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We present results from deep observations toward the Cygnus region using 300 hr of very high energy (VHE)gamma-ray data taken with the VERITAS Cerenkov telescope array and over 7 yr of high-energy.-ray data taken with the Fermi satellite at an energy above 1 GeV. As the brightest region of diffuse gamma-ray emission in the northern sky, the Cygnus region provides a promising area to probe the origins of cosmic rays. We report the identification of a potential Fermi-LAT counterpart to VER J2031+415 (TeV J2032+4130) and resolve the extended VHE source VER J2019+368 into two source candidates (VER J2018+367* and VER J2020+368*) and characterize their energy spectra. The Fermi-LAT morphology of 3FGL J2021.0+4031e (the Gamma Cygni supernova remnant) was examined, and a region of enhanced emission coincident with VER J2019+407 was identified and jointly fit with the VERITAS data. By modeling 3FGL J2015.6+3709 as two sources, one located at the location of the pulsar wind nebula CTB 87 and one at the quasar QSO J2015+371, a continuous spectrum from 1 GeV to 10 TeV was extracted for VER J2016+371 (CTB 87). An additional 71 locations coincident with Fermi-LAT sources and other potential objects of interest were tested for VHE gamma-ray emission, with no emission detected and upper limits on the differential flux placed at an average of 2.3% of the Crab Nebula flux. We interpret these observations in a multiwavelength context and present the most detailed gamma-ray view of the region to date.
Earth’s surface temperature will continue to rise for another 20 to 30 years even with the strongest carbon emission reduction currently considered. The associated changes in rainfall patterns can result in an increased flood risk worldwide. We compute the required increase in flood protection to keep high-end fluvial flood risk at present levels. The analysis is carried out worldwide for subnational administrative units. Most of the United States, Central Europe, and Northeast and West Africa, as well as large parts of India and Indonesia, require the strongest adaptation effort. More than half of the United States needs to at least double their protection within the next two decades. Thus, the need for adaptation to increased river flood is a global problem affecting industrialized regions as much as developing countries.
Diketopyrrolopyrrole (DPP)-based donor acceptor copolymers have gained a significant amount of research interest in the organic electronics community because of their high charge carrier mobilities in organic field-effect transistors (OFETs) and their ability to harvest near-infrared (NIR) photons in solar cells. In this study, we have synthesized four DPP based donor-acceptor copolymers with variations in the donor unit and the branching point of the solubilizing alkyl chains (at the second or sixth carbon position). Grazing incidence wide-angle X-ray scattering (GIWAXS) results suggest that moving the branching point further away from the polymer backbone increases the tendency for aggregation and yields polymer phases with a higher degree of crystallinity (DoC). The polymers were blended with PC70BM and used as active layers in solar cells. A careful analysis of the energetics of the neat polymer and blend films reveals that the charge-transfer state energy (E-CT) of the blend films lies exceptionally close to the singlet energy of the donor (E-D*), indicating near zero electron transfer losses. The difference between the optical gap and open-circuit voltage (V-OC) is therefore determined to be due to rather high nonradiative 418 +/- 13 mV) and unavoidable radiative voltage losses (approximate to 255 +/- 8 mV). Even though the four materials have similar optical gaps, the short-circuit current density (J(SC)) covers a vast span from 7 to 18 mA cm(-2) for the best performing system. Using photoluminescence (PL) quenching and transient charge extraction techniques, we quantify geminate and nongeminate losses and find that fewer excitons reach the donor-acceptor interface in polymers with further away branching points due to larger aggregate sizes. In these material systems, the photogeneration is therefore mainly limited by exciton harvesting efficiency.
