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At least 307 records · Page 17

Hard color-singlet exchange in dijet events in proton-proton collisions at $\sqrt{s} = 13$ TeV

We present a measurement of events with two jets separated by a pseudorapidity gap (jet-gap-jet). The signature is expected from hard color-singlet exchange. The jets are reconstructed with the CMS detector. The highest p_\text{T} p T jets have p_\text{T}^\text{jet1,2} > 40 p T jet1,2 > 40 GeV, with 1.4 < |\eta^\text{jet1,2}| < 4.7 1.4 < | η jet1,2 | < 4.7 and \eta^\text{jet1} \eta^\text{jet2} < 0 η jet1 η jet2 < 0 . We measure the fraction of color-singlet exchange dijet events, f_\text{CSE} f CSE , and compare it to previous measurements and to predictions. We also study jet-gap-jet events where the colliding protons remain intact and are detected with the Roman pots of TOTEM. A larger fraction f_\text{CSE} f CSE is found in the latter subsample.

Baldenegro Barrera, Cristian↗

Λ spin polarization in event-by-event relativistic heavy-ion collisions

We present a systematic study of $\Lambda$ hyperon's polarization observables using event-by-event (3+1)D relativistic hydrodynamics. The effects of initial hot spot size and QGP's specific shear viscosity on the polarization observables are quantified. We examine the effects of the two formulations of the thermal shear tensor on the polarization observables using the same hydrodynamic background. With event-by-event simulations, we make predictions for the Fourier coefficients of $\Lambda$'s longitudinal polarization $P^z$ with respect to the event planes of different orders of anisotropic flow. We propose new correlations among the Fourier coefficients of $P^z$ and charged hadron anisotropic flow coefficients to further test the mapping from fluid velocity gradients to hyperon's polarization. Finally, we present a system size scan with Au+Au, Ru+Ru, and O+O collisions at $\sqrt{s_\mathrm{NN}} = 200$ GeV to study the system size dependence of polarization observables at the Relativistic Heavy-ion Collider.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Nexus of thermal resilience and energy efficiency in buildings: A case study of a nursing home

Extreme weather events become more frequent and severe due to climate change. Although energy efficiency technologies can influence thermal resilience of buildings, they are traditionally studied separately, and their interconnections are rarely quantified. This study developed a methodology of modeling and analysis to provide insights into the nexus of thermal resilience and energy efficiency of buildings. In this work, we conducted a case study of a real nursing home in Florida, where 12 patients died during Hurricane Irma in 2017 due to HVAC system power loss, to understand and quantify how passive and active energy efficiency measures (EEMs) can improve thermal resilience to reduce heat-exposure risk of patients. Results show that passive measures of opening windows and doors for natural ventilation, as well as miscellaneous load reduction, are very effective in eliminating the extreme dangerous occasions. However, to maintain safe conditions, active measures such as on-site power generators and thermal storage are also needed. The nursing home was further studied by changing its location to two other cities: San Francisco (mild climate) and Chicago (cold winter and hot summer). Results revealed that the EEMs' impacts on thermal resilience vary significantly by climate and building characteristics. The study also estimated the costs of EEMs to help stakeholders prioritize the measures. Passive measures that may not save energy may greatly improve thermal resilience, and thus should be considered in building design or retrofit. Findings from this study indicate energy efficiency technologies should be evaluated not only by their energy savings performance but also by their influence on a building's resilience to extreme weather events.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

The short-term comprehensive impact of the phase-out of global coal combustion on air pollution and climate change

With the continuous intensification of global warming, the reduction and ultimate phase-out of coal combustion is an inevitable trend in the future global energy transformation. This study comprehensively analyzed the impact of phasing out coal combustion on global emissions and concentrations of air pollutants, radiative fluxes, meteorology and climate using Community Earth System Model 2 (CESM2). The results indicate that after the global phase-out of coal combustion, there is a marked decrease in the concentrations of sulfur dioxide (SO 2 ), nitrogen oxides (NO x ) and fine particulate matter (PM 2.5 ), with some regions experiencing a reduction of exceeding 50%. There is no significant change in global ozone (O 3 ) concentration. There are decreasing AOD and positive radiative fluxes globally in the short term, though the cloud contributes minor negative radiative fluxes. The global air temperature may increase by approximately (0.02 ± 0.15) °C on average with regional and seasonal variations, and the precipitation may potentially increase by approximately (2.7 ± 40.6) mm yr −1 globally and over 20% in equatorial regions in the short term. But combined with the decreasing trend of cloud water content in the Northern Hemisphere, it indicates a potential increase in the extremity of precipitation events. In conclusion, this study provides references for global control of air pollution, mitigation strategies of climate change, and transformation of energy structures under the objective of “carbon neutrality”, such as focusing on the negative climate impacts of exacerbating regional warming and increasing extreme precipitation resulting from the rapid reduction of aerosols in the short term.

