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At least 1,531 records · Page 85

Reimagine fire science for the anthropocene

Fire is an integral component of ecosystems globally and a tool that humans have harnessed for millennia. Altered fire regimes are a fundamental cause and consequence of global change, impacting people and the biophysical systems on which they depend. As part of the newly emerging Anthropocene, marked by human-caused climate change and radical changes to ecosystems, fire danger is increasing, and fires are having increasingly devastating impacts on human health, infrastructure, and ecosystem services. Increasing fire danger is a vexing problem that requires deep transdisciplinary, trans-sector, and inclusive partnerships to address. Here, we outline barriers and opportunities in the next generation of fire science and provide guidance for investment in future research. We synthesize insights needed to better address the long-standing challenges of innovation across disciplines to (i) promote coordinated research efforts; (ii) embrace different ways of knowing and knowledge generation; (iii) promote exploration of fundamental science; (iv) capitalize on the “firehose” of data for societal benefit; and (v) integrate human and natural systems into models across multiple scales. Fire science is thus at a critical transitional moment. We need to shift from observation and modeled representations of varying components of climate, people, vegetation, and fire to more integrative and predictive approaches that support pathways toward mitigating and adapting to our increasingly flammable world, including the utilization of fire for human safety and benefit. Only through overcoming institutional silos and accessing knowledge across diverse communities can we effectively undertake research that improves outcomes in our more fiery future.

54 ENVIRONMENTAL SCIENCES↗

On the position of the near-earth neutral sheet - A comparison of magnetic model predictions with empirical formulas

A detailed comparison of the near-earth neutral sheet position according to several approximations has been made. In particular, two empirical formulas for the neutral sheet location, recently derived from AMPTE/CCE data, have been compared with the corresponding positions derived from Tsyganenko's magnetic field models. Cylindrical coordinates referenced to the geodipole have been used, and the position of the neutral sheet has been identified by the reversal of the radial component of the magnetic field. The analysis reveals that, in the region X(GSM) = -9 to -5 earth radii, abs. value of Y(GSM) not greater than 5 earth radii, close agreement exists between the empirical formulas and the Tsyganenko models. Furthermore, the Tsyganenko models provide a representation for the neutral sheet position in the transition region between near-earth and distant tail models.

Peredo, Mauricio↗

Nonequilibrium ionization effects in asymmetrically heated loops

The effects of nonequilibrium ionization on magnetic loop models with a steady siphon flow that is driven by a nonuniform heating rate are investigated. The model developed by Mariska (1988) to explain the observed redshifts of transition region emission lines is examined, and the number densities of the ions of carbon and oxygen along the loop are computed, with and without the approximation of ionization equilibrium. Considerable deviations from equilibrium were found. In order to determine the consequences of these nonequilibrium effects on the characteristics of the EUV emission from the loop plasma, the profiles and wavelength positions of all the important emission lines due to carbon and oxygen were calculated. The calculations are in broad agreement with Mariska's conclusions, although they show a significant diminution of the Doppler shifts, as well as modifications to the line widths. It is concluded that the inclusion of nonequilibrium effects make it more difficult to reproduce the observed characteristics of the solar transition region by means of the asymmetric-heating models.

Spadaro, D.↗

Investigating the influence of latent lifestyles on productive travels: Insights into designing autonomous transit system

As a special case of multitasking, travel-based multitasking typically refers to conducting a set of in-vehicle activities while traveling. Travel-based multitasking has an indisputable influence on offering a pleasant travel experience to transit users during their rides, given that they can use their travel time to perform desirable activities and gain benefits in various form. For instance, the in-activities could help the rider free up time from his/her schedule for the day (i.e., a worthwhile use of travel time). In this study, we investigate how the worthwhileness of a travel-based multitasking could be under the influence of: (1) the transit user’s lifestyle, and (2) socio-demographics, and (3) the characteristics of the transit trip. Towards this, we conducted an intercept survey focusing on the transit trips in the Chicago metropolitan area and analyzed it using latent class modeling approach. Per the results, two classes of transit users could be identified: (1) worthwhileness seekers, productively travelers and (2) leisure seekers, occasional worthwhile travelers. The results also suggest travel time, waiting time and walking distance to the transit station, and the set of in-vehicle activities as significant predictors of worthwhile use of travel time. Finally, the findings provide insights to policymakers for improving public transit systems in the current form, as well as designing an autonomous mobility system as the future form of public transit.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Structural visualization of transcription activated by a multidrug-sensing MerR family regulator

