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At least 1,783 records · Page 99

Star formation in self-gravitating turbulent fluids

We present a model of star formation in self-gravitating turbulent gas in which the turbulent velocity, v{sub T}, is a dynamical variable and is adiabatically heated by the collapse. The theory predicts the run of density, infall, and turbulent velocity and the rate of star formation in compact massive clouds. The adiabatic heating ensures that the turbulent pressure is dynamically important at all radii. The system evolves toward a coherent spatial structure with a fixed run of density, ρ(r,t)→ρ(r); mass flows through this structure onto the central star or star cluster. We define the sphere of influence of the accreted matter by m{sub ∗}=M{sub g}(r{sub ∗}), where m{sub *} is the stellar plus disk mass in the nascent star cluster and M{sub g}(r) is the gas mass inside radius r. Both v{sub T} and the infall velocity, |u{sub r}|, decrease with decreasing r for r>r{sub ∗}; v{sub T}(r)∼r{sup p}, the size–line-width relation, with p≈0.2−0.3, explaining the observation that Larson’s Law is altered in massive star-forming regions. The infall velocity is generally smaller than the turbulent velocity at r>r{sub ∗}. For r<r{sub ∗}, the infall and turbulent velocities are again similar, and both increase with decreasing r as r{sup −1/2}, with a magnitude about half of the free-fall velocity. The accreted (stellar) mass grows superlinearly with time, M-dot {sub ∗}=ϕM{sub cl}(t/τ{sub ff}){sup 2}, with ϕ a dimensionless number somewhat less than unity, M{sub cl} the clump mass, and τ{sub ff} the free-fall time of the clump. We suggest that small values of p can be used as a tracer of convergent collapsing flows.

79 ASTRONOMY AND ASTROPHYSICS↗

From disorganized data to emergent dynamic models: Questionnaires to partial differential equations

Starting with sets of disorganized observations of spatially varying and temporally evolving systems, obtained at different (also disorganized) sets of parameters, we demonstrate the data-driven derivation of parameter dependent, evolutionary partial differential equation (PDE) models capable of generating the data. This tensor type of data is reminiscent of shuffled (multidimensional) puzzle tiles. The independent variables for the evolution equations (their “space” and “time”) as well as their effective parameters are all emergent , i.e. determined in a data-driven way from our disorganized observations of behavior in them. We use a diffusion map based questionnaire approach to build a smooth parametrization of our emergent space/time/parameter space for the data. This approach iteratively processes the data by successively observing them on the “space,” the “time” and the “parameter” axes of a tensor. Once the data become organized, we use machine learning (here, neural networks) to approximate the operators governing the evolution equations in this emergent space. Our illustrative examples are based (i) on a simple advection–diffusion model; (ii) on a previously developed vertex-plus-signaling model of Drosophila embryonic development; and (iii) on two complex dynamic network models (one neuronal and one coupled oscillator model) for which no obvious smooth embedding geometry is known a priori. This allows us to discuss features of the process like symmetry breaking, translational invariance, and autonomousness of the emergent PDE model, as well as its interpretability.

generative models↗

Depot-Based Vehicle Data for National Analysis of Medium- and Heavy-Duty Electric Vehicle Charging

Medium- and heavy-duty vehicles (MHDVs) are a major source of greenhouse gases and local criteria air pollutants. Electrifying MHDVs may reduce these harmful emissions, which disproportionately impact disadvantaged communities. Due to their relatively high per-vehicle energy needs, consistent fleet operations, and frequent colocation of multiple vehicles at depots, MHDVs may have more spatially and temporally concentrated charging demands than light-duty passenger electric vehicles. That charging concentration means their electrification may require careful advance planning and coordination to manage potential impacts to the electrical grid via charge management or infrastructure upgrades. However, MHDV duty cycles and parking schedules are highly variable across vocations of operation, and there is a shortage of nationally representative, vocationally diverse public data describing typical MHDV operations. This report summarizes the methodology - designed with national representativeness in mind - used to create a new set of data describing typical daily driving distances, dwell durations, and normalized electric vehicle depot charging load curves for MHDVs. The dataset reflects the subset of MHDV operating patterns that may originate from a consistent depot each day and rely on the same depot for charging. In addition to trucks with depot-centric vocational patterns, the data describes operations of transit buses and school buses, each with a depot-centric focus. The dataset is available to the public and suitable for national analysis. It can inform research, infrastructure planning, and policymaking regarding the electrification of MHDVs.

