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  1. As the complexity of our food systems increases, they also become susceptible to unanticipated natural and human-initiated events. Commodity trade networks are a critical component of our food systems in ensuring food availability. We develop a generic data-driven framework to construct realistic agricultural commodity trade networks. Our work is motivated by the need to study food flows in the context of biological invasions. These networks are derived by fusing gridded, administrative-level, and survey datasets on production, trade, and consumption. Further, they are periodic temporal networks reflecting seasonal variations in production and trade of the crop. We apply this approach to create networks of tomato flow for two regions – Senegal and Nepal. Using statistical methods and network analysis, we gain insights into spatiotemporal dynamics of production and trade. Our results suggest that agricultural systems are increasingly vulnerable to attacks through trade of commodities due to their vicinity to regions of high demand and seasonal variations in production and flows.
  2. 3D printing technology has played an integral part in the growth of makerspaces, showing potential in enabling the integration of art (A) with science, technology, engineering, and math (STEM) disciplines, giving new possibilities to STEAM implementation. This paper presents the effectiveness of a deployable mobile making platform and its curriculum, focused on 3D printing education. This setup, which draws inspiration from modern makerspaces, was deployed for 227 undergraduate students in Art and Engineering majors at multiple campuses of a large northeastern university and used in either a pre-arranged hour-long session or voluntary walk-in session. Self-reported surveys were created to measure participants’ pre- and post-exposure awareness of 3D printing, design, and STEAM quantified through their (1) familiarity, (2) attitude, (3) interest, and (4) self-efficacy. Additionally, observations on participant engagement and use of the space were made. Statistically significant increases in awareness of 3D printing technology were observed in the participants from both Art and Engineering majors, as well as at different campus locations, irrespective of their initial differences. Observations also show a difference in engagement between prearranged sessions and walk-in sessions, which indicates that different session formats may promote specific engagement with different participant types. Ultimately, this research demonstrates two keymore »findings: (1) though they may gravitate to different elements of 3D printing and design, a single makerspace can be used to engage both Art and Engineering students and (2) by introducing mobility to the traditional idea of a makerspace, participants with different initial levels of AM awareness can be brought to similar final awareness. This second finding is especially essential given the disparities in modern student access to 3D printing technology.« less
  3. Non-shivering thermogenesis through mitochondrial proton uncoupling is one of the dominant thermoregulatory mechanisms crucial for normal cellular functions. The metabolic pathway for intracellular temperature rise has widely been considered as steady-state substrate oxidation. Here, we show that a transient proton motive force (pmf) dissipation is more dominant than steady-state substrate oxidation in stimulated thermogenesis. Using transient intracellular thermometry during stimulated proton uncoupling in neurons of Aplysia californica, we observe temperature spikes of ~7.5 K that decay over two time scales: a rapid decay of ~4.8 K over ~1 s followed by a slower decay over ~17 s. The rapid decay correlates well in time with transient electrical heating from proton transport across the mitochondrial inner membrane. Beyond ~33 s, we do not observe any heating from intracellular sources, including substrate oxidation and pmf dissipation. Our measurements demonstrate the utility of transient thermometry in better understanding the thermochemistry of mitochondrial metabolism.
  4. Abstract The ATLAS experiment at the Large Hadron Collider has a broad physics programme ranging from precision measurements to direct searches for new particles and new interactions, requiring ever larger and ever more accurate datasets of simulated Monte Carlo events. Detector simulation with Geant4 is accurate but requires significant CPU resources. Over the past decade, ATLAS has developed and utilized tools that replace the most CPU-intensive component of the simulation—the calorimeter shower simulation—with faster simulation methods. Here, AtlFast3, the next generation of high-accuracy fast simulation in ATLAS, is introduced. AtlFast3 combines parameterized approaches with machine-learning techniques and is deployed to meet current and future computing challenges, and simulation needs of the ATLAS experiment. With highly accurate performance and significantly improved modelling of substructure within jets, AtlFast3 can simulate large numbers of events for a wide range of physics processes.
    Free, publicly-accessible full text available December 1, 2023
  5. 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 hard 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.
    Free, publicly-accessible full text available December 1, 2023
  6. Free, publicly-accessible full text available May 1, 2023
  7. Free, publicly-accessible full text available May 1, 2023
  8. Abstract The energy response of the ATLAS calorimeter is measured for single charged pions with transverse momentum in the range $$10more »response in the hadronic calorimeter are also compared between data and simulation.« less
    Free, publicly-accessible full text available March 1, 2023