A search for OH 6 GHz maser emission towards southern supernova remnants

OH masers at 1720 MHz have proven to be excellent indicators of interactions between supernova remnants and molecular clouds. Recent calculations suggest that the 6049 MHz OH maser line is excited for higher column densities than for the 1720 MHz line. It is therefore a potentially valuable indicator of remnant-cloud interaction. We present preliminary results of a survey using the Parkes Methanol Multibeam receiver for 6049 MHz and 6035/6030 MHz OH masers towards 36 supernova remnants and 4 fields in the Large and Small Magellanic Clouds. While no 6049 MHz masers have been found, three new sites of 6035 and 6030 MHz OH maser emission have been discovered in star-forming regions.Comment: 2 pages, 1 fig, iaus.cls. To appear in IAU 242, Astrophysical Masers and Their Environments, eds. J. Chapman & W. Baa

Fish Habitat Utilization Patterns and Evaluation of the Efficacy of Marine Protected Areas in Hawaii: Integration of NOAA Digital Benthic Habitat Mapping and Coral Reef Ecological Studies

Over the past four decades, the state of Hawaii has developed a system of eleven Marine Life Conservation Districts (MLCDs) to conserve and replenish marine resources around the state. Initially established to provide opportunities for public interaction with the marine environment, these MLCDs vary in size, habitat quality, and management regimes, providing an excellent opportunity to test hypotheses concerning marine protected area (MPA) design and function using multiple discreet sampling units. NOAA/NOS/NCCOS/Center for Coastal Monitoring and Assessment’s Biogeography Team developed digital benthic habitat maps for all MLCD and adjacent habitats. These maps were used to evaluate the efficacy of existing MLCDs for biodiversity conservation and fisheries replenishment, using a spatially explicit stratified random sampling design. Coupling the distribution of habitats and species habitat affinities using GIS technology elucidates species habitat utilization patterns at scales that are commensurate with ecosystem processes and is useful in defining essential fish habitat and biologically relevant boundaries for MPAs. Analysis of benthic cover validated the a priori classification of habitat types and provided justification for using these habitat strata to conduct stratified random sampling and analyses of fish habitat utilization patterns. Results showed that the abundance and distribution of species and assemblages exhibited strong correlations with habitat types. Fish assemblages in the colonized and uncolonized hardbottom habitats were found to be most similar among all of the habitat types. Much of the macroalgae habitat sampled was macroalgae growing on hard substrate, and as a result showed similarities with the other hardbottom assemblages. The fish assemblages in the sand habitats were highly variable but distinct from the other habitat types. Management regime also played an important role in the abundance and distribution of fish assemblages. MLCDs had higher values for most fish assemblage characteristics (e.g. biomass, size, diversity) compared with adjacent fished areas and Fisheries Management Areas (FMAs) across all habitat types. In addition, apex predators and other targeted resources species were more abundant and larger in the MLCDs, illustrating the effectiveness of these closures in conserving fish populations. Habitat complexity, quality, size and level of protection from fishing were important determinates of MLCD effectiveness with respect to their associated fish assemblages. (PDF contains 217 pages

A generalization of moderated statistics to data adaptive semiparametric estimation in high-dimensional biology

The widespread availability of high-dimensional biological data has made the simultaneous screening of numerous biological characteristics a central statistical problem in computational biology. While the dimensionality of such datasets continues to increase, the problem of teasing out the effects of biomarkers in studies measuring baseline confounders while avoiding model misspecification remains only partially addressed. Efficient estimators constructed from data adaptive estimates of the data-generating distribution provide an avenue for avoiding model misspecification; however, in the context of high-dimensional problems requiring simultaneous estimation of numerous parameters, standard variance estimators have proven unstable, resulting in unreliable Type-I error control under standard multiple testing corrections. We present the formulation of a general approach for applying empirical Bayes shrinkage approaches to asymptotically linear estimators of parameters defined in the nonparametric model. The proposal applies existing shrinkage estimators to the estimated variance of the influence function, allowing for increased inferential stability in high-dimensional settings. A methodology for nonparametric variable importance analysis for use with high-dimensional biological datasets with modest sample sizes is introduced and the proposed technique is demonstrated to be robust in small samples even when relying on data adaptive estimators that eschew parametric forms. Use of the proposed variance moderation strategy in constructing stabilized variable importance measures of biomarkers is demonstrated by application to an observational study of occupational exposure. The result is a data adaptive approach for robustly uncovering stable associations in high-dimensional data with limited sample sizes

Semi-automatic semantic enrichment of raw sensor data

One of the more recent sources of large volumes of generated data is sensor devices, where dedicated sensing equipment is used to monitor events and happenings in a wide range of domains, including monitoring human biometrics. In recent trials to examine the effects that key moments in movies have on the human body, we fitted fitted with a number of biometric sensor devices and monitored them as they watched a range of dierent movies in groups. The purpose of these experiments was to examine the correlation between humans' highlights in movies as observed from biometric sensors, and highlights in the same movies as identified by our automatic movie analysis techniques. However,the problem with this type of experiment is that both the analysis of the video stream and the sensor data readings are not directly usable in their raw form because of the sheer volume of low-level data values generated both from the sensors and from the movie analysis. This work describes the semi-automated enrichment of both video analysis and sensor data and the mechanism used to query the data in both centralised environments, and in a peer-to-peer architecture when the number of sensor devices grows to large numbers. We present and validate a scalable means of semi-automating the semantic enrichment of sensor data, thereby providing a means of large-scale sensor management

Spatial restriction of alpha4 integrin phosphorylation regulates lamellipodial stability and alpha4beta1-dependent cell migration.

