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DOE OSTI2026

Search for the chiral magnetic effect through beam energy dependence of charge separation using event shape selection

High-energy, heavy-ion collisions can create local domains of chirality-imbalanced quarks, reflecting the topological features of quantum chromodynamics. The chiral magnetic effect (CME) predicts an electric charge separation of quarks in such topological domains along the magnetic field ($\vec{B}$) generated by the passing of two high-Z nuclei. Here, we use a correlation observable Δ⁢𝛾$^{112}$ between charged meson pairs to detect the CME-induced charge separation and a novel event shape selection (ESS) method to mitigate the background effects related to elliptic flow (𝑣 2 ). The ESS method classifies events based on the emission pattern of final-state particles and determines Δ⁢𝛾$^{112}_{ESS}$ from the zero-flow limit. We reconstruct the $\vec{B}$ field direction from the spectator nucleons, which minimizes backgrounds unrelated to the collective motion of the system. In this work, we report the measurements of Δ⁢𝛾$^{112}$ and a background indicator Δ⁢𝛾$^{132}$ in Au+Au collisions from the Brookhaven National Laboratory Relativistic Heavy Ion Collider (RHIC) Beam Energy Scan phase II and at the top RHIC energy. After background suppression, Δ⁢𝛾$^{132}_{ESS}$ aligns with zero, and Δ⁢𝛾$^{112}_{ESS}$ is reduced to no more than 20% of Δ⁢𝛾$^{112}$. We observe a finite residual charge separation with 2.5⁢𝜎, 3⁢𝜎, and 3.2⁢𝜎 significance in the 20–50% centrality range of Au + Au collisions at 11.5, 14.6, and 19.6 GeV. The results at 17.3 and 27 GeV also show positive values but with a lower significance of 1.3⁢𝜎 and 1.1⁢𝜎, respectively. The corresponding Δ⁢𝛾$^{112}_{ESS}$ values at 7.7, 9.2, and 200 GeV are consistent with zero within uncertainties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2017

Testing autonomous cyber-physical systems using fuzzing features from convolutional neural networks: work-in-progress

Autonomous cyber-physical systems rely on modern machine learning methods such as deep neural networks to control their interactions with the physical world. Testing of such intelligent cyber-physical systems is a challenge due to the huge state space associated with high-resolution visual sensory inputs. We demonstrate how fuzzing the input using patterns obtained from the convolutional filters of an unrelated convolutional neural network can be used to test computer vision algorithms implemented in intelligent cyber-physical systems. Our method discovers interesting counterexamples to a pedestrian detection algorithm implemented in the popular OpenCV library. Our approach also unearths counterexamples to the correct behavior of an autonomous car similar to NVIDIA's end-to-end self-driving deep neural net running on the Udacity open-source simulator.

Raj, Sunny↗

DOE OSTI2021

Searching for Interstellar Quantum Communications

The modern search for extraterrestrial intelligence began with the seminal publications of Cocconi & Morrison and Schwartz & Townes, who proposed searching for narrowband signals in the radio spectrum and optical laser pulses. Over the last six decades, more than 100 dedicated search programs have targeted these wavelengths, all with null results. All of these campaigns searched for classical communications, that is, for a significant number of photons above a noise threshold, with the assumption of a pattern encoded in time and/or frequency space. I argue that future searches should also target quantum communications. They are preferred over classical communications with regard to security and information efficiency, and they would have escaped detection in all previous searches. The measurement of Fock state photons or squeezed light would indicate the artificiality of a signal. I show that quantum coherence is feasible over interstellar distances and explain for the first time how astronomers can search for quantum transmissions sent by ETI to Earth using commercially available telescopes and receiver equipment.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2017

A SEARCH FOR SPECTRAL HYSTERESIS AND ENERGY-DEPENDENT TIME LAGS FROM X-RAY AND TeV GAMMA-RAY OBSERVATIONS OF Mrk 421

Blazars are variable emitters across all wavelengths over a wide range of timescales, from months down to minutes. It is therefore essential to observe blazars simultaneously at different wavelengths, especially in the X-ray and gamma-ray bands, where the broadband spectral energy distributions usually peak. In this work, we report on three “target-of-opportunity” observations of Mrk 421, one of the brightest TeV blazars, triggered by a strong flaring event at TeV energies in 2014. These observations feature long, continuous, and simultaneous exposures with XMM-Newton (covering the X-ray and optical/ultraviolet bands) and VERITAS (covering the TeV gamma-ray band), along with contemporaneous observations from other gamma-ray facilities (MAGIC and Fermi -Large Area Telescope) and a number of radio and optical facilities. Although neither rapid flares nor significant X-ray/TeV correlation are detected, these observations reveal subtle changes in the X-ray spectrum of the source over the course of a few days. We search the simultaneous X-ray and TeV data for spectral hysteresis patterns and time delays, which could provide insight into the emission mechanisms and the source properties (e.g., the radius of the emitting region, the strength of the magnetic field, and related timescales). The observed broadband spectra are consistent with a one-zone synchrotron self-Compton model. We find that the power spectral density distribution at ≳4 × 10{sup −4} Hz from the X-ray data can be described by a power-law model with an index value between 1.2 and 1.8, and do not find evidence for a steepening of the power spectral index (often associated with a characteristic length scale) compared to the previously reported values at lower frequencies.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2017

