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Particles in Saturn's main rings range in size from dust to kilometer-sized objects. Their size distribution is thought to be a result of competing accretion and fragmentation processes. While growth is naturally limited in tidal environments, frequent collisions among these objects may contribute to both accretion and fragmentation. As ring particles are primarily made of water ice attractive surface forces like adhesion could significantly influence these processes, finally determining the resulting size distribution. Here, we derive analytic expressions for the specific self-energy Q and related specific break-up energy Q(star) of aggregates. These expressions can be used for any aggregate type composed of monomeric constituents. We compare these expressions to numerical experiments where we create aggregates of various types including: regular packings like the face-centered cubic (fcc), Ballistic Particle Cluster Aggregates (BPCA), and modified BPCAs including e.g. different constituent size distributions. We show that accounting for attractive surface forces such as adhesion a simple approach is able to: (a) generally account for the size dependence of the specific break-up energy for fragmentation to occur reported in the literature, namely the division into "strength" and "gravity" regimes and (b) estimate the maximum aggregate size in a collisional ensemble to be on the order of a few tens of meters, consistent with the maximum particle size observed in Saturn's rings of about 10 m.
On 27 February 2010 the M-w 8.8 Maule earthquake in Central Chile ruptured a seismic gap where significant strain had accumulated since 1835. Shortly after the mainshock a dense network of temporary seismic stations was installed along the whole rupture zone in order to capture the aftershock activity. Here, we present the aftershock distribution and first motion polarity focal mechanisms based on automatic detection algorithms and picking engines. By processing the seismic data between 15 March and 30 September 2010 from stations from IRIS, IPGP, GFZ and University of Liverpool we determined 20,205 hypocentres with magnitudes M-w between 1 and 5.5. Seismic activity occurs in six groups: 1.) Normal faulting outer rise events 2.) A shallow group of plate interface seismicity apparent at 25-35 km depth and 50-120 km distance to the trench with some variations between profiles. Along strike, the aftershocks occur largely within the zone of coseismic slip but extend similar to 50 km further north, and with predominantly shallowly dipping thrust mechanisms. Along dip, the events are either within the zone of coseismic slip, or downdip from it, depending on the coseismic slip model used. 3.) A third band of seismicity is observed further downdip at 40-50 km depth and further inland at 150-160 km trench perpendicular distance, with mostly shallow dipping (similar to 28 degrees) thrust focal mechanisms indicating rupture of the plate interface significantly downdip of the coseismic rupture, and presumably above the intersection of the continental Moho with the plate interface. 4.) A deep group of intermediate depth events between 80 and 120 km depth is present north of 36 degrees S. Within the Maule segment, a large portion of events during the inter-seismic phase originated from this depth range. 5.) The magmatic arc exhibits a small amount of crustal seismicity but does not appear to show significantly enhanced activity after the M-w 8.8 Maule 2010 earthquake. 6.) Pronounced crustal aftershock activity with mainly normal faulting mechanisms is found in the region of Pichilemu (similar to 34.5 degrees S). These crustal events occur in a similar to 30 km wide region with sharp inclined boundaries and oriented oblique to the trench. The best-located events describe a plane dipping to the southwest, consistent with one of the focal planes of the large normal-faulting aftershock (M-w = 6.9) on 11 March 2010.
Microbial communities can subsist at depth in marine sediments without fresh supply of organic matter for millions of years. At threshold sedimentation rates of 1 millimeter per 1000 years, the low rates of microbial community metabolism in the North Pacific Gyre allow sediments to remain oxygenated tens of meters below the sea floor. We found that the oxygen respiration rates dropped from 10 micromoles of O-2 liter(-1) year(-1) near the sediment-water interface to 0.001 micromoles of O-2 liter(-1) year(-1) at 30-meter depth within 86 million-year-old sediment. The cell-specific respiration rate decreased with depth but stabilized at around 10(-3) femtomoles of O-2 cell(-1) day(-1) 10 meters below the seafloor. This result indicated that the community size is controlled by the rate of carbon oxidation and thereby by the low available energy flux.
We propose a simple theoretical model for aggregative and fragmentative collisions in Saturn's dense rings. In this model the ring matter consists of a bimodal size distribution: large (meter sized) boulders and a population of smaller particles (tens of centimeters down to dust). The small particles can adhesively stick to the boulders and can be released as debris in binary collisions of their carriers. To quantify the adhesion force we use the JKR theory (Johnson, K., Kendall, K., Roberts, A. [1971]. Proc. R. Soc. Lond. A 324, 301-313). The rates of release and adsorption of particles are calculated, depending on material parameters, sizes, and plausible velocity dispersions of carriers and debris particles. In steady state we obtain an expression for the amount of free debris relative to the fraction still attached to the carriers. In terms of this conceptually simple model a paucity of subcentimeter particles in Saturn's rings (French, R.G., Nicholson, P.D. [2000]. Icarus 145, 502-523; Marouf, E. et al. [2008]. Abstracts for "Saturn after Cassini-Huygens" Symposium, Imperial College London, UK, July 28 to August 1, p. 113) can be understood as a consequence of the increasing strength of adhesion (relative to inertial forces) for decreasing particle size. In this case particles smaller than a certain critical radius remain tightly attached to the surfaces of larger boulders, even when the boulders collide at their typical speed. Furthermore, we find that already a mildly increased velocity dispersion of the carrier-particles may significantly enhance the fraction of free debris particles, in this way increasing the optical depth of the system.
Duplicate detection is the task of identifying all groups of records within a data set that represent the same real-world entity, respectively. This task is difficult, because (i) representations might differ slightly, so some similarity measure must be defined to compare pairs of records and (ii) data sets might have a high volume making a pair-wise comparison of all records infeasible. To tackle the second problem, many algorithms have been suggested that partition the data set and compare all record pairs only within each partition. One well-known such approach is the Sorted Neighborhood Method (SNM), which sorts the data according to some key and then advances a window over the data comparing only records that appear within the same window. We propose several variations of SNM that have in common a varying window size and advancement. The general intuition of such adaptive windows is that there might be regions of high similarity suggesting a larger window size and regions of lower similarity suggesting a smaller window size. We propose and thoroughly evaluate several adaption strategies, some of which are provably better than the original SNM in terms of efficiency (same results with fewer comparisons).
