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General relativity (GR) has proven to be a highly successful theory of gravity since its inception. The theory has thrivingly passed numerous experimental tests, predominantly in weak gravity, low relative speeds, and linear regimes, but also in the strong-field and very low-speed regimes with binary pulsars. Observable gravitational waves (GWs) originate from regions of spacetime where gravity is extremely strong, making them a unique tool for testing GR, in previously inaccessible regions of large curvature, relativistic speeds, and strong gravity. Since their first detection, GWs have been extensively used to test GR, but no deviations have been found so far. Given GR’s tremendous success in explaining current astronomical observations and laboratory experiments, accepting any deviation from it requires a very high level of statistical confidence and consistency of the deviation across GW sources. In this paper, we compile a comprehensive list of potential causes that can lead to a false identification of a GR violation in standard tests of GR on data from current and future ground-based GW detectors. These causes include detector noise, signal overlaps, gaps in the data, detector calibration, source model inaccuracy, missing physics in the source and in the underlying environment model, source misidentification, and mismodeling of the astrophysical population. We also provide a rough estimate of when each of these causes will become important for tests of GR for different detector sensitivities. We argue that each of these causes should be thoroughly investigated, quantified, and ruled out before claiming a GR violation in GW observations. 

Abstract Nitrogen (N) doped graphene materials have been synthesized using the sole precursor adenine on the Ir(111) and Ru(0001) surfaces. X-ray photoelectron spectroscopy and scanning tunneling microscopy (STM) have been used to characterize the obtained N-doped graphene materials. Several graphitic and pyridinic N dopants have been identified on the atomic scale by combining STM measurements and STM simulations based on density functional theory calculations. 

Abstract Glycerol dibiphytanyl glycerol tetraethers (GDGTs) are archaeal monolayer membrane lipids that can provide a competitive advantage in extreme environments. Here, we identify a radical SAM protein, tetraether synthase (Tes), that participates in the synthesis of GDGTs. Attempts to generate a tes-deleted mutant in Sulfolobus acidocaldarius were unsuccessful, suggesting that the gene is essential in this organism. Heterologous expression of tes homologues leads to production of GDGT and structurally related lipids in the methanogen Methanococcus maripaludis (which otherwise does not synthesize GDGTs and lacks a tes homolog, but produces a putative GDGT precursor, archaeol). Tes homologues are encoded in the genomes of many archaea, as well as in some bacteria, in which they might be involved in the synthesis of bacterial branched glycerol dialkyl glycerol tetraethers. 

Recently, wireless communication technologies, such as Wireless Local Area Networks (WLANs), have gained increasing popularity in industrial control systems (ICSs) due to their low cost and ease of deployment, but communication delays associated with these technologies make it unsuitable for critical real-time and safety applications. To address concerns on network-induced delays of wireless communication technologies and bring their advantages into modern ICSs, wireless network infrastructure based on the Parallel Redundancy Protocol (PRP) has been proposed. Although application-specific simulations and measurements have been conducted to show that wireless network infrastructure based on PRP can be a viable solution for critical applications with stringent delay performance constraints, little has been done to devise an analytical framework facilitating the adoption of wireless PRP infrastructure in miscellaneous ICSs. Leveraging the deterministic network calculus (DNC) theory, we propose to analytically derive worst-case bounds on network- induced delays for critical ICS applications. We show that the problem of worst-case delay bounding for a wireless PRP network can be solved by performing network-calculus-based analysis on its non-feedforward traffic pattern. Closed-form expressions of worst-case delays are derived, which has not been found previously and allows ICS architects/designers to compute worst- case delay bounds for ICS tasks in their respective application domains of interest. Our analytical results not only provide insights into the impacts of network-induced delays on latency- critical tasks but also allow ICS architects/operators to assess whether proper wireless RPR network infrastructure can be adopted into their systems.