33 ADVANCED PROPULSION SYSTEMS↗

Method of and apparatus for thermomagnetically processing a workpiece

A method of thermomagnetically processing a material includes disposing a workpiece within a bore of a magnet; exposing the workpiece to a magnetic field of at least about 1 Tesla generated by the magnet; and, while exposing the workpiece to the magnetic field, applying heat energy to the workpiece at a plurality of frequencies to achieve spatially-controlled heating of the workpiece. An apparatus for thermomagnetically processing a material comprises: a high field strength magnet having a bore extending therethrough for insertion of a workpiece therein; and an energy source disposed adjacent to an entrance to the bore. The energy source is an emitter of variable frequency heat energy, and the bore comprises a waveguide for propagation of the variable frequency heat energy from the energy source to the workpiece.

36 MATERIALS SCIENCE↗

Imaging spectroscopy algorithms for mapping canopy foliar chemical and morphological traits and their uncertainties

A major goal of remote sensing is the development of generalizable algorithms to repeatedly and accurately map ecosystem properties across space and time. Imaging spectroscopy has great potential to map vegetation traits that cannot be retrieved from broadband spectral data, but rarely have such methods been tested across broad regions. Here we illustrate a general approach for estimating key foliar chemical and morphological traits through space and time using NASA's Airborne Visible/Infrared Imaging Spectrometer (AVIRIS-Classic). We apply partial least squares regression (PLSR) to data from 237 field plots within 51 images acquired between 2008 and 2011. Using a series of 500 randomized 50/50 subsets of the original data, we generated spatially explicit maps of seven traits (leaf mass per area (M area ), percentage nitrogen, carbon, fiber, lignin, and cellulose, and isotopic nitrogen concentration, δ 15 N) as well as pixel-wise uncertainties in their estimates based on error propagation in the analytical methods. Both Marea and %N PLSR models had a R 2 > 0.85. Root mean square errors (RMSEs) for both variables were less than 9% of the range of data. Fiber and lignin were predicted with R 2 > 0.65 and carbon and cellulose with R 2 > 0.45. Although R 2 of %C and cellulose were lower than Marea and %N, the measured variability of these constituents (especially %C) was also lower, and their RMSE values were beneath 12% of the range in overall variability. Model performance for δ 15 N was the lowest (R 2 = 0.48, RMSE = 0.95‰), but within 15% of the observed range. The resulting maps of chemical and morphological traits, together with their overall uncertainties, represent a first-of-its-kind approach for examining the spatiotemporal patterns of forest functioning and nutrient cycling across a broad range of temperate and sub-boreal ecosystems. These results offer an alternative to categorical maps of functional or physiognomic types by providing non-discrete maps (i.e., on a continuum) of traits that define those functional types. A key contribution of this work is the ability to assign retrieval uncertainties by pixel, a requirement to enable assimilation of these data products into ecosystem modeling frameworks to constrain carbon and nutrient cycling projections.

54 ENVIRONMENTAL SCIENCES↗

Anomalous cluster detection in spatiotemporal meteorological fields

Finding anomalous regions in spatiotemporal climate data is an important problem with a need for greater accuracy. The collective and contextual nature of anomalies (e.g., heat waves) coupled with the real‐valued, seasonal, multimodal, highly correlated, and gridded nature of climate variable observations poses a multitude of challenges. Existing anomaly detection methods have limitations in the specific setting of real‐valued areal spatiotemporal data. In this paper, we develop a method for extreme event detection in meteorological datasets that follows from well known distribution‐based anomaly detection approaches. The method models spatial and temporal correlations explicitly through a piecewise parametric assumption and generalizes the Mahalanobis distance across distributions of different dimensionalities. The result is an effective method to mine contiguous spatiotemporal anomalous regions from meteorological fields which improves upon the current standard approach in climatology. The proposed method has been evaluated on a real global surface temperature dataset and validated using historical records of extreme events.