01 COAL, LIGNITE, AND PEAT↗

The Influence of Environment on Post-Detonation Chemistry and Debris Formation (Abbreviated Final Report: 20-SI-006)

Predicting, responding to, or interpreting the chemical record preserved in debris derived from nuclear events can be challenging due to chemical fractionation. Chemical fractionation is where different species of the evolving radionuclide inventory segregate and/or are lost from the system over the timescales of debris formation. Both historic data and recent research suggest that the interaction and character of the local environment may exert controls on chemical fractionation by influencing the cooling and evolution of the associated fireball as well as the composition of the vapor term and resultant speciation. Prior to this work, an integrated platform permitting dynamic and concurrent consideration of physical and chemical evolution of early time post-detonation event environments did not exist. Our work merged historic data and experimental approaches to support development of a computational framework able to simulate fundamental processes (e.g., entrainment of local environment, oxidation chemistry, and cooling time scales) that may perturb the radionuclide inventory captured in post-detonation debris. Work with historic debris confirmed that entrained environmental material affect debris composition, structure, and radionuclide incorporation. Complementary work utilizing a readily controllable and tunable benchtop setup (a plasma flow reactor) simulated the late cooling of a nuclear fireball (e.g., T < 6000 K) and bounded the sensitivity of actinide speciation and particle size distribution to variations in oxygen concentration and cooling rates. Concurrent laser ablation and laser heating experiments were used to investigate the chemistry and physics of processes occurring in vaporized and/or rapidly heated actinides and other elements in the presence of oxygen. A more computationally efficient microphysical model was developed for predicting and evolving size distributions of particles forming from mixed vapor terms and simulating particle formation processes under a variety of extreme conditions. Continued study of historic nuclear event film confirmed that shockwave data and physics codes agree to within the uncertainty of the data. Good agreement was achieved for thermal emission from an airburst, however the paucity of low-temperature molecular opacity data for mixtures of air, bomb debris, entrained dirt, and water vapor complicate agreement for more elaborate scenarios. A multiphysics code (ALE3D) was modified to bring the necessary physics and chemistry, including these new data and insights, onto a single platform. Code development included improved initialization of large physical systems, modernization of chemistry capabilities, and modifications to enable inclusion of particle transport.

07 ISOTOPE AND RADIATION SOURCES↗

Estimating soybean yields from high-temporal-resolution multi-source data using deep learning

Accurate and timely crop yield prediction is crucial for ensuring food security and maintaining stable agricultural markets. In recent years, there has been a surge in interest in leveraging high-temporal-resolution, multi-source data for effective crop growth monitoring and yield estimation. A notable challenge arises from the difficulty in capturing the intricate interactions between variables across different time steps within these high-temporal-resolution time series datasets. This complexity hinders the reliable extraction of yield information from voluminous and often noisy datasets, especially during periods of extreme weather events. Here, in this study, we propose an Attention and Graph Isomorphism Network-enhanced Bi-directional Long Short-Term Memory network (AGB-LSTM) for estimating county-level soybean yield in the United States. This model integrates a diverse set of remote sensing data, including Near-Infrared Reflectance of Vegetation (NIRv), Sun-Induced chlorophyll Fluorescence (SIF), and Gross Primary Productivity (GPP), along with environmental covariates. The AGB-LSTM effectively leverages information related to crop yield from high-temporal-resolution time series data (5-days), achieving an accuracy of R²= 0.67 and rRMSE = 14.46%. This approach significantly outperforms traditional machine learning methods such as Random Forest (RF) (R²= 0.52, rRMSE = 17.36%) and Bi-LSTM (R²= 0.58, rRMSE = 16.17%). Sensitivity experiments with different time steps and ranges demonstrated that our model could accurately and stably predict yields 1 to 2 months before harvest. Moreover, data with a finer temporal resolution consistently improved prediction performance, resulting in an approximately 20% increase in and an approximately 20% decrease in rRMSE compared to using monthly composites. We also evaluated the robustness of the model under extreme climate events and observed strong performance (R²= 0.50, rRMSE = 21.32%). Finally, yield mapping for major soybean-producing regions in North America in 2023 revealed spatial patterns that closely matched USDA yield reports. Our findings suggest that the AGB-LSTM model is a promising and effective method for estimating yield and has notable potential for global crop yield forecasting.

