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Aims. We present an extensive study of the BL Lac object Mrk 501 based on a data set collected during the multi-instrument campaign spanning from 2009 March 15 to 2009 August 1, which includes, among other instruments, MAGIC, VERITAS, Whipple 10 m, and Fermi-LAT to cover the gamma-ray range from 0.1 GeV to 20 TeV; RXTE and Swift to cover wavelengths from UV to hard X-rays; and GASP-WEBT, which provides coverage of radio and optical wavelengths. Optical polarization measurements were provided for a fraction of the campaign by the Steward and St. Petersburg observatories. We evaluate the variability of the source and interband correlations, the gamma-ray flaring activity occurring in May 2009, and interpret the results within two synchrotron self-Compton (SSC) scenarios. Methods. The multiband variability observed during the full campaign is addressed in terms of the fractional variability, and the possible correlations are studied by calculating the discrete correlation function for each pair of energy bands where the significance was evaluated with dedicated Monte Carlo simulations. The space of SSC model parameters is probed following a dedicated grid-scan strategy, allowing for a wide range of models to be tested and offering a study of the degeneracy of model-to-data agreement in the individual model parameters, hence providing a less biased interpretation than the "single-curve SSC model adjustment" typically reported in the literature. Results. We find an increase in the fractional variability with energy, while no significant interband correlations of flux changes are found on the basis of the acquired data set. The SSC model grid-scan shows that the flaring activity around May 22 cannot be modeled adequately with a one-zone SSC scenario (using an electron energy distribution with two breaks), while it can be suitably described within a two (independent) zone SSC scenario. Here, one zone is responsible for the quiescent emission from the averaged 4.5-month observing period, while the other one, which is spatially separated from the first, dominates the flaring emission occurring at X-rays and very-high-energy (> 100 GeV, VHE) gamma-rays. The flaring activity from May 1, which coincides with a rotation of the electric vector polarization angle (EVPA), cannot be satisfactorily reproduced by either a one-zone or a two-independent-zone SSC model, yet this is partially affected by the lack of strictly simultaneous observations and the presence of large flux changes on sub-hour timescales (detected at VHE gamma rays). Conclusions. The higher variability in the VHE emission and lack of correlation with the X-ray emission indicate that, at least during the 4.5-month observing campaign in 2009, the highest energy (and most variable) electrons that are responsible for the VHE gamma rays do not make a dominant contribution to the similar to 1 keV emission. Alternatively, there could be a very variable component contributing to the VHE gamma-ray emission in addition to that coming from the SSC scenario. The studies with our dedicated SSC grid-scan show that there is some degeneracy in both the one-zone and the two-zone SSC scenarios probed, with several combinations of model parameters yielding a similar model-to-data agreement, and some parameters better constrained than others. The observed gamma-ray flaring activity, with the EVPA rotation coincident with the first gamma-ray flare, resembles those reported previously for low frequency peaked blazars, hence suggesting that there are many similarities in the flaring mechanisms of blazars with different jet properties.
Low thermal conductivity boulder with high porosity identified on C-type asteroid (162173) Ryugu
(2019)
C-type asteroids are among the most pristine objects in the Solar System, but little is known about their interior structure and surface properties. Telescopic thermal infrared observations have so far been interpreted in terms of a regolith-covered surface with low thermal conductivity and particle sizes in the centimetre range. This includes observations of C-type asteroid (162173) Ryugu1,2,3. However, on arrival of the Hayabusa2 spacecraft at Ryugu, a regolith cover of sand- to pebble-sized particles was found to be absent4,5 (R.J. et al., manuscript in preparation). Rather, the surface is largely covered by cobbles and boulders, seemingly incompatible with the remote-sensing infrared observations. Here we report on in situ thermal infrared observations of a boulder on the C-type asteroid Ryugu. We found that the boulder’s thermal inertia was much lower than anticipated based on laboratory measurements of meteorites, and that a surface covered by such low-conductivity boulders would be consistent with remote-sensing observations. Our results furthermore indicate high boulder porosities as well as a low tensile strength in the few hundred kilopascal range. The predicted low tensile strength confirms the suspected observational bias6 in our meteorite collections, as such asteroidal material would be too frail to survive atmospheric entry7.