Bacterial RNA polymerase (RNAP) holoenzyme initiates transcription by recognizing the conserved –35 and –10 promoter elements that are optimally separated by a 17-bp spacer. The MerR family of transcriptional regulators activate suboptimal 19–20 bp spacer promoters in response to myriad cellular signals, ranging from heavy metals to drug-like compounds. The regulation of transcription by MerR family regulators is not fully understood. Here we report one crystal structure of a multidrug-sensing MerR family regulator EcmrR and nine cryo-electron microscopy structures that capture the EcmrR-dependent transcription process from promoter opening to initial transcription to RNA elongation. These structures reveal that EcmrR is a dual ligand-binding factor that reshapes the suboptimal 19-bp spacer DNA to enable optimal promoter recognition, sustains promoter remodeling to stabilize initial transcribing complexes, and finally dissociates from the promoter to reverse DNA remodeling and facilitate the transition to elongation. Our findings yield a comprehensive model for transcription regulation by MerR family factors and provide insights into the transition from transcription initiation to elongation.

59 BASIC BIOLOGICAL SCIENCES↗

Hidden-Markov-Model Analysis Of Telemanipulator Data

Mathematical model and procedure based on hidden-Markov-model concept undergoing development for use in analysis and prediction of outputs of force and torque sensors of telerobotic manipulators. In model, overall task broken down into subgoals, and transition probabilities encode ease with which operator completes each subgoal. Process portion of model encodes task-sequence/subgoal structure, and probability-density functions for forces and torques associated with each state of manipulation encode sensor signals that one expects to observe at subgoal. Parameters of model constructed from engineering knowledge of task.

Hannaford, Blake↗

Monte Carlo simulations of neutrino and charged lepton propagation in the Earth with nuPyProp

An accurate modeling of neutrino flux attenuation and the distribution of leptons they produce in transit through the Earth is an essential component to determine neutrino flux sensitivities of underground, sub-orbital and space-based detectors. Through neutrino oscillations over cosmic distances, astrophysical neutrino sources are expected to produce nearly equal fluxes of electron, muon and tau neutrinos. Of particular interest are tau neutrinos that interact in the Earth at modest slant depths to produce leptons. Some leptons emerge from the Earth and decay in the atmosphere to produce extensive air showers. Future balloon-borne and satellite-based opticalCherenkov neutrino telescopes will be sensitive to upward air showers from tau neutrino induced lepton decays. We present nuPyProp, a python code that is part of the nuSpaceSim package. nuPyProp generates look-up tables for exit probabilities and energy distributions for (see paper for proper equation) propagation in the Earth. This flexible code runs with either stochastic or continuous electromagnetic energy losses for the lepton transit through the Earth. Current neutrino cross section models and energy loss models are included along with templates for user input of other models. Results from nuPyProp are compared with other recent simulation packages for neutrino and charged lepton propagation. Sources of modeling uncertainties are described and quantified.

Yosui Akaike↗

Do people spend travel time the way they think they would? a comparative study of generic and trip-specific travel time allocation using hybrid multiple discrete continuous (MDC) framework

Unlike driving alone, public transportation allows one to engage in extraneous activities while traveling – often referred to as travel-based multitasking. Research involving travel-based multitasking often relies on either generic (i.e. not related to an actual trip) or revealed (i.e. related to an executed trip) data. The data collected for this study provided a unique opportunity to compare the generic and trip-specific preferences while traveling on public transportation. To this end, the study develops two integrated choice and latent variable models with multiple discrete-continuous (MDC) kernels to simultaneously model the activity selection and the time allocation for generic and trip-specific data, respectively. According to the results the trip-specific data could identify more nuances in the travel-based multitasking behavior than the generic data. Finally, the heterogeneity identified by the developed models will be helpful for the transit operators in providing appropriate facilities (e.g. internet access, reading lights) along various transit corridors.

