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Microcracked conductors for wearable sensors
No full textA stretchable and conductive micrometre-thick elastic conductor, which has a controlled morphology of microcracks, can be used in on-skin and implantable sensor applications
Using Anisotropies as a Forensic Tool for Decoding Supernova Remnants
No full textWe present a method for analyzing supernova remnants (SNRs) by diagnosing the drivers responsible for structure at different angular scales. First, we perform a suite of hydrodynamic models of the Rayleigh–Taylor instability (RTI) as a supernova (SN) collides with its surrounding medium. Using these models we demonstrate how power spectral analysis can be used to attribute which scales in an SNR are driven by RTI and which must be caused by intrinsic asymmetries in the initial explosion. We predict the power spectrum of turbulence driven by RTI and identify a dominant angular mode that represents the largest scale that efficiently grows via RTI. We find that this dominant mode relates to the density scale height in the ejecta, and therefore reveals the density profile of the SN ejecta. If there is significant structure in an SNR on angular scales larger than this mode, then it is likely caused by anisotropies in the explosion. Structure on angular scales smaller than the dominant mode exhibits a steep scaling with wavenumber, possibly too steep to be consistent with a turbulent cascade, and therefore might be determined by the saturation of RTI at different length scales (although systematic 3D studies are needed to investigate this). We also demonstrate, consistent with previous studies, that this power spectrum is independent of the magnitude and length scales of perturbations in the surrounding medium and therefore this diagnostic is unaffected by “clumpiness” in the circumstellar medium
A Method to Generate Initial Fault Stresses for Physics-Based Ground-Motion Prediction Consistent with Regional Seismicity
No full textNear‐field ground motion is the major blind spot of seismic hazard studies, mainly because of the challenges in accounting for source effects. Initial stress heterogeneity is an important component of physics‐based approaches to ground‐motion prediction that represents source effects through dynamic earthquake rupture modeling. We hypothesize that stress heterogeneity on a fault primarily originates from past background seismicity. We develop a new method to generate stochastic stress distributions as a superposition of residual stresses left by the previous ruptures that are consistent with regional distributions of earthquake size and hypocentral depth. We validate our method on M_w 7 earthquake models suitable for California by obtaining a satisfactory agreement with empirical earthquake scaling laws and ground‐motion prediction equations. To avoid the excessive seismic radiation produced by dynamic models with abrupt arrest at preset rupture borders, we achieve spontaneous rupture arrest by incorporating a growth of fracture energy as a function of hypocentral distance. Our analyses of rupture and ground motion reveal particular signatures of the initial stress heterogeneity: rupture can locally propagate at supershear speed near the highly stressed areas; the position of high‐stress and low‐stress areas due to initial stress heterogeneity determines how the peak ground‐motion amplitudes and polarization spatially vary along the fault, as low‐stress areas slow down the rupture and decrease stress drop. We also find that the medium stratification in the fault zone amplifies fault slip and consequent ground motion, which requires understanding the interaction between site effects and rupture dynamics. Our approach advances our understanding of the relations between dynamic features of earthquake ruptures and the statistics of regional seismicity, and our capability to integrate information about regional seismicity into near‐field ground‐motion prediction
Dynamic neural reconfiguration for distinct strategies during competitive social interactions
No full textInformation exchange between brain regions is key to understanding information processing for social decision-making, but most analyses ignore its dynamic nature. New insights on this dynamic might help us to uncover the neural correlates of social cognition in the healthy population and also to understand the malfunctioning neural computations underlying dysfunctional social behavior in patients with mental disorders. In this work, we used a multi-round bargaining game to detect switches between distinct bargaining strategies in a cohort of 76 healthy participants. These switches were uncovered by dynamic behavioral modeling using the hidden Markov model. Proposing a novel model of dynamic effective connectivity to estimate the information flow between key brain regions, we found a stronger interaction between the right temporoparietal junction (rTPJ) and the right dorsolateral prefrontal cortex (rDLPFC) for the strategic deception compared with the social heuristic strategies. The level of deception was associated with the information flow from the Brodmann area 10 to the rTPJ, and this association was modulated by the rTPJ-to-rDLPFC information flow. These findings suggest that dynamic bargaining strategy is supported by dynamic reconfiguration of the rDLPFC-and-rTPJ interaction during competitive social interactions