Low thermal conductivity boulder with high porosity identified on C-type asteroid (162173) Ryugu
(2019)
C-type asteroids are among the most pristine objects in the Solar System, but little is known about their interior structure and surface properties. Telescopic thermal infrared observations have so far been interpreted in terms of a regolith-covered surface with low thermal conductivity and particle sizes in the centimetre range. This includes observations of C-type asteroid (162173) Ryugu1,2,3. However, on arrival of the Hayabusa2 spacecraft at Ryugu, a regolith cover of sand- to pebble-sized particles was found to be absent4,5 (R.J. et al., manuscript in preparation). Rather, the surface is largely covered by cobbles and boulders, seemingly incompatible with the remote-sensing infrared observations. Here we report on in situ thermal infrared observations of a boulder on the C-type asteroid Ryugu. We found that the boulder’s thermal inertia was much lower than anticipated based on laboratory measurements of meteorites, and that a surface covered by such low-conductivity boulders would be consistent with remote-sensing observations. Our results furthermore indicate high boulder porosities as well as a low tensile strength in the few hundred kilopascal range. The predicted low tensile strength confirms the suspected observational bias6 in our meteorite collections, as such asteroidal material would be too frail to survive atmospheric entry7
Myofibrillar myopathy (MFM) is a human disease that is characterized by focal myofibrillar destruction and pathological cytoplasmic protein aggregations. In an extended German pedigree with a novel form of MFM characterized by clinical features of a limb-girdle myopathy and morphological features of MFM, we identified a cosegregating, heterozygous nonsense mutation (8130G -> A; W2710X) in the filamin c gene ( FLNC) on chromosome 7q32.1. The mutation is the first found in FLNC and is localized in the dimerization domain of filamin c. Functional studies showed that, in the truncated mutant protein, this domain has a disturbed secondary structure that leads to the inability to dimerize properly. As a consequence of this malfunction, the muscle fibers of our patients display massive cytoplasmic aggregates containing filamin c and several Z-disk-associated and sarcolemmal proteins
AimAdvancement in ecological methods predicting species distributions is a crucial precondition for deriving sound management actions. Maximum entropy (MaxEnt) models are a popular tool to predict species distributions, as they are considered able to cope well with sparse, irregularly sampled data and minor location errors. Although a fundamental assumption of MaxEnt is that the entire area of interest has been systematically sampled, in practice, MaxEnt models are usually built from occurrence records that are spatially biased towards better-surveyed areas. Two common, yet not compared, strategies to cope with uneven sampling effort are spatial filtering of occurrence data and background manipulation using environmental data with the same spatial bias as occurrence data. We tested these strategies using simulated data and a recently collated dataset on Malay civet Viverra tangalunga in Borneo.
LocationBorneo, Southeast Asia.
MethodsWe collated 504 occurrence records of Malay civets from Borneo of which 291 records were from 2001 to 2011 and used them in the MaxEnt analysis (baseline scenario) together with 25 environmental input variables. We simulated datasets for two virtual species (similar to a range-restricted highland and a lowland species) using the same number of records for model building. As occurrence records were biased towards north-eastern Borneo, we investigated the efficacy of spatial filtering versus background manipulation to reduce overprediction or underprediction in specific areas.
ResultsSpatial filtering minimized omission errors (false negatives) and commission errors (false positives). We recommend that when sample size is insufficient to allow spatial filtering, manipulation of the background dataset is preferable to not correcting for sampling bias, although predictions were comparatively weak and commission errors increased.
Main ConclusionsWe conclude that a substantial improvement in the quality of model predictions can be achieved if uneven sampling effort is taken into account, thereby improving the efficacy of species conservation planning.