Terrestrial mud volcanoes (TMVs) represent geochemically diverse habitats with varying sulfur sources and yet sulfur cycling in these environments remains largely unexplored. Here we characterized the sulfur-metabolizing microorganisms and activity in four TMVs in Azerbaijan. A combination of geochemical analyses, biological rate measurements and molecular diversity surveys (targeting metabolic genes aprA and dsrA and SSU ribosomal RNA) supported the presence of active sulfur-oxidizing and sulfate-reducing guilds in all four TMVs across a range of physiochemical conditions, with diversity of these guilds being unique to each TMV. The TMVs varied in potential sulfate reduction rates (SRR) by up to four orders of magnitude with highest SRR observed in sediments where in situ sulfate concentrations were highest. Maximum temperatures at which SRR were measured was 60 degrees C in two TMVs. Corresponding with these trends in SRR, members of the potentially thermophilic, spore-forming, Desulfotomaculum were detected in these TMVs by targeted 16S rRNA analysis. Additional sulfate-reducing bacterial lineages included members of the Desulfobacteraceae and Desulfobulbaceae detected by aprA and dsrA analyses and likely contributing to the mesophilic SRR measured. Phylotypes affiliated with sulfide-oxidizing Gamma- and Betaproteobacteria were abundant in aprA libraries from low sulfate TMVs, while the highest sulfate TMV harboured 16S rRNA phylotypes associated with sulfur-oxidizing Epsilonproteobacteria. Altogether, the biogeochemical and microbiological data indicate these unique terrestrial habitats support diverse active sulfur-cycling microorganisms reflecting the in situ geochemical environment.
The field of machine learning studies algorithms that infer predictive models from data. Predictive models are applicable for many practical tasks such as spam filtering, face and handwritten digit recognition, and personalized product recommendation. In general, they are used to predict a target label for a given data instance. In order to make an informed decision about the deployment of a predictive model, it is crucial to know the model’s approximate performance. To evaluate performance, a set of labeled test instances is required that is drawn from the distribution the model will be exposed to at application time. In many practical scenarios, unlabeled test instances are readily available, but the process of labeling them can be a time- and cost-intensive task and may involve a human expert. This thesis addresses the problem of evaluating a given predictive model accurately with minimal labeling effort. We study an active model evaluation process that selects certain instances of the data according to an instrumental sampling distribution and queries their labels. We derive sampling distributions that minimize estimation error with respect to different performance measures such as error rate, mean squared error, and F-measures. An analysis of the distribution that governs the estimator leads to confidence intervals, which indicate how precise the error estimation is. Labeling costs may vary across different instances depending on certain characteristics of the data. For instance, documents differ in their length, comprehensibility, and technical requirements; these attributes affect the time a human labeler needs to judge relevance or to assign topics. To address this, the sampling distribution is extended to incorporate instance-specific costs. We empirically study conditions under which the active evaluation processes are more accurate than a standard estimate that draws equally many instances from the test distribution. We also address the problem of comparing the risks of two predictive models. The standard approach would be to draw instances according to the test distribution, label the selected instances, and apply statistical tests to identify significant differences. Drawing instances according to an instrumental distribution affects the power of a statistical test. We derive a sampling procedure that maximizes test power when used to select instances, and thereby minimizes the likelihood of choosing the inferior model. Furthermore, we investigate the task of comparing several alternative models; the objective of an evaluation could be to rank the models according to the risk that they incur or to identify the model with lowest risk. An experimental study shows that the active procedure leads to higher test power than the standard test in many application domains. Finally, we study the problem of evaluating the performance of ranking functions, which are used for example for web search. In practice, ranking performance is estimated by applying a given ranking model to a representative set of test queries and manually assessing the relevance of all retrieved items for each query. We apply the concepts of active evaluation and active comparison to ranking functions and derive optimal sampling distributions for the commonly used performance measures Discounted Cumulative Gain and Expected Reciprocal Rank. Experiments on web search engine data illustrate significant reductions in labeling costs.
Although the positive effect of elevated CO2 concentration [CO2] on plant growth is well known, it remains unclear whether global climate change will positively or negatively affect crop yields. In particular, relatively little is known about the role of hormone pathways in controlling the growth responses to elevated [CO2]. Here, we studied the impact of elevated [CO2] on plant biomass and metabolism in Arabidopsis (Arabidopsis thaliana) in relation to the availability of gibberellins (GAs). Inhibition of growth by the GA biosynthesis inhibitor paclobutrazol (PAC) at ambient [CO2] (350 mu mol CO2 mol(-1)) was reverted by elevated [CO2] (750 mu mol CO2 mol(-1)). Thus, we investigated the metabolic adjustment and modulation of gene expression in response to changes in growth of plants imposed by varying the GA regime in ambient and elevated [CO2]. In the presence of PAC (low-GA regime), the activities of enzymes involved in photosynthesis and inorganic nitrogen assimilation were markedly increased at elevated [CO2], whereas the activities of enzymes of organic acid metabolism were decreased. Under ambient [CO2], nitrate, amino acids, and protein accumulated upon PAC treatment; however, this was not the case when plants were grown at elevated [CO2]. These results suggest that only under ambient [CO2] is GA required for the integration of carbohydrate and nitrogen metabolism underlying optimal biomass determination. Our results have implications concerning the action of the Green Revolution genes in future environmental conditions.