Deep learning↗

Intelligent Energy Optimizer for Residential Buildings

Demand-side management in the buildings is essential for meeting grid flexibility needs in a highly renewable energy scenario. Appliance load monitoring helps decision making for demand-side management by providing the information on operation status/power consumption from different appliances in the buildings. Nonintrusive load monitoring (NILM) is an attractive option for appliance load monitoring using because it has lower cost for sensors and helps mitigate privacy concerns. In this study, the team used an event detection technique followed by two different methods for event classification. The results from k-means clustering showed that the events from a single appliance are often distributed in multiple clusters. Thus, the unsupervised method of NILM using k-means clustering used in this study was not very suitable for load disaggregation. The results from NILM showed that the F1 score for event classification was 0.77 for a heat pump water heater and very low for other appliances using the rule-based classification.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Reflections on the anomalous ANITA events: the Antarctic subsurface as a possible explanation

The Antarctic Impulsive Transient Antenna (ANITA) balloon experiment was designed to detect radio signals initiated by high-energy neutrinos and cosmic ray (CR) air showers. These signals are typically discriminated by the polarization and phase inversions of the radio signal. The reflected signal from CRs suffer phase inversion compared to a direct ‘tau neutrino’ event. In this paper, we study subsurface reflection, which can occur without phase inversion, in the context of the two anomalous up-going events reported by ANITA. It is found that subsurface layers and firn density inversions may plausibly account for the events, while ice fabric layers and wind ablation crusts could also play a role. This hypothesis can be tested with radar surveying of the Antarctic region in the vicinity of the anomalous ANITA events. Future experiments should not use phase inversion as a sole criterion to discriminate between down-going and up-going events, unless the subsurface reflection properties are well understood.

54 ENVIRONMENTAL SCIENCES↗

Time interval distributions of nuclear events in a digital spectrometer

This study compares the theoretical formula for time interval density distributions (TIDs) in counters with pileup rejection to TIDs measured using a digital spectrometer with trapezoid filtering. The TIDs were derived from successive time stamps of 60 Co and 133 Ba γ rays detected with a HPGe spectrometer. The results demonstrate that the theoretical formula is applicable up to 40% count loss and can be used to retrospectively deduce the incident event rate.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Multi-Mechanism Flood Hazard Assessment: Example Use Case Studies

Multi-mechanism flood (MMF) events are caused by the combined effects of more than one flooding mechanism. Although floods can result from the occurrence of individual flood mechanisms, they can (and often do) result from multiple flooding mechanisms. MMF events may be more severe than single mechanism events, or they may differ in characteristics. To facilitate comprehensive risk-informed decision-making to protect against and mitigate the effects of flood events, understanding the hazard contributions from MMFs is important. Nevertheless, conventional probabilistic flood hazard assessment approaches typically focus on individual flood hazard mechanisms. This report is part of a research project funded by the US Nuclear Regulatory Commission (NRC) intended to assist NRC in developing the technical basis for guidance on developing probabilistic estimates of flood hazards for combinations of flood mechanisms. Specifically, the purpose of this report is to document two case studies to illustrate approaches for quantifying MMF hazards for inland and coastal flooding scenarios.

