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ACID: Action-Conditional Implicit Visual Dynamics for Deformable Object Manipulation
No full textManipulating volumetric deformable objects in the real world, like plush toys and pizza dough, bring substantial challenges due to infinite shape variations, non-rigid motions, and partial observability. We introduce ACID, an action-conditional visual dynamics model for volumetric deformable objects based on structured implicit neural representations. ACID integrates two new techniques: implicit representations for action-conditional dynamics and geodesics-based contrastive learning. To represent deformable dynamics from partial RGB-D observations, we learn implicit representations of occupancy and flow-based forward dynamics. To accurately identify state change under large non-rigid deformations, we learn a correspondence embedding field through a novel geodesics-based contrastive loss. To evaluate our approach, we develop a simulation framework for manipulating complex deformable shapes in realistic scenes and a benchmark containing over 17,000 action trajectories with six types of plush toys and 78 variants. Our model achieves the best performance in geometry, correspondence, and dynamics predictions over existing approaches. The ACID dynamics models are successfully employed to goal-conditioned deformable manipulation tasks, resulting in a 30% increase in task success rate over the strongest baseline. For more results and information, please visit https://b0ku1.github.io/acid/
FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators
No full textFourCastNet, short for Fourier Forecasting Neural Network, is a global data-driven weather forecasting model that provides accurate short to medium-range global predictions at 0.25∘ resolution. FourCastNet accurately forecasts high-resolution, fast-timescale variables such as the surface wind speed, precipitation, and atmospheric water vapor. It has important implications for planning wind energy resources, predicting extreme weather events such as tropical cyclones, extra-tropical cyclones, and atmospheric rivers. FourCastNet matches the forecasting accuracy of the ECMWF Integrated Forecasting System (IFS), a state-of-the-art Numerical Weather Prediction (NWP) model, at short lead times for large-scale variables, while outperforming IFS for variables with complex fine-scale structure, including precipitation. FourCastNet generates a week-long forecast in less than 2 seconds, orders of magnitude faster than IFS. The speed of FourCastNet enables the creation of rapid and inexpensive large-ensemble forecasts with thousands of ensemble-members for improving probabilistic forecasting. We discuss how data-driven deep learning models such as FourCastNet are a valuable addition to the meteorology toolkit to aid and augment NWP models
Decentralized, Communication- and Coordination-free Learning in Structured Matching Markets
No full textWe study the problem of online learning in competitive settings in the context of two-sided matching markets. In particular, one side of the market, the agents, must learn about their preferences over the other side, the firms, through repeated interaction while competing with other agents for successful matches. We propose a class of decentralized, communication- and coordination-free algorithms that agents can use to reach to their stable match in structured matching markets. In contrast to prior works, the proposed algorithms make decisions based solely on an agent's own history of play and requires no foreknowledge of the firms' preferences. Our algorithms are constructed by splitting up the statistical problem of learning one's preferences, from noisy observations, from the problem of competing for firms. We show that under realistic structural assumptions on the underlying preferences of the agents and firms, the proposed algorithms incur a regret which grows at most logarithmically in the time horizon. Our results show that, in the case of matching markets, competition need not drastically affect the performance of decentralized, communication and coordination free online learning algorithms
Interface dynamics and flow fields’ structure under thermal heat flux, thermal conductivity, destabilizing acceleration and inertial stabilization
