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  1. ; ; ; ; ; ; ( , 17th International Conference on Motivation (ICM))
    Free, publicly-accessible full text available August 1, 2023
  2. ; ; ; ; ; ; ; ( , 2022 Network Gender & STEM Conference)
    Free, publicly-accessible full text available July 1, 2023
  3. ; ; ; ; ( , IEEE transactions on knowledge and data engineering)
    Free, publicly-accessible full text available February 1, 2023
  4. ; ; ; ; ; ; ; ( , 2022 Network Gender & STEM Conference)
    Accepted Manuscript Full Text Available
  5. ; ; ; ; ; ; ; ; ; ; et al ( , Nature Communications)
    Abstract A recent focus of quantum spin liquid (QSL) studies is how disorder/randomness in a QSL candidate affects its true magnetic ground state. The ultimate question is whether the QSL survives disorder or the disorder leads to a “spin-liquid-like” state, such as the proposed random-singlet (RS) state. Since disorder is a standard feature of most QSL candidates, this question represents a major challenge for QSL candidates. YbMgGaO 4 , a triangular lattice antiferromagnet with effective spin-1/2 Yb 3+ ions, is an ideal system to address this question, since it shows no long-range magnetic ordering with Mg/Ga site disorder. Despite themore »intensive study, it remains unresolved as to whether YbMgGaO 4 is a QSL or in the RS state. Here, through ultralow-temperature thermal conductivity and magnetic torque measurements, plus specific heat and DC magnetization data, we observed a residual κ 0 / T term and series of quantum spin state transitions in the zero temperature limit for YbMgGaO 4 . These observations strongly suggest that a QSL state with itinerant excitations and quantum spin fluctuations survives disorder in YbMgGaO 4 .« less
    Free, publicly-accessible full text available December 1, 2022
  6. ( , European Conference on Computer Vision (ECCV))
    Vedaldi A., Bischof H. (Ed.)
    Full Text Available 
  7. ; ; ; ; ; ; ; ; ; ; et al ( , Nature Communications)
    Full Text Available 
  8. ; ; ( , 2018 Solid-State Sensors, Actuators and Microsystems Workshop)
    We report a flexible and wearable bacteria-powered battery in which four functional yarns are placed in parallel for biological energy harvesting. A current collecting yarn is sandwiched between two conductive/hydrophilic active yarns including electricity-generating bacteria while a polymer-passivated cathodic yarn is located next to one of the active yarns to form a biological fuel cell configuration. The device uses Shewanella oneidensis MR-1 as a biocatalyst to produce a maximum power of 17μW/cm3 and current density 327μA/cm3, which are enough to power small-power applications. This yarn-structured biobattery can be potentially woven or knitted into an energy storage fabric to provide amore »higher power for smart textiles. Furthermore, sweat generated from the human body can be a potential fuel to support bacterial viability, providing the long-term operation of the battery.« less
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  9. ; ; ; ; ; ; ; ; ; ; et al ( , Computing and Software for Big Science)
    Abstract The accurate simulation of additional interactions at the ATLAS experiment for the analysis of proton–proton collisions delivered by the Large Hadron Collider presents a significant challenge to the computing resources. During the LHC Run 2 (2015–2018), there were up to 70 inelastic interactions per bunch crossing, which need to be accounted for in Monte Carlo (MC) production. In this document, a new method to account for these additional interactions in the simulation chain is described. Instead of sampling the inelastic interactions and adding their energy deposits to a hard-scatter interaction one-by-one, the inelastic interactions are presampled, independent of the hardmore »scatter, and stored as combined events. Consequently, for each hard-scatter interaction, only one such presampled event needs to be added as part of the simulation chain. For the Run 2 simulation chain, with an average of 35 interactions per bunch crossing, this new method provides a substantial reduction in MC production CPU needs of around 20%, while reproducing the properties of the reconstructed quantities relevant for physics analyses with good accuracy.« less
    Free, publicly-accessible full text available December 1, 2023
  10. ; ; ; ; ; ; ; ; ( , Physical Review A)
    Full Text Available