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  1. Abstract

    We present a comprehensive study of the nonproportionality of NaI(Tl) scintillation detectors within the context of dark matter search experiments. Our investigation, which integrates COSINE-100 data with supplementary$$\gamma $$γspectroscopy, measures light yields across diverse energy levels from full-energy$$\gamma $$γpeaks produced by the decays of various isotopes. These$$\gamma $$γpeaks of interest were produced by decays supported by both long and short-lived isotopes. Analyzing peaks from decays supported only by short-lived isotopes presented a unique challenge due to their limited statistics and overlapping energies, which was overcome by long-term data collection and a time-dependent analysis. A key achievement is the direct measurement of the 0.87 keV light yield, resulting from the cascade following electron capture decay of$$\mathrm {^{22}Na}$$22Nafrom internal contamination. This measurement, previously accessible only indirectly, deepens our understanding of NaI(Tl) scintillator behavior in the region of interest for dark matter searches. This study holds substantial implications for background modeling and the interpretation of dark matter signals in NaI(Tl) experiments.

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  2. Augmented Reality (AR) is widely considered the next evolution in personal devices, enabling seamless integration of the digital world into our reality. Such integration, however, often requires unfettered access to sensor data, causing significant over privilege for applications that run on these platforms. Through analysis of 17 AR systems and 45 popular AR applications, we explore existing mechanisms for access control in AR platforms, identify key trends in how AR applications use sensor data, and pinpoint unique threats users face in AR environments. Using these findings, we design and implement Erebus, an access control framework for AR platforms that enables fine-grained control over data used by AR applications. Erebus achieves the principle of least privileged through the creation of a domain-specific language (DSL) for permission control in AR platforms, allowing applications to specify data needed for their functionality. Using this DSL, Erebus further enables users to customize app permissions to apply under specific user conditions. We implement Erebus on Google’s ARCore SDK and port five existing AR applications to demonstrate the capability of Erebus to secure various classes of apps. Performance results using these applications and various microbenchmarks show that Erebus achieves its security goals while being practical, introducing negligible performance overhead to the AR system. 
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  3. Abstract Serial x-ray crystallography can uncover binding events, and subsequent chemical conversions occurring during enzymatic reaction. Here, we reveal the structure, binding and cleavage of moxalactam antibiotic bound to L1 metallo-β-lactamase (MBL) from Stenotrophomonas maltophilia . Using time-resolved serial synchrotron crystallography, we show the time course of β-lactam hydrolysis and determine ten snapshots (20, 40, 60, 80, 100, 150, 300, 500, 2000 and 4000 ms) at 2.20 Å resolution. The reaction is initiated by laser pulse releasing Zn 2+ ions from a UV-labile photocage. Two metal ions bind to the active site, followed by binding of moxalactam and the intact β-lactam ring is observed for 100 ms after photolysis. Cleavage of β-lactam is detected at 150 ms and the ligand is significantly displaced. The reaction product adjusts its conformation reaching steady state at 2000 ms corresponding to the relaxed state of the enzyme. Only small changes are observed in the positions of Zn 2+ ions and the active site residues. Mechanistic details captured here can be generalized to other MBLs. 
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  4. Langran, L. ; Henriksen, D. (Ed.)
    This study introduces an Augmented-Reality-based learning system that aims to support young students’ embodied learning in block-based programming activities where they learn computational concepts and create meaningful chunks of codes. Students are going to perform episode-embedded path-finding tasks, which are designed to practice their capacities of applying computational thinking in a reasonable manner to solve problems within different scenarios. Grounded on an embodied cognition approach, the AR integration creates a concrete and tangible environment for young students to understand abstract conceptual knowledge in an engaging and interactive way, with a close connection built between the real and virtual worlds. 
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