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50 records · Page 3

A temporal hierarchy underpins the transcription factor–DNA interactome of the maize UPR

Adverse environmental conditions reduce crop productivity and often increase the load of unfolded or misfolded proteins in the endoplasmic reticulum (ER). This potentially lethal condition, known as ER stress, is buffered by the unfolded protein response (UPR), a set of signaling pathways designed to either recover ER functionality or ignite programmed cell death. Despite the biological significance of the UPR to the life of the organism, the regulatory transcriptional landscape underpinning ER stress management is largely unmapped, especially in crops. To fill this significant knowledge gap, we performed a large–scale systems–level analysis of the protein–DNA interaction (PDI) network in maize (Zea mays). Using 23 promoter fragments of six UPR marker genes in a high–throughput enhanced yeast one–hybrid assay, we identified a highly interconnected network of 262 transcription factors (TFs) associated with significant biological traits and 831 PDIs underlying the UPR. We established a temporal hierarchy of TF binding to gene promoters within the same family as well as across different families of TFs. Cistrome analysis revealed the dynamic activities of a variety of cis–regulatory elements (CREs) in ER stress–responsive gene promoters. By integrating the cistrome results into a TF network analysis, we mapped a subnetwork of TFs associated with a CRE that may contribute to UPR management. Lastly, we validated the role of a predicted network hub gene using the Arabidopsis system. The PDIs, TF networks, and CREs identified in our work are foundational resources for understanding transcription–regulatory mechanisms in the stress responses and crop improvement.

59 BASIC BIOLOGICAL SCIENCES↗

Diversifying Composition Leads to Hierarchical Composites with Design Flexibility and Structural Fidelity

Although significant progress has been made in the self-assembly of nanostructures, present successes heavily rely on precision in building block design, composition, and pair interactions. These requirements fundamentally limit our ability to synthesize macroscopic materials where the likelihood of impurity inclusion escalates and, more importantly, to access molecular-to-nanoscopic-to-microscopic-to-macroscopic hierarchies, since the types and compositions of building blocks vary at each stage. Inspired by biological blends and high-entropy alloys, we hypothesize that diversifying the blend’s composition can overcome these limitations. Increasing the number of components increases mixing entropy, leading to the dispersion of different components and, as a result, enhances interphase miscibility, weakens the dependence on specific pair interactions, and enables long-range cooperativity. This hypothesis is validated in complex blends containing small molecules, block copolymer-based supramolecules, and nanoparticles/colloidal particles. Hierarchically structured composites can be obtained with formulation flexibility in the filler selection and blend composition. It is worth noting that, by adding small molecules, we can solve the size constraint that plagues traditional block copolymer/nanoparticle blends. Detailed characterization and simulation further confirm that each component is distributed to locally mediate unfavorable interactions, cooperatively mitigate composition fluctuations, and retain structural fidelity. Furthermore, the blends have sufficient mobility to access tunable microstructures without compromising the order of the nanostructure. Besides establishing a kinetically viable pathway to release current constraints in the composite design and to navigate uncertainties during structure formation over multiple length scales, the present study demonstrates that entropy-driven behaviors can be realized in systems beyond high-entropy alloys despite inherent differences between metal alloys and organic/inorganic hybrids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dirty dishes or dirty laundry? Comparing two methods for quantifying American consumers' preferences for load management in a smart home

One challenge of transitioning to renewable energy is that household electricity use and renewable generation are often misaligned. Smart home energy management systems hold promise for shifting usage to match generation, but these systems need to be designed with the occupants’ preferences in mind. The purpose of the present research is to compare two approaches for collecting and modeling consumers’ load management preferences, both of which are amenable to use in a home energy management system. Specifically, we examine the performance of Simple Multi-Attribute Rating Technique Exploiting Ranks (SMARTER) and Analytic Hierarchy Process (AHP) in quantifying consumers’ preferences regarding air temperature (air conditioning and heating), water heating, dishwashing, clothes washing and drying, monetary costs, environmental impacts, and comfort/convenience. Two studies are presented: Study 1 examines the SMARTER approach, and Study 2 focuses on the AHP approach. In both studies, online surveys (N SMARTER = 956 and N AHP = 1023) were conducted to elicit preferences from participants across the United States. The preferences modeled by both approaches were validated based on (a) their ability to predict participants’ choices in a Discrete Choice Experiment and (b) their convergence with previous research on load-shifting behavior. The validation procedure suggests that the SMARTER approach is superior in modeling consumers’ preferences for load management. Overall, this research lays the groundwork for designing a smart home interface capable of collecting occupants’ preferences and using those preferences to deliver improved occupant comfort, lower operating costs, reduced environmental impact, and more significant demand response than exists today.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Description of FY25 Theory and Simulation Performance Target: Development of an integrated modeling framework for fusion reactor design and assessment