We present a momentum transfer mechanism mediated by electromagnetic fields that originates in a system of two nearby molecules: one excited (donor D*) and the other in ground state (acceptor A). An intermolecular force related to fluorescence resonant energy or Forster transfer (FRET) arises in the unstable D* A molecular system, which differs from the equilibrium van der Waals interaction. Due to the its finite lifetime, a mechanical impulse is imparted to the relative motion in the system. We analyze the FRET impulse when the molecules are embedded in free space and find that its magnitude can be much greater than the single recoil photon momentum, getting comparable with the thermal momentum (Maxwell-Boltzmann distribution) at room temperature. In addition, we propose that this FRET impulse can be exploited in the generation of acoustic waves inside a film containing layers of donor and acceptor molecules, when a picosecond laser pulse excites the donors. This acoustic transient is distinguishable from that produced by thermal stress due to laser absorption, and may therefore play a role in photoacoustic spectroscopy. The effect can be seen as exciting a vibrating system like a string or organ pipe with light; it may be used as an opto-mechanical transducer.
Information integration across company borders becomes increasingly important for the success of product lifecycle management in industry and complex supply chains. Semantic technologies are about to play a crucial role in this integrative process. However, cross-company data exchange requires mechanisms to enable fine-grained access control definition and enforcement, preventing unauthorized leakage of confidential data across company borders. Currently available semantic repositories are not sufficiently equipped to satisfy this important requirement. This paper presents an infrastructure for controlled sharing of semantic data between cooperating business partners. First, we motivate the need for access control in semantic data federations by a case study in the industrial service sector. Furthermore, we present an architecture for controlling access to semantic repositories that is based on our newly developed SemForce security service. Finally, we show the practical feasibility of this architecture by an implementation and several performance experiments.
We investigate the physical state of H?i absorbing gas at low redshift (z = 0.25) using a subset of cosmological, hydrodynamic simulations from the OverWhelmingly Large Simulations project, focusing in particular on broad (bHI=40 km s-1) H?i Lya absorbers (BLAs), which are believed to originate in shock-heated gas in the warm-hot intergalactic medium (WHIM). Our fiducial model, which includes radiative cooling by heavy elements and feedback by supernovae and active galactic nuclei, predicts that by z = 0.25 nearly 60?per cent of the gas mass ends up at densities and temperatures characteristic of the WHIM and we find that half of this fraction is due to outflows. The standard H?i observables (distribution of H?i column densities NH?I, distribution of Doppler parameters bHI, bHINH?I correlation) and the BLA line number density predicted by our simulations are in remarkably good agreement with observations. BLAs arise in gas that is hotter, more highly ionized and more enriched than the gas giving rise to typical Lya forest absorbers. The majority of the BLAs arise in warm-hot [log?(T/?K) similar to 5] gas at low (log?? < 1.5) overdensities. On average, thermal broadening accounts for at least 60?per cent of the BLA linewidth, which in turn can be used as a rough indicator of the thermal state of the gas. Detectable BLAs account for only a small fraction of the true baryon content of the WHIM at low redshift. In order to detect the bulk of the mass in this gas phase, a sensitivity at least one order of magnitude better than achieved by current ultraviolet spectrographs is required. We argue that BLAs mostly trace gas that has been shock heated and enriched by outflows and that they therefore provide an important window on a poorly understood feedback process.
The first 1400-year floating varve chronology for north-eastern Germany covering the late Allered to the early Holocene has been established by microscopic varve counts from the Rehwiese palaeolake sediment record. The Laacher See Tephra (LST), at the base of the studied interval, forms the tephrochronological anchor point. The fine laminations were examined using a combination of micro-facies and mu XRF analyses and are typical of calcite varves, which in this case provide mainly a warm season signal. Two varve types with different sub-layer structures have been distinguished: (I) complex varves consisting of up to four seasonal sub-layers formed during the Allered and early Holocene periods, and, (II) simple two sub-layer type varves only occurring during the Younger Dryas. The precision of the chronology has been improved by varve-to-varve comparison of two independently analyzed sediment profiles based on well-defined micro-marker layers. This has enabled both (1) the precise location of single missing varies in one of the sediment profiles, and, (2) the verification of varve interpolation in disturbed varve intervals in the parallel core. Inter-annual and decadal-scale variability in sediment deposition processes were traced by multi-proxy data series including seasonal layer thickness, high-resolution element scans and total organic and inorganic carbon data at a five-varve resolution. These data support the idea of a two-phase Younger Dryas, with the first interval (12,675-12,275 varve years BP) characterised by a still significant but gradually decreasing warm-season calcite precipitation and a second phase (12,275-11,690 varve years BP) with only weak calcite precipitation. Detailed correlation of these two phases with the Meerfelder Maar record based on the LST isochrone and independent varve counts provides clues about regional differences and seasonal aspects of YD climate change along a transect from a location proximal to the North Atlantic in the west to a more continental site in the east
Dielectric elastomer actuators (DEAs) draw their function from their dielectric and mechanical properties. The paper describes the fabrication and various properties of molecularly grafted silicone elastomer films. This was achieved by addition of high-dipole molecular co-substituents to off-the-shelf silicone elastomer kits, Elastosil RT 625 and Sylgard 184 by Wacker and Dow Corning, respectively. Strong push-pull dipoles were chemically grafted to both polymer networks during a one step film formation process. All manufactured films were characterized using (13) C-NMR and FT-IR spectroscopy, confirming a successful attachment of the dipoles to the silicone network. Differential scanning calorimetry (DSC) results showed that grafted dipoles were distributed homogeneously throughout the material avoiding the formation of nano-scale aggregates. The permittivity increased with the amount of dipole at all frequencies, while the Young's modulus and electrical breakdown strength were reduced. Actuation strain measurements in the pure shear configuration independently confirmed the increase in electromechanical sensitivity. The ability to enhance electromechanical properties of off-the-shelf materials could strongly expand the range of actuator properties available to researchers and end-users.