54 ENVIRONMENTAL SCIENCES↗

Singularity variables for missing energy event kinematics

We discuss singularity variables which are properly suited for analyzing the kinematics of events with missing transverse energy at the LHC. We consider six of the simplest event topologies encountered in studies of leptonic W-bosons and top quarks, as well as in SUSY-like searches for new physics with dark matter particles. In each case, we illustrate the general prescription for finding the relevant singularity variable, which in turn helps delineate the visible parameter subspace on which the singularities are located. Our results can be used in two different ways — first, as a guide for targeting the signal-rich regions of parameter space during the stage of discovery, and second, as a sensitive focus point method for measuring the particle mass spectrum after the initial discovery.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Power quality disturbances diagnosis: A 2D densely connected convolutional network framework

The fast and accurate diagnosis of power quality disturbances (PQD) aids in avoiding shutdowns and unnecessary procedures, concerning electric energy distribution systems. As such, a number of techniques have been tested and applied in order to reach this objective. Majority of the techniques applied are two-step based. On the first step, power quality disturbances features are extracted. Second step, considering features extracted, disturbance classification is implemented. Recently, relevant literature has presented data-driven signal processing-based approaches, as deep convolutional neural networks (DCNN), which can implement both processing steps while providing automated recognition of patterns and outliers in data. However, not considered by state-of-art, power quality disturbances are evolving in nature, while all possible regularities might not be represented in the dataset. In this work a 2 Dimension Densely Connected Convolutional Network (2D-DenseNet) framework is presented. Further, a case study with synthetic disturbance events are analyzed. Easy-to-implement formulation, built on the 2D-DenseNet, without hard-to-design parameters, highlight potential aspects for real-life implementation.

42 ENGINEERING↗

Association Between Dispatch Complaint and Critical Prehospital Time Intervals in Suspected Stroke 911 Activations in the National Emergency Medical Services Information System, 2012–2016

Emergency Medical Services can help improve stroke outcomes by recognizing stroke symptoms, establishing response priority for 911 calls, and minimizing prehospital delays. This study examines 911 stroke events and evaluates associations between events dispatched as stroke and critical EMS time intervals. Data from the National Emergency Medical Services Information System, 2012 to 2016, were analyzed. Activations from 911 calls with a primary or secondary provider impression of stroke were included for adult patients transported to a hospital destination. Three prehospital time intervals were evaluated: (1) response time (RT) ≤8 min, (2) on-scene time (OST) ≤15 min, and (3) transport time (TT) ≤12 min. Associations between stroke dispatch complaint and prehospital time intervals were assessed using multivariate regression to estimate adjusted risk ratios (ARR) and 95% confidence intervals (CIs). Approximately 37% of stroke dispatch complaints were identified by EMS as a suspected stroke. Compared to stroke events without a stroke dispatch complaint, median OST was shorter for events with a stroke dispatch (16 min vs. 14 min, respectively). In adjusted analyses, events dispatched as stroke were more likely to meet the EMS time benchmark for OST ≤15 min (OST, 1.20 [1.20–1.21]), but not RT or TT (RT, [1.00–1.01]; TT, 0.95 [0.94–0.95]). Furthermore, our results indicate that dispatcher recognition of stroke symptoms reduces the time spent on-scene by EMS personnel. These findings can inform future EMS stroke education and quality improvement efforts to emphasize dispatcher recognition of stroke signs and symptoms, as EMS dispatchers play a crucial role in optimizing the prehospital response.

59 BASIC BIOLOGICAL SCIENCES↗

Evaluating direct vessel injection accident-event progression of AP1000 and key figures of merit to support the design and development of water-cooled small modular reactors

The passive safety systems (PSSs) within water-cooled reactors are meticulously engineered to function autonomously, requiring no external power source or manual intervention. They depend exclusively on inherent natural forces and the fundamental principles of reactor physics, such as gravity, natural convection, and phase changes, to manage, alleviate, and avert the release of radioactive materials into the environment during accident scenarios like a loss-of-coolant accident (LOCA). PSSs are already integrated into such operating commercial reactors as the Advanced Pressurized Reactor-1000 MWe (AP1000) and the Water-Water Energetic Reactor-1200 MWe (WWER-1200) are adopted in most of the upcoming small modular reactor (SMR) designs. Examples of water-cooled SMR PSSs are the passive emergency core-cooling system (ECCS), passive containment cooling system (PCCS), and passive decay-heat removal system, the designs of which vary based on reactor system-design requirements. However, understanding the accident-event progression and phases of a LOCA is pivotal for adopting a specific PSS for a new SMR design. This study covers the accident-event progression for direct vessel injection (DVI) small-break loss-of-coolant accident (SB-LOCA), associated physics phenomena, knowledge gaps, and important figures of merit (FOMs) that may need to be evaluated and assessed to validate thermal-hydraulics models with an available experimental dataset to support new SMR design and development.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Study of charged particle production at high p T using event topology in pp, p–Pb and Pb–Pb collisions at $\sqrt{s_{NN}}=5.02$ TeV