Ramachandra, Bharathkumar↗

Effects of turbulent flow regime on perforated plate stabilized piloted lean premixed flames

An experimental study of the effects of turbulent flow regime on the flame structure is conducted by using perforated-plate-stabilized, hydrogen-piloted, lean premixed methane/air turbulent flames. The underlying turbulent flow field was investigated using two-dimensional three-component particle imaging velocimetry (2D3C-PIV) with two perforated plates of different blockage ratios. The flow data allowed a separation of the turbulent flow regime into axial velocity stream dominated and vortex dominated flows. A plate with 62% blockage ratio was used to establish the stream-dominated flow regime and another with 86% blockage ratio was used to establish the vortex-dominated flow regime. OH laser-induced fluorescence was used to study the effects of the turbulent flow regime on the mean progress variable, flame brush thickness, flame surface density, and global consumption speed. In comparison with the stream-dominated flow, the vortex-dominated flow makes a wider and shorter flame. Also, the vortex-dominated flow has a thicker horizontal flame brush and a thinner longitudinal flame brush. Especially, the spatial variation of the horizontal flame brush thickness for the vortex-dominated flow does not follow the turbulent diffusion theory. The vortex-dominated flow shows a relatively constant flame surface density and the stream-dominated flow shows a decreasing flame surface density along the streamwise direction. The flame surface density for the vortex-dominated flow is higher than the one for the stream-dominated flow. Lastly, the vortex-dominated turbulent flow shows a much higher consumption speed in comparison with that of the stream-dominated turbulent flow with identical velocity fluctuation levels.

42 ENGINEERING↗

A low-rank control variate for multilevel Monte Carlo simulation of high-dimensional uncertain systems

Multilevel Monte Carlo (MLMC) is a recently proposed variation of Monte Carlo (MC) simulation that achieves variance reduction by simulating the governing equations on a series of spatial (or temporal) grids with increasing resolution. Instead of directly employing the fine grid solutions, MLMC estimates the expectation of the quantity of interest from the coarsest grid solutions as well as differences between each two consecutive grid solutions. When the differences corresponding to finer grids become smaller, hence less variable, fewer MC realizations of finer grid solutions are needed to compute the difference expectations, thus leading to a reduction in the overall work. Here this paper presents an extension of MLMC, referred to as multilevel control variates (MLCV), where a low-rank approximation to the solution on each grid, obtained primarily based on coarser grid solutions, is used as a control variate for estimating the expectations involved in MLMC. Cost estimates as well as numerical examples are presented to demonstrate the advantage of this new MLCV approach over the standard MLMC when the solution of interest admits a low-rank approximation and the cost of simulating finer grids grows fast.

97 MATHEMATICS AND COMPUTING↗

Evidence of Abrupt Transitions Between Sea Ice Dynamical Regimes in the East Greenland Marginal Ice Zone

Sea ice modulates the energy exchange between the atmosphere and the ocean through its kinematics. Marginal ice zone (MIZ) dynamics are complex and are not well resolved in routine observations. Here, we investigate sea ice dynamics in the Greenland Sea MIZ using in situ and remote sensing Lagrangian drift datasets. These datasets provide a unique view into ice dynamics spanning spatial scales. We find evidence of tidal currents strongly affecting sub-daily ice motion. Velocity anomalies show abrupt transitions aligned with gradients in seafloor topography, indicating changes in ocean currents. Remote-sensed ice floe trajectories derived from moderate resolution satellite imagery provide a view of small-scale variability across the Greenland continental shelf. Ice floe trajectories reveal a west-east increasing velocity gradient imposed by the East Greenland Current, with maximum velocities aligned along the continental shelf edge. These results highlight the importance of small scale ocean variability for ice dynamics in the MIZ.