99 GENERAL AND MISCELLANEOUS↗

Marginalizing Instrument Systematics in HST WFC3 Transit Light Curves

Hubble Space Telescope (HST) Wide Field Camera 3 (WFC3) infrared observations at 1.1-1.7 microns probe primarily the H2O absorption band at 1.4 microns, and have provided low-resolution transmission spectra for a wide range of exoplanets. We present the application of marginalization based on Gibson to analyze exoplanet transit light curves obtained from HST WFC3 to better determine important transit parameters such as "ramp" probability (R (sub p)) divided by "ramp" total (R (sub asterisk)), which are important for accurate detections of H2O. We approximate the evidence, often referred to as the marginal likelihood, for a grid of systematic models using the Akaike Information Criterion. We then calculate the evidence-based weight assigned to each systematic model and use the information from all tested models to calculate the final marginalized transit parameters for both the band-integrated and spectroscopic light curves to construct the transmission spectrum. We find that a majority of the highest weight models contain a correction for a linear trend in time as well as corrections related to HST orbital phase. We additionally test the dependence on the shift in spectral wavelength position over the course of the observations and find that spectroscopic wavelength shifts delta (sub lambda) times lambda) best describe the associated systematic in the spectroscopic light curves for most targets while fast scan rate observations of bright targets require an additional level of processing to produce a robust transmission spectrum. The use of marginalization allows for transparent interpretation and understanding of the instrument and the impact of each systematic evaluated statistically for each data set, expanding the ability to make true and comprehensive comparisons between exoplanet atmospheres.

Wakeford, H. R.↗

Implementing belowground controls on nutrient uptake in ELMv2-SPRUCE improves representation of a boreal peatland ecosystem

Boreal peatlands store 13 %–32 % of the global soil carbon (C) stock, a service dependent on plant-mycorrhizal fungi associations. In these nutrient poor systems, ectomycorrhizal and ericoid mycorrhizal fungi supply up to >80 % of the nutrient requirements of their plant hosts, partly with mined nitrogen (N) and phosphorus (P) from soil organic matter that are otherwise inaccessible to plants. Despite the ecological significance, mycorrhizal associations are only represented in a few land surface or ecosystem models. We modify the peatland branch of version 2 of the Energy Exascale Earth System Land Model (ELMv2-SPRUCE) to replace the default photosynthesis-driven inorganic N and P (NP) uptake process with a more realistic representation of the process via three pathways: (1) direct inorganic NP uptake by uncolonized fine roots, (2) indirect inorganic NP acquisition and (3) indirect NP acquisition from organic sources by mycorrhizal roots. We systematically evaluated the performance of the default and modified models with field observations from a whole ecosystem warming and carbon dioxide fertilization experimental site: Spruce and Peatland Responses Under Changing Environment (SPRUCE), in northern Minnesota, USA. The modified model reduces the underestimation of the growth response of shrubs in the default model to warming from 40 %–80 % to 17 %–35 % and reduces the overall relative absolute error on C fluxes from 1.61 to 1.54 in calibration. Improvements on modeled shrub growths and shrub-moss community net ecosystem exchanges are also seen in validation. The improved growth response of shrubs to warming is accompanied by several-fold increase in direct inorganic NP uptake and decrease in fungal colonization rate. The modified model simulates a smaller magnitude of transition of the ecosystem from C sink to C source under warming due to alleviation of plant nutrient limitation. Equifinality analysis shows the newly added parameters in the modified model can be constrained by the observed C fluxes. Sensitivity analysis shows the newly added parameters have stronger statistical interactions than the preexisting parameters in the default model. Overall, the modified model is an improvement over the default ELMv2-SPRUCE and will be a useful tool for understanding boreal peatland change.

Wang, Yaoping [Oak Ridge National Laboratory (ORNL↗

EUV spectra from Skylab /1175-1940 A/ - Mass motions in the transition zone in regions of solar activity

The profiles of spectral lines in the 1100-2000-A range emitted by transition-zone ions in regions of solar activity are discussed. The data were recorded by the NRL spectrograph on Skylab. At the spatial resolution of the Skylab spectrograph (2 x 60 arcsec), it is shown that the line profiles result from the superposed emission of a number of physically distinct regions at different electron densities and with different mass motions. Although high densities are found for some surgelike phenomena at transition-zone temperatures, the densities can also be comparable to normal active-region densities. Line profiles, as well as spectral line intensities, must be considered if meaningful theoretical models of dynamic activity in the transition zone are to be constructed.