Detection Identification and Quantification of Keto-Hydroperoxides in Low-Temperature Oxidation.

Keto-hydroperoxides are reactive partially oxidized intermediates that play a central role in chain-branching reactions during the low-temperature oxidation of hydrocarbons. In this Perspective, we outline how these short lived species can be detected, identified, and quantified using integrated experimental and theoretical approaches. The procedures are based on direct molecular-beam sampling from reactive environments, followed by mass spectrometry with single-photon ionization, identification of fragmentation patterns, and theoretical calculations of ionization thresholds, fragment appearance energies, and photoionization cross sections. Using the oxidation of neo-pentane and tetrahydrofuran as examples, the individual steps of the experimental approaches are described in depth together with a detailed description of the theoretical efforts. For neo-pentane, the experimental data are consistent with the calculated ionization and fragment appearance energies of the keto-hydroperoxide, thus adding confidence to the analysis routines and the employed levels of theory. For tetrahydrofuran, multiple keto-hydroperoxide isomers are possible due to the presence of nonequivalent O 2 addition sites. Despite this additional complexity, the experimental data allow for the identification of two to four keto-hydroperoxides. Mole fraction profiles of the keto-hydroperoxides, which are quantified using calculated photoionization cross sections, are provided together with estimated uncertainties as function of the temperature of the reactive mixture and can serve as validation targets for chemically detailed mechanisms.

Hansen, Nils↗

DOE OSTI2017

Soil organic matter availability and climate drive latitudinal patterns in bacterial diversity from tropical to cold temperate forests

Bacteria are one of the most abundant and diverse groups of micro-organisms and mediate many critical terrestrial ecosystem processes. Despite the crucial ecological role of bacteria, our understanding of their large-scale biogeography patterns across forests, and the processes that determine these patterns lags significantly behind that of macroorganisms. Here, we evaluated the geographic distributions of bacterial diversity and their driving factors across nine latitudinal forests along a 3,700-km north–south transect in eastern China, using high-throughput 16S rRNA gene sequencing. Four of 32 phyla detected were dominant: Acidobacteria , Actinobacteria , Alphaproteobacteria and Chloroflexi (relative abundance > 5%). Significant increases in bacterial richness and phylogenetic diversity were observed for temperate forests compared with subtropical or tropical forests. The soil organic matter (SOM) mineralisation rate (SOM min , an index of SOM availability) explained the largest significant variations in bacterial richness. Variation partition analysis revealed that the bacterial community structure was closely correlated with environmental variables and geographic distance, which together explained 80.5% of community variation. Among all environmental factors, climatic features (MAT and MAP) were the best predictors of the bacterial community structure, whereas soil pH and SOM min emerged as the most important edaphic drivers of the bacterial community structure. Plant functional traits (community weighted means of litter N content) and diversity resulted in weak but significant correlations with the bacterial community structure. Our findings provide new evidence of bacterial biogeography patterns from tropical to cold temperate forests. Additionally, the results indicated a close linkage among soil bacterial diversity, climate and SOM decomposition, which is critical for predicting continental-scale responses under future climate change scenarios and promoting sustainable forest ecosystem services.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

Natural Attenuation Progress, Plume Movement, and Source Reduction for the SRS CMP Pits VOC Plume - 18384