The urgency to deliver fusion power is growing now more than ever, with increasing pressure for both public programs and private companies to meet milestones timelines and overcome significant remaining technical challenges to ensure growth of a nascent fusion industry in time to meet rapidly growing clean energy demands. With incredible advancements in computation and years of investment in fusion model development and validation, integrated modeling is poised to fill a key role in accelerating the timeline to a fusion pilot plant (FPP). Future fusion pilot plants will operate in regimes far beyond current experience, and device design will rely on physics-based prediction and extrapolation. Many concepts will also rely on simulation to assess safety (shielding, tritium management, materials activation and lifetimes), economics and scalability before the decision to build. Importantly, integrated simulation can be used to reveal and solve the complexities of system integration that may otherwise not be apparent in physical components or models developed in isolation. New experimental test facilities that produce relevant conditions to validate and resolve key technical challenges for various subsystems (materials, blankets, fuel cycle, etc.) have been repeatedly called for by the fusion community but are not yet realized. Integrated modeling has an important role in identifying realistic load conditions (thermal, electromagnetic, plasma, neutron and photon loads, etc.) and defining the components and experiments for these test facilities in order to ensure meaningful validation that sufficiently reduces modeling uncertainties and technical risk for the full integrated reactor. The Fusion REactor Design and Assessment (FREDA) SciDAC project is building a component-based integrated modeling framework & data structure to enable self-consistent, multi-fidelity, iterative optimization workflows for the fusion reactor design process. FREDA aims to shorten the time to viable designs by providing a set of flexible workflows to support the various stages of the design process using an integrated model hierarchy, ranging from the simple analytic descriptions to the highest fidelity, theory-based plasma and engineering modeling developed by the fusion and fission communities. These tools are expected to be needed for timely support of FPP design in the milestone program and in the FIRE collaboratives. The plasma simulation backbone of FREDA is IPS-FASTRAN with newly developed coupled Core-Edge Pedestal-SOL (CESOL) workflows, which is being extended to the far-SOL region up to the plasma facing components. FREDA incorporates the FERMI engineering modeling suite and will enable self-consistent evaluation of the thermal shields, limiters, blanket, magnets, and other surrounding structures with predictions of temperatures, erosion, dpa, activation, tritium generation and transport, creep, corrosion, material degradation, etc. Parametric generation of 3D CAD enables rapid iteration of component geometry in response to plasma and loading specifications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Structural and Dynamical Roles of Bound Polymer Chains in Rubber Reinforcement

The addition of nanofillers to rubber matrices is a powerful route to improve the mechanical properties. Here, we focus on a molecular understanding of basic mechanisms that are important for the reinforcement in rubbers. The key role in this process is ascribed to bound rubber (BR) that engages with the matrix as well as with adjacent nanofillers. To date, this understanding has been impeded by the lack of experimental tools to directly probe the BR chains buried in a polymer matrix composed of the same polymer. To tackle this challenge, we combine neutron scattering/spectroscopy techniques with isotope-labeling and molecular dynamics simulations. The system is a simplified carbon-black-filled polybutadiene. The combined experimental and computational results provide new insights into the local structural and dynamical heterogeneities of BR chains and their interactions with the matrix polymer, highlighting (i) the structural partition of the bound chains into three components (i.e., trains, loops, and tails) and their fractions; (ii) their dynamical hierarchies, i.e., the trains that remain immobile on the filler surface, the loops that are fairly large and hence allow the interdigitation of matrix chains, and the tails with their unique characteristics to reach far out into the matrix and entangle with matrix chains. These multiple roles of the constituent components of the BR chains promote the formation of a well-developed adhesive polymer–filler interface, enhancing the elastic property of a filled rubber. Finally, the comprehensive understanding derived and validated by the model rubber will be translatable to many other polymer nanocomposites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Geothermal Play-Fairway Analysis of Washington State Prospects: Final Report