Doschek, G. A.↗

High pressure phase transitions in tetrahedrally coordinated semiconducting compounds

New experimental results are reported for structural transitions at high pressure in several III-V compounds and two II-VI compounds. These data, together with earlier results, are then compared with the predictions of model calculations of Van Vechten. Experimental transition pressures are often at variance with calculated values. However, his calculation assumes that the high pressure phase is metallic, with the beta-Sn structure. The present results show that several compounds assume an ionic NaCl structure at high pressure, while others have neither the beta-Sn nor NaCl structure.

Yu, S. C.↗

Analyzing Tabular and State-Transition Requirements Specifications in PVS

We describe PVS's capabilities for representing tabular specifications of the kind advocated by Parnas and others, and show how PVS's Type Correctness Conditions (TCCs) are used to ensure certain well-formedness properties. We then show how these and other capabilities of PVS can be used to represent the AND/OR tables of Leveson and the Decision Tables of Sherry, and we demonstrate how PVS's TCCs can expose and help isolate errors in the latter. We extend this approach to represent the mode transition tables of the Software Cost Reduction (SCR) method in an attractive manner. We show how PVS can check these tables for well-formedness, and how PVS's model checking capabilities can be used to verify invariants and reachability properties of SCR requirements specifications, and inclusion relations between the behaviors of different specifications. These examples demonstrate how several capabilities of the PVS language and verification system can be used in combination to provide customized support for specific methodologies for documenting and analyzing requirements. Because they use only the standard capabilities of PVS, users can adapt and extend these customizations to suit their own needs. Those developing dedicated tools for individual methodologies may find these constructions in PVS helpful for prototyping purposes, or as a useful adjunct to a dedicated tool when the capabilities of a full theorem prover are required. The examples also illustrate the power and utility of an integrated general-purpose system such as PVS. For example, there was no need to adapt or extend the PVS model checker to make it work with SCR specifications described using the PVS TABLE construct: the model checker is applicable to any transition relation, independently of the PVS language constructs used in its definition.

Owre, Sam↗

The Artificial Scientist: in-Transit Machine Learning of Plasma Simulations

Large-scale simulations or scientific experiments produce petabytes of data per run. This poses massive challenges for I/O and storage when scientific analysis workflows are run manually offline. Unsupervised deep learning-based techniques to extract patterns and non-linear relations from these large amounts of data provide a way to build scientific understanding from raw data, reducing the need for manual pre-selection of analysis steps, but require exascale compute and memory to process the full dataset available. In this paper, we demonstrate a heterogeneous streaming workflow in which plasma simulation data is streamed directly to a Machine Learning (ML) application training a model on the simulation data in-transit, completely circumventing the capacity-constrained filesystem bottleneck. This workflow employs openPMD to provide a high level interface to describe scientific data and also uses ADIOS2, to transfer volumes of data that exceed the capabilities of the filesystem. We employ experience replay to avoid catastrophic forgetting in learning from this non-steady state process in a continual manner and adapt it to improve model convergence while learning in-transit. As a proof-of-concept, we approach the ill-posed inverse problem of predicting particle dynamics from radiation in a particle-incell (PIConGPU) simulation of the Kelvin-Helmholtz instability (KHI). We detail hardware-software co-design challenges as we scale PIConGPU to full Frontier, the Top-1 system as of June 2024 Top500 list.

Kelling, Jeffrey [Helmholtz-Zentrum Dresden Rossen↗

Large-eddy simulation of transitional channel flow

A large-eddy simulation (LES) of transition in plane channel flow was carried out. The LES results were compared with those of a fine direct numerical simulation (DNS), and with those of a coarse DNS that uses the same mesh as the LES, but does not use a residual stress model. While at the early stages of transition, LES and coarse DNS give the same results: the presence of the residual stress model was found to be necessary to predict accurately mean velocity and Reynolds stress profiles during the late stages of transition (after the second spike stage). The evolution of single Fourier modes is also predicted more accurately by the LES than by the DNS. As small scales are generated, the dissipative character of the residual stress starts to reproduce correctly the energy cascade. As transition progresses, the flow approaches its fully developed turbulent state, the subgrid scales tend towards equilibrium, and the model becomes more accurate.