The combination of a non-coated silicon photodiode with electron repelling meshes makes a versatile detector for total fluorescence yield and electron yield techniques highly suitable for x-ray absorption spectroscopy. In particular, a copper mesh with a bias voltage allows to suppress or transmit the electron yield signal. The performance of this detection scheme has been characterized by near edge x-ray absorption fine structure studies of thermal oxidized silicon and sapphire. The results show that the new detector probes both electron yield and for a bias voltage exceeding the maximum photon energy the total fluorescence yield.
In this work we construct a unified model of dark energy and dark matter. This is done with the following three elements: a gravitating scalar field, phi with a non-conventional kinetic term, as in the string theory tachyon; an arbitrary potential, V (phi); two measures - a metric measure (root-g) and a non-metric measure (Phi). The model has two interesting features: (i) For potentials which are unstable and would give rise to tachyonic scalar field, this model can stabilize the scalar field. (ii) The form of the dark energy and dark matter that results from this model is fairly insensitive to the exact form of the scalar field potential.
Transparent, ion-conducting, luminescent, and flexible ionogels based on the room temperature ionic liquid (IL) 1-butyl-3-methylimidazolium bis(trifluoromethane sulfonyl) imide [Bmim][N(Tf)(2)], a PtEu2 chromophore, and poly(methylmethacrylate) (PMMA) have been prepared. The thermal stability of the PMMA significantly increases with IL incorporation. In particular, the onset weight loss observed at ca. 229 degrees C for pure PMMA increases to 305 degrees C with IL addition. The ionogel has a high ionic conductivity of 10(-3) S cm(-1) at 373 K and exhibits a strong emission in the red with a long average luminescence decay time of tau = 890 mu s. The resulting material is a new type of soft hybrid material featuring useful thermal, optical, and ion transport properties.
High-pressure is a key feature of deep subsurface environments. High partial pressure of dissolved gasses plays an important role in microbial metabolism, because thermodynamic feasibility of many reactions depends on the concentration of reactants. For gases, this is controlled by their partial pressure, which can exceed 1 MPa at in situ conditions. Therefore, high hydrostatic pressure alone is not sufficient to recreate true deep subsurface in situ conditions, but the partial pressure of dissolved gasses has to be controlled as well. We developed an incubation system that allows for incubations at hydrostatic pressure up to 60 MPa, temperatures up to 120 degrees C, and at high gas partial pressure. The composition and partial pressure of gasses can be manipulated during the experiment. To keep costs low, the system is mainly made from off-the-shelf components with only very few custommade parts. A flexible and inert PVDF (polyvinylidene fluoride) incubator sleeve, which is almost impermeable for gases, holds the sample and separates it from the pressure fluid. The flexibility of the incubator sleeve allows for sub-sampling of the medium without loss of pressure. Experiments can be run in both static and flow-through mode. The incubation system described here is usable for versatile purposes, not only the incubation of microorganisms and determination of growth rates, but also for chemical degradation or extraction experiments under high gas saturation, e.g., fluid-gas-rock-interactions in relation to carbon dioxide sequestration. As an application of the system we extracted organic compounds from sub-bituminous coal using H2O as well as a H2O-CO2 mixture at elevated temperature (90 degrees C) and pressure (5 MPa). Subsamples were taken at different time points during the incubation and analyzed by ion chromatography. Furthermore we demonstrated the applicability of the system for studies of microbial activity, using samples from the Isis mud volcano. We could detect an increase in sulfate reduction rate upon the addition of methane to the sample.
Chemotaxis, the directed motion of a cell toward a chemical source, plays a key role in many essential biological processes. Here, we derive a statistical model that quantitatively describes the chemotactic motion of eukaryotic cells in a chemical gradient. Our model is based on observations of the chemotactic motion of the social ameba Dictyostelium discoideum, a model organism for eukaryotic chemotaxis. A large number of cell trajectories in stationary, linear chemoattractant gradients is measured, using microfluidic tools in combination with automated cell tracking. We describe the directional motion as the interplay between deterministic and stochastic contributions based on a Langevin equation. The functional form of this equation is directly extracted from experimental data by angle-resolved conditional averages. It contains quadratic deterministic damping and multiplicative noise. In the presence of an external gradient, the deterministic part shows a clear angular dependence that takes the form of a force pointing in gradient direction. With increasing gradient steepness, this force passes through a maximum that coincides with maxima in both speed and directionality of the cells. The stochastic part, on the other hand, does not depend on the orientation of the directional cue and remains independent of the gradient magnitude. Numerical simulations of our probabilistic model yield quantitative agreement with the experimental distribution functions. Thus our model captures well the dynamics of chemotactic cells and can serve to quantify differences and similarities of different chemotactic eukaryotes. Finally, on the basis of our model, we can characterize the heterogeneity within a population of chemotactic cells.
Indian monsoon rainfall is vital for a large share of the world's population. Both reliably projecting India's future precipitation and unraveling abrupt cessations of monsoon rainfall found in paleorecords require improved understanding of its stability properties. While details of monsoon circulations and the associated rainfall are complex, full-season failure is dominated by large-scale positive feedbacks within the region. Here we find that in a comprehensive climate model, monsoon failure is possible but very rare under pre-industrial conditions, while under future warming it becomes much more frequent. We identify the fundamental intraseasonal feedbacks that are responsible for monsoon failure in the climate model, relate these to observational data, and build a statistically predictive model for such failure. This model provides a simple dynamical explanation for future changes in the frequency distribution of seasonal mean all-Indian rainfall. Forced only by global mean temperature and the strength of the Pacific Walker circulation in spring, it reproduces the trend as well as the multidecadal variability in the mean and skewness of the distribution, as found in the climate model. The approach offers an alternative perspective on large-scale monsoon variability as the result of internal instabilities modulated by pre-seasonal ambient climate conditions.