No full textInterfaces and interfacial mixing are omnipresent in fluids, plasmas, materials in vastly different environments. A thorough understanding of their fundamentals is essential in many areas of science, mathematics, and technology. This work focuses on the classical problem of stability of a phase boundary that is a subject to fluxes of heat and mass across it for non-ideal thermally conducting fluids. We develop a rigorous theory resolving challenges not addressed before, including boundary conditions for thermal heat flux, structure of perturbation waves, and dependence of waves coupling on system parameters in a broad range of conditions. We discover the novel class of fluid instabilities in the three regimes—advection, diffusion, and low Mach—with properties that were never earlier discussed and that are defined by the interplay of the thermal heat flux, thermal conductivity and destabilizing acceleration with the inertial stabilization. We reveal the parameter controlling transitions between the regimes through varying the initial conditions. We find that the interface stability is set primarily by the macroscopic inertial mechanism balancing the destabilizing acceleration. The thermal heat flux and the microscopic thermodynamics create vortical fields in the bulk. By linking micro to macro scales, the interface is the place where balances are achieved
Rupture Model for the 29 July 2021 M_W 8.2 Chignik, Alaska Earthquake Constrained by Seismic, Geodetic, and Tsunami Observations
No full textA great earthquake struck the Semidi segment of the plate boundary along the Alaska Peninsula on 29 July 2021, re-rupturing part of the 1938 rupture zone. The 2021 M_W 8.2 Chignik earthquake occurred just northeast of the 22 July 2020 M_W 7.8 Simeonof earthquake, with little slip overlap. Analysis of teleseismic P and SH waves, regional Global Navigation Satellite System (GNSS) displacements, and near-field and far-field tsunami observations provides a good resolution of the 2021 rupture process. During ∼60-s long faulting, the slip was nonuniformly distributed along the megathrust over depths from 32 to 40 km, with up to ∼12.9-m slip in an ∼170-km-long patch. The 40–45 km down-dip limit of slip is well constrained by GNSS observations along the Alaska Peninsula. Tsunami observations preclude significant slip from extending to depths <25 km, confining all coseismic slip to beneath the shallow continental shelf. Most aftershocks locate seaward of the large-slip zones, with a concentration of activity up-dip of the deeper southwestern slip zone. Some localized aftershock patches locate beneath the continental slope. The surface-wave magnitude MS of 8.1 for the 2021 earthquake is smaller than Mₛ = 8.3–8.4 for the 1938 event. Seismic and tsunami data indicate that slip in 1938 was concentrated in the eastern region of its aftershock zone, extending beyond the Semidi Islands, where the 2021 event did not rupture
Search for a heavy resonance decaying into a top quark and a W boson in the lepton+jets final state at √s = 13 TeV
No full textA search for a heavy resonance decaying into a top quark and a W boson in proton-proton collisions at √s = 13 TeV is presented. The data analyzed were recorded with the CMS detector at the LHC and correspond to an integrated luminosity of 138 fb⁻¹. The top quark is reconstructed as a single jet and the W boson, from its decay into an electron or muon and the corresponding neutrino. A top quark tagging technique based on jet clustering with a variable distance parameter and simultaneous jet grooming is used to identify jets from the collimated top quark decay. The results are interpreted in the context of two benchmark models, where the heavy resonance is either an excited bottom quark b∗ or a vector-like quark B. A statistical combination with an earlier search by the CMS Collaboration in the all-hadronic final state is performed to place upper cross section limits on these two models. The new analysis extends the lower range of resonance mass probed from 1.4 down to 0.7 TeV. For left-handed, right-handed, and vector-like couplings, b∗ masses up to 3.0, 3.0, and 3.2 TeV are excluded at 95% confidence level, respectively. The observed upper limits represent the most stringent constraints on the b∗ model to date
Search for heavy resonances decaying to ZZ or ZW and axion-like particles mediating nonresonant ZZ or ZH production at √s = 13 TeV
No full textA search has been performed for heavy resonances decaying to ZZ or ZW and for axion-like particles (ALPs) mediating nonresonant ZZ or ZH production, in final states with two charged leptons (ℓ = e, μ) produced by the decay of a Z boson, and two quarks produced by the decay of a Z, W, or Higgs boson H. The analysis is sensitive to resonances with masses in the range 450 to 2000 GeV. Two categories are defined corresponding to the merged or resolved reconstruction of the hadronically decaying boson. The search is based on data collected during 2016–2018 by the CMS experiment at the LHC in proton-proton collisions at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 138 fb⁻¹. No significant excess is observed in the data above the standard model background expectation. Upper limits on the production cross section of heavy, narrow spin-2 and spin-1 resonances are derived as functions of the resonance mass, and exclusion limits on the production of bulk graviton particles and W′ bosons are calculated in the framework of the warped extra dimensions and heavy vector triplet models, respectively. In addition, upper limits on the ALP-mediated diboson production cross section and ALP couplings to standard model particles are obtained in the framework of linear and chiral effective field theories. These are the first limits on nonresonant ALP-mediated ZZ and ZH production obtained by the LHC experiments