54 ENVIRONMENTAL SCIENCES↗

Nanoscale ultrafast lattice modulation with a free-electron laser

Ultrafast optical laser-based techniques have enabled the probing of atomistic processes at their intrinsic temporal scales with femto- and attosecond resolution. However, the long wavelengths of optical lasers have prevented their interrogation and manipulation with nanoscale spatial specificity. Advances in hard X-ray free-electron lasers have enabled progress in developing X-ray transient-grating spectroscopy, a technique that aims to coherently control elementary excitations with nanoscale X-ray standing waves. Thus far, the realization of this technique at the nanoscale has been a challenge. Here we demonstrate X-ray transient-grating spectroscopy with spatial periods of the order of 10 nm via the subfemtosecond synchronization of two hard X-ray pump pulses at a precisely controlled crossing angle. This creates a thermal grating and preferentially excites coherent longitudinal acoustic phonon modes with the transient-grating wavevector. On probing with a third, variably delayed, X-ray pulse with the same photon energy, time-and-wavevector-resolved measurements of the modulation of the induced scattering intensity provide evidence of ballistic thermal transport at nanometre scales. Finally, these results highlight the potential of X-ray transient gratings as a powerful platform for studying nanoscale transport in condensed matter and the coherent control of nanoscale dynamics.

nonlinear optics↗

A mapped dataset of surface ocean acidification indicators in large marine ecosystems of the United States

Mapped monthly data products of surface ocean acidification indicators from 1998 to 2022 on a 0.25° by 0.25° spatial grid have been developed for eleven U.S. large marine ecosystems (LMEs). The data products were constructed using observations from the Surface Ocean CO 2 Atlas, co-located surface ocean properties, and two types of machine learning algorithms: Gaussian mixture models to organize LMEs into clusters of similar environmental variability and random forest regressions (RFRs) that were trained and applied within each cluster to spatiotemporally interpolate the observational data. The data products, called RFR-LMEs, have been averaged into regional timeseries to summarize the status of ocean acidification in U.S. coastal waters, showing a domain-wide carbon dioxide partial pressure increase of 1.4 ± 0.4 μatm yr -1 and pH decrease of 0.0014 ± 0.0004 yr -1 . RFR-LMEs have been evaluated via comparisons to discrete shipboard data, fixed timeseries, and other mapped surface ocean carbon chemistry data products. Regionally averaged timeseries of RFR-LME indicators are provided online through the NOAA National Marine Ecosystem Status web portal.

54 ENVIRONMENTAL SCIENCES↗

Diffusion-induced periodic transition between oscillatory modes in amplitude-modulated patterns

We study amplitude-modulated waves, e.g., wave packets in one dimension, overtarget spirals and superspirals in two dimensions, under mixed-mode oscillatory conditions in a three-variable reaction-diffusion model. New transition zones, not seen in the homogeneous system, are found, in which periodic transitions occur between local 1{sup N−1} and 1{sup N} oscillations. Amplitude-modulated complex patterns result from periodic transition between (N − 1)-armed and N-armed waves. Spatial recurrence rates provide a useful guide to the stability of these modulated patterns.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Disentangling the drivers of non-stationarity in tree growth

Tree-ring chronologies are an invaluable data source that provides insight into the ecology and physiology of forests across broad spatial and temporal scales. Furthermore, these data have a foundation in paleoclimatic research and have been used for decades to reconstruct climate, fire and other disturbances for several centuries to millennia into the past. Contemporary ecological studies have also used growth data to examine the responses of trees to environmental variability or biotic and abiotic stressors.