We trace the specific star formation rate (sSFR) of massive star-forming galaxies (greater than or similar to 10(10)M(circle dot)) from z similar to 2 to 7. Our method is substantially different from previous analyses, as it does not rely on direct estimates of star formation rate, but on the differential evolution of the galaxy stellar mass function (SMF). We show the reliability of this approach by means of semianalytical and hydrodynamical cosmological simulations. We then apply it to real data, using the SMFs derived in the COSMOS and CANDELS fields. We find that the sSFR is proportional to (1 + z)(1.1) (+/-) (0.2) at z > 2, in agreement with other observations but in tension with the steeper evolution predicted by simulations from z similar to 4 to 2. We investigate the impact of several sources of observational bias, which, however, cannot account for this discrepancy. Although the SMF of high-redshift galaxies is still affected by significant errors, we show that future large-area surveys will substantially reduce them, making our method an effective tool to probe the massive end of the main sequence of star-forming galaxies.
When the network is reconstructed, two types of errors can occur: false positive and false negative errors about the presence or absence of links. In this paper, the influence of these two errors on the vertex degree distribution is analytically analyzed. Moreover, an analytic formula of the density of the biased vertex degree distribution is found. In the inverse problem, we find a reliable procedure to reconstruct analytically the density of the vertex degree distribution of any network based on the inferred network and estimates for the false positive and false negative errors based on, e.g., simulation studies.
Ocean-induced melting below ice shelves is one of the dominant drivers for mass loss from the Antarctic Ice Sheet at present. An appropriate representation of sub-shelf melt rates is therefore essential for model simulations of marine-based ice sheet evolution. Continental-scale ice sheet models often rely on simple melt-parameterizations, in particular for long-term simulations, when fully coupled ice-ocean interaction becomes computationally too expensive. Such parameterizations can account for the influence of the local depth of the ice-shelf draft or its slope on melting. However, they do not capture the effect of ocean circulation underneath the ice shelf. Here we present the Potsdam Ice-shelf Cavity mOdel (PICO), which simulates the vertical overturning circulation in ice-shelf cavities and thus enables the computation of sub-shelf melt rates consistent with this circulation. PICO is based on an ocean box model that coarsely resolves ice shelf cavities and uses a boundary layer melt formulation. We implement it as a module of the Parallel Ice Sheet Model (PISM) and evaluate its performance under present-day conditions of the Southern Ocean. We identify a set of parameters that yield two-dimensional melt rate fields that qualitatively reproduce the typical pattern of comparably high melting near the grounding line and lower melting or refreezing towards the calving front. PICO captures the wide range of melt rates observed for Antarctic ice shelves, with an average of about 0.1 ma(-1) for cold sub-shelf cavities, for example, underneath Ross or Ronne ice shelves, to 16 ma(-1) for warm cavities such as in the Amundsen Sea region. This makes PICO a computationally feasible and more physical alternative to melt parameterizations purely based on ice draft geometry.
The design of an array configuration is an important task in array seismology during experiment planning. Often the array response function (ARF), which depends on the relative position of array stations and frequency content of the incoming signals, is used as the array design criterion. In practice, additional constraints and parameters have to be taken into account, for example, land ownership, site-specific noise levels or characteristics of the seismic sources under investigation. In this study, a flexible array design framework is introduced that implements a customizable scenario modelling and optimization scheme by making use of synthetic seismograms. Using synthetic seismograms to evaluate array performance makes it possible to consider additional constraints. We suggest to use synthetic array beamforming as an array design criterion instead of the ARF. The objective function of the optimization scheme is defined according to the monitoring goals, and may consist of a number of subfunctions. The array design framework is exemplified by designing a seven-station small-scale array to monitor earthquake swarm activity in Northwest Bohemia/Vogtland in central Europe. Two subfunctions are introduced to verify the accuracy of horizontal slowness estimation; one to suppress aliasing effects due to possible secondary lobes of synthetic array beamforming calculated in horizontal slowness space and the other to reduce the event’s mislocation caused by miscalculation of the horizontal slowness vector. Subsequently, a weighting technique is applied to combine the subfunctions into one single scalar objective function to use in the optimization process.