Tracing Milky Way substructure with an RR Lyrae hierarchical clustering forest
No full textRR Lyrae variable stars have long been reliable standard candles used to discern structure in the Local Group. With this in mind, we present a routine to identify groupings containing a statistically significant number of RR Lyrae variables in the Milky Way environment. RR Lyrae variable groupings, or substructures, with potential Galactic archaeology applications are found using a forest of agglomerative, hierarchical clustering trees, whose leaves are Milky Way RR Lyrae variables. Each grouping is validated by ensuring that the internal RR Lyrae variable proper motions are sufficiently correlated. Photometric information was collected from the Gaia second data release and proper motions from the (early) third data release. After applying this routine to the catalogue of 91 234 variables, we are able to report 16 unique RR Lyrae substructures with physical sizes of less than 1 kpc. Five of these substructures are in close proximity to Milky Way globular clusters with previously known tidal tails and/or a potential connection to Galactic merger events. One candidate substructure is in the neighbourhood of the Large Magellanic Cloud but is more distant (and older) than known satellites of the dwarf galaxy. Our study ends with a discussion of ways in which future surveys could be applied to the discovery of Milky Way stellar streams
Antioxidant technology for durability enhancement in polymer electrolyte membranes for fuel cell applications
No full textWhile polymer electrolyte membrane fuel cells (PEMFCs) have surged in popularity due to their low environmental impact and high efficiency, their susceptibility to degradation by in-situ generated peroxide and oxygen radical species has prevented their widespread adoption. To alleviate chemical attack on components of PEMFCs, particularly on polymer electrolyte membranes (PEMs), antioxidant approaches have been the subject of enormous interest as a key solution because they can directly scavenge and remove detrimental peroxide and oxygen radical species. However, a consequence is that long-term PEMFC device operation can cause undesirable adverse degradation of antioxidant additives provoked by the distinctive chemical/electrochemical environment of low pH, electric potential, water flux, and ion exchange/concentration gradient. Moreover, changes in the physical state such as migration, agglomeration, and dissolution of antioxidants by mechanical or chemical pressures are serious problems that gradually deteriorate antioxidant activity and capacity. This review presents current opportunities for and limitations to antioxidant therapy for durability enhancement in PEMs for electrochemical device applications. We also provide a summary of advanced synthetic design strategies and in-depth analyses of antioxidants regarding optimizing activity-stability factors. This review will bring new insight into the design to realization of ideal antioxidant nanostructures for PEMs and open up new opportunities for enhancing proliferation of durable PEMFCs
Population response to earthquakes and earthquake early warnings in Mexico
No full textHuman responses to various natural hazards have been studied for more than a few decades. However, the effects of early warning interventions that alert the population to allow them time to take protective actions are not well known, at least to an extent where it could be compared within a socio-culturally similar region under two different scenarios: events without early warning versus those where early warning is transmitted. To understand to what extent the behaviors of populations and their emotional reactions differ under these two scenarios, we compared individual responses to an earthquake with and without an earthquake early warning (EEW) alert of the populations’ (N = 430) from the states of Mexico, Guerrero, and Mexico City in Mexico. We considered the warnings from the Mexican Seismic Early Warning System (SASMEX) and private providers. Our results indicate that EEW potentially has implications for emotional responses and risk perception during the event and that the populations that respond to the EEW that provides a window of opportunity to perform protective actions, may not necessarily use the time adequately for life saving activities. On the other hand, population reactions to seismic events without any warning include evacuation during the event, which may have negative implications to their life safety. The results draw attention to the need of education of the public to events under two different circumstances – those with and without EEW. To further strengthen the understanding of population response, socio-technical aspects should be considered in future studies