Macromolecular crowding in living biological cells effects subdiffusion of larger biomolecules such as proteins and enzymes. Mimicking this subdiffusion in terms of random walks on a critical percolation cluster, we here present a case study of EcoRV restriction enzymes involved in vital cellular defence. We show that due to its so far elusive propensity to an inactive state the enzyme avoids non-specific binding and remains well-distributed in the bulk cytoplasm of the cell. Despite the reduced volume exploration capability of subdiffusion processes, this mechanism guarantees a high efficiency of the enzyme. By variation of the non-specific binding constant and the bond occupation probability on the percolation network, we demonstrate that reduced nonspecific binding are beneficial for efficient subdiffusive enzyme activity even in relatively small bacteria cells. Our results corroborate a more local picture of cellular regulation.
The Riemann hypothesis is equivalent to the fact the the reciprocal function 1/zeta (s) extends from the interval (1/2,1) to an analytic function in the quarter-strip 1/2 < Re s < 1 and Im s > 0. Function theory allows one to rewrite the condition of analytic continuability in an elegant form amenable to numerical experiments.
A setup for resonant inelastic soft x-ray scattering on liquids at free electron laser light sources
(2012)
We present a flexible and compact experimental setup that combines an in vacuum liquid jet with an x-ray emission spectrometer to enable static and femtosecond time-resolved resonant inelastic soft x-ray scattering (RIXS) measurements from liquids at free electron laser (FEL) light sources. We demonstrate the feasibility of this type of experiments with the measurements performed at the Linac Coherent Light Source FEL facility. At the FEL we observed changes in the RIXS spectra at high peak fluences which currently sets a limit to maximum attainable count rate at FELs. The setup presented here opens up new possibilities to study the structure and dynamics in liquids.
Volcanic eruptions are often preceded by seismic activity that can be used to quantify the volcanic activity. In order to allow consistent inference of the volcanic activity state from the observed seismicity patterns, objective and time-invariant classification results achievable by automatic systems should be preferred. Most automatic classification approaches need a large preclassified data set for training the system. However, in case of a volcanic crisis, we are often confronted with a lack of training data due to insufficient prior observations. In the worst case (e. g., volcanic crisis related reconfiguration of stations), there are even no prior observations available. Finally, due to the imminent crisis there might be no time for the time-consuming process of preparing a training data set. For this reason, we have developed a novel seismic-event spotting technique in order to be less dependent on previously acquired data bases and classification schemes. We are using a learning-while-recording approach based on a minimum number of reference waveforms, thus allowing for the build-up of a classification scheme as early as interesting events have been identified. First, short-term wave-field parameters (here, polarization and spectral attributes) are extracted from a continuous seismic data stream. The sequence of multidimensional feature vectors is then used to identify a fixed number of clusters in the feature space. Based on this general description of the overall wave field by a mixture of multivariate Gaussians, we are able to learn particular event classifiers (here, hidden Markov models) from a single waveform example. To show the capabilities of this new approach we apply the algorithm to a data set recorded at Soufriere Hills volcano, Montserrat. Supported by very high classification rates, we conclude that the suggested approach provides a valuable tool for volcano monitoring systems.
We reconsider the fundamental work of Fichtner 2 and exhibit the permanental structure of the ideal Bose gas again, using a new approach which combines a characterization of infinitely divisible random measures (due to Kerstan, Kummer and Matthes 4, 6 and Mecke 9, 10) with a decomposition of the moment measures into its factorial measures due to Krickeberg 5. To be more precise, we exhibit the moment measures of all orders of the general ideal Bose gas in terms of certain loop integrals. This representation can be considered as a point process analogue of the old idea of Symanzik 15 that local times and self-crossings of the Brownian motion can be used as a tool in quantum field theory. Behind the notion of a general ideal Bose gas there is a class of infinitely divisible point processes of all orders with a Levy-measure belonging to some large class of measures containing that of the classical ideal Bose gas considered by Fichtner. It is well-known that the calculation of moments of higher order of point processes is notoriously complicated. See for instance Krickebergs calculations for the Poisson or the Cox process in 5. Relations to the work of Shirai, Takahashi 12 and Soshnikov 14 on permanental and determinantal processes are outlined.
Sk 183 is the visually brightest star in the N90 nebula, a young star-forming region in the Wing of the Small Magellanic Cloud (SMC). We present new optical spectroscopy from the Very Large Telescope which reveals Sk 183 to be one of the most massive O-type stars in the SMC. Classified as an O3-type dwarf on the basis of its nitrogen spectrum, the star also displays broadened He I absorption, which suggests a later type. We propose that Sk 183 has a composite spectrum and that it is similar to another star in the SMC, MPG 324. This brings the number of rare O2- and O3-type stars known in the whole of the SMC to a mere four. We estimate physical parameters for Sk 183 from analysis of its spectrum. For a single-star model, we estimate an effective temperature of 46 +/- 2 kK, a low mass-loss rate of similar to 10(-7) M-circle dot yr(-1), and a spectroscopic mass of 46(-8)(+ 9) M-circle dot (for an adopted distance modulus of 18.7 mag to the young population in the SMC Wing). An illustrative binary model requires a slightly hotter temperature (similar to 47.5 kK) for the primary component. In either scenario, Sk 183 is the earliest-type star known in N90 and will therefore be the dominant source of hydrogen-ionizing photons. This suggests Sk 183 is the primary influence on the star formation along the inner edge of the nebula.
Land use is increasingly recognized as a major driver of biodiversity and ecosystem functioning in many current research projects. In grasslands, land use is often classified by categorical descriptors such as pastures versus meadows or fertilized versus unfertilized sites. However, to account for the quantitative variation of multiple land-use types in heterogeneous landscapes, a quantitative, continuous index of land-use intensity (LUI) is desirable. Here we define such a compound, additive LUI index for managed grasslands including meadows and pastures. The LUI index summarizes the standardized intensity of three components of land use, namely fertilization, mowing, and livestock grazing at each site. We examined the performance of the LUI index to predict selected response variables on up to 150 grassland sites in the Biodiversity Exploratories in three regions in Germany(Alb, Hainich, Schorlheide). We tested the average Ellenberg nitrogen indicator values of the plant community, nitrogen and phosphorus concentration in the aboveground plant biomass, plant-available phosphorus concentration in the top soil, and soil C/N ratio, and the first principle component of these five response variables.
