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Introducing the CTA concept
(2013)
The Cherenkov Telescope Array (CTA) is a new observatory for very high-energy (VHE) gamma rays. CTA has ambitions science goals, for which it is necessary to achieve full-sky coverage, to improve the sensitivity by about an order of magnitude, to span about four decades of energy, from a few tens of GeV to above 100 TeV with enhanced angular and energy resolutions over existing VHE gamma-ray observatories. An international collaboration has formed with more than 1000 members from 27 countries in Europe, Asia, Africa and North and South America. In 2010 the CTA Consortium completed a Design Study and started a three-year Preparatory Phase which leads to production readiness of CTA in 2014. In this paper we introduce the science goals and the concept of CTA, and provide an overview of the project.
Ground-based gamma-ray astronomy has had a major breakthrough with the impressive results obtained using systems of imaging atmospheric Cherenkov telescopes. Ground-based gamma-ray astronomy has a huge potential in astrophysics, particle physics and cosmology. CTA is an international initiative to build the next generation instrument, with a factor of 5-10 improvement in sensitivity in the 100 GeV-10 TeV range and the extension to energies well below 100 GeV and above 100 TeV. CTA will consist of two arrays (one in the north, one in the south) for full sky coverage and will be operated as open observatory. The design of CTA is based on currently available technology. This document reports on the status and presents the major design concepts of CTA.
Reproducibility is a defining feature of science, but the extent to which it characterizes current research is unknown. We conducted replications of 100 experimental and correlational studies published in three psychology journals using high-powered designs and original materials when available. Replication effects were half the magnitude of original effects, representing a substantial decline. Ninety-seven percent of original studies had statistically significant results. Thirty-six percent of replications had statistically significant results; 47% of original effect sizes were in the 95% confidence interval of the replication effect size; 39% of effects were subjectively rated to have replicated the original result; and if no bias in original results is assumed, combining original and replication results left 68% with statistically significant effects. Correlational tests suggest that replication success was better predicted by the strength of original evidence than by characteristics of the original and replication teams.
Moving in the Anthropocene
(2018)
Animal movement is fundamental for ecosystem functioning and species survival, yet the effects of the anthropogenic footprint on animal movements have not been estimated across species. Using a unique GPS-tracking database of 803 individuals across 57 species, we found that movements of mammals in areas with a comparatively high human footprint were on average one-half to one-third the extent of their movements in areas with a low human footprint. We attribute this reduction to behavioral changes of individual animals and to the exclusion of species with long-range movements from areas with higher human impact. Global loss of vagility alters a key ecological trait of animals that affects not only population persistence but also ecosystem processes such as predator-prey interactions, nutrient cycling, and disease transmission.
During the summer of 2013, a 4-month spectroscopic campaign took place to observe the variabilities in three Wolf-Rayet stars. The spectroscopic data have been analysed for WR 134 (WN6b), to better understand its behaviour and long-term periodicity, which we interpret as arising from corotating interaction regions (CIRs) in the wind. By analysing the variability of the He ii lambda 5411 emission line, the previously identified period was refined to P = 2.255 +/- 0.008 (s.d.) d. The coherency time of the variability, which we associate with the lifetime of the CIRs in the wind, was deduced to be 40 +/- 6 d, or similar to 18 cycles, by cross-correlating the variability patterns as a function of time. When comparing the phased observational grey-scale difference images with theoretical grey-scales previously calculated from models including CIRs in an optically thin stellar wind, we find that two CIRs were likely present. A separation in longitude of Delta I center dot a parts per thousand integral 90A degrees was determined between the two CIRs and we suggest that the different maximum velocities that they reach indicate that they emerge from different latitudes. We have also been able to detect observational signatures of the CIRs in other spectral lines (C iv lambda lambda 5802,5812 and He i lambda 5876). Furthermore, a DAC was found to be present simultaneously with the CIR signatures detected in the He i lambda 5876 emission line which is consistent with the proposed geometry of the large-scale structures in the wind. Small-scale structures also show a presence in the wind, simultaneously with the larger scale structures, showing that they do in fact co-exist.
