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Abstract The tidal disruption event (TDE) AT2022cmc represents the fourth known example of a relativistic jet produced by the tidal disruption of a stray star, providing a unique probe of the formation and evolution of relativistic jets in otherwise dormant supermassive black holes (SMBHs). Here we present deep, late-time Chandra observations of AT2022cmc extending tot_obs≈ 400 days after disruption. Our observations reveal a sudden decrease in the X-ray brightness by a factor of ≳14 over a factor of ≈2.3 in time, and a deviation from the earlier power-law decline with a steepeningα≳ 3.2 (F_X∝t^−α), steeper than expected for a jet break, and pointing to the cessation of jet activity att_obs≈ 215 days. Such a transition has been observed in two previous TDEs (Swift J1644+57 and Swift J2058+05). From the X-ray luminosity and the timescale of jet shut-off, we parameterize the mass of the SMBH in terms of unknown jet efficiency and accreted mass fraction parameters. Motivated by the disk–jet connection in active galactic nuclei, we favor black hole masses ≲10⁵M_⊙(where the jet and disk luminosities are comparable), and disfavor larger black holes (in which extremely powerful jets are required to outshine their accretion disks). We additionally estimate a total accreted mass of ≈0.1M_⊙. Applying the same formalism to Swift J1644+57 and Swift J2058+05, we favor comparable black hole masses for these TDEs of ≲ a few × 10⁵M_⊙, and suggest that jetted TDEs may preferentially form from lower-mass black holes when compared to nonrelativistic events, owing to generally lower jet and higher disk efficiencies at higher black hole masses. 

Abstract Supermassive black holes can experience super-Eddington peak mass fallback rates following the tidal disruption of a star. The theoretical expectation is that part of the infalling material is expelled by means of an accretion disk wind, whose observational signature includes blueshifted absorption lines of highly ionized species in X-ray spectra. To date, however, only one such ultrafast outflow (UFO) has been reported in the tidal disruption event (TDE) ASASSN–14li. Here we report on the discovery of a transient absorption-like signature in X-ray spectra of the TDE AT2020ksf/Gaia20cjk (at a redshift ofz= 0.092), following an X-ray brightening ∼230 days after UV/optical peak. We find that while no statistically significant absorption features are present initially, they appear on a timescale of several days and remain detected up to 770 days after peak. Simple thermal continuum models, combined with a power-law or neutral absorber, do not describe these features well. Adding a partial-covering, low-velocity ionized absorber improves the fit at early times but fails at late times. A high-velocity (v_w∼ 42,000 km s⁻¹), ionized absorber (UFO) provides a good fit to all data. The few-day timescale of variability is consistent with expectations for a clumpy wind. We discuss several scenarios that could explain the X-ray delay, as well as the potential for larger-scale wind feedback. The serendipitous nature of the discovery could suggest a high incidence of UFOs in TDEs, alleviating some of the tension with theoretical expectations. 

Conformance tests are critical for finding security weaknesses in carrier network systems. However, building a conformance test procedure from specifications is challenging, as indicated by the slow progress made by the 3GPP, particularly in developing security-related tests, even with a large amount of resources already committed. A unique challenge in building the procedure is that a testing system often cannot directly invoke the condition event in a security requirement or directly observe the occurrence of the operation expected to be triggered by the event. Addressing this issue requires an event chain to be found, which once initiated leads to a chain reaction so the testing system can either indirectly triggers the target event or indirectly observe the occurrence of the expected event. To find a solution to this problem and make progress towards a fully automated conformance test generation, we developed a new approach called Contester , which utilizes natural language processing and machine learning to build an event dependency graph from a 3GPP specification, and further perform automated reasoning on the graph to discover the event chains for a given security requirement. Such event chains are further converted by Contester into a conformance testing procedure, which is then executed by a testing system to evaluate the compliance of user equipment (UE) with the security requirement. Our evaluation shows that given 22 security requirements from the LTE NAS specifications, Contester successfully generated over a hundred test procedures in just 25 minutes. After running these procedures on 22 popular UEs including iPhone 13, Pixel 5a and IoT devices, our approach uncovered 197 security requirement violations, with 190 never reported before, rendering these devices to serious security risks such as MITM, fake base station and reply attacks. 

Abstract This work studies the use of laser shock peening (LSP) to improve back stress in additively manufactured (AM) 316L parts. Unusual hardening behavior in AM metal due to tortuous microstructure and strong texture poses additional design challenges. Anisotropic mechanical behavior complicates application for mechanical design because 3D printed parts will behave differently than traditionally manufactured parts under the same loading conditions. The prevalence of back-stress hardening or the Bauschinger effect causes reduced fatigue life under random loading and dissipates beneficial compressive residual stresses that prevent crack propagation. LSP is known to improve fatigue life by inducing compressive residual stress and has been applied with promising results to AM metal parts. It is here demonstrated that LSP may also be used as a tool for mitigating tensile back-stress hardening in AM parts, thereby reducing anisotropic hardening behavior and improving design use. It is also shown that the method of application of LSP to additively manufactured parts is key for achieving effective back-stress reduction. Back stress is extracted from additively manufactured dog bone samples built in both XY and XZ directions using hysteresis tensile. Both LSPed and as-built conditions are tested and compared, showing that LSPed samples exhibit a significant reduction to back stress when the laser processing is applied to the sample along the build direction. Electron backscatter diffraction (EBSD) performed under these conditions elucidates how grain morphologies and texture contribute to the observed improvement. Crystal plasticity finite element (CPFE) modeling develops insights as to the mechanisms by which this reduction is achieved in comparison with EBSD results. In particular, the difference in plastic behavior across build orientations of identified crystal planes and grain families are shown to impact the degree of LSP-induced back-stress reduction that is sustained through tensile loading. 

Abstract Laser shock peening (LSP) is investigated as a potential tool for reducing tensile back stress, shown here applied to rolled and annealed 304L austenitic steel. The back stress of treated and untreated dog-bone samples is extracted from hysteresis tensile testing. Electron back-scatter diffraction (EBSD) and orientation imaging microscopy (OIM) analysis quantify the geometrically necessary dislocation (GND) density distribution of unstrained and strained as well as unpeened and peened conditions. Finite element analysis (FEA) simulation models back stress and residual stress development through tensile testing and LSP treatment using known LSP pressure models and Ziegler's nonlinear kinematic hardening law. Nonlinear regression fitting of tensile testing stress–strain in as-received specimens extracts the kinematic hardening parameters that are used in numerical study. This research shows LSP may be used to overcome manufacturing design challenges presented by yield asymmetry due to back stress in rolled steel. 

Standardized privacy labels that succinctly summarize those data practices that people are most commonly concerned about offer the promise of providing users with more effective privacy notices than fulllength privacy policies. With their introduction by Apple in iOS 14 and Google’s recent adoption in its Play Store, mobile app privacy labels are for the first time available at scale to users. We report the first in-depth interview study with 24 lay iPhone users to investigate their experiences, understanding, and perceptions of Apple’s privacy labels. We uncovered misunderstandings of and dissatisfaction with the iOS privacy labels that hinder their effectiveness, including confusing structure, unfamiliar terms, and disconnection from permission settings and controls. We identify areas where app privacy labels might be improved and propose suggestions to address shortcomings to make them more understandable, usable, and useful.