The Washington State Geothermal Play-Fairway Analysis overcomes the exploration challenges posed by dense vegetation, glacial deposits, and extreme precipitation. The geothermal play-fairways we target are locations where heat, permeability, and saturated porosity are present in sufficient volume to provide adequate heat exchange at depths accessible by modern drilling technology. The three study areas lie along the Cascade Range magmatic arc and are near Mount Baker, Mount St. Helens, and the Wind River Valley. The seven-year project is divided into three phases. In Phase 1 we build on a previous statewide assessment of geothermal resources and develop an initial modeling approach. The results are a series of favorability, uncertainty, and risk maps for three targeted study areas. Based on these initial results, we collect new geologic and geophysical data to further refine our modeling and reduce exploration uncertainty in Phase 2. We improve the modeling method to handle the new data and update the favorability, uncertainty, and risk maps. We also update the conceptual geothermal resource models. In Phase 3 we validate our modeling approach by drilling two temperature-gradient holes and collecting and analyzing core, image logs, and new geochemistry. Our modeling approach improves on an earlier statewide method through a more-rigorous and detailed assessment of heat and permeability. Permeability potential is assessed through geomechanical modeling of the deformation that can generate and maintain reservoir porosity and permeability. Metrics to inform heat potential include temperature-gradient wells, which are sparse in Washington; proximity of Quaternary volcanic vents and young intrusive rock; spring temperature; and reservoir temperature inferred from geothermometry. We weight the individual components using an expert-guided approach known as the Analytical Hierarchy Process. During Phase 2 we also develop a fluid-filled fracture model, and an infrastructure model that helps to delineate areas which are more favorable for geothermal development based on proximity to transmission lines, elevation, land ownership and use restrictions, and availability of process water. New geologic and geophysical data is collected during Phase 2 in each of our three main study areas. At Mount Baker and north of Mount St. Helens we conduct 1:24,000-scale geologic mapping and lidar analysis to better constrain the location and character of surface faults; detailed mapping in the Wind River Valley was completed just prior to the start of this project. Ages of intrusive rocks are determined with 40 Ar/ 39 Ar geochronology, though all of our samples are Miocene or older. We collect ground based gravity observations (a total of 1,580 new stations) in all of our study areas and ground-based magnetic lines (a total of 93 km) at Mount Baker. These data are combined with existing gravity and aeromagnetic data and used to constrain fault locations and geometry. Two to three cross sections are constructed at each study area using the mapped surface geology and forward-modeling of the gravity and magnetic data; these cross sections form the basis for our updated conceptual models. We collect magnetotelluric surveys at Mount Baker and Mount St. Helens and these data are inverted to form a resistivity model from the surface to about 10 km depth; each model shows conductive zones that can be interpreted as upwelling geothermal fluids. At Mount St. Helens we deploy a passive seismic array and use the newly detected events to refine the location of the Saint Helens seismic zone. We also employ ambient-noise tomography to develop a detailed seismic-velocity model for the study area and use this model to help constrain our cross sections and conceptual model. Based on the new data collected during Phase 2—and our updated models—we develop a campaign of temperature-gradient holes and core analysis to validate our modeling in Phase 3. Drill hole MB76-31 is located near Little Park Creek, 11 km west-southwest of the summit of Mount Baker, and is 1,471 ft deep. About 410 ft of core from the lower portion of the hole—and image logs from ~175 ft below ground surface to the bottom—are collected and analyzed. Water samples are collected and processed for geothermometry. Drill hole MSH17-24 is located along upper Schultz Creek, 16 km north-northeast of Mount St. Helens and has core from 470 ft to the bottom at 1,053 ft. We did not collect image logs due to borehole stability concerns, but water samples are collected and analyzed for geothermometry. Repeat temperature-gradient measurements are made at both sites and thermal conductivity is measured from core samples. At MB76-31, the equilibrated temperature gradient of 64°C/km and calculated heat flow of 141–159 mW/m 2 is more than twice the regional average. Detailed mapping and analysis of the core, coupled with correlation to the image logs, indicates a history of permeability generation consistent with our predictions of high permeability. Because the site has high favorability in the Phase 2 model, we consider the results a positive validation of the modeling. At site MSH17-24, the equilibrated temperature gradient of ~15°C/km and calculated heat flow of 41–43 mW/m 2 are similar to regional. Geochemical analysis of the water samples indicates a meteoric source without any geothermal component. Detailed outcrop-based mapping of fault exposures near the drill site and analysis of image logs from nearby boreholes indicates a history of permeability generation consistent with our predictions. Because the site has low favorability in the Phase 2 model, we consider the results a positive validation of the modeling. Together, the two sites provide a reasonably positive validation of the Phase 2 modeling and should encourage future use of this modeling approach.

