The highD Dataset: A Drone Dataset of Naturalistic Vehicle Trajectories on German Highways for Validation of Highly Automated Driving Systems

Scenario-based testing for the safety validation of highly automated vehicles is a promising approach that is being examined in research and industry. This approach heavily relies on data from real-world scenarios to derive the necessary scenario information for testing. Measurement data should be collected at a reasonable effort, contain naturalistic behavior of road users and include all data relevant for a description of the identified scenarios in sufficient quality. However, the current measurement methods fail to meet at least one of the requirements. Thus, we propose a novel method to measure data from an aerial perspective for scenario-based validation fulfilling the mentioned requirements. Furthermore, we provide a large-scale naturalistic vehicle trajectory dataset from German highways called highD. We evaluate the data in terms of quantity, variety and contained scenarios. Our dataset consists of 16.5 hours of measurements from six locations with 110 000 vehicles, a total driven distance of 45 000 km and 5600 recorded complete lane changes. The highD dataset is available online at: http://www.highD-dataset.comComment: IEEE International Conference on Intelligent Transportation Systems (ITSC) 201

Robots as Companions: What can we Learn from Servants and Companions in Literature, Theater, and Film?

Many researchers are working on developing robots into adequate partners, be it at the working place, be it at home or in leisure activities, or enabling elder persons to lead a self-determined, independent life. While quite some progress has been made in e.g. speech or emotion understanding, processing and expressing, the relations between humans and robots are usually only short-term. In order to build long-term, i.e. social relations, qualities like empathy, trust building, dependability, non-patronizing, and others will be required. But these are just terms and as such no adequate starting points to “program” these capacities even more how to avoid the problems and pitfalls in interactions between humans and robots. However, a rich source for doing this is available, unused until now for this purpose: artistic productions, namely literature, theater plays, not to forget operas, and films with their multitude of examples. Poets, writers, dramatists, screen-writers, etc. have studied for centuries the facets of interactions between persons, their dynamics, and the related snags. And since we wish for human-robot relations as master-servant relations - the human obviously being the master - the study of these relations will be prominent. A procedure is proposed, with four consecutive steps, namely Selection, Analysis, Categorization, and Integration. Only if we succeed in developing robots which are seen as servants we will be successful in supporting and helping humans through robots

Inter-comparison Of Reflectivity Measurements Between GPM DPR And NEXRAD Radars

This study demonstrates the potential use of the NASA\u27s Global Precipitation Measurement (GPM) Dual-frequency Precipitation Radar (DPR) to examine ground radar (GR) miscalibration and other uncertainty sources (e.g., partial beam blockage). We acquired the GPM Ground Validation System Validation Network reflectivity matchups between the DPR and three GRs (two in Iowa and one in South Dakota) for 2014–2017. We then refined the matching parameters (e.g., time separation) to reduce uncertainty in the matchup samples by analyzing the sensitivity of the matchup statistical properties to changes in these parameters. To reconcile the same observables (i.e., reflectivity) with different observational properties among the space- and ground-based radars, we developed a statistically integrated framework using inter-comparisons of them all with a Monte Carlo simulation. This method verifies the absolute calibration bias estimated from the refined DPR–GR matchups using relative calibration biases between GRs. We found that taking samples with a narrow temporal gap, estimated by actual measurement time of the DPR and GRs, can significantly reduce sample variability. Through inter-comparisons among the DPR and GRs, we observed that reflectivity differences among GRs in a similar environment (e.g., climatology and geography) are likely to be affected primarily by the calibration mismatch. In this case, the inter-comparison results demonstrated good agreement, and we inferred that the differences can be mitigated by calibration bias correction against the DPR. On the other hand, when the disagreement level of the inter-comparison results is significant, the authors found that other factors, such as partial beam blockage even in relatively plain regions, are more dominant than the calibration bias. In fact, the partial beam blockage effects can manifest themselves as a seasonal pattern in the GR inter-comparison results

Demonstrating high-precision photometry with a CubeSat: ASTERIA observations of 55 Cancri e

