limited precision and largely facilitated by mapping DEs to terminological resources

Species interactions in a grassland mixture under low nitrogen fertilization and two cutting frequencies:I. dry-matter yield and dynamics of species composition

acceptedVersio

Memória Organizacional de Comunidades de Prática como Fator de Vantagem Competitiva das Organizações

Este artigo apresenta uma análise de referências e estudo de caso sobre memória organizacional em Comunidades de Prática (CoP) como fator competitivo nas organizações. Inicia conceituando e analisando o papel da memória organizacional na gestão do conhecimento, a visão das comunidades de práticas e suas interações nas organizações. Mostra como a construção da memória organizacional é de fundamental importância nas organizações de sucesso e que estão na vanguarda tecnológica. A pesquisa realizada reflete a visibilidade de seus envolvidos: empregados e colaboradores, como também de seus líderes, identificando os principais fatores de vantagem competitiva e demonstrando suas percepções de influência no negócio. Os resultados obtidos evidenciam o potencial das CoPs para os negócios e vantagem competitiva, ao ampliarem a capacidade de atuação de equipes de projetos. Conclui-se que CoPs são elementos chave para construção do capital social que serve para possibilitar o compartilhamento de conhecimento e promover inovação

An automatic method to generate domain-specific investigator networks using PubMed abstracts

<p>Abstract</p> <p>Background</p> <p>Collaboration among investigators has become critical to scientific research. This includes ad hoc collaboration established through personal contacts as well as formal consortia established by funding agencies. Continued growth in online resources for scientific research and communication has promoted the development of highly networked research communities. Extending these networks globally requires identifying additional investigators in a given domain, profiling their research interests, and collecting current contact information. We present a novel strategy for building investigator networks dynamically and producing detailed investigator profiles using data available in PubMed abstracts.</p> <p>Results</p> <p>We developed a novel strategy to obtain detailed investigator information by automatically parsing the affiliation string in PubMed records. We illustrated the results by using a published literature database in human genome epidemiology (HuGE Pub Lit) as a test case. Our parsing strategy extracted country information from 92.1% of the affiliation strings in a random sample of PubMed records and in 97.0% of HuGE records, with accuracies of 94.0% and 91.0%, respectively. Institution information was parsed from 91.3% of the general PubMed records (accuracy 86.8%) and from 94.2% of HuGE PubMed records (accuracy 87.0). We demonstrated the application of our approach to dynamic creation of investigator networks by creating a prototype information system containing a large database of PubMed abstracts relevant to human genome epidemiology (HuGE Pub Lit), indexed using PubMed medical subject headings converted to Unified Medical Language System concepts. Our method was able to identify 70–90% of the investigators/collaborators in three different human genetics fields; it also successfully identified 9 of 10 genetics investigators within the PREBIC network, an existing preterm birth research network.</p> <p>Conclusion</p> <p>We successfully created a web-based prototype capable of creating domain-specific investigator networks based on an application that accurately generates detailed investigator profiles from PubMed abstracts combined with robust standard vocabularies. This approach could be used for other biomedical fields to efficiently establish domain-specific investigator networks.</p

An open source infrastructure for managing knowledge and finding potential collaborators in a domain-specific subset of PubMed, with an example from human genome epidemiology

<p>Abstract</p> <p>Background</p> <p>Identifying relevant research in an ever-growing body of published literature is becoming increasingly difficult. Establishing domain-specific knowledge bases may be a more effective and efficient way to manage and query information within specific biomedical fields. Adopting controlled vocabulary is a critical step toward data integration and interoperability in any information system. We present an open source infrastructure that provides a powerful capacity for managing and mining data within a domain-specific knowledge base. As a practical application of our infrastructure, we presented two applications – Literature Finder and Investigator Browser – as well as a tool set for automating the data curating process for the human genome published literature database. The design of this infrastructure makes the system potentially extensible to other data sources.</p> <p>Results</p> <p>Information retrieval and usability tests demonstrated that the system had high rates of recall and precision, 90% and 93% respectively. The system was easy to learn, easy to use, reasonably speedy and effective.</p> <p>Conclusion</p> <p>The open source system infrastructure presented in this paper provides a novel approach to managing and querying information and knowledge from domain-specific PubMed data. Using the controlled vocabulary UMLS enhanced data integration and interoperability and the extensibility of the system. In addition, by using MVC-based design and Java as a platform-independent programming language, this system provides a potential infrastructure for any domain-specific knowledge base in the biomedical field.</p