Energy versus information based estimations of dissipation using a pair of magnetic colloidal particles

Using the framework of stochastic thermodynamics, we present an experimental study of a doublet of magnetic colloidal particles which is manipulated by a time-dependent magnetic field. Due to hydrodynamic interactions, each bead experiences a state-dependent friction, which we characterize using a hydrodynamic model. In this work, we compare two estimates of the dissipation in this system: the first one is energy based since it relies on the measured interaction potential, while the second one is information based since it uses only the information content of the trajectories. While the latter only offers a lower bound of the former, we find it to be simple to implement and of general applicability to more complex systems.Comment: Main text: 5 pages, 4 figures. Supplementary material: 5 pages, 5 figure

Estimating causal networks in biosphere–atmosphere interaction with the PCMCI approach

Local meteorological conditions and biospheric activity are tightly coupled. Understanding these links is an essential prerequisite for predicting the Earth system under climate change conditions. However, many empirical studies on the interaction between the biosphere and the atmosphere are based on correlative approaches that are not able to deduce causal paths, and only very few studies apply causal discovery methods. Here, we use a recently proposed causal graph discovery algorithm, which aims to reconstruct the causal dependency structure underlying a set of time series. We explore the potential of this method to infer temporal dependencies in biosphere-atmosphere interactions. Specifically we address the following questions: How do periodicity and heteroscedasticity influence causal detection rates, i.e. the detection of existing and non-existing links? How consistent are results for noise-contaminated data? Do results exhibit an increased information content that justifies the use of this causal-inference method? We explore the first question using artificial time series with well known dependencies that mimic real-world biosphere-atmosphere interactions. The two remaining questions are addressed jointly in two case studies utilizing observational data. Firstly, we analyse three replicated eddy covariance datasets from a Mediterranean ecosystem at half hourly time resolution allowing us to understand the impact of measurement uncertainties. Secondly, we analyse global NDVI time series (GIMMS 3g) along with gridded climate data to study large-scale climatic drivers of vegetation greenness. Overall, the results confirm the capacity of the causal discovery method to extract time-lagged linear dependencies under realistic settings. The violation of the method's assumptions increases the likelihood to detect false links. Nevertheless, we consistently identify interaction patterns in observational data. Our findings suggest that estimating a directed biosphere-atmosphere network at the ecosystem level can offer novel possibilities to unravel complex multi-directional interactions. Other than classical correlative approaches, our findings are constrained to a few meaningful set of relations which can be powerful insights for the evaluation of terrestrial ecosystem models

Cosmic shear analysis of archival HST/ACS data: I. Comparison of early ACS pure parallel data to the HST/GEMS Survey

This is the first paper of a series describing our measurement of weak lensing by large-scale structure using archival observations from the Advanced Camera for Surveys (ACS) on board the Hubble Space Telescope (HST). In this work we present results from a pilot study testing the capabilities of the ACS for cosmic shear measurements with early parallel observations and presenting a re-analysis of HST/ACS data from the GEMS survey and the GOODS observations of the Chandra Deep Field South (CDFS). We describe our new correction scheme for the time-dependent ACS PSF based on observations of stellar fields. This is currently the only technique which takes the full time variation of the PSF between individual ACS exposures into account. We estimate that our PSF correction scheme reduces the systematic contribution to the shear correlation functions due to PSF distortions to < 2*10^{-6} for galaxy fields containing at least 10 stars. We perform a number of diagnostic tests indicating that the remaining level of systematics is consistent with zero for the GEMS and GOODS data confirming the success of our PSF correction scheme. For the parallel data we detect a low level of remaining systematics which we interpret to be caused by a lack of sufficient dithering of the data. Combining the shear estimate of the GEMS and GOODS observations using 96 galaxies arcmin^{-2} with the photometric redshift catalogue of the GOODS-MUSIC sample, we determine a local single field estimate for the mass power spectrum normalisation sigma_{8,CDFS}=0.52^{+0.11}_{-0.15} (stat) +/- 0.07 (sys) (68% confidence assuming Gaussian cosmic variance) at fixed Omega_m=0.3 for a LambdaCDM cosmology. We interpret this exceptionally low estimate to be due to a local under-density of the foreground structures in the CDFS.Comment: Version accepted for publication in Astronomy & Astrophysics with 28 pages, 25 figures. A version with full resolution figures can be downloaded from http://www.astro.uni-bonn.de/~schrabba/papers/cosmic_shear_acs1_v2.pd

Beyond the pale?: the implications of the RSLG Report for non-CURL modern university libraries: Perspectives on the support libraries group: Final report

We have shown that the cluster-mass reconstruction method which combines strong and weak gravitational lensing data, developed in the first paper in the series, successfully reconstructs the mass distribution of a simulated cluster. In this paper we apply the method to the ground-based high-quality multi-colour data of RX J1347.5-114

GaBoDS: The Garching-Bonn Deep Survey -- II. Confirmation of EIS cluster candidates by weak gravitational lensing

We report the first confirmation of colour-selected galaxy cluster candidates by means of weak gravitational lensing. Significant lensing signals were identified in the course of the shear-selection programme of dark matter haloes in the Garching-Bonn Deep Survey, which currently covers 20 square degrees of deep, high-quality imaging data on the southern sky. The detection was made in a field that was previously covered by the ESO Imaging Survey (EIS) in 1997. A highly significant shear-selected mass-concentration perfectly coincides with the richest EIS cluster candidate at z~0.2, thus confirming its cluster nature. Several other shear patterns in the field can also be identified with cluster candidates, one of which could possibly be part of a filament at z~0.45.Comment: 4 pages, 4 figures, submitted to A&A Letter

Store depletion induces Gαq-mediated PLCβ1 activity to stimulate TRPC1 channels in vascular smooth muscle cells.