15 GEOTHERMAL ENERGY↗

Gold-Standard Chemical Database 137 (GSCDB137): A Diverse Set of Accurate Energy Differences for Assessing and Developing Density Functionals

We present GSCDB137, a rigorously curated benchmark library of 137 data sets (8377 entries) covering main-group and transition-metal reaction energies and barrier heights, (intra- and intermolecular) noncovalent interactions, dipole moments, polarizabilities, electric-field response energies, and vibrational frequencies. Legacy data from GMTKN55 and MGCDB84 have been updated to today's best reference values; redundant or low-quality points were removed, and many new, property-focused sets were added. Testing 29 popular density functional approximations (DFAs) confirms the expected Jacob's-ladder hierarchy overall but also reveals notable exceptions: functional performance for frequencies and electric-field properties correlates poorly with that for other ground-state energetics. ωB97M-V and ωB97X-V are the most balanced hybrid meta-GGA and hybrid GGA, respectively; B97M-V and revPBE-D4 lead the meta-GGA and GGA classes. Double hybrids lower mean errors by about 30% versus their hybrid analogues but demand careful frozen-core, basis set, and spin contamination treatment. GSCDB137 offers a comprehensive, openly documented platform for rigorous validation of DFA and universal machine learning potentials, and training of the next generation of exchange-correlation functionals.

Liang, Jiashu [University of California, Berkeley,↗

Development and validation of a gamma-ray detection response model for neutron-diagnosed subcritical experiments

In a neutron-diagnosed subcritical experiment, a highly sensitive and fast detector is required to accurately determine the true fission γ-ray emission rate from an object composed of special nuclear material under interrogation, in addition to a proper detector response model for use in forward modeling. We present the development of a detector response model that is based in GEANT4 and uses post-processing techniques to include photomultiplier tube time and pulse height response effects. We also define a set of detector performance evaluation metrics that emphasized our experimental objectives. A suite of time and pulse height response measurements for several diverse detector assemblies are described. These assemblies were simulated with this response model and benchmarked against the laboratory measurements. This response model reproduces the pulse height curve shapes and performance hierarchy of the measured detectors well. Additionally, the simulated time response curves exhibit reasonable agreement with counterpart measurements. These measurements and simulation results together suggest that a large volume EJ-299-49 plastic scintillator that is mated to an ultraviolet transmitting plastic light guide and relies on total internal reflection for light transport to the photocathode will provide significantly faster timing, increase pulse height by a factor of 3, and require 25% less γ rays to meet experimental needs, compared to the candidate detector design developed prior to the availability of this response model. Application of this response model and associated performance metrics in the context of large-scale design sensitivity studies is also discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

MeV-scale performance of water-based and pure liquid scintillator detectors

This paper presents studies of the performance of water-based liquid scintillators (WbLS) in both 1-kt and 50-kt detectors. In this work, performance is evaluated in comparison to both pure water Cherenkov detectors and a nominal model for pure scintillator detectors. Performance metrics include energy, vertex, and angular resolution, along with a metric for the ability to separate the Cherenkov from the scintillation signal as being representative of various particle identification capabilities that depend on the Cherenkov/scintillation ratio. We also modify the time profile of scintillation light to study the same performance metrics as a function of rise and decay time. We go on to interpret these results in terms of their impact on certain physics goals, such as solar neutrinos and the search for Majorana neutrinos. This work supports and validates previous results, and the assumptions made therein, and serves as a significant stepping stone to complete detector design studies by using a more detailed detector model and full reconstruction, with a primarily data-driven optical model, and fewer model assumptions. With this model, a high-coverage 50-kt detector achieves better than 10 (1)% precision on the flux of neutrinos from the Carbon-Nitrogen-Oxygen cycle with a water-based liquid scintillator (pure LS) target in five years of data taking. A 1-kt LS detector, with a conservative 50% fiducial volume of 0.5 kt, can achieve better than 5% detection. A liquid scintillator detector has sensitivity into the normal hierarchy region for Majorana neutrinos with half-life sensitivity of $T^{0νββ}_{1/2}$ > 1.4 × 10 28 years at 90% C.L. for 10 years of data taking with a Te-loaded target.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Characterization of cubic Li$_{2}$$^{100}$MoO$_4$ crystals for the CUPID experiment

