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  1. ; ; ; ; ; ; ( , Journal of Materials Chemistry A)

    Na-doped BiFeO3demonstrates an enhanced p-type behavior compared to p-type BiFeO3prepared without extrinsic dopants, and Na-doped BiFeO3can serve as a photocathode for solar O2reduction to H2O2when coupled with Ag nanoparticle catalysts.

     
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    Free, publicly-accessible full text available August 6, 2025
  2. ; ( , ACM)
    The Dragonfly networks have been adopted in the current supercomputers, and will be deployed in future generation supercomputers and data centers. Effective routing on Dragonfly is challenging. Universal Globally Adaptive Load-balanced routing (UGAL) is the state-of-the-art routing algorithm for Dragonfly. For each packet, UGAL selects either a minimal path or a non-minimal path based on their estimated latencies. Practical UGAL makes routing decisions with local information, deriving the estimated latency for each path from the local queue occupancy and path hop count information. In this work, we develop techniques to improve the accuracy of the latency estimation for UGAL with local information, which results in more effective routing decisions. In particular, our schemes are able to proactively mitigate the potential network congestion with imbalanced network traffic. Extensive simulation experiments using synthetic traffic patterns and application workloads demonstrate that our enhanced UGAL schemes significantly improve the routing performance for many common traffic conditions. 
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    Free, publicly-accessible full text available May 30, 2025
  3. ; ; ( , NeurIPS Proceedings)
    Free, publicly-accessible full text available May 30, 2025
  4. ; ; ; ; ( , Bioinformatics)
    Abstract Motivation

    Many tasks in sequence analysis ask to identify biologically related sequences in a large set. The edit distance, being a sensible model for both evolution and sequencing error, is widely used in these tasks as a measure. The resulting computational problem—to recognize all pairs of sequences within a small edit distance—turns out to be exceedingly difficult, since the edit distance is known to be notoriously expensive to compute and that all-versus-all comparison is simply not acceptable with millions or billions of sequences. Among many attempts, we recently proposed the locality-sensitive bucketing (LSB) functions to meet this challenge. Formally, a (d1,d2)-LSB function sends sequences into multiple buckets with the guarantee that pairs of sequences of edit distance at most d1 can be found within a same bucket while those of edit distance at least d2 do not share any. LSB functions generalize the locality-sensitive hashing (LSH) functions and admit favorable properties, with a notable highlight being that optimal LSB functions for certain (d1,d2) exist. LSB functions hold the potential of solving above problems optimally, but the existence of LSB functions for more general (d1,d2) remains unclear, let alone constructing them for practical use.

     Results

    In this work, we aim to utilize machine learning techniques to train LSB functions. With the development of a novel loss function and insights in the neural network structures that can potentially extend beyond this specific task, we obtained LSB functions that exhibit nearly perfect accuracy for certain (d1,d2), matching our theoretical results, and high accuracy for many others. Comparing to the state-of-the-art LSH method Order Min Hash, the trained LSB functions achieve a 2- to 5-fold improvement on the sensitivity of recognizing similar sequences. An experiment on analyzing erroneous cell barcode data is also included to demonstrate the application of the trained LSB functions.

     Availability and implementation

    The code for the training process and the structure of trained models are freely available at https://github.com/Shao-Group/lsb-learn.

     
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  5. ; ; ; ; ; ( , IEEE)
    Free, publicly-accessible full text available November 17, 2024
  6. ; ; ; ; ; ; ( , IEEE Communications Surveys & Tutorials)
    Accepted Manuscript Full Text Available
  7. ; ; ; ; ( , Soft Matter)

    We use molecular simulation to investigate the pH response of sequence-controlled polyampholyte brushes (PABs) with polymer chains consisting of alternating blocks of weakly acidic and basic monomers.

     
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    Full Text Available 
  8. ; ; ( , 31th Usenix Security Symposium 2022)
    Accepted Manuscript Full Text Available
  9. ; ; ( , the 31th USENIX Security Symposium)
    Accepted Manuscript Full Text Available
  10. ; ; ; ( , 2021 IEEE International Performance, Computing, and Communications Conference (IPCCC))
    Full Text Available