Depletion of sarcoplasmic reticulum (SR) Ca(2+) stores activates store-operated channels (SOCs) composed of canonical transient receptor potential (TRPC) 1 proteins in vascular smooth muscle cells (VSMCs), which contribute to important cellular functions. We have previously shown that PKC is obligatory for activation of TRPC1 SOCs in VSMCs, and the present study investigates if the classic phosphoinositol signaling pathway involving Gαq-mediated PLC activity is responsible for driving PKC-dependent channel gating. The G-protein inhibitor GDP-β-S, anti-Gαq antibodies, the PLC inhibitor U73122, and the PKC inhibitor GF109203X all inhibited activation of TRPC1 SOCs, and U73122 and GF109203X also reduced store-operated PKC-dependent phosphorylation of TRPC1 proteins. Three distinct SR Ca(2+) store-depleting agents, 1,2-bis(2-aminophenoxy)ethane-N,N,N',N'-tetraacetic acid acetoxymethyl ester, cyclopiazonic acid, and N,N,N',N'-tetrakis(2-pyridylmethyl)ethane-1,2-diamineed, induced translocations of the fluorescent biosensor GFP-PLCδ1-PH from the cell membrane to the cytosol, which were inhibited by U73122. Knockdown of PLCβ1 with small hairpin RNA reduced both store-operated PLC activity and stimulation of TRPC1 SOCs. Immunoprecipitation studies and proximity ligation assays revealed that store depletion induced interactions between TRPC1 and Gαq, and TRPC1 and PLCβ1. We propose a novel activation mechanism for TRPC1 SOCs in VSMCs, in which store depletion induces formation of TRPC1-Gαq-PLCβ1 complexes that lead to PKC stimulation and channel gating.-Shi, J., Miralles, F., Birnbaumer, L., Large, W. A., Albert, A. P. Store depletion induces Gαq-mediated PLCβ1 activity to stimulate TRPC1 channels in vascular smooth muscle cells

The future of Earth observation in hydrology

In just the past 5 years, the field of Earth observation has progressed beyond the offerings of conventional space-agency-based platforms to include a plethora of sensing opportunities afforded by CubeSats, unmanned aerial vehicles (UAVs), and smartphone technologies that are being embraced by both for-profit companies and individual researchers. Over the previous decades, space agency efforts have brought forth well-known and immensely useful satellites such as the Landsat series and the Gravity Research and Climate Experiment (GRACE) system, with costs typically of the order of 1 billion dollars per satellite and with concept-to-launch timelines of the order of 2 decades (for new missions). More recently, the proliferation of smart-phones has helped to miniaturize sensors and energy requirements, facilitating advances in the use of CubeSats that can be launched by the dozens, while providing ultra-high (3-5 m) resolution sensing of the Earth on a daily basis. Start-up companies that did not exist a decade ago now operate more satellites in orbit than any space agency, and at costs that are a mere fraction of traditional satellite missions. With these advances come new space-borne measurements, such as real-time high-definition video for tracking air pollution, storm-cell development, flood propagation, precipitation monitoring, or even for constructing digital surfaces using structure-from-motion techniques. Closer to the surface, measurements from small unmanned drones and tethered balloons have mapped snow depths, floods, and estimated evaporation at sub-metre resolutions, pushing back on spatio-temporal constraints and delivering new process insights. At ground level, precipitation has been measured using signal attenuation between antennae mounted on cell phone towers, while the proliferation of mobile devices has enabled citizen scientists to catalogue photos of environmental conditions, estimate daily average temperatures from battery state, and sense other hydrologically important variables such as channel depths using commercially available wireless devices. Global internet access is being pursued via high-altitude balloons, solar planes, and hundreds of planned satellite launches, providing a means to exploit the "internet of things" as an entirely new measurement domain. Such global access will enable real-time collection of data from billions of smartphones or from remote research platforms. This future will produce petabytes of data that can only be accessed via cloud storage and will require new analytical approaches to interpret. The extent to which today's hydrologic models can usefully ingest such massive data volumes is unclear. Nor is it clear whether this deluge of data will be usefully exploited, either because the measurements are superfluous, inconsistent, not accurate enough, or simply because we lack the capacity to process and analyse them. What is apparent is that the tools and techniques afforded by this array of novel and game-changing sensing platforms present our community with a unique opportunity to develop new insights that advance fundamental aspects of the hydrological sciences. To accomplish this will require more than just an application of the technology: in some cases, it will demand a radical rethink on how we utilize and exploit these new observing systems

The dark clump near Abell 1942: dark matter halo or statistical fluke?

Weak lensing surveys provide the possibility of identifying dark matter halos based on their total matter content rather than just the luminous matter content. On the basis of two sets of observations carried out with the CFHT, Erben et al. (2000) presented the first candidate dark clump, i.e. a dark matter concentration identified by its significant weak lensing signal without a corresponding galaxy overdensity or X-ray emission. We present a set of HST mosaic observations which confirms the presence of an alignment signal at the dark clump position. The signal strength, however, is weaker than in the ground-based data. It is therefore still unclear whether the signal is caused by a lensing mass or is just a chance alignment. We also present Chandra observations of the dark clump, which fail to reveal any significant extended emission. A comparison of the ellipticity measurements from the space-based HST data and the ground-based CFHT data shows a remarkable agreement on average, demonstrating that weak lensing studies from high-quality ground-based observations yield reliable results.Comment: 33 pages, 34 figures, submitted to A&A. Version with full resolution figures available at http://www.mpa-garching.mpg.de/~anja/aaclump.pd