ASTERIA (Arcsecond Space Telescope Enabling Research In Astrophysics) is a 6U CubeSat space telescope (10 cm x 20 cm x 30 cm, 10 kg). ASTERIA's primary mission objective was demonstrating two key technologies for reducing systematic noise in photometric observations: high-precision pointing control and high-stabilty thermal control. ASTERIA demonstrated 0.5 arcsecond RMS pointing stability and $\pm$10 milliKelvin thermal control of its camera payload during its primary mission, a significant improvement in pointing and thermal performance compared to other spacecraft in ASTERIA's size and mass class. ASTERIA launched in August 2017 and deployed from the International Space Station (ISS) November 2017. During the prime mission (November 2017 -- February 2018) and the first extended mission that followed (March 2018 - May 2018), ASTERIA conducted opportunistic science observations which included collection of photometric data on 55 Cancri, a nearby exoplanetary system with a super-Earth transiting planet. The 55 Cancri data were reduced using a custom pipeline to correct CMOS detector column-dependent gain variations. A Markov Chain Monte Carlo (MCMC) approach was used to simultaneously detrend the photometry using a simple baseline model and fit a transit model. ASTERIA made a marginal detection of the known transiting exoplanet 55 Cancri e ($\sim2$~\Rearth), measuring a transit depth of $374\pm170$ ppm. This is the first detection of an exoplanet transit by a CubeSat. The successful detection of super-Earth 55 Cancri e demonstrates that small, inexpensive spacecraft can deliver high-precision photometric measurements.Comment: 23 pages, 9 figures. Accepted in A

A Read/Write Mechanism Connects p300 Bromodomain Function to H2A.Z Acetylation

Acetylation of the histone variant H2A.Z (H2A.Zac) occurs at active regulatory regions associated with gene expression. Although the Tip60 complex is proposed to acetylate H2A.Z, functional studies suggest additional enzymes are involved. Here, we show that p300 acetylates H2A.Z at multiple lysines. In contrast, we found that although Tip60 does not efficiently acetylate H2A.Z in vitro, genetic inhibition of Tip60 reduces H2A.Zac in cells. Importantly, we found that interaction between the p300-bromodomain and H4 acetylation (H4ac) enhances p300-driven H2A.Zac. Indeed, H2A.Zac and H4ac show high genomic overlap, especially at active promoters. We also reveal unique chromatin features and transcriptional states at enhancers correlating with co-occurrence or exclusivity of H4ac and H2A.Zac. We propose that differential H4 and H2A.Z acetylation signatures can also define the enhancer state. In conclusion, we show both Tip60 and p300 contribute to H2A.Zac and reveal molecular mechanisms of writer/reader crosstalk between H2A.Z and H4 acetylation through p300

The strategies to support the COVID-19 vaccination with evidence-based communication and tackling misinformation

COVID-19 vaccinations are about to begin in various countries or are already ongoing. This is an unprecedented operation that is also met with a loud response from anti-vaccine communities—currently using all available channels to manipulate public opinion. At the same time, the strategy to educate on vaccinations, explain their mechanism of action, and build trust in science is subdued in different world parts. Such actions should go much beyond campaigns promoting the COVID-19 vaccines solely on the information provided by the health institutions and national authorities. In this paper, actions provided by independent expert groups needed to counteract the anti-vaccine propaganda and provide scientific-based information to the general public are offered. These actions encompass organizing groups continuously communicating science on COVID-19 vaccines to the general public; tracking and tackling emerging and circulating fake news; and equipping celebrities and politicians with scientific information to ensure the quality of messages they communicate, as well as public letters, and statements of support for vaccination by healthcare workers, recognized scientists, VIPs, and scientific societies; and no tolerance to false and manipulated claims on vaccination spread via traditional and social media as well as by health professionals, scientists, and academics. These activities should be promptly implemented worldwide, regardless of the current status and availability of the COVID-19 vaccine in a particular region. If we are about to control the pandemic for the sake of public benefit, it is high time to collectively speak out as academic and medical societies with support from decision-makers. Otherwise, the battle will be lost to those who stand against scientific evidence while offering no feasible solution to the problem