The LUI index significantly predicted the principal component of all five response variables, as well as some of the individual responses. Moreover, vascular plant diversity decreased significantly with LUI in two regions (Alb and Hainich).
Inter-annual changes in management practice were pronounced from 2006 to 2008, particularly due to variation in grazing intensity. This rendered the selection of the appropriate reference year(s) an important decision for analyses of land-use effects, whereas details in the standardization of the index were of minor importance. We also tested several alternative calculations of a LUI index, but all are strongly linearly correlated to the proposed index.
The proposed LUI index reduces the complexity of agricultural practices to a single dimension and may serve as a baseline to test how different groups of organisms and processes respond to land use. In combination with more detailed analyses, this index may help to unravel whether and how land-use intensities, associated disturbance levels or other local or regional influences drive ecological processes.
A parametric study of erupting flux rope rotation modeling the "Cartwheel CME" on 9 April 2008
(2012)
The rotation of erupting filaments in the solar corona is addressed through a parametric simulation study of unstable, rotating flux ropes in bipolar force-free initial equilibrium. The Lorentz force due to the external shear-field component and the relaxation of tension in the twisted field are the major contributors to the rotation in this model, while reconnection with the ambient field is of minor importance, due to the field's simple structure. In the low-beta corona, the rotation is not guided by the changing orientation of the vertical field component's polarity inversion line with height. The model yields strong initial rotations which saturate in the corona and differ qualitatively from the profile of rotation vs. height obtained in a recent simulation of an eruption without preexisting flux rope. Both major mechanisms writhe the flux rope axis, converting part of the initial twist helicity, and produce rotation profiles which, to a large part, are very similar within a range of shear-twist combinations. A difference lies in the tendency of twist-driven rotation to saturate at lower heights than shear-driven rotation. For parameters characteristic of the source regions of erupting filaments and coronal mass ejections, the shear field is found to be the dominant origin of rotations in the corona and to be required if the rotation reaches angles of order 90 degrees and higher; it dominates even if the twist exceeds the threshold of the helical kink instability. The contributions by shear and twist to the total rotation can be disentangled in the analysis of observations if the rotation and rise profiles are simultaneously compared with model calculations. The resulting twist estimate allows one to judge whether the helical kink instability occurred. This is demonstrated for the erupting prominence in the "Cartwheel CME" on 9 April 2008, which has shown a rotation of a parts per thousand aEuro parts per thousand 115(a similar to) up to a height of 1.5 R (aS (TM)) above the photosphere. Out of a range of initial equilibria which include strongly kink-unstable (twist I broken vertical bar=5 pi), weakly kink-unstable (I broken vertical bar=3.5 pi), and kink-stable (I broken vertical bar=2.5 pi) configurations, only the evolution of the weakly kink-unstable flux rope matches the observations in their entirety.
Silver nanoparticles (SNPs) are among the most commercialized nanoparticles worldwide. Often SNP are used because of their antibacterial properties. Besides that they possess unique optic and catalytic features, making them highly interesting for the creation of novel and advanced functional materials. Despite its widespread use only little data exist in terms of possible adverse effects of SNP on human health. Conventional synthesis routes usually yield products of varying quality and property. It thus may become puzzling to compare biological data from different studies due to the great variety in sizes, coatings or shapes of the particles applied. Here, we applied a novel synthesis approach to obtain SNP of well-defined colloidal and structural properties. Being stabilized by a covalently linked small peptide, these particles are nicely homogenous, with narrow size distribution, and form monodisperse suspensions in aqueous solutions. We applied these peptide-coated SNP in two different sizes of 20 or 40 nm (Ag20Pep and Ag40Pep) and analyzed responses of THP-1-derived human macrophages while being exposed against these particles. Gold nanoparticles of similar size and coating (Au20Pep) were used for comparison. The cytotoxicity of particles was assessed by WST-1 and LDH assays, and the uptake into the cells was confirmed via transmission electron microscopy. In summary, our data demonstrate that this novel type of SNP is well suited to serve as model system for nanoparticles to be tested in toxicological studies in vitro.
A nanostructured chip surface was fabricated enabling binding via spaced antibodies specifically targeting surface proteins of cancer cells and detection of extremely low numbers of circulating tumor cells (CTC) without labeling using a sam (R) 5 biosensor. The antibody surfaces mostly were generated by self assembly of antibodies to gold nanospots on the sensitive SiO2-surface of a sam (R) 5 chip. Compared with a complete gold surface, only 40% of the amount of antibodies was bound to the nanospot surface, but structured such that 15-fold higher sensitivity to vital cancer cells was achieved. Human cancer cell lines JEG-3 (lmphoblastic leukemia) and MOLT-17 (placental choriocarcinoma) from cell cultures were successfully detected. The sensor showed significant responses on less than 10 cells injected in a single run. The extreme increase in sensitivity and its simple regeneration emphasizes the usefulness of its introduction in biomedical applications. (C) 2011 Elsevier B.V. All rights reserved.
