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Triplet energy back transfer in conjugated polymers with pendant phosphorescent iridium complexes
(2006)
The nature of Dexter triplet energy transfer between bonded systems of a red phosphorescent iridium complex 13 and a conjugated polymer, polyfluorene, has been investigated in electrophosphorescent organic light-emitting diodes. Red- emitting phosphorescent iridium complexes based on the [Ir(btp)2(acac)]fragment (where btp is 2-(2 '- benzo[b]thienyl)pyridinato and acac is acetylacetonate) have been attached either directly (spacerless) or through a - (CH2)(8)-chain (octamethylene-tethered) at the 9-position of a 9-octylfluorene host. The resulting dibromo- functionalized spacerless (8) or octamethylene-tethered (12) fluorene monomers were chain extended by Suzuki polycondensations using the bis(boronate)-terminated fluorene macromonomers 16 in the presence of end-capping chlorobenzene solvent to produce the statistical spacerless (17) and octamethylene-tethered ( 18) copolymers containing an even dispersion of the pendant phosphorescent fragments. The spacerless monomer 12 adopts a face-to-face conformation with a separation of only 3.6 angstrom between the iridium complex and fluorenyl group, as shown by X-ray analysis of a single crystal, and this facilitates intramolecular triplet energy transfer in the spacerless copolymers 17. The photo- and electroluminescence efficiencies of the octamethylene-tethered copolymers 18 are double those of the spacerless copolymers 17, and this is consistent with suppression of the back transfer of triplets from the red phosphorescent iridium complex to the polyfluorene backbone in 18. The incorporation of a -(CH2)(8)- chain between the polymer host and phosphorescent guest is thus an important design principle for achieving higher efficiencies in those electrophosphorescent organic light-emitting diodes for which the triplet energy levels of the host and guest are similar
In population ecology, there has been a fundamental controversy about the relative importance of competition- driven (density-dependent) population regulation vs. abiotic influences such as temperature and precipitation. The same issue arises at the community level; are population sizes driven primarily by changes in the abundances of cooccurring competitors (i.e., compensatory dynamics), or do most species have a common response to environmental factors? Competitive interactions have had a central place in ecological theory, dating back to Gleason, Volterra, Hutchison and MacArthur, and, more recently, Hubbell's influential unified neutral theory of biodiversity and biogeography. If competitive interactions are important in driving year-to-year fluctuations in abundance, then changes in the abundance of one species should generally be accompanied by compensatory changes in the abundances of others. Thus, one necessary consequence of strong compensatory forces is that, on average, species within communities will covary negatively. Here we use measures of community covariance to assess the prevalence of negative covariance in 41 natural communities comprising different taxa at a range of spatial scales. We found that species in natural communities tended to covary positively rather than negatively, the opposite of what would be expected if compensatory dynamics were important. These findings suggest that abiotic factors such as temperature and precipitation are more important than competitive interactions in driving year-to-year fluctuations in species abundance within communities.
A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others ('reinventing the wheel'). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available ('having tunnel vision'). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: super-individual models (Piscator, Charisma), physiologically structured models, stage-structured models and traitbased models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its 'leading principle', there are many opportunities for combining approaches. We take the point of view that a single 'right' approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative view on the functioning of lake ecosystems. We end with a set of specific recommendations that may be of help in the further development of lake ecosystem models.
A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others ('reinventing the wheel'). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available ('having tunnel vision'). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: super-individual models (Piscator, Charisma), physiologically structured models, stage-structured models and traitbased models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its 'leading principle', there are many opportunities for combining approaches. We take the point of view that a single 'right' approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative view on the functioning of lake ecosystems. We end with a set of specific recommendations that may be of help in the further development of lake ecosystem models.
We have developed lists of likely B3-A0 stars (called "late B" stars) in the young cluster Trumpler 16. The following criteria were used: location within 3' of eta Car, an appropriate V and B - V combination, and proper motion (where available). Color and magnitude cuts have been made assuming an E(B - V) = 0.55 mag +/- 0.1, which is a good approximation close to the center of Trumpler 16. These lists have been cross-correlated with X-ray sources found in the Chandra Carina Complex Project. Previous studies have shown that only very rarely (if at all) do late main-sequence B stars produce X-rays. We present evidence that the X-ray-detected sources are binaries with low-mass companions, since stars less massive than 1.4 M-circle dot are strong X-ray sources at the age of the cluster. Both the median X-ray energies and X-ray luminosities of these sources are in good agreement with values for typical low-mass coronal X-ray sources. We find that 39% of the late B stars based on a list with proper motions have low-mass companions. Similarly, 32% of a sample without proper motions have low-mass companions. We discuss the X-ray detection completeness. These results on low-mass companions of intermediate-mass stars are complementary to spectroscopic and interferometric results and probe new parameter space of low-mass companions at all separations. They do not support a steeply rising distribution of mass ratios to low masses for intermediate-mass (5 M-circle dot) primaries, such as would be found by random pairing from the initial mass function.