Monitoring the effectiveness of natural attenuation for remediating the Savannah River Site (SRS) Chemical, Metals, and Pesticides (CMP) Pits plume fringe has focused intensive sampling of shallow groundwater for different reaches of Pen Branch from 2005 to 2017. Volatile organic compounds (VOCs) were analyzed for the critical hyporheic zone beneath Pen Branch and adjacent floodplain. These sampling efforts assisted larger-scale compliance monitoring in accordance with US Environmental Protection Agency (EPA) guidelines. When applicable, EPA has found natural attenuation to be an acceptable mode of achieving regulatory compliance. While natural attenuation can include any ecosystem function that reduces contaminant loads, it is focused on microbial biochemical pathways. The study plume originated from CMP Pits, a waste disposal area in operation from 1971 to 1979, when the pits were closed and backfilled. In 1984, excavations of source material and contaminated soils were removed up to a depth of 7.6 m below the trenches. However, monitoring well data indicated that perchloroethylene (PCE) and trichloroethylene (TCE) had seeped beneath the vadose zone and formed groundwater plumes reaching the Pen Branch valley below. Although 'hot spots' of TCE were found within the Pen Branch floodplain, it was unknown just how the flow pattern was entering Pen Branch and to what degree natural attenuation was reducing the contaminant load. For this reason, our stations were located along the Pen Branch reach bordering the modelled plume fringe. In general, VOCs were highest at station piezometer holes in the middle study zone. Moderate VOC levels were detected at upstream stations and lowest VOC levels were found at downstream stations. Electrical resistance heating (ERH) with soil vapor extraction (SVE) conducted by Savannah River Nuclear Solutions (SRNS) from 2008 to 2009 at the filled CMP Pits helped to remove contaminants trapped in clay horizons beneath the CMP Pits and to reduce overall new plume concentrations. Collectively PCE, TCE, and their degradation products displayed a favorable yearly trend of contaminant natural attenuation. Additionally, phytoremediation actions by native bamboo, Arundinaria gigantea, added to VOC removal from wetlands soils. Total VOC concentrations at some stations declined by >25% and concentrations of vinyl chloride (VC), a nearly-final stage degradation product increased from 0.0 ppb to >20 ppb. Temporal patterns displayed a continued reduction of VOCs, while spatial patterns indicated a possible slow progression of the plume downstream along Pen Branch. Conclusions about plume export into surface waters must address the seasonal and geological complexities of this system. Hydrological patterns are complex and plumes do not directly outcrop into Pen Branch surface waters, but emerge into the stream through pathways in the porous hyporheic zone. For this reason, continued sampling must identify critical depths and downstream locations where plume flows may be more intense. During drought periods with no surface flow in Pen Branch, subsurface plume flows may be flowing downslope in the hyporheic zone. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2015

TU-F-CAMPUS-T-05: A Cloud-Based Monte Carlo Dose Calculation for Electron Cutout Factors

Purpose: For electron cutouts of smaller sizes, it is necessary to verify electron cutout factors due to perturbations in electron scattering. Often, this requires a physical measurement using a small ion chamber, diode, or film. The purpose of this study is to develop a fast Monte Carlo based dose calculation framework that requires only a smart phone photograph of the cutout and specification of the SSD and energy to determine the electron cutout factor, with the ultimate goal of making this cloud-based calculation widely available to the medical physics community. Methods: The algorithm uses a pattern recognition technique to identify the corners of the cutout in the photograph as shown in Figure 1. It then corrects for variations in perspective, scaling, and translation of the photograph introduced by the user’s positioning of the camera. Blob detection is used to identify the portions of the cutout which comprise the aperture and the portions which are cutout material. This information is then used define physical densities of the voxels used in the Monte Carlo dose calculation algorithm as shown in Figure 2, and select a particle source from a pre-computed library of phase-spaces scored above the cutout. The electron cutout factor is obtained by taking a ratio of the maximum dose delivered with the cutout in place to the dose delivered under calibration/reference conditions. Results: The algorithm has been shown to successfully identify all necessary features of the electron cutout to perform the calculation. Subsequent testing will be performed to compare the Monte Carlo results with a physical measurement. Conclusion: A simple, cloud-based method of calculating electron cutout factors could eliminate the need for physical measurements and substantially reduce the time required to properly assure accurate dose delivery.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2017

The medical science DMZ: a network design pattern for data-intensive medical science

Abstract Objective We describe a detailed solution for maintaining high-capacity, data-intensive network flows (eg, 10, 40, 100 Gbps+) in a scientific, medical context while still adhering to security and privacy laws and regulations. Materials and Methods High-end networking, packet-filter firewalls, network intrusion-detection systems. Results We describe a “Medical Science DMZ” concept as an option for secure, high-volume transport of large, sensitive datasets between research institutions over national research networks, and give 3 detailed descriptions of implemented Medical Science DMZs. Discussion The exponentially increasing amounts of “omics” data, high-quality imaging, and other rapidly growing clinical datasets have resulted in the rise of biomedical research “Big Data.” The storage, analysis, and network resources required to process these data and integrate them into patient diagnoses and treatments have grown to scales that strain the capabilities of academic health centers. Some data are not generated locally and cannot be sustained locally, and shared data repositories such as those provided by the National Library of Medicine, the National Cancer Institute, and international partners such as the European Bioinformatics Institute are rapidly growing. The ability to store and compute using these data must therefore be addressed by a combination of local, national, and industry resources that exchange large datasets. Maintaining data-intensive flows that comply with the Health Insurance Portability and Accountability Act (HIPAA) and other regulations presents a