Interest in developing a new method of man-to-machine communication-a brain-computer interface (BCI)-has grown steadily over the past few decades. BCIs create a new communication channel between the brain and an output device by bypassing conventional motor output pathways of nerves and muscles. These systems use signals recorded from the scalp, the surface of the cortex, or from inside the brain to enable users to control a variety of applications including simple word-processing software and orthotics. BCI technology could therefore provide a new communication and control option for individuals who cannot otherwise express their wishes to the outside world. Signal processing and classification methods are essential tools in the development of improved BCI technology. We organized the BCI Competition 2003 to evaluate the current state of the art of these tools. Four laboratories well versed in EEG-based BCI research provided six data sets in a documented format. We made these data sets (i.e., labeled training sets and unlabeled test sets) and their descriptions available on the Internet. The goal in the competition was to maximize the performance measure for the test labels. Researchers worldwide tested their algorithms and competed for the best classification results. This paper describes the six data sets and the results and function of the most successful algorithms
The prototypical photoinduced dissociation of Fe(CO)(5) in the gas phase is used to test time-resolved x-ray photoelectron spectroscopy for studying photochemical reactions. Upon one-photon excitation at 266 nm, Fe(CO)(5) successively dissociates to Fe(CO)(4) and Fe(CO)(3) along a pathway where both fragments retain the singlet multiplicity of Fe(CO)(5). The x-ray free-electron laser FLASH is used to probe the reaction intermediates Fe(CO)(4) and Fe(CO)(3) with time-resolved valence and core-level photoelectron spectroscopy, and experimental results are interpreted with ab initio quantum chemical calculations. Changes in the valence photoelectron spectra are shown to reflect changes in the valenceorbital interactions upon Fe-CO dissociation, thereby validating fundamental theoretical concepts in Fe-CO bonding. Chemical shifts of CO 3 sigma inner-valence and Fe 3 sigma core-level binding energies are shown to correlate with changes in the coordination number of the Fe center. We interpret this with coordination-dependent charge localization and core-hole screening based on calculated changes in electron densities upon core-hole creation in the final ionic states. This extends the established capabilities of steady-state electron spectroscopy for chemical analysis to time-resolved investigations. It could also serve as a benchmark for howcharge and spin density changes in molecular dissociation and excited-state dynamics are expressed in valence and core-level photoelectron spectroscopy. Published by AIP Publishing.
Collinearity a review of methods to deal with it and a simulation study evaluating their performance
(2013)
Collinearity refers to the non independence of predictor variables, usually in a regression-type analysis. It is a common feature of any descriptive ecological data set and can be a problem for parameter estimation because it inflates the variance of regression parameters and hence potentially leads to the wrong identification of relevant predictors in a statistical model. Collinearity is a severe problem when a model is trained on data from one region or time, and predicted to another with a different or unknown structure of collinearity. To demonstrate the reach of the problem of collinearity in ecology, we show how relationships among predictors differ between biomes, change over spatial scales and through time. Across disciplines, different approaches to addressing collinearity problems have been developed, ranging from clustering of predictors, threshold-based pre-selection, through latent variable methods, to shrinkage and regularisation. Using simulated data with five predictor-response relationships of increasing complexity and eight levels of collinearity we compared ways to address collinearity with standard multiple regression and machine-learning approaches. We assessed the performance of each approach by testing its impact on prediction to new data. In the extreme, we tested whether the methods were able to identify the true underlying relationship in a training dataset with strong collinearity by evaluating its performance on a test dataset without any collinearity. We found that methods specifically designed for collinearity, such as latent variable methods and tree based models, did not outperform the traditional GLM and threshold-based pre-selection. Our results highlight the value of GLM in combination with penalised methods (particularly ridge) and threshold-based pre-selection when omitted variables are considered in the final interpretation. However, all approaches tested yielded degraded predictions under change in collinearity structure and the folk lore'-thresholds of correlation coefficients between predictor variables of |r| >0.7 was an appropriate indicator for when collinearity begins to severely distort model estimation and subsequent prediction. The use of ecological understanding of the system in pre-analysis variable selection and the choice of the least sensitive statistical approaches reduce the problems of collinearity, but cannot ultimately solve them.
Species distribution models are useful for identifying driving environmental factors that determine earthworm distributions as well as for predicting earthworm distribution patterns and abundances at different scales. However, due to large efforts in data acquisition, studies on larger scales are rare and often focus on single species or earthworms in general. In this study, we use boosted regression tree models (BRTs) for predicting the distribution of the three functional earthworm types, i.e. anecics, endogeics and epigeics, in an agricultural area in Baden-Wurttemberg (Southwest Germany).
First, we predicted presence and absence and later earthworm abundances, considering predictors depicting land management, topography, and soil conditions as well as biotic interaction by using the abundance of the other functional earthworm types. The final presence-absence models performed reasonably well, with explained deviances between 24 and 51% after crossvalidation. Models for abundances of anecics and endogeics were less successful, since the high small-scale variability and patchiness in earthworm abundance influenced the representativeness of the field measurements. This resulted in a significant model uncertainty, which is practically very difficult to overcome with earthworm sampling campaigns at the catchment scale.