Integrins coordinate spatial signaling events essential for cell polarity and directed migration. Such signals from alpha4 integrins regulate cell migration in development and in leukocyte trafficking. Here, we report that efficient alpha4-mediated migration requires spatial control of alpha4 phosphorylation by protein kinase A, and hence localized inhibition of binding of the signaling adaptor, paxillin, to the integrin. In migrating cells, phosphorylated alpha4 accumulated along the leading edge. Blocking alpha4 phosphorylation by mutagenesis or by inhibition of protein kinase A drastically reduced alpha4-dependent migration and lamellipodial stability. alpha4 phosphorylation blocks paxillin binding in vitro; we now find that paxillin and phospho-alpha4 were in distinct clusters at the leading edge of migrating cells, whereas unphosphorylated alpha4 and paxillin colocalized along the lateral edges of those cells. Furthermore, enforced paxillin association with alpha4 inhibits migration and reduced lamellipodial stability. These results show that topographically specific integrin phosphorylation can control cell migration and polarization by spatial segregation of adaptor protein binding

Anisotropic Nonlinear Diffusion with Absorption: Existence and Extinction

The authors prove that the nonlinear parabolic partial differential equation ∂ u ∂ t = ∑ i , j = 1 n ∂ 2 ∂ x i ∂ x j φ i j ( u ) − f ( u ) with homogeneous Dirichlet boundary conditions and a nonnegative initial condition has a nonnegative generalized solution u . They also give necessary and sufficient conditions on the constitutive functions φ i j and f which ensure the existence of a time t 0 \u3e 0 for which u vanishes for all t ≥ t 0

A search for OH 6 GHz maser emission towards supernova remnants

OH masers at 1720 MHz have proven to be excellent indicators of interactions between supernova remnants and molecular clouds. OH excitation calculations suggest that the 6049 MHz OH maser line is excited for higher column densities than for the 1720 MHz line. Previous observations and modelling of 1612, 1665 and 1667 MHz OH absorption and 1720 MHz OH masers indicated that the column densities in some supernova remnants, ~1e17 cm^-2, may be high enough for 6049 MHz OH masers to exist. It is therefore a potentially valuable indicator of remnant-cloud interaction. We present excitation calculations predicting the formation of 6049 MHz OH masers and results of a survey using the Parkes Methanol Multibeam receiver for 6049, 6035 and 6030 MHz OH masers towards 35 supernova remnants, a star-forming region and 4 fields in the Large and Small Magellanic Clouds. Two new sites of 6035 and 6030 MHz OH maser emission associated with star-forming regions have been discovered, but no 6049 MHz masers were detected to a brightness temperature limit of ~0.3-0.6 K, even though modelling of the OH excitation suggests that maser emission should have been detected. Our upper-limits indicate that the OH column density for a typical remnant is less than 1e16.4 cm^-2, which conflicts with observed and modelled column densities. One possible explanation is that 6049 MHz OH masers may be more sensitive to velocity coherence than 1720 MHz OH masers under some conditions.Comment: 11 pages, 5 figures, mn2e.cls. Submitted to MNRAS Apr 2008. Accepted for publication in MNRAS 2008 July 15. Minor changes in the accepted version. LaTex2

Population Intervention Models in Causal Inference

Marginal structural models (MSM) provide a powerful tool for estimating the causal effect of a] treatment variable or risk variable on the distribution of a disease in a population. These models, as originally introduced by Robins (e.g., Robins (2000a), Robins (2000b), van der Laan and Robins (2002)), model the marginal distributions of treatment-specific counterfactual outcomes, possibly conditional on a subset of the baseline covariates, and its dependence on treatment. Marginal structural models are particularly useful in the context of longitudinal data structures, in which each subject\u27s treatment and covariate history are measured over time, and an outcome is recorded at a final time point. In addition to the simpler, weighted regression approaches (inverse probability of treatment weighted estimators), more general (and robust) estimators have been developed and studied in detail for standard MSM (Robins (2000b), Neugebauer and van der Laan (2004), Yu and van der Laan (2003), van der Laan and Robins (2002)). In this paper we argue that in many applications one is interested in modeling the difference between a treatment-specific counterfactual population distribution and the actual population distribution of the target population of interest. Relevant parameters describe the effect of a hypothetical intervention on such a population, and therefore we refer to these models as intervention models. We focus on intervention models estimating the effect on an intervention in terms of a difference of means, ratio in means (e.g., relative risk if the outcome is binary), a so called switch relative risk for binary outcomes, and difference in entire distributions as measured by the quantile-quantile function. In addition, we provide a class of inverse probability of treatment weighed estimators, and double robust estimators of the causal parameters in these models. We illustrate the finite sample performance of these new estimators in a simulation study