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AM CVn-type systems are ultracompact, helium-accreting binary systems which are evolutionarily linked to the progenitors of thermonuclear supernovae and are expected to be strong Galactic sources of gravitational waves detectable to upcoming space-based interferometers. AM CVn binaries with orbital periods $\lesssim$ 20--23 min exist in a constant high state with a permanently ionised accretion disc. We present the discovery of TIC 378898110, a bright ($G=14.3$ mag), nearby ($309.3 \pm 1.8$ pc), high-state AM CVn binary discovered in TESS two-minute-cadence photometry. At optical wavelengths this is the third-brightest AM CVn binary known. The photometry of the system shows a 23.07172(6) min periodicity, which is likely to be the `superhump' period and implies an orbital period in the range 22--23 min. There is no detectable spectroscopic variability. The system underwent an unusual, year-long brightening event during which the dominant photometric period changed to a shorter period (constrained to $20.5 \pm 2.0$ min), which we suggest may be evidence for the onset of disc-edge eclipses. The estimated mass transfer rate, $\log (\dot{M} / \mathrm{M_\odot} \mathrm{yr}^{-1}) = -6.8 \pm 1.0$, is unusually high and may suggest a high-mass or thermally inflated donor. The binary is detected as an X-ray source, with a flux of $9.2 ^{+4.2}_{-1.8} \times 10^{-13}$ erg cm$^{-2}$ s$^{-1}$ in the 0.3--10 keV range. TIC 378898110 is the shortest-period binary system discovered with TESS, and its large predicted gravitational-wave amplitude makes it a compelling verification binary for future space-based gravitational wave detectors., Comment: 15 pages, 14 figures. Accepted to MNRAS

Despite their highly anisotropic complex-oxidic nature, certain delafossite compounds (e.g., PdCoO2, PtCoO2) are the most conductive oxides known, for reasons that remain poorly understood. Their room-temperature conductivity can exceed that of Au, while their low-temperature electronic mean-free-paths reach an astonishing 20 microns. It is widely accepted that these materials must be ultrapure to achieve this, although the methods for their growth (which produce only small crystals) are not typically capable of such. Here, we first report a new approach to PdCoO2 crystal growth, using chemical vapor transport methods to achieve order-of-magnitude gains in size, the highest structural qualities yet reported, and record residual resistivity ratios (>440). Nevertheless, the first detailed mass spectrometry measurements on these materials reveal that they are not ultrapure, typically harboring 100s-of-parts-per-million impurity levels. Through quantitative crystal-chemical analyses, we resolve this apparent dichotomy, showing that the vast majority of impurities are forced to reside in the Co-O octahedral layers, leaving the conductive Pd sheets highly pure (~1 ppm impurity concentrations). These purities are shown to be in quantitative agreement with measured residual resistivities. We thus conclude that a previously unconsidered "sublattice purification" mechanism is essential to the ultrahigh low-temperature conductivity and mean-free-path of metallic delafossites.

Empirical technology and society research is in a methodological crisis. Problems increasingly involve closed platforms, targeted content, and context-specific behavior. Prevailing research methods, such as surveys, tasks, and web crawls, pose design and ecological validity limitations. Deploying studies in participant browsers and devices is a promising direction. These vantage points can observe individualized experiences and implement UI interventions in real settings. We survey scholarship that uses these methods, annotating 284 sampled papers. Our analysis demonstrates their potential, but also recurring implementation barriers and shortcomings. We then present Rally and sdkName, a platform and toolkit for browser-based research. These systems lower implementation barriers and advance the science of measuring online behavior. Finally, we evaluate Rally and sdkName against our design goals. We report results from a one-month pilot study on news engagement, analyzing 4,466,200 webpage visits from 1,817 participants. We also present observations from interviews with researchers using these systems.

Disinformation is proliferating on the internet, and platforms are responding by attaching warnings to content. There is little evidence, however, that these warnings help users identify or avoid disinformation. In this work, we adapt methods and results from the information security warning literature in order to design and evaluate effective disinformation warnings. In an initial laboratory study, we used a simulated search task to examine contextual and interstitial disinformation warning designs. We found that users routinely ignore contextual warnings, but users notice interstitial warnings -- and respond by seeking information from alternative sources. We then conducted a follow-on crowdworker study with eight interstitial warning designs. We confirmed a significant impact on user information-seeking behavior, and we found that a warning's design could effectively inform users or convey a risk of harm. We also found, however, that neither user comprehension nor fear of harm moderated behavioral effects. Our work provides evidence that disinformation warnings can -- when designed well -- help users identify and avoid disinformation. We show a path forward for designing effective warnings, and we contribute repeatable methods for evaluating behavioral effects. We also surface a possible dilemma: disinformation warnings might be able to inform users and guide behavior, but the behavioral effects might result from user experience friction, not informed decision making., Comment: Published at USENIX Security '21

Platforms have struggled to keep pace with the spread of disinformation. Current responses like user reports, manual analysis, and third-party fact checking are slow and difficult to scale, and as a result, disinformation can spread unchecked for some time after being created. Automation is essential for enabling platforms to respond rapidly to disinformation. In this work, we explore a new direction for automated detection of disinformation websites: infrastructure features. Our hypothesis is that while disinformation websites may be perceptually similar to authentic news websites, there may also be significant non-perceptual differences in the domain registrations, TLS/SSL certificates, and web hosting configurations. Infrastructure features are particularly valuable for detecting disinformation websites because they are available before content goes live and reaches readers, enabling early detection. We demonstrate the feasibility of our approach on a large corpus of labeled website snapshots. We also present results from a preliminary real-time deployment, successfully discovering disinformation websites while highlighting unexplored challenges for automated disinformation detection.

Bitcoin's success has led to significant interest in its underlying components, particularly Blockchain technology. Over 10 years after Bitcoin's initial release, the community still suffers from a lack of clarity regarding what properties defines Blockchain technology, its relationship to similar technologies, and which of its proposed use-cases are tenable and which are little more than hype. In this paper we answer four common questions regarding Blockchain technology: (1) what exactly is Blockchain technology, (2) what capabilities does it provide, and (3) what are good applications for Blockchain technology, and (4) how does it relate to other approache distributed technologies (e.g., distributed databases). We accomplish this goal by using grounded theory (a structured approach to gathering and analyzing qualitative data) to thoroughly analyze a large corpus of literature on Blockchain technology. This method enables us to answer the above questions while limiting researcher bias, separating thought leadership from peddled hype and identifying open research questions related to Blockchain technology. The audience for this paper is broad as it aims to help researchers in a variety of areas come to a better understanding of Blockchain technology and identify whether it may be of use in their own research., Comment: Technical report

As Bitcoin's popularity has grown over the decade since its creation, it has become an increasingly attractive target for adversaries of all kinds. One of the most powerful potential adversaries is the country of China, which has expressed adversarial positions regarding the cryptocurrency and demonstrated powerful capabilities to influence it. In this paper, we explore how China threatens the security, stability, and viability of Bitcoin through its dominant position in the Bitcoin ecosystem, political and economic control over domestic activity, and control over its domestic Internet infrastructure. We explore the relationship between China and Bitcoin, document China's motivation to undermine Bitcoin, and present a case study to demonstrate the strong influence that China has over Bitcoin. Finally, we systematize the class of attacks that China can deploy against Bitcoin to better understand the threat China poses. We conclude that China has mature capabilities and strong motives for performing a variety of attacks against Bitcoin.