We analyze the multi-time correlations of a laser-induced Bose Einstein condensate. We use quantum stochastic methods to obtain under certain circumstances a Fokker-Planck equation which describes the phase-difussion process, and obtain an analytical expression of the two-time correlations. We perform also quantum Monte Carlo numerical simulations of the correlations, which are in good agreement with the predicted analytical results.
New mesoporous silk fibroin (SF)/silica hybrids were processed via a one-pot soft and energy-efficient sol-gel chemistry and self-assembly from a silica precursor, an acidic or basic catalyst, and the ionic liquid 1-butyl-3-methylimidazolium chloride, acting as both solvent and mesoporosity-inducer. The as-prepared materials were obtained as slightly transparent-opaque, amorphous monoliths, easily transformed into powders, and stable up to ca. 300 degrees C. Structural data suggest the formation of a hexagonal mesostructure with low range order and apparent surface areas, pore volumes, and pore radii of 205-263 m(2) g(-1), 0.16-0.19 cm(3) g(-1), and 1.2-1.6 nm, respectively. In all samples, the dominating conformation of the SF chains is the beta-sheet. Cytotoxicity/bioactivity resazurin assays and fluorescence microscopy demonstrate the high viability of MC3T3 pre-osteoblasts to indirect (>= 99 +/- 9%) and direct (78 +/- 2 to 99 +/- 13%) contact with the SF/silica materials. Considering their properties and further improvements, these systems are promising candidates to be explored in bone tissue engineering. They also offer excellent prospects as electrolytes for solid-state electrochemical devices, in particular for fuel cells.
EMOOCs 2021
(2021)
From June 22 to June 24, 2021, Hasso Plattner Institute, Potsdam, hosted the seventh European MOOC Stakeholder Summit (EMOOCs 2021) together with the eighth ACM Learning@Scale Conference.
Due to the COVID-19 situation, the conference was held fully online.
The boost in digital education worldwide as a result of the pandemic was also one of the main topics of this year’s EMOOCs. All institutions of learning have been forced to transform and redesign their educational methods, moving from traditional models to hybrid or completely online models at scale. The learnings, derived from practical experience and research, have been explored in EMOOCs 2021 in six tracks and additional workshops, covering various aspects of this field. In this publication, we present papers from the conference’s Experience Track, the Policy Track, the Business Track, the International Track, and the Workshops.
Home range estimation is routine practice in ecological research. While advances in animal tracking technology have increased our capacity to collect data to support home range analysis, these same advances have also resulted in increasingly autocorrelated data. Consequently, the question of which home range estimator to use on modern, highly autocorrelated tracking data remains open. This question is particularly relevant given that most estimators assume independently sampled data. Here, we provide a comprehensive evaluation of the effects of autocorrelation on home range estimation. We base our study on an extensive data set of GPS locations from 369 individuals representing 27 species distributed across five continents. We first assemble a broad array of home range estimators, including Kernel Density Estimation (KDE) with four bandwidth optimizers (Gaussian reference function, autocorrelated‐Gaussian reference function [AKDE], Silverman's rule of thumb, and least squares cross‐validation), Minimum Convex Polygon, and Local Convex Hull methods. Notably, all of these estimators except AKDE assume independent and identically distributed (IID) data. We then employ half‐sample cross‐validation to objectively quantify estimator performance, and the recently introduced effective sample size for home range area estimation ( N̂ area
) to quantify the information content of each data set. We found that AKDE 95% area estimates were larger than conventional IID‐based estimates by a mean factor of 2. The median number of cross‐validated locations included in the hold‐out sets by AKDE 95% (or 50%) estimates was 95.3% (or 50.1%), confirming the larger AKDE ranges were appropriately selective at the specified quantile. Conversely, conventional estimates exhibited negative bias that increased with decreasing N̂ area. To contextualize our empirical results, we performed a detailed simulation study to tease apart how sampling frequency, sampling duration, and the focal animal's movement conspire to affect range estimates. Paralleling our empirical results, the simulation study demonstrated that AKDE was generally more accurate than conventional methods, particularly for small N̂ area. While 72% of the 369 empirical data sets had >1,000 total observations, only 4% had an N̂ area >1,000, where 30% had an N̂ area <30. In this frequently encountered scenario of small N̂ area, AKDE was the only estimator capable of producing an accurate home range estimate on autocorrelated data.