Many-body cavity quantum electrodynamics with driven inhomogeneous emitters
No full textQuantum emitters coupled to optical resonators are quintessential systems for exploring fundamental phenomena in cavity quantum electrodynamics (cQED) and are commonly used in quantum devices acting as qubits, memories and transducers. Many previous experimental cQED studies have focused on regimes in which a small number of identical emitters interact with a weak external drive, such that the system can be described with simple, effective models. However, the dynamics of a disordered, many-body quantum system subject to a strong drive have not been fully explored, despite its importance and potential in quantum applications. Here we study how a large, inhomogeneously broadened ensemble of solid-state emitters coupled with high cooperativity to a nanophotonic resonator behaves under strong excitation. We discover a sharp, collectively induced transparency (CIT) in the cavity reflection spectrum, resulting from quantum interference and collective response induced by the interplay between driven inhomogeneous emitters and cavity photons. Furthermore, coherent excitation within the CIT window leads to highly nonlinear optical emission, spanning from fast superradiance to slow subradiance. These phenomena in the many-body cQED regime enable new mechanisms for achieving slow light and frequency referencing, pave a way towards solid-state superradiant lasers and inform the development of ensemble-based quantum interconnects
Reduced Marine Molybdenum Inventory Related to Enhanced Organic Carbon Burial and an Expansion of Reducing Environments in the Toarcian (Early Jurassic) Oceans
No full textMany metals present in trace concentrations in the oceans are sensitive to reduction and oxidation reactions (termed redox-sensitive trace metals or RSTMs) and can therefore be affected during intervals of expanded oceanic anoxia and euxinia (anoxic and sulfidic waters). These RSTMs are important micronutrients; and their availability plays a significant role in controlling metabolic pathways and therefore ecosystem structure. Understanding the links to ecosystem restructuring and potential collapse is important since past deoxygenation events are associated with biological turnover. The Early Jurassic Toarcian Oceanic Anoxic Event (T-OAE) was one such event. We focus on the RSTM molybdenum (Mo), important in the nitrogen cycle, from a basin transect where local redox conditions permit the tracking of the marine reservoir of Mo. Mo enrichments start to decline in the Pliensbachian, continue to decline in the early Toarcian, drop precipitously during the T-OAE interval, and remain low afterward before a protracted increase toward the initial values seen in the Pliensbachian. From a compilation of available data, we estimate that ∼41 Gt of Mo was buried during the T-OAE using a range of possible flux estimates. Given the known correlations of Mo with total organic carbon, the estimated burial of organic carbon during the T-OAE interval was ∼244,000 Gt. This requires a minimum of 3.25% of the ocean floor to be covered by euxinic waters. Finally, we suggest that the intervals traditionally classified as OAEs are associated with the greatest extent of euxinia
A very luminous jet from the disruption of a star by a massive black hole
No full textTidal disruption events (TDEs) are bursts of electromagnetic energy that are released when supermassive black holes at the centres of galaxies violently disrupt a star that passes too close1. TDEs provide a window through which to study accretion onto supermassive black holes; in some rare cases, this accretion leads to launching of a relativistic jet, but the necessary conditions are not fully understood. The best-studied jetted TDE so far is Swift J1644+57, which was discovered in γ-rays, but was too obscured by dust to be seen at optical wavelengths. Here we report the optical detection of AT2022cmc, a rapidly fading source at cosmological distance (redshift z = 1.19325) the unique light curve of which transitioned into a luminous plateau within days. Observations of a bright counterpart at other wavelengths, including X-ray, submillimetre and radio, supports the interpretation of AT2022cmc as a jetted TDE containing a synchrotron ‘afterglow’, probably launched by a supermassive black hole with spin greater than approximately 0.3. Using four years of Zwicky Transient Facility survey data, we calculate a rate of 0.02⁺⁰⋅⁰⁴₋₀.₀₁ Gpc⁻³ yr⁻¹ for on-axis jetted TDEs on the basis of the luminous, fast-fading red component, thus providing a measurement complementary to the rates derived from X-ray and radio observations. Correcting for the beaming angle effects, this rate confirms that approximately 1 per cent of TDEs have relativistic jets. Optical surveys can use AT2022cmc as a prototype to unveil a population of jetted TDEs