We present a minimal conceptual model for the Atlantic meridional overturning circulation which incorporates the advection of salinity and the basic dynamics of the oceanic pycnocline. Four tracer transport processes following Gnanadesikan in Science 283(5410):2077-2079, (1999) allow for a dynamical adjustment of the oceanic pycnocline which defines the vertical extent of a mid-latitudinal box. At the same time the model captures the salt-advection feedback (Stommel in Tellus 13(2):224-230, (1961)). Due to its simplicity the model can be solved analytically in the purely wind- and purely mixing-driven cases. We find the possibility of abrupt transition in response to surface freshwater forcing in both cases even though the circulations are very different in physics and geometry. This analytical approach also provides expressions for the critical freshwater input marking the change in the dynamics of the system. Our analysis shows that including the pycnocline dynamics in a salt-advection model causes a decrease in the freshwater sensitivity of its northern sinking up to a threshold at which the circulation breaks down. Compared to previous studies the model is restricted to the essential ingredients. Still, it exhibits a rich behavior which reaches beyond the scope of this study and might be used as a paradigm for the qualitative behaviour of the Atlantic overturning in the discussion of driving mechanisms.
Structural kinetic modeling (SKM) enables the analysis of dynamical properties of metabolic networks solely based on topological information and experimental data. Current SKM-based experiments are hampered by the time-intensive process of assigning model parameters and choosing appropriate sampling intervals for MonteCarlo experiments. We introduce a toolbox for the automatic and efficient construction and evaluation of structural kinetic models (SK models). Quantitative and qualitative analyses of network stability properties are performed in an automated manner. We illustrate the model building and analysis process in detailed example scripts that provide toolbox implementations of previously published literature models.
A lamin in lower eukaryotes?
(2012)
Lamins are the major components of the nuclear lamina and serve not only as a mechanical support, but are also involved in chromatin organization, epigenetic regulation, transcription and mitotic events. Despite these universal tasks, lamins have so far been found only in metazoans. Yet, recently we have identified Dictyostelium NE81 as the first lamin-like protein in a lower eukaryote. Based on the current knowledge, we draw a model for nuclear envelope organization in Dictyostelium in this Extra View and we review the experimental data that justified this classification. Furthermore we provide unpublished data underscoring the requirement of posttranslational CaaX-box processing for proper protein localization at the nuclear envelope. Sequence comparison of NE81 sequences from four Dictyostelia with bona fide lamins illustrates the evolutional relationship between these proteins. Under certain conditions these usually unicellular social amoebae congregate to form a multicellular body. We propose that the evolution of the lamin-like NE81 went along with the invention of multicellularity.
There is much recent interest in the idea that we represent our knowledge together with the sensory and motor features that were activated during its acquisition. This paper reviews the evidence for such "embodiment" in the domain of numerical cognition, a traditional stronghold of abstract theories of knowledge representation. The focus is on spatial-numerical associations, such as the SNARC effect (small numbers are associated with left space, larger numbers with right space). Using empirical evidence from behavioral research, I first describe sensory and motor biases induced by SNARC, thus identifying numbers as embodied concepts. Next, I propose a hierarchical relationship between grounded, embodied, and situated aspects of number knowledge. This hierarchical conceptualization helps to understand the variety of SNARC-related findings and yields testable predictions about numerical cognition. I report several such tests, ranging from cross-cultural comparisons of horizontal and vertical SNARC effects (Shaki and Fischer in J Exp Psychol Hum Percept Perform 38(3): 804-809, 2012) to motor cortical activation studies in adults with left- and right-hand counting preferences (Tschentscher et al. in NeuroImage 59: 3139-3148, 2012). It is concluded that the diagnostic features for each level of the proposed hierarchical knowledge representation, together with the spatial associations of numbers, make the domain of numerical knowledge an ideal testing ground for embodied cognition research.
In the present study, the effects of ionic liquids (ILs) on the stability of nanoparticles in several IL compositions were investigated. In this context, we examined the primary role of ILs in the synthesis of metal/metal oxide nanoparticles and their dispersions extensively. However, the focus of the discussion in this communication centers mainly on the effect of EMIM Ethyl Sulfate on growth and stability of nanoparticles. The dispersion properties of ILs based on their ability to aid the synthesis of uniformly dispersed nanoparticles have been further explored to produce nanoparticles of an effective catalyst useful in water purification, soil remediation and battery applications. Two independent protocols were developed for the synthesis of nanoparticles, namely (a) one pot process via chemical reduction (b) dispersion of the inorganic material in ILs. The protocols are simple, sustainable and environmentally friendly because the processes are conducted in ILs as harmless non-toxic green solvent materials. The catalysts were analyzed by x-ray diffraction, electron microscopy, UV visible spectroscopy and dynamic light scattering as the main methodologies.
We generalize the popular ensemble Kalman filter to an ensemble transform filter, in which the prior distribution can take the form of a Gaussian mixture or a Gaussian kernel density estimator. The design of the filter is based on a continuous formulation of the Bayesian filter analysis step. We call the new filter algorithm the ensemble Gaussian-mixture filter (EGMF). The EGMF is implemented for three simple test problems (Brownian dynamics in one dimension, Langevin dynamics in two dimensions and the three-dimensional Lorenz-63 model). It is demonstrated that the EGMF is capable of tracking systems with non-Gaussian uni- and multimodal ensemble distributions.
Background
High blood glucose and diabetes are amongst the conditions causing the greatest losses in years of healthy life worldwide. Therefore, numerous studies aim to identify reliable risk markers for development of impaired glucose metabolism and type 2 diabetes. However, the molecular basis of impaired glucose metabolism is so far insufficiently understood. The development of so called 'omics' approaches in the recent years promises to identify molecular markers and to further understand the molecular basis of impaired glucose metabolism and type 2 diabetes. Although univariate statistical approaches are often applied, we demonstrate here that the application of multivariate statistical approaches is highly recommended to fully capture the complexity of data gained using high-throughput methods.
Methods
We took blood plasma samples from 172 subjects who participated in the prospective Metabolic Syndrome Berlin Potsdam follow-up study (MESY-BEPO Follow-up). We analysed these samples using Gas Chromatography coupled with Mass Spectrometry (GC-MS), and measured 286 metabolites. Furthermore, fasting glucose levels were measured using standard methods at baseline, and after an average of six years. We did correlation analysis and built linear regression models as well as Random Forest regression models to identify metabolites that predict the development of fasting glucose in our cohort.
