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  1. Growth control is essential to establish organism size, so organisms must have mechanisms to both sense and adjust growth. Studies of single cells have revealed that size homeostasis can be achieved using distinct control methods: Sizer, Timer, and Adder. In multicellular organisms, mechanisms that regulate body size must not only control single cell growth but also integrate it across organs and tissues during development to generate adult size and shape. To investigate body size and growth control in metazoans, we can leverage the roundworm Caenorhabditis elegans as a scalable and tractable model. We collected precise growth measurements of thousands ofmore »individuals throughout larval development, measured feeding behavior to pinpoint larval transitions, and quantified highly accurate changes in animal size and shape during development. We find differences in the growth of animal length and width during larval transitions. Using a combination of quantitative measurements and mathematical modeling, we present two physical mechanisms by which C. elegans can control growth. First, constraints on cuticle stretch generate mechanical signals through which animals sense body size and initiate larval-stage transitions. Second, mechanical control of food intake drives growth rate within larval stages, but between stages, regulatory mechanisms influence growth. These results suggest how physical constraints control developmental timing and growth rate in C. elegans.« less
  2. Amorphous solids lack long-range order. Therefore identifying structural defects—akin to dislocations in crystalline solids—that carry plastic flow in these systems remains a daunting challenge. By comparing many different structural indicators in computational models of glasses, under a variety of conditions we carefully assess which of these indicators are able to robustly identify the structural defects responsible for plastic flow in amorphous solids. We further demonstrate that the density of defects changes as a function of material preparation and strain in a manner that is highly correlated with the macroscopic material response. Our work represents an important step towards predicting howmore »and when an amorphous solid will fail from its microscopic structure.« less
  3. 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
  4. Free, publicly-accessible full text available October 14, 2022