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The current paper discusses conversation-based assessments (CBAs) created with prompt engineering for LLMs based on Evidence-Centered Design (ECD). Conversation-based assessments provide students the opportunity to discuss a given topic with artificial agent(s). These conversations elicit evidence of students’ knowledge, skills and abilities that may not be uncovered by traditional tests. We discuss our previous method of creating such conversations with regular expressions and latent semantic analysis in an expensive methodology requiring time and various expertise. Thus, in this novel work, we created a prompt-engineered version of CBAs based on evidence-centered design that remains on the domain topic throughout the conversation as well as provides evidence of the student knowledge in a less expensive way. We present the methodology for creating these prompts, compare responses to various student speech acts between the previous version and the prompt engineered version, and discuss the evidence gleaned from the conversation and based on the prompt. Finally, limitations, conclusions and implications of this work are discussed. 

A novel structural system is being developed collaboratively by researchers from the United States and Japan to protect essential facilities, such as hospitals, where damage to the building and its contents and occupant injuries must be prevented and where continuity of operation must be maintained. The development is focusing on new construction, but it also has potential for use in seismic retrofit of deficient existing buildings. The new system employs practical structural components, including (1) flexible steel moment frames, (2) stiff steel elastic spines and (3) force-limiting connections (FLC) that connect the frames to the spines, to economically control building response and prevent damaging levels of displacement and acceleration. The moment frames serve as the economical primary element of the system to resist a significant proportion of the lateral load, dissipate energy through controlled nonlinear response and provide persistent positive lateral stiffness. The spines distribute response evenly over the height of the building and prevent story mechanisms, and the FLC reduce higher-mode effects and provide supplemental energy dissipation. The full-scale shake-table testing of a building with the Frame-Spine-FLC System, which represents a hospital facility and includes realistic nonstructural components and medical equipment, validated the functionality of the structural system. 

Abstract The Pandora Software Development Kit and algorithm libraries perform reconstruction of neutrino interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at the Deep Underground Neutrino Experiment, which will operate four large-scale liquid argon time projection chambers at the far detector site in South Dakota, producing high-resolution images of charged particles emerging from neutrino interactions. While these high-resolution images provide excellent opportunities for physics, the complex topologies require sophisticated pattern recognition capabilities to interpret signals from the detectors as physically meaningful objects that form the inputs to physics analyses. A critical component is the identification of the neutrino interaction vertex. Subsequent reconstruction algorithms use this location to identify the individual primary particles and ensure they each result in a separate reconstructed particle. A new vertex-finding procedure described in this article integrates a U-ResNet neural network performing hit-level classification into the multi-algorithm approach used by Pandora to identify the neutrino interaction vertex. The machine learning solution is seamlessly integrated into a chain of pattern-recognition algorithms. The technique substantially outperforms the previous BDT-based solution, with a more than 20% increase in the efficiency of sub-1 cm vertex reconstruction across all neutrino flavours. 

The determination of the direction of a stellar core collapse via its neutrino emission is crucial for the identification of the progenitor for a multimessenger follow-up. A highly effective method of reconstructing supernova directions within the Deep Underground Neutrino Experiment (DUNE) is introduced. The supernova neutrino pointing resolution is studied by simulating and reconstructing electron-neutrino charged-current absorption on ${}^{40}\mathrm{Ar}$and elastic scattering of neutrinos on electrons. Procedures to reconstruct individual interactions, including a newly developed technique called “brems flipping,” as well as the burst direction from an ensemble of interactions are described. Performance of the burst direction reconstruction is evaluated for supernovae happening at a distance of 10 kpc for a specific supernova burst flux model. The pointing resolution is found to be 3.4 degrees at 68% coverage for a perfect interaction-channel classification and a fiducial mass of 40 kton, and 6.6 degrees for a 10 kton fiducial mass respectively. Assuming a 4% rate of charged-current interactions being misidentified as elastic scattering, DUNE’s burst pointing resolution is found to be 4.3 degrees (8.7 degrees) at 68% coverage. Published by the American Physical Society2025 

Abstract This paper introduces a novel track-length extension fitting algorithm for measuring the kinetic energies of inelastically interacting particles in liquid argon time projection chambers (LArTPCs). The algorithm finds the most probable offset in track length for a track-like object by comparing the measured ionization density as a function of position with a theoretical prediction of the energy loss as a function of the energy, including models of electron recombination and detector response. The algorithm can be used to measure the energies of particles that interact before they stop, such as charged pions that are absorbed by argon nuclei. The algorithm's energy measurement resolutions and fractional biases are presented as functions of particle kinetic energy and number of track hits using samples of stopping secondary charged pions in data collected by the ProtoDUNE-SP detector, and also in a detailed simulation. Additional studies describe the impact of thedE/dxmodel on energy measurement performance. The method described in this paper to characterize the energy measurement performance can be repeated in any LArTPC experiment using stopping secondary charged pions. 

The international collaboration designing and constructing the Deep Underground Neutrino Experiment (DUNE) at the Long-Baseline Neutrino Facility (LBNF) has developed a two-phase strategy toward the implementation of this leading-edge, large-scale science project. The 2023 report of the US Particle Physics Project Prioritization Panel (P5) reaffirmed this vision and strongly endorsed DUNE Phase I and Phase II, as did the European Strategy for Particle Physics. While the construction of the DUNE Phase I is well underway, this White Paper focuses on DUNE Phase II planning. DUNE Phase-II consists of a third and fourth far detector (FD) module, an upgraded near detector complex, and an enhanced 2.1 MW beam. The fourth FD module is conceived as a "Module of Opportunity", aimed at expanding the physics opportunities, in addition to supporting the core DUNE science program, with more advanced technologies. This document highlights the increased science opportunities offered by the DUNE Phase II near and far detectors, including long-baseline neutrino oscillation physics, neutrino astrophysics, and physics beyond the standard model. It describes the DUNE Phase II near and far detector technologies and detector design concepts that are currently under consideration. A summary of key R&D goals and prototyping phases needed to realize the Phase II detector technical designs is also provided. DUNE's Phase II detectors, along with the increased beam power, will complete the full scope of DUNE, enabling a multi-decadal program of groundbreaking science with neutrinos. 

ProtoDUNE Single-Phase (ProtoDUNE-SP) is a 770-ton liquid argon time projection chamber that operated in a hadron test beam at the CERN Neutrino Platform in 2018. We present a measurement of the total inelastic cross section of charged kaons on argon as a function of kaon energy using 6 and $7\mathrm{GeV}/c$beam momentum settings. The flux-weighted average of the extracted inelastic cross section at each beam momentum setting was measured to be $380\pm 26\mathrm{mbarns}$for the $6\mathrm{GeV}/c$setting and $379\pm 35\mathrm{mbarns}$for the $7\mathrm{GeV}/c$setting. Published by the American Physical Society2024