The CUPID Collaboration is designing a tonne-scale, background-free detector to search for double beta decay with sufficient sensitivity to fully explore the parameter space corresponding to the inverted neutrino mass hierarchy scenario. One of the CUPID demonstrators, CUPID-Mo, has proved the potential of enriched Li$_{2}$$^{100}$MoO$_4$ crystals as suitable detectors for neutrinoless double beta decay search. In this work, we characterised cubic crystals that, compared to the cylindrical crystals used by CUPID-Mo, are more appealing for the construction of tightly packed arrays. We measured an average energy resolution of (6.7$\pm$0.6) keV FWHM in the region of interest, approaching the CUPID target of 5 keV FWHM. We assessed the identification of $\alpha$ particles with and without a reflecting foil that enhances the scintillation light collection efficiency, proving that the baseline design of CUPID already ensures a complete suppression of this $\alpha$-induced background contribution. We also used the collected data to validate a Monte Carlo simulation modelling the light collection efficiency, which will enable further optimisations of the detector.

100Mo↗

Code Verification and Solution Verification framework in pin-resolved neutron transport code MPACT

Program verification in scientific computing encompasses the application of formal and mathematical techniques to a scientific computing code for its credibility, accuracy, and validity. Code Verification identifies bugs and performance issues in the software development stage. Solution Verification assesses the applicability of the code and the accuracy of the solution to problems of interest. Both activities utilize application cases and quantify the error against prescribed acceptance criteria. However, simply executing more application cases does not guarantee stronger or more comprehensive credibility. Here, we establish a verification framework that involves Code Verification and Solution Verification, both of which work together such that the overarching goal of “converge to the correct answer for the intended application” can be reasonably inferred. The application of such a verification framework is demonstrated using the pin-resolved neutron transport code MPACT, where standard unit tests and regression tests are covered, and where the Method of Exact Solutions and the Method of Manufactured Solutions are successfully used. Additionally, the applicability of Method of Manufactured Solutions is extended to the OECD/NEA C5G7 benchmark problems of practical material and geometric configurations. Solution Verification activities are demonstrated on a practical hierarchy of application models of increasing complexity ranging from 2D pin cell problems to 3D assembly problems. The convergence behavior and rate of convergence with respect to each individual variable are studied and provided. This framework can be adapted broadly to other fields involving scientific computing codes.

97 MATHEMATICS AND COMPUTING↗

Building Intelligent Cyberinfrastructure to Learn Iteratively from both Observations and Models for Understanding Watershed Dynamics

Focal Area(s): Predictive modeling through the use of AI techniques and AI-derived model components; the use of AI and other tools to design a prediction system comprising of a hierarchy of models (e.g., AI-driven model/component/parameterization selection). Science Challenge: Watershed processes, such as the fate and transport of sediment, carbon and nutrients across landscapes and their fluxes to water bodies (e.g., streams, rivers and lakes), have important implications for global and regional carbon and nutrient dynamics, biogeochemical functioning of terrestrial ecosystems, and soil functions. The magnitude of lateral surface/subsurface transport and fluxes of sediment, carbon and nutrients are key factors controlling the vulnerability of watersheds to climate extremes such as droughts, wildfires, and floods. Recent field observations and other scientific evidence suggest that the magnitudes of lateral transport and fluxes of sediment, carbon and nutrients are governed primarily by the spatial and vertical heterogeneity of landscape and soil properties and by pedogenic processes. However, the current generation of land surface and watershed models do not mechanistically couple the terrestrial and hydrologic systems, nor do they represent sufficiently the spatial and vertical heterogeneity of land surface and subsurface properties. On the other hand, increasing complexity of coupled watershed and land surface models requires more data to parameterize, calibrate and validate. Remote sensing (RS) provides a means to acquire spatial data and characterize their heterogeneity at the watershed scale, overcoming a major limitation associated with conventional point measurements. To improve the representation of land-surface and surface/subsurface process coupling and sub-grid heterogeneity in watershed models, it is essential to build our predictive understanding by learning from both the multi-scale multi-process modeling and diverse multi-scale data while leveraging powerful artificial intelligence (AI) techniques.