Piomelli, Ugo↗

Probabilistic Modeling of Climate Change Impacts on Renewable Energy and Storage Requirements for NM's Energy Transition Act (SAND Report)

This report provides a study of the potential impacts of climate change on intermittent renewable energy resources, battery storage, and resource adequacy in Public Service Company of New Mexico’s Integrated Resource Plan for 2020 – 2040. Climate change models and available data were first evaluated to determine uncertainty and potential changes in solar irradiance, temperature, and wind speed in NM in the coming decades. These changes were then implemented in solar and wind energy models to determine impacts on renewable energy resources in NM. Results for the extreme climate-change scenario show that the projected wind power may decrease by ~13% due to projected decreases in wind speed. Projected solar power may decrease by ~4% due to decreases in irradiance and increases in temperature in NM. Uncertainty in these climate-induced changes in wind and solar resources was accommodated in probabilistic models assuming uniform distributions in the annual reductions in solar and wind resources. Uncertainty in battery storage performance was also evaluated based on increased temperature, capacity fade, and degradation in round-trip efficiency. The hourly energy balance was determined throughout the year given uncertainties in the renewable energy resources and energy storage. The loss of load expectation (LOLE) was evaluated for the 2040 No New Combustion portfolio and found to increase from 0 days/year to a median value of ~2 days/year due to potential reductions in renewable energy resources and battery storage performance and capacity. A rank-regression analyses revealed that battery round-trip efficiency was the most significant parameter that impacted LOLE, followed by solar resource, wind resource, and battery fade. An increase in battery storage capacity to ~25,000 – 30,000 MWh from a baseline value of ~14,000 MWh was required to reduce the median value of LOLE to ~0.2 days/year with consideration of potential climate impacts and battery degradation.

54 ENVIRONMENTAL SCIENCES↗

Replica wormhole and information retrieval in the SYK model coupled to Majorana chains

Motivated by recent studies of the information paradox in (1+1)-D anti-de Sitter spacetime with a bath described by a (1+1)-D conformal field theory, we study the dynamics of second Ŕenyi entropy of the Sachdev-Ye-Kitaev (SYK) model (χ) coupled to a Majorana chain bath (ψ). The system is prepared in the thermofield double (TFD) state and then evolved by HL + HR. For small system-bath coupling, we find that the second Rényi entropy $S^(2)_{χL,χR}$ of the SYK model undergoes a first order transition during the evolution. In the sense of holographic duality, the long-time solution corresponds to a “replica wormhole”. The transition time corresponds to the Page time of a black hole coupled to a thermal bath. We further study the information scrambling and retrieval by introducing a classical control bit, which controls whether or not we add a perturbation in the SYK system. The mutual information between the bath and the control bit shows a positive jump at the Page time, indicating that the entanglement wedge of the bath includes an island in the holographic bulk.

1/N Expansion↗

Characterizing the flux effect on the irradiation embrittlement of reactor pressure vessel steels using machine learning

In-service exposure to high-energy neutrons embrittles reactor pressure vessel (RPV) steels. An increase in the yield stress (Δσ y ) results in a corresponding increase in the brittle to ductile transition temperature (ΔT c ). Most existing models underpredict ΔT c at higher fluence following accelerated irradiations in test reactors. High fluence, up to 10 20 n/cm 2 in some cases, will be reached over extended RPV vessel operation of 80 years, or more, at low service flux. Embrittlement has been extensively studied in accelerated, higher flux test reaction irradiations. However, the use of test reactor data naturally raises the question of flux effects. Here, this study used a machine learning approach trained on a set of hardening data, covering a wide range of flux, fluence, and steel compositions to determine the interactive effects of both irradiation and material variables on Δσ y . The analysis included machine learning-based cross-plots of the variable dependence of Δσ y for six core steels (i.e., CM6, LC, LD, LG, LH, and LI), with controlled differences in their Cu and Ni contents. A primary objective is to evaluate an effective to actual fluence (Φt e /Φt) ratio, as a function of flux, fluence, and steel composition. This is information critical to properly use intermediate flux-high fluence data in calibrating a low flux-high fluence embrittlement model. The predicted Φt e /Φt is reasonably consistent with estimates previously derived from a physics-based solute recombination trap model.

36 MATERIALS SCIENCE↗