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Microbial community dynamics in the forefield of glaciers
Retreating ice fronts (as a result of a warming climate) expose large expanses of deglaciated forefield, which become colonized by microbes and plants. There has been increasing interest in characterizing the biogeochemical development of these ecosystems using a chronosequence approach. Prior to the establishment of plants, microbes use autochthonously produced and allochthonously delivered nutrients for growth. The microbial community composition is largely made up of heterotrophic microbes (both bacteria and fungi), autotrophic microbes and nitrogen-fixing diazotrophs. Microbial activity is thought to be responsible for the initial build-up of labile nutrient pools, facilitating the growth of higher order plant life in developed soils. However, it is unclear to what extent these ecosystems rely on external sources of nutrients such as ancient carbon pools and periodic nitrogen deposition. Furthermore, the seasonal variation of chronosequence dynamics and the effect of winter are largely unexplored. Modelling this ecosystem will provide a quantitative evaluation of the key processes and could guide the focus of future research. Year-round datasets combined with novel metagenomic techniques will help answer some of the pressing questions in this relatively new but rapidly expanding field, which is of growing interest in the context of future large-scale ice retreat
Comments on gauge-invariance in cosmology
We revisit the gauge issue in cosmological perturbation theory, and highlight
its relation to the notion of covariance in general relativity. We also discuss
the similarities and differences of the covariant approach in perturbation
theory to the Bardeen or metric approach in a non-technical fashion.Comment: 7 pages, 1 figure, revtex4; v3: minor changes, typos corrected,
discussion extended; v4: typos corrected, corresponding to published versio
Dark Matter, Muon g-2 and Other SUSY Constraints
Recent developments constraining the SUSY parameter space are reviewed within
the framework of SUGRA GUT models. The WMAP data is seen to reduce the error in
the density of cold dark matter by about a factor of four, implying that the
lightest stau is only 5 -10 GeV heavier than the lightest neutralino when m_0,
m_{1/2} < 1 TeV. The CMD-2 re-analysis of their data has reduced the
disagreement between the Standard Model prediction and the Brookhaven
measurement of the muon magnetic moment to 1.9 sigma, while using the tau decay
data plus CVC, the disagreement is 0.7 sigma. (However, the two sets of data
remain inconsistent at the 2.9 sigma level.) The recent Belle and BABAR
measurements of the B -> phi K CP violating parameters and branching ratios are
discussed. They are analyzed theoretically within the BBNS improved
factorization method. The CP parameters are in disagreement with the Standard
Model at the 2.7 sigma level, and the branching ratios are low by a factor of
two or more over most of the parameter space. It is shown that both anomalies
can naturally be accounted for by adding a non-universal cubic soft breaking
term at M_G mixing the second and third generations.Comment: 16 pages, 7 figures, plenary talk at Beyond The Desert '03, Castle
Ringberg, Germany, June 9, 2003. Typos correcte
A Multi-Armed Bandit to Smartly Select a Training Set from Big Medical Data
With the availability of big medical image data, the selection of an adequate
training set is becoming more important to address the heterogeneity of
different datasets. Simply including all the data does not only incur high
processing costs but can even harm the prediction. We formulate the smart and
efficient selection of a training dataset from big medical image data as a
multi-armed bandit problem, solved by Thompson sampling. Our method assumes
that image features are not available at the time of the selection of the
samples, and therefore relies only on meta information associated with the
images. Our strategy simultaneously exploits data sources with high chances of
yielding useful samples and explores new data regions. For our evaluation, we
focus on the application of estimating the age from a brain MRI. Our results on
7,250 subjects from 10 datasets show that our approach leads to higher accuracy
while only requiring a fraction of the training data.Comment: MICCAI 2017 Proceeding
Mapping species distributions: A comparison of skilled naturalist and lay citizen science recording
To assess the ability of traditional biological recording schemes and lay citizen science approaches to gather data on species distributions and changes therein, we examined bumblebee records from the UK’s national repository (National Biodiversity Network) and from BeeWatch. The two recording approaches revealed similar relative abundances of bumblebee species but different geographical distributions. For the widespread common carder (Bombus pascuorum), traditional recording scheme data were patchy, both spatially and temporally, reflecting active record centre rather than species distribution. Lay citizen science records displayed more extensive geographic coverage, reflecting human population density, thus offering better opportunities to account for recording effort. For the rapidly spreading tree bumblebee (Bombus hypnorum), both recording approaches revealed similar distributions due to a dedicated mapping project which overcame the patchy nature of naturalist records. We recommend, where possible, complementing skilled naturalist recording with lay citizen science programmes to obtain a nation-wide capability, and stress the need for timely uploading of data to the national repository
Process evaluation of appreciative inquiry to translate pain management evidence into pediatric nursing practice
Background
Appreciative inquiry (AI) is an innovative knowledge translation (KT) intervention that is compatible with the Promoting Action on Research in Health Services (PARiHS) framework. This study explored the innovative use of AI as a theoretically based KT intervention applied to a clinical issue in an inpatient pediatric care setting. The implementation of AI was explored in terms of its acceptability, fidelity, and feasibility as a KT intervention in pain management.
Methods
A mixed-methods case study design was used. The case was a surgical unit in a pediatric academic-affiliated hospital. The sample consisted of nurses in leadership positions and staff nurses interested in the study. Data on the AI intervention implementation were collected by digitally recording the AI sessions, maintaining logs, and conducting individual semistructured interviews. Data were analysed using qualitative and quantitative content analyses and descriptive statistics. Findings were triangulated in the discussion.
Results
Three nurse leaders and nine staff members participated in the study. Participants were generally satisfied with the intervention, which consisted of four 3-hour, interactive AI sessions delivered over two weeks to promote change based on positive examples of pain management in the unit and staff implementation of an action plan. The AI sessions were delivered with high fidelity and 11 of 12 participants attended all four sessions, where they developed an action plan to enhance evidence-based pain assessment documentation. Participants labeled AI a 'refreshing approach to change' because it was positive, democratic, and built on existing practices. Several barriers affected their implementation of the action plan, including a context of change overload, logistics, busyness, and a lack of organised follow-up.
Conclusions
Results of this case study supported the acceptability, fidelity, and feasibility of AI as a KT intervention in pain management. The AI intervention requires minor refinements (e.g., incorporating continued follow-up meetings) to enhance its clinical utility and sustainability. The implementation process and effectiveness of the modified AI intervention require evaluation in a larger multisite study
Measuring V_ub and probing SUSY with double ratios of purely leptonic decays of B and D mesons
The experimental prospects for precise measurements of the leptonic decays
B_u -> tau nu / mu nu, B_s -> mu+ mu-, D -> mu nu and D_s -> mu nu / tau nu are
very promising. Double ratios involving four of these decays can be defined in
which the dependence on the values of the decay constants is essentially
eliminated, thus enabling complementary measurements of the CKM matrix element
V_ub with a small theoretical error. We quantify the experimental error in a
possible future measurement of |V_ub| using this approach, and show that it is
competitive with the anticipated precision from the conventional approaches.
Moreover, it is shown that such double ratios can be more effective than the
individual leptonic decays as a probe of the parameter space of supersymmetric
models. We emphasize that the double ratios have the advantage of using |V_ub|
as an input parameter (for which there is experimental information), while the
individual decays have an uncertainty from the decay constants (e.g. f_B_s),
and hence a reliance on theoretical techniques such as lattice QCD.Comment: 21 pages, 4 figure
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