Results showed that management practices (i.e. disturbances), topography, soil conditions, and biotic interactions with other earthworm groups are the most relevant predictors for spatial distribution (incidence) patterns of all three functional groups. The response curves and contributions of predictors differ for the three functional earthworm types. Epigeics are also controlled by topographic features, endogeics by soil parameters.
Questions: Which are the factors that influence forest and shrubland loss and regeneration and their underlying drivers?
Location: Central Chile, a world biodiversity hotspot.
Methods: Using land-cover data from the years 1975, 1985, 1999 and 2008, we fitted classification trees and multiple logistic regression models to account for the relationship between different trajectories of vegetation change and a range of biophysical and socio-economic factors.
Results: The variables that most consistently showed significant effects on vegetation change across all time-intervals were slope and distance to primary roads. We found that forest and shrubland loss on one side and regeneration on the other often displayed opposite patterns in relation to the different explanatory variables. Deforestation was positively related to distance to primary roads and to distance within forest edges and was favoured by a low insolation and a low slope. In turn, forest regeneration was negatively related to the distance to primary roads and positively to the distance to the nearest forest patch, insolation and slope. Shrubland loss was positively influenced by slope and distance to cities and primary roads and negatively influenced by distance to rivers. Conversely, shrubland regeneration was negatively related to slope, distance to cities and distance to primary roads and positively related to distance from existing forest patches and distance to rivers.
Conclusions: This article reveals how biophysical and socioeconomic factors influence vegetation cover change and the underlying social, political and economical drivers. This assessment provides a basis for management decisions, considering the crucial role of perennial vegetation cover for sustaining biodiversity and ecosystem services.
We prove the hitherto hypothesized sequential dissociation of Fe(CO)(5) in the gas phase upon photoexcitation at 266 nm via a singlet pathway with time-resolved valence and core-level photoelectron spectroscopy with an x-ray free-electron laser. Valence photoelectron spectra are used to identify free CO molecules and to determine the time constants of stepwise dissociation to Fe(CO)(4) within the temporal resolution of the experiment and further to Fe(CO)(3) within 3 ps. Fe 3p core-level photoelectron spectra directly reflect the singlet spin state of the Fe center in Fe(CO)(5), Fe(CO)(4), and Fe(CO)(3) showing that the dissociation exclusively occurs along a singlet pathway without triplet-state contribution. Our results are important for assessing intra- and intermolecular relaxation processes in the photodissociation dynamics of the prototypical Fe(CO)(5) complex in the gas phase and in solution, and they establish time-resolved core-level photoelectron spectroscopy as a powerful tool for determining the multiplicity of transition metals in photochemical reactions of coordination complexes. Published by AIP Publishing.
Das 10. Herbsttreffen Patholinguistik mit dem Schwerpunktthema »Panorama Patholinguistik: Sprachwissenschaft trifft Sprachtherapie« fand am 19.11.2016 in Potsdam statt. Das Herbsttreffen wird seit 2007 jährlich vom Verband für Patholinguistik e.V. (vpl) durchgeführt. Der vorliegende Tagungsband beinhaltet die vier Hauptvorträge zum Schwerpunktthema sowie Beiträge zu den Kurzvorträgen »Patholinguistik im Fokus« und der Posterpräsentationen zu weiteren Themen aus der sprachtherapeutischen Forschung und Praxis.
L-edge spectroscopy of 3d transition metals provides important electronic structure information and has been used in many fields. However, the use of this method for studying dilute aqueous systems, such as metalloenzymes, has not been prevalent because of severe radiation damage and the lack of suitable detection systems. Here we present spectra from a dilute Mn aqueous solution using a high-transmission zone-plate spectrometer at the Linac Coherent Light Source (LCLS). The spectrometer has been optimized for discriminating the Mn L-edge signal from the overwhelming 0 K-edge background that arises from water and protein itself, and the ultrashort LCLS X-ray pulses can outrun X-ray induced damage. We show that the deviations of the partial-fluorescence yield-detected spectra from the true absorption can be well modeled using the state-dependence of the fluorescence yield, and discuss implications for the application of our concept to biological samples.