59 BASIC BIOLOGICAL SCIENCES↗

Modeling and forecasting the distribution of Vibrio vulnificus in Chesapeake Bay

The aim is to construct statistical models to predict the presence, abundance and potential virulence of Vibrio vulnificus in surface waters. A variety of statistical techniques were used in concert to identify water quality parameters associated with V. vulnificus presence, abundance and virulence markers in the interest of developing strong predictive models for use in regional oceanographic modeling systems. A suite of models are provided to represent the best model fit and alternatives using environmental variables that allow them to be put to immediate use in current ecological forecasting efforts. Conclusions: Environmental parameters such as temperature, salinity and turbidity are capable of accurately predicting abundance and distribution of V. vulnificus in Chesapeake Bay. Forcing these empirical models with output from ocean modeling systems allows for spatially explicit forecasts for up to 48 h in the future. This study uses one of the largest data sets compiled to model Vibrio in an estuary, enhances our understanding of environmental correlates with abundance, distribution and presence of potentially virulent strains and offers a method to forecast these pathogens that may be replicated in other regions.

Jacobs, John M.↗

Automated characterization of perceptual quality of clinical chest radiographs: Validation and calibration to observer preference

Purpose: The authors previously proposed an image-based technique [Y. Lin et al. Med. Phys. 39, 7019–7031 (2012)] to assess the perceptual quality of clinical chest radiographs. In this study, an observer study was designed and conducted to validate the output of the program against rankings by expert radiologists and to establish the ranges of the output values that reflect the acceptable image appearance so the program output can be used for image quality optimization and tracking. Methods: Using an IRB-approved protocol, 2500 clinical chest radiographs (PA/AP) were collected from our clinical operation. The images were processed through our perceptual quality assessment program to measure their appearance in terms of ten metrics of perceptual image quality: lung gray level, lung detail, lung noise, rib–lung contrast, rib sharpness, mediastinum detail, mediastinum noise, mediastinum alignment, subdiaphragm–lung contrast, and subdiaphragm area. From the results, for each targeted appearance attribute/metric, 18 images were selected such that the images presented a relatively constant appearance with respect to all metrics except the targeted one. The images were then incorporated into a graphical user interface, which displayed them into three panels of six in a random order. Using a DICOM calibrated diagnostic display workstation and under low ambient lighting conditions, each of five participating attending chest radiologists was tasked to spatially order the images based only on the targeted appearance attribute regardless of the other qualities. Once ordered, the observer also indicated the range of image appearances that he/she considered clinically acceptable. The observer data were analyzed in terms of the correlations between the observer and algorithmic rankings and interobserver variability. An observer-averaged acceptable image appearance was also statistically derived for each quality attribute based on the collected individual acceptable ranges. Results: The observer study indicated that, for each image quality attribute, the averaged observer ranking strongly correlated with the algorithmic ranking (linear correlation coefficient R > 0.92), with highest correlation (R = 1) for lung gray level and the lowest (R = 0.92) for mediastinum noise. There was a strong concordance between the observers in terms of their rankings (i.e., Kendall’s tau agreement > 0.84). The observers also generally indicated similar tolerance and preference levels in terms of acceptable ranges, as 85% of the values were close to the overall tolerance or preference levels and the differences were smaller than 0.15. Conclusions: The observer study indicates that the previously proposed technique provides a robust reflection of the perceptual image quality in clinical images. The results established the range of algorithmic outputs for each metric that can be used to quantitatively assess and qualify the appearance quality of clinical chest radiographs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

AttentionFire_v1.0: interpretable machine learning fire model for burned-area predictions over tropics

Abstract. African and South American (ASA) wildfires account for more than 70 % of global burned areas and have strong connection to local climate for sub-seasonal to seasonal wildfire dynamics. However, representation of the wildfire–climate relationship remains challenging due to spatiotemporally heterogenous responses of wildfires to climate variability and human influences. Here, we developed an interpretable machine learning (ML) fire model (AttentionFire_v1.0) to resolve the complex controls of climate and human activities on burned areas and to better predict burned areas over ASA regions. Our ML fire model substantially improved predictability of burned areas for both spatial and temporal dynamics compared with five commonly used machine learning models. More importantly, the model revealed strong time-lagged control from climate wetness on the burned areas. The model also predicted that, under a high-emission future climate scenario, the recently observed declines in burned area will reverse in South America in the near future due to climate changes. Our study provides a reliable and interpretable fire model and highlights the importance of lagged wildfire–climate relationships in historical and future predictions.

