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  1. ; ; ; ; ; ; ; ; ( , ACM SIGMOD)
    Free, publicly-accessible full text available January 1, 2023
  2. ; ; ; ; ; ; ; ; ; ; et al ( , Physical Review Letters)
    Free, publicly-accessible full text available May 1, 2023
  3. ; ; ; ; ; ; ; ; ; ; et al ( , EPJ Web of Conferences)
    Liu, W. ; Wang, Y. ; Guo, B. ; Tang, X. ; Zeng, S. (Ed.)
    Sensitivity studies have shown that the 15 O(α, γ) 19 Ne reaction is the most important reaction rate uncertainty affecting the shape of light curves from Type I X-ray bursts. This reaction is dominated by the 4.03 MeV resonance in 19 Ne. Previous measurements by our group have shown that this state is populated in the decay sequence of 20 Mg. A single 20 Mg(βp α) 15 O event through the key 15 O(α, γ) 19 Ne resonance yields a characteristic signature: the emission of a proton and alpha particle. To achieve the granularity necessary for the identification of thismore »signature, we have upgraded the Proton Detector of the Gaseous Detector with Germanium Tagging (GADGET) into a time projection chamber to form the GADGET II detection system. GADGET II has been fully constructed, and is entering the testing phase.« less
    Free, publicly-accessible full text available January 1, 2023
  4. ; ; ; ; ; ; ; ; ; ; et al ( , EPJ Web of Conferences)
    Liu, W. ; Wang, Y. ; Guo, B. ; Tang, X. ; Zeng, S. (Ed.)
    15 O( α , γ ) 19 Ne is regarded as one of the most important thermonuclear reactions in type I X-ray bursts. For studying the properties of the key resonance in this reaction using β decay, the existing Proton Detector component of the Gaseous Detector with Germanium Tagging (GADGET) assembly is being upgraded to operate as a time projection chamber (TPC) at FRIB. This upgrade includes the associated hardware as well as software and this paper mainly focusses on the software upgrade. The full detector set up is simulated using the ATTPCROOTv 2 data analysis framework for 20 Mgmore »and 241 Am.« less
    Free, publicly-accessible full text available January 1, 2023
  5. ; ; ( , Third International Workshop on Automotive and Autonomous Vehicle Security (AutoSec) 2021 (part of NDSS))
    Accepted Manuscript Full Text Available
  6. ; ; ( , USENIX Security)
    Accepted Manuscript Full Text Available
  7. ( , Frontiers in bioengineering and biotechnology)
    Alarcon, Emilio I. (Ed.)
    Membrane proteins (MPs) are essential to many organisms’ major functions. They are notorious for being difficult to isolate and study, and mimicking native conditions for studies in vitro has proved to be a challenge. Lipid nanodiscs are among the most promising platforms for MP reconstitution, but they contain a relatively labile lipid bilayer and their use requires previous protein solubilization in detergent. These limitations have led to the testing of copolymers in new types of nanodisc platforms. Polymer-encased nanodiscs and polymer nanodiscs support functional MPs and address some of the limitations present in other MP reconstitution platforms. In this review,more »we provide a summary of recent developments in the use of polymers in nanodiscs.« less
    Full Text Available 
  8. ; ; ; ( , ASPLOS)
    Accepted Manuscript Full Text Available
  9. ; ; ; ; ; ( , Computer supported cooperative work CSCW)
    Crowdworkers depend on Amazon Mechanical Turk (AMT) as an important source of income and it is left to workers to determine which tasks on AMT are fair and worth completing. While there are existing tools that assist workers in making these decisions, workers still spend significant amounts of time finding fair labor. Difficulties in this process may be a contributing factor in the imbalance between the median hourly earnings ($2.00/hour) and what the average requester pays ($11.00/hour). In this paper, we study how novices and experts select what tasks are worth doing. We argue that differences between the two populationsmore »likely lead to the wage imbalances. For this purpose, we first look at workers' comments in TurkOpticon (a tool where workers share their experience with requesters on AMT). We use this study to start to unravel what fair labor means for workers. In particular, we identify the characteristics of labor that workers consider is of "good quality'' and labor that is of "poor quality'' (e.g., work that pays too little.) Armed with this knowledge, we then conduct an experiment to study how experts and novices rate tasks that are of both good and poor quality. Through our research we uncover that experts and novices both treat good quality labor in the same way. However, there are significant differences in how experts and novices rate poor quality labor, and whether they believe the poor quality labor is worth doing. This points to several future directions, including machine learning models that support workers in detecting poor quality labor, and paths for educating novice workers on how to make better labor decisions on AMT.« less
    Accepted Manuscript Full Text Available
  10. ; ; ; ; ; ; ; ; ; ; et al ( , Physical Review C)
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