Drawing causal inferences from observational studies (OS) requires unverifiable validity assumptions; however, one can falsify those assumptions by benchmarking the OS with experimental data from a randomized controlled trial (RCT). A major limitation of existing procedures is not accounting for censoring, despite the abundance of RCTs and OSes that report right-censored time-to-event outcomes. We consider two cases where censoring time (1) is independent of time-to-event and (2) depends on time-to-event the same way in OS and RCT. For the former, we adopt a censoring-doubly-robust signal for the conditional average treatment effect (CATE) to facilitate an equivalence test of CATEs in OS and RCT, which serves as a proxy for testing if the validity assumptions hold. For the latter, we show that the same test can still be used even though unbiased CATE estimation may not be possible. We verify the effectiveness of our censoring-aware tests via semi-synthetic experiments and analyze RCT and OS data from the Women's Health Initiative study.

From military-grade drones to sensor systems and experimental technology, the EU and its members have spent hundreds of millions of euros over the past decade on technologies to track down and keep at bay the refugees on its borders. Poland's border with Belarus is becoming the latest frontline for this technology, with the country approving last month a €350m (£300m) wall with advanced cameras and motion sensors. The Guardian has mapped out the result of the EU's investment: a digital wall on the harsh sea, forest and mountain frontiers, and a technological playground for military and tech companies repurposing products for new markets. The EU is central to the push towards using technology on its borders, whether it has been bought by the EU's border force, Frontex, or financed for member states through EU sources, such as its internal security fund or Horizon 2020, a project to drive innovation. In 2018, the EU predicted that the European security market would grow to €128bn (£108bn) by 2020.

Repeated activity wears on soft robotic actuators, but these machines' moving parts need to be reliable and easily fixed. Now a team of researchers has a biosynthetic polymer, patterned after squid ring teeth, that is self-healing and biodegradable, creating a material not only good for actuators, but also for hazmat suits and other applications where tiny holes could cause a danger. "Current self-healing materials have shortcomings that limit their practical application, such as low healing strength and long healing times (hours)," the researchers report in today's (July 27) issue of Nature Materials. The researchers produced high-strength synthetic proteins that mimic those found in nature. Like the creatures they are patterned on, the proteins can self-heal both minute and visible damage.

"Current self-healing materials have shortcomings that limit their practical application, such as low healing strength and long healing times (hours)," the researcher report in today's issue of Nature Materials. The researchers produced high-strength synthetic proteins that mimic those found in nature. Like the creatures they are patterned on, the proteins can self-heal both minute and visible damage. "Our goal is to create self-healing programmable materials with unprecedented control over their physical properties using synthetic biology," said Melik Demirel, professor of engineering science and mechanics and holder of the Lloyd and Dorothy Foehr Huck Chair in Biomimetic Materials. Robotic machines from industrial robotic arms and prosthetic legs have joints that move and require a soft material that will accommodate this movement.