Results
We found a metabolic pattern consisting of nine metabolites that predicted fasting glucose development with an accuracy of 0.47 in tenfold cross-validation using Random Forest regression. We also showed that adding established risk markers did not improve the model accuracy. However, external validation is eventually desirable. Although not all metabolites belonging to the final pattern are identified yet, the pattern directs attention to amino acid metabolism, energy metabolism and redox homeostasis.
Conclusions
We demonstrate that metabolites identified using a high-throughput method (GC-MS) perform well in predicting the development of fasting plasma glucose over several years. Notably, not single, but a complex pattern of metabolites propels the prediction and therefore reflects the complexity of the underlying molecular mechanisms. This result could only be captured by application of multivariate statistical approaches. Therefore, we highly recommend the usage of statistical methods that seize the complexity of the information given by high-throughput methods.
A direct competitive homogeneous immunoassay for progesterone - the Redox Quenching Immunoassay
(2012)
A direct competitive amperometric immunoassay format for the detection of haptens and proteins was developed. The method is based on the quenching of electroactivity of ferrocenium, which is coupled to the antigen and used as the primary reporter, upon binding to a monoclonal anti-ferrocenium antibody, which is coupled to the detection antibody and used as a secondary reporter. A separation-free progesterone immunoassay with a lower detection limit of 1 ng?mL-1 (3.18 nmol?L-1) in 1?:?2 diluted blood serum was realised by combining two bifunctional conjugates, a ferrocenium-PEG-progesterone tracer and a bioconjugate of one anti-progesterone and one anti-ferrocenium antibody. The immune complex is formed within 30 s upon addition of progesterone, resulting in a total analysis time of 1.5 min.
In the context of cosmological structure formation sheets, filaments and eventually halos form due to gravitational instabilities. It is noteworthy, that at all times, the majority of the baryons in the universe does not reside in the dense halos but in the filaments and the sheets of the intergalactic medium. While at higher redshifts of z > 2, these baryons can be detected via the absorption of light (originating from more distant sources) by neutral hydrogen at temperatures of T ~ 10^4 K (the Lyman-alpha forest), at lower redshifts only about 20 % can be found in this state. The remain (about 50 to 70 % of the total baryons mass) is unaccounted for by observational means. Numerical simulations predict that these missing baryons could reside in the filaments and sheets of the cosmic web at high temperatures of T = 10^4.5 - 10^7 K, but only at low to intermediate densities, and constitutes the warm-hot intergalactic medium (WHIM). The high temperatures of the WHIM are caused by the formation of shocks and the subsequent shock-heating of the gas. This results in a high degree of ionization and renders the reliable detection of the WHIM a challenging task. Recent high-resolution hydrodynamical simulations indicate that, at redshifts of z ~ 2, filaments are able to provide very massive galaxies with a significant amount of cool gas at temperatures of T ~ 10^4 K. This could have an important impact on the star-formation in those galaxies. It is therefore of principle importance to investigate the particular hydro- and thermodynamical conditions of these large filament structures. Density and temperature profiles, and velocity fields, are expected to leave their special imprint on spectroscopic observations. A potential multiphase structure may act as tracer in observational studies of the WHIM. In the context of cold streams, it is important to explore the processes, which regulate the amount of gas transported by the streams. This includes the time evolution of filaments, as well as possible quenching mechanisms. In this context, the halo mass range in which cold stream accretion occurs is of particular interest. In order to address these questions, we perform particular hydrodynamical simulations of very high resolution, and investigate the formation and evolution of prototype structures representing the typical filaments and sheets of the WHIM. We start with a comprehensive study of the one-dimensional collapse of a sinusoidal density perturbation (pancake formation) and examine the influence of radiative cooling, heating due to an UV background, thermal conduction, and the effect of small-scale perturbations given by the cosmological power spectrum. We use a set of simulations, parametrized by the wave length of the initial perturbation L. For L ~ 2 Mpc/h the collapse leads to shock-confined structures. As a result of radiative cooling and of heating due to an UV background, a relatively cold and dense core forms. With increasing L the core becomes denser and more concentrated. Thermal conduction enhances this trend and may lead to an evaporation of the core at very large L ~ 30 Mpc/h. When extending our simulations into three dimensions, instead of a pancake structure, we obtain a configuration consisting of well-defined sheets, filaments, and a gaseous halo. For L > 4 Mpc/h filaments form, which are fully confined by an accretion shock. As with the one-dimensional pancakes, they exhibit an isothermal core. Thus, our results confirm a multiphase structure, which may generate particular spectral tracers. We find that, after its formation, the core becomes shielded against further infall of gas onto the filament, and its mass content decreases with time. In the vicinity of the halo, the filament's core can be attributed to the cold streams found in other studies. We show, that the basic structure of these cold streams exists from the very beginning of the collapse process. Further on, the cross section of the streams is constricted by the outwards moving accretion shock of the halo. Thermal conduction leads to a complete evaporation of the cold stream for L > 6 Mpc/h. This corresponds to halos with a total mass higher than M_halo = 10^13 M_sun, and predicts that in more massive halos star-formation can not be sustained by cold streams. Far away from the gaseous halo, the temperature gradients in the filament are not sufficiently strong for thermal conduction to be effective.
Monsoon systems around the world are governed by the so-called moisture-advection feedback. Here we show that, in a minimal conceptual model, this feedback implies a critical threshold with respect to the atmospheric specific humidity q(o) over the ocean adjacent to the monsoon region. If q(o) falls short of this critical value q(o)(c), monsoon rainfall over land cannot be sustained. Such a case could occur if evaporation from the ocean was reduced, e.g. due to low sea surface temperatures. Within the restrictions of the conceptual model, we estimate q(o)(c) from present-day reanalysis data for four major monsoon systems, and demonstrate how this concept can help understand abrupt variations in monsoon strength on orbital timescales as found in proxy records.