1,822 research outputs found

    Near-surface remote sensing of spatial and temporal variation in canopy phenology

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    There is a need to document how plant phenology is responding to global change factors, particularly warming trends. “Near-surface” remote sensing, using radiometric instruments or imaging sensors, has great potential to improve phenological monitoring because automated observations can be made at high temporal frequency. Here we build on previous work and show how inexpensive, networked digital cameras (“webcams”) can be used to document spatial and temporal variation in the spring and autumn phenology of forest canopies. We use two years of imagery from a deciduous, northern hardwood site, and one year of imagery from a coniferous, boreal transition site. A quantitative signal is obtained by splitting images into separate red, green, and blue color channels and calculating the relative brightness of each channel for “regions of interest” within each image. We put the observed phenological signal in context by relating it to seasonal patterns of gross primary productivity, inferred from eddy covariance measurements of surface–atmosphere CO2 exchange. We show that spring increases, and autumn decreases, in canopy greenness can be detected in both deciduous and coniferous stands. In deciduous stands, an autumn red peak is also observed. The timing and rate of spring development and autumn senescence varies across the canopy, with greater variability in autumn than spring. Interannual variation in phenology can be detected both visually and quantitatively; delayed spring onset in 2007 compared to 2006 is related to a prolonged cold spell from day 85 to day 110. This work lays the foundation for regional- to continental-scale camera-based monitoring of phenology at network observatory sites, e.g., National Ecological Observatory Network (NEON) or AmeriFlux

    Continuous subcutaneous insulin infusion alters microRNA expression and glycaemic variability in children with type 1 diabetes

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    To determine whether continuous subcutaneous insulin infusion (CSII) vs. multiple daily injections (MDI) therapy from near-diagnosis of type 1 diabetes is associated with reduced glycaemic variability (GV) and altered microRNA (miRNAs) expression. Adolescents (74% male) within 3-months of diabetes diagnosis (n = 27) were randomized to CSII (n = 12) or MDI. HbA1c, 1-5-Anhydroglucitol (1,5-AG), high sensitivity C-peptide and a custom TaqMan qPCR panel of 52 miRNAs were measured at baseline and follow-up (median (LQ-UQ); 535 (519-563) days). There were no significant differences between groups in baseline or follow-up HbA1c or C-peptide, nor baseline miRNAs. Mean +/- SD 1,5-AG improved with CSII vs. MDI (3.1 +/- 4.1 vs. - 2.2 +/- - 7.0 mg/ml respectively, P = 0.029). On follow-up 11 miRNAs associated with diabetes vascular complications had altered expression in CSII-users. Early CSII vs. MDI use is associated with lower GV and less adverse vascular-related miRNAs. Relationships with future complications are of interest

    Personal identity (de)formation among lifestyle travellers: A double-edged sword?

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    This article explores the personal identity work of lifestyle travellers – individuals for whom extended leisure travel is a preferred lifestyle that they return to repeatedly. Qualitative findings from in-depth semi-structured interviews with lifestyle travellers in northern India and southern Thailand are interpreted in light of theories on identity formation in late modernity that position identity as problematic. It is suggested that extended leisure travel can provide exposure to varied cultural praxes that may contribute to a sense of social saturation. Whilst a minority of the respondents embraced a saturation of personal identity in the subjective formation of a cosmopolitan cultural identity, several of the respondents were paradoxically left with more identity questions than answers as the result of their travels

    Foreground simulations for the LOFAR - Epoch of Reionization Experiment

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    Future high redshift 21-cm experiments will suffer from a high degree of contamination, due both to astrophysical foregrounds and to non-astrophysical and instrumental effects. In order to reliably extract the cosmological signal from the observed data, it is essential to understand very well all data components and their influence on the extracted signal. Here we present simulated astrophysical foregrounds datacubes and discuss their possible statistical effects on the data. The foreground maps are produced assuming 5 deg x 5 deg windows that match those expected to be observed by the LOFAR Epoch-of-Reionization (EoR) key science project. We show that with the expected LOFAR-EoR sky and receiver noise levels, which amount to ~52 mK at 150 MHz after 300 hours of total observing time, a simple polynomial fit allows a statistical reconstruction of the signal. We also show that the polynomial fitting will work for maps with realistic yet idealised instrument response, i.e., a response that includes only a uniform uv coverage as a function of frequency and ignores many other uncertainties. Polarized galactic synchrotron maps that include internal polarization and a number of Faraday screens along the line of sight are also simulated. The importance of these stems from the fact that the LOFAR instrument, in common with all current interferometric EoR experiments has an instrumentally polarized response.Comment: 18 figures, 3 tables, accepted to be published in MNRA

    Detection and extraction of signals from the epoch of reionization using higher-order one-point statistics

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    Detecting redshifted 21-cm emission from neutral hydrogen in the early Universe promises to give direct constraints on the epoch of reionization (EoR). It will, though, be very challenging to extract the cosmological signal (CS) from foregrounds and noise which are orders of magnitude larger. Fortunately, the signal has some characteristics which differentiate it from the foregrounds and noise, and we suggest that using the correct statistics may tease out signatures of reionization. We generate mock data cubes simulating the output of the Low Frequency Array (LOFAR) EoR experiment. These cubes combine realistic models for Galactic and extragalactic foregrounds and the noise with three different simulations of the CS. We fit out the foregrounds, which are smooth in the frequency direction, to produce residual images in each frequency band. We denoise these images and study the skewness of the one-point distribution in the images as a function of frequency. We find that, under sufficiently optimistic assumptions, we can recover the main features of the redshift evolution of the skewness in the 21-cm signal. We argue that some of these features ¿ such as a dip at the onset of reionization, followed by a rise towards its later stages ¿ may be generic, and give us a promising route to a statistical detection of reionization

    10 simple rules to create a serious game, illustrated with examples from structural biology

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    Serious scientific games are games whose purpose is not only fun. In the field of science, the serious goals include crucial activities for scientists: outreach, teaching and research. The number of serious games is increasing rapidly, in particular citizen science games, games that allow people to produce and/or analyze scientific data. Interestingly, it is possible to build a set of rules providing a guideline to create or improve serious games. We present arguments gathered from our own experience ( Phylo , DocMolecules , HiRE-RNA contest and Pangu) as well as examples from the growing literature on scientific serious games
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