The Great Nebula in Carina provides an exceptional view into the violent massive star formation and feedback that typifies giant H II regions and starburst galaxies. We have mapped the Carina star-forming complex in X-rays, using archival Chandra data and a mosaic of 20 new 60 ks pointings using the Chandra X-ray Observatory's Advanced CCD Imaging Spectrometer, as a testbed for understanding recent and ongoing star formation and to probe Carina's regions of bright diffuse X-ray emission. This study has yielded a catalog of properties of > 14,000 X-ray point sources;> 9800 of them have multiwavelength counterparts. Using Chandra's unsurpassed X-ray spatial resolution, we have separated these point sources from the extensive, spatially-complex diffuse emission that pervades the region; X-ray properties of this diffuse emission suggest that it traces feedback from Carina's massive stars. In this introductory paper, we motivate the survey design, describe the Chandra observations, and present some simple results, providing a foundation for the 15 papers that follow in this special issue and that present detailed catalogs, methods, and science results.
To identify genetic variants associated with head circumference in infancy, we performed a meta-analysis of seven genome-wide association studies (GWAS) (N = 10,768 individuals of European ancestry enrolled in pregnancy and/or birth cohorts) and followed up three lead signals in six replication studies (combined N = 19,089). rs7980687 on chromosome 12q24 (P = 8.1 x 10(-9)) and rs1042725 on chromosome 12q15 (P = 2.8 x 10(-10)) were robustly associated with head circumference in infancy. Although these loci have previously been associated with adult height(1), their effects on infant head circumference were largely independent of height (P = 3.8 x 10(-7) for rs7980687 and P = 1.3 x 10(-7) for rs1042725 after adjustment for infant height). A third signal, rs11655470 on chromosome 17q21, showed suggestive evidence of association with head circumference (P = 3.9 x 10(-6)). SNPs correlated to the 17q21 signal have shown genome-wide association with adult intracranial volume(2), Parkinson's disease and other neurodegenerative diseases(3-5), indicating that a common genetic variant in this region might link early brain growth with neurological disease in later life.
The near-infrared is an important part of the spectrum in astronomy, especially in cosmology because the light from objects in the early universe is redshifted to these wavelengths. However, deep near-infrared observations are extremely difficult to make from ground-based telescopes due to the bright background from the atmosphere. Nearly all of this background comes from the bright and narrow emission lines of atmospheric hydroxyl (OH) molecules. The atmospheric background cannot be easily removed from data because the brightness fluctuates unpredictably on short timescales. The sensitivity of ground-based optical astronomy far exceeds that of near-infrared astronomy because of this long-standing problem. GNOSIS is a prototype astrophotonic instrument that utilizes "OH suppression fibers" consisting of fiber Bragg gratings and photonic lanterns to suppress the 103 brightest atmospheric emission doublets between 1.47 and 1.7 mu m. GNOSIS was commissioned at the 3.9 m Anglo-Australian Telescope with the IRIS2 spectrograph to demonstrate the potential of OH suppression fibers, but may be potentially used with any telescope and spectrograph combination. Unlike previous atmospheric suppression techniques GNOSIS suppresses the lines before dispersion and in a manner that depends purely on wavelength. We present the instrument design and report the results of laboratory and on-sky tests from commissioning. While these tests demonstrated high throughput (approximate to 60%) and excellent suppression of the skylines by the OH suppression fibers, surprisingly GNOSIS produced no significant reduction in the interline background and the sensitivity of GNOSIS+IRIS2 is about the same as IRIS2. It is unclear whether the lack of reduction in the interline background is due to physical sources or systematic errors as the observations are detector noise dominated. OH suppression fibers could potentially impact ground-based astronomy at the level of adaptive optics or greater. However, until a clear reduction in the interline background and the corresponding increasing in sensitivity is demonstrated optimized OH suppression fibers paired with a fiber-fed spectrograph will at least provide a real benefit at low resolving powers.