21 research outputs found
Probing interaction and spatial curvature in the holographic dark energy model
In this paper we place observational constraints on the interaction and
spatial curvature in the holographic dark energy model. We consider three kinds
of phenomenological interactions between holographic dark energy and matter,
i.e., the interaction term is proportional to the energy densities of dark
energy (), matter (), and matter plus dark energy
(). For probing the interaction and spatial curvature in
the holographic dark energy model, we use the latest observational data
including the type Ia supernovae (SNIa) Constitution data, the shift parameter
of the cosmic microwave background (CMB) given by the five-year Wilkinson
Microwave Anisotropy Probe (WMAP5) observations, and the baryon acoustic
oscillation (BAO) measurement from the Sloan Digital Sky Survey (SDSS). Our
results show that the interaction and spatial curvature in the holographic dark
energy model are both rather small. Besides, it is interesting to find that
there exists significant degeneracy between the phenomenological interaction
and the spatial curvature in the holographic dark energy model.Comment: 11 pages, 5 figures; to appear in JCA
Bio-analytical Assay Methods used in Therapeutic Drug Monitoring of Antiretroviral Drugs-A Review
TRY plant trait database â enhanced coverage and open access
Plant traitsâthe morphological, anatomical, physiological, biochemical and phenological characteristics of plantsâdetermine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of traitâbased plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traitsâalmost complete coverage for âplant growth formâ. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and traitâenvironmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives
Graphene aerogels: a simultaneous blend of high porosity and large electrical conductivity in a single material
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