Higgs branch, Coulomb branch, and Hall-Littlewood index
No full textThe Higgs branch of 4D N = 2 superconformal field theories can be analyzed via the Hilbert series of the Higgs branch or, in special cases, by computing the Hall-Littlewood index. For any class S theory corresponding to a genus-zero Riemann surface, they are conjectured to be identical. We present several families of counterexamples. We find that for any class S theory with four or more ℤ₂-twisted punctures, they do not match. We construct 3D mirrors for such theories and analyze their Coulomb branch Hilbert series to compute the Higgs branch Hilbert series of the 4D theory. We further construct a = c theories in class S using the twisted punctures, and these theories, which includes the D̂₄(SU(2n + 1)) theories, have Hall-Littlewood index different from the Hilbert series of the Higgs branch. We conjecture that this is the case for all a = c theories with nonempty Higgs branch, including N ≥ 3 superconformal field theories
Incorporating information from LIGO data quality streams into the PyCBC search for gravitational waves
No full textWe present a new method which accounts for changes in the properties of gravitational-wave detector noise over time in the PyCBC search for gravitational waves from compact binary coalescences. We use information from LIGO data quality streams that monitor the status of each detector and its environment to model changes in the rate of noise in each detector. These data quality streams allow candidates identified in the data during periods of detector malfunctions to be more efficiently rejected as noise. This method allows data from machine learning predictions of the detector state to be included as part of the PyCBC search, increasing the total number of detectable gravitational-wave signals by up to 5%. When both machine learning classifications and manually generated flags are used to search data from LIGO-Virgo’s third observing run, the total number of detectable gravitational-wave signals is increased by up to 20% compared to not using any data quality streams. We also show how this method is flexible enough to include information from large numbers of additional arbitrary data streams that may be able to further increase the sensitivity of the search
Design and Evaluation Challenges of Conversational Agents in Health Care and Well-being: Selective Review Study
No full textBackground: Health care and well-being are 2 main interconnected application areas of conversational agents (CAs). There is a significant increase in research, development, and commercial implementations in this area. In parallel to the increasing interest, new challenges in designing and evaluating CAs have emerged.
Objective: This study aims to identify key design, development, and evaluation challenges of CAs in health care and well-being research. The focus is on the very recent projects with their emerging challenges.
Methods: A review study was conducted with 17 invited studies, most of which were presented at the ACM (Association for Computing Machinery) CHI 2020 conference workshop on CAs for health and well-being. Eligibility criteria required the studies to involve a CA applied to a health or well-being project (ongoing or recently finished). The participating studies were asked to report on their projects’ design and evaluation challenges. We used thematic analysis to review the studies.
Results: The findings include a range of topics from primary care to caring for older adults to health coaching. We identified 4 major themes: (1) Domain Information and Integration, (2) User-System Interaction and Partnership, (3) Evaluation, and (4) Conversational Competence.
Conclusions: CAs proved their worth during the pandemic as health screening tools, and are expected to stay to further support various health care domains, especially personal health care. Growth in investment in CAs also shows the value as a personal assistant. Our study shows that while some challenges are shared with other CA application areas, safety and privacy remain the major challenges in the health care and well-being domains. An increased level of collaboration across different institutions and entities may be a promising direction to address some of the major challenges that otherwise would be too complex to be addressed by the projects with their limited scope and budget