Plastid ribosomes are very similar in structure and function to the ribosomes of their bacterial ancestors. Since ribosome biogenesis is not thermodynamically favorable under biological conditions it requires the activity of many assembly factors. Here we have characterized a homolog of bacterial RsgA in Arabidopsis thaliana and show that it can complement the bacterial homolog. Functional characterization of a strong mutant in Arabidopsis revealed that the protein is essential for plant viability, while a weak mutant produced dwarf, chlorotic plants that incorporated immature pre-16S ribosomal RNA into translating ribosomes. Physiological analysis of the mutant plants revealed smaller, but more numerous, chloroplasts in the mesophyll cells, reduction of chlorophyll a and b, depletion of proplastids from the rib meristem and decreased photosynthetic electron transport rate and efficiency. Comparative RNA sequencing and proteomic analysis of the weak mutant and wild-type plants revealed that various biotic stress-related, transcriptional regulation and post-transcriptional modification pathways were repressed in the mutant. Intriguingly, while nuclear- and chloroplast-encoded photosynthesis-related proteins were less abundant in the mutant, the corresponding transcripts were increased, suggesting an elaborate compensatory mechanism, potentially via differentially active retrograde signaling pathways. To conclude, this study reveals a chloroplast ribosome assembly factor and outlines the transcriptomic and proteomic responses of the compensatory mechanism activated during decreased chloroplast function. Significance Statement AtRsgA is an assembly factor necessary for maturation of the small subunit of the chloroplast ribosome. Depletion of AtRsgA leads to dwarfed, chlorotic plants, a decrease of mature 16S rRNA and smaller, but more numerous, chloroplasts. Large-scale transcriptomic and proteomic analysis revealed that chloroplast-encoded and -targeted proteins were less abundant, while the corresponding transcripts were increased in the mutant. We analyze the transcriptional responses of several retrograde signaling pathways to suggest the mechanism underlying this compensatory response.
We employ Bayesian statistics using the nested-sampling algorithm to compare and rank multiple models of ergodic diffusion (including anomalous diffusion) as well as to assess their optimal parameters for in silico-generated and real time-series. We focus on the recently-introduced model of Brownian motion with "diffusing diffusivity'-giving rise to widely-observed non-Gaussian displacement statistics-and its comparison to Brownian and fractional Brownian motion, also for the time-series with some measurement noise. We conduct this model-assessment analysis using Bayesian statistics and the nested-sampling algorithm on the level of individual particle trajectories. We evaluate relative model probabilities and compute best-parameter sets for each diffusion model, comparing the estimated parameters to the true ones. We test the performance of the nested-sampling algorithm and its predictive power both for computer-generated (idealised) trajectories as well as for real single-particle-tracking trajectories. Our approach delivers new important insight into the objective selection of the most suitable stochastic model for a given time-series. We also present first model-ranking results in application to experimental data of tracer diffusion in polymer-based hydrogels.
We examine renewal processes with power-law waiting time distributions (WTDs) and non-zero drift via computing analytically and by computer simulations their ensemble and time averaged spreading characteristics. All possible values of the scaling exponent alpha are considered for the WTD psi(t) similar to 1/t(1+alpha). We treat continuous-time random walks (CTRWs) with 0 < alpha < 1 for which the mean waiting time diverges, and investigate the behaviour of the process for both ordinary and equilibrium CTRWs for 1 < alpha < 2 and alpha > 2. We demonstrate that in the presence of a drift CTRWs with alpha < 1 are ageing and non-ergodic in the sense of the non-equivalence of their ensemble and time averaged displacement characteristics in the limit of lag times much shorter than the trajectory length. In the sense of the equivalence of ensemble and time averages, CTRW processes with 1 < alpha < 2 are ergodic for the equilibrium and non-ergodic for the ordinary situation. Lastly, CTRW renewal processes with alpha > 2-both for the equilibrium and ordinary situation-are always ergodic. For the situations 1 < alpha < 2 and alpha > 2 the variance of the diffusion process, however, depends on the initial ensemble. For biased CTRWs with alpha > 1 we also investigate the behaviour of the ergodicity breaking parameter. In addition, we demonstrate that for biased CTRWs the Einstein relation is valid on the level of the ensemble and time averaged displacements, in the entire range of the WTD exponent alpha.