54 ENVIRONMENTAL SCIENCES↗

First Measurement of Inclusive Muon Neutrino Charged Current Triple Differential Cross Section on Argon

The field of accelerator neutrino experiments is entering an era of precision oscillation measurements where the remaining unknown neutrino measurements will be determined. The upcoming DUNE and Hyper-K experiments aim to determine the neutrino mass hierarchy and degree of Charge-Parity (CP) violation in the neutrino sector, providing potential insight on the matter-antimatter imbalance observed in the universe. However, these experiments require highly accurate measurements, and neutrino cross section modeling uncertainties may limit their capabilities. Cross section measurements at current- generation experiments can aid the development of neutrino interaction models to reduce these uncertainties. This is especially true for measurements of neutrino energy, as it drives neutrino oscillations and is of key importance to oscillation experiments. The MicroBooNE experiment uses a Liquid Argon Time Projection Chamber (LArTPC) to produce neutrino-argon cross sections as one of its physics goals. The MicroBooNE detector’s fully active volume, precision reconstruction, and calorimetry information are leveraged in the Wire-Cell analysis to produce a muon neutrino selection that is 92% pure while maintaining 68% efficiency. A reconstruction chain featuring a fully 3D charge reconstruction and a graph-based particle trajectory fit are used to produce accurate measurements of lepton kinematics as well as visible hadronic energy produced in a neutrino interaction. This thesis presents the first neutrino-argon triple-differential cross section measurement, targeting inclusive charged-current final states. Wiener SVD unfolding is used to produce a measurement over neutrino energy, muon momentum, and muon scattering angle. A series of constrained goodness of fit tests are used to demonstrate the validity of MicroBooNE’s model in describing the distribution of reconstructed kinematics seen in data to ensure the accuracy of unfolding. The validated unfolding to neutrino energy represents a step forward in the field of neutrino cross sections, and demonstrates the capabilities of the LArTPC detector.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Searching for Sterile Neutrinos In the NOvA Experiment and Measurements of Hadronic Energy Response with NOvA Test Beam Data

The NOvA (NuMI Off-Axis electron neutrino Appearance) experiment is a long-baseline neutrino oscillation experiment composed of two functionally identical detectors: a 300-ton Near Detector and a 14-kton Far Detector, separated by 809 km and placed 14 mrad off the axis of the NuMI neutrino beam created at Fermilab. This configuration enables NOvA’s rich neutrino physics program, which includes measuring neutrino mixing parameters, determining the neutrino mass hierarchy, probing CP violation in the leptonic sector, studying neutrino cross sections, searching for sterile neutrinos, and more.\\ In this thesis I will present two independent analyses developed within the NOvA experiment. The first is a search for light sterile neutrino oscillations in the 3+1 framework using $\nu_\mu$-CC and NC samples from the NOvA Near and Far Detectors. Light sterile neutrinos are hypothetical neutral leptons that do not participate in the weak interactions but can mix with the three known active neutrinos: $\nu_e$, $\nu_\mu$, and $\nu_\tau$. Anomalous results, such as $\nu_e$/$\bar{\nu}e$ appearance in a $\nu_\mu$ ($\bar{\nu}_\mu$) beam observed by the MiniBooNE and LSND experiments, can be explained by the existence of sterile neutrinos. Thus, proving the existence of this type of neutrino is essential. The latest results of these searches in the NOvA experiment, along with contributions to this effort, will be presented.\\ The second is the first measurement of the pion energy response using data from the NOvA Test Beam experiment. The NOvA Test Beam experiment, deployed at Fermilab, uses a scaled-down 30-ton NOvA detector to analyze tagged beamline particles. The beamline can select and identify electrons, muons, pions, kaons, and protons with momenta ranging from 0.4 to 1.4 GeV/c. Pions are an important component of the hadronic system in neutrino interactions, and understanding how the detector responds to these particles is crucial for the validation of the simulation and the reduction of detector calibration uncertainties, which remain one of the largest systematic uncertainties in NOvA analyses.

Dueñas Tonguino, David Francisco [Cincinnati U.] (↗