This letter reports measurements which characterize the underlying event associated with hard scatterings at mid-pseudorapidity (|$η$| < 0.8) in pp, p–Pb and Pb–Pb collisions at centre-of-mass energy per nucleon pair, $\sqrt{s_{NN}}=5.02$ TeV. The measurements are performed with ALICE at the LHC. Different multiplicity classes are defined based on the event activity measured at forward rapidities. The hard scatterings are identified by the leading particle defined as the charged particle with the largest transverse momentum ($p_{T}$) in the collision and having 8 < $p_{T}$ < 15 GeV/c. The $p_{T}$ spectra of associated particles (0.5 < $p_{T}$ < 6 GeV/c) are measured in different azimuthal regions defined with respect to the leading particle direction: toward, transverse, and away. The associated charged particle yields in the transverse region are subtracted from those of the away and toward regions. The remaining jet-like yields are reported as a function of the multiplicity measured in the transverse region. The measurements show a suppression of the jet-like yield in the away region and an enhancement of high-$p_{T}$ associated particles in the toward region in central Pb–Pb collisions, as compared to minimum-bias pp collisions. These observations are consistent with previous measurements that used two-particle correlations, and with an interpretation in terms of parton energy loss in a high-density quark gluon plasma. These yield modifications vanish in peripheral Pb–Pb collisions and are not observed in either high-multiplicity pp or p–Pb collisions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

eCoral: How Electrolysis Could Restore Seawater Conditions Ideal for Coral Reefs

Coral reefs suffer from climate change, including long-term ocean acidification (OA) and warming and short-term bleaching, tropical storms, and pollution events, all of which are increasing in frequency and severity. It is urgent yet unclear how to intervene to save coral reefs. Reversal of the ocean pH to preindustrial levels could restore coral reefs to their preindustrial growth rates; however, strategies to reverse OA on environmentally relevant scales have not been established. Anecdotally, electrolysis seems to help coral reefs recover from acidification and short-term events, but few uncontrolled studies support such claims. Here, using two independent continuum simulation approaches (COMSOL and CrunchFlow), we show the effect of electrolysis on seawater chemistry relevant to coral reef survival and growth. We conclude that near the negative electrodes, the cathodes, seawater pH, supersaturation, and carbonate concentration all increase significantly. Electrolysis of seawater, therefore, can be used to restore preindustrial ocean conditions locally to save coral reefs, an approach termed eCoral here. We anticipate these simulation results to be the starting point for controlled experiments to test whether seawater electrolysis promotes coral reef growth and restoration, as these simulations predict.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The complex circumstellar environment of supernova 2023ixf

The early evolution of a supernova (SN) can reveal information about the environment and the progenitor star. When a star explodes in vacuum, the first photons to escape from its surface appear as a brief, hours-long shock-breakout flare, followed by a cooling phase of emission. However, for stars exploding within a distribution of dense, optically thick circumstellar material (CSM), the first photons escape from the material beyond the stellar edge and the duration of the initial flare can extend to several days, during which the escaping emission indicates photospheric heating. Early serendipitous observations that lacked ultraviolet (UV) data were unable to determine whether the early emission is heating or cooling and hence the nature of the early explosion event. Here, in this study, we report UV spectra of the nearby SN 2023ixf in the galaxy Messier 101 (M101). Using the UV data as well as a comprehensive set of further multiwavelength observations, we temporally resolve the emergence of the explosion shock from a thick medium heated by the SN emission. We derive a reliable bolometric light curve that indicates that the shock breaks out from a dense layer with a radius substantially larger than typical supergiants.

79 ASTRONOMY AND ASTROPHYSICS↗