This paper evaluates the short-run impact of the introduction of a statutory minimum wage in Germany on the hourly wages and monthly earnings of workers targeted by the reform. We first provide detailed descriptive evidence of changes to the wage structure in particular at the bottom of the distribution and distinguish between trends for regularly employed and marginally employed workers. In the causal analysis, we then employ a differential trend adjusted difference-in-differences (DTADD) strategy to identify the extent to which these changes in wages and earnings can be attributed to the minimum wage introduction. We find that the minimum wage introduction can account for hourly wage growth in the order of roughly 6.5 % or (sic)0.45/hour and an increase in monthly earnings of 6.6 % or (sic)53/month. Despite finding wage growth at the bottom of the distribution, the paper documents widespread non-compliance with the mandated wage floor of (sic)8.50/hour.
Movement of organisms is one of the key mechanisms shaping biodiversity, e.g. the distribution of genes, individuals and species in space and time. Recent technological and conceptual advances have improved our ability to assess the causes and consequences of individual movement, and led to the emergence of the new field of ‘movement ecology’. Here, we outline how movement ecology can contribute to the broad field of biodiversity research, i.e. the study of processes and patterns of life among and across different scales, from genes to ecosystems, and we propose a conceptual framework linking these hitherto largely separated fields of research. Our framework builds on the concept of movement ecology for individuals, and demonstrates its importance for linking individual organismal movement with biodiversity. First, organismal movements can provide ‘mobile links’ between habitats or ecosystems, thereby connecting resources, genes, and processes among otherwise separate locations. Understanding these mobile links and their impact on biodiversity will be facilitated by movement ecology, because mobile links can be created by different modes of movement (i.e., foraging, dispersal, migration) that relate to different spatiotemporal scales and have differential effects on biodiversity. Second, organismal movements can also mediate coexistence in communities, through ‘equalizing’ and ‘stabilizing’ mechanisms. This novel integrated framework provides a conceptual starting point for a better understanding of biodiversity dynamics in light of individual movement and space-use behavior across spatiotemporal scales. By illustrating this framework with examples, we argue that the integration of movement ecology and biodiversity research will also enhance our ability to conserve diversity at the genetic, species, and ecosystem levels.
The Argentine-German Geodetic Observatory (AGGO) is one of the very few sites in the Southern Hemisphere equipped with comprehensive cutting-edge geodetic instrumentation. The employed observation techniques are used for a wide range of geophysical applications. The data set provides gravity time series and selected gravity models together with the hydrometeorological monitoring data of the observatory. These parameters are of great interest to the scientific community, e.g. for achieving accurate realization of terrestrial and celestial reference frames. Moreover, the availability of the hydrometeorological products is beneficial to inhabitants of the region as they allow for monitoring of environmental changes and natural hazards including extreme events. The hydrological data set is composed of time series of groundwater level, modelled and observed soil moisture content, soil temperature, and physical soil properties and aquifer properties. The meteorological time series include air temperature, humidity, pressure, wind speed, solar radiation, precipitation, and derived reference evapotranspiration. These data products are extended by gravity models of hydrological, oceanic, La Plata estuary, and atmospheric effects. The quality of the provided meteorological time series is tested via comparison to the two closest WMO (World Meteorological Organization) sites where data are available only in an inferior temporal resolution. The hydrological series are validated by comparing the respective forward-modelled gravity effects to independent gravity observations reduced up to a signal corresponding to local water storage variation. Most of the time series cover the time span between April 2016 and November 2018 with either no or only few missing data points. The data set is available at https://doi.org/10.588/GFZ.5.4.2018.001 (Mikolaj et al., 2018).
It has long been appreciated that material chemistry and topology profoundly affect cell adhesion and migration. Here, aqueous poly(N- isopropyl acrylamide) nanogels are designed, synthesized and printed in form of colloidal arrays on glass substrates using wrinkled polydimethylsiloxane templates. Using low-temperature plasma treatment, nanogels are chemically grafted onto glass supports thus leading to highly stable nanogel layers in cell culture media. Liquid cell atomic force microscopy investigations show that surface-grafted nanogels retain their swelling behavior in aqueous media and that extracellular matrix protein coating do not alter their stability and topography. It is demonstrated that surface-grafted nanogels could serve as novel substrates for the analysis of cell adhesion and migration. Nanogels influence size, speed, and dynamics of focal adhesions and cell motility forcing cells to move along highly directional trajectories. Moreover, modulation of nanogel state or spacing serves as an effective tool for regulation of cell motility. It is suggested that nanogel arrays deposited on solid surfaces could be used to provide a precise and tunable system to understand and control cell migration. Additionally, such nanogel arrays will contribute to the development of implantable systems aimed at supporting and enhancing cell migration during, for instance, wound healing and tissue regeneration.