58 GEOSCIENCES↗

WE-DE-BRA-03: Construction of An Ultrasound Guidance Platform for Image-Guided Radiotherapy with the Intent to Treat Transitional Cell Carcinoma

Purpose: Ultrasound (US) is a noninvasive, nonradiographic imaging technique with high spatial and temporal resolution that can be used for localizing soft-tissue structures and tumors in real-time during radiotherapy (inter- and intra-fraction). A detailed methodology integrating 3D-US within RT is presented. This method is easier to adopt into current treatment protocol than current US based systems and reduces user variability for image acquisition, thus eliminating transducer induced changes that limit CT planning system. Methods: We designed an in-house integrated US manipulator and platform to relate CT, 3D-US and linear accelerator coordinate systems. To validate the platform, an agar-based phantom with measured densities and speed-of-sound consistent with tissues surrounding the bladder, was rotated (0–45°) resulting in translations (up to 55mm) relative to the CT and US coordinate systems. After acquiring and integrating CT and US images into the treatment planning system, US-to-US and US-to-CT images were co-registered to re-align the phantom relative to the linear accelerator. Errors in the transformation matrix components were calculate to determine precision of this method under different patient positions. Results: Statistical errors from US-US registrations for different patient orientations ranged from 0.06–1.66mm for x, y, and z translational components, and 0.00–1.05° for rotational components. Statistical errors from US-CT registrations were 0.23–1.18mm for the x, y and z translational components, and 0.08–2.52° for the rotational components. Conclusion: Based on our result, this is consistent with currently used techniques for positioning prostate patients if couch re-positioning is less than a 5 degree rotation. We are now testing this on a dog patient to obtain both inter and intra-fractional positional errors. Additional design considerations include the future use of ultrasound-based functionality (photoacoustics, radioacoustics, Doppler) to monitor blood flow and hypoxia and/or in-vivo dosimetry for applications in other therapeutic techniques, such as hyperthermia, anti-angiogenesis, and particle therapy.

60 APPLIED LIFE SCIENCES↗

Aridity changes in the Tibetan Plateau in a warming climate

Desertification in the Tibetan Plateau (TP) has drawn increasing attention in the recent decades. It has been postulated as a consequence of climate aridity due to the observed warming. This study quantifies the aridity changes in the TP and attributes the changes to different climatic factors. Using the ratio of P/PET (precipitation to potential evapotranspiration) as an aridity index to indicate changes in dryness and wetness in a given area, P/PET was calculated using observed records at 83 stations in the TP, with PET calculated using the Penman–Monteith (PM) algorithm. Spatial and temporal changes of P/PET in 1979-2011 are analyzed. Results show that stations located in the arid and semi-arid northwestern TP are becoming significantly wetter and stations in the semi-humid southeastern TP are becoming drier, though not significantly, in the recent three decades. The aridity change patterns are significantly correlated with precipitation, sunshine duration and diurnal temperature range changes at confidence level of 99.9% from two-tail t-test. Temporal correlations also confirm the significant correlation between aridity changes with the three variables, with precipitation being the most dominant driver of P/PET changes at interannual time scale. PET changes are insignificant but negatively correlated with P/PET in the cold season. In the warm season, however, correlation between PET changes and P/PET changes are significant at confidence level of 99.9% when the cryosphere melts near the surface. Significant correlation between wind speed changes and aridity changes occurs in limited locations and months. Consistency in the climatology pattern and linear trends in surface air temperature and precipitation calculated using station data, gridded data, and nearest grid-to-stations for the TP average and across sub-basins indicate the robustness of the trends despite the large spatial heterogeneity in the TP that challenge climate monitoring.

54 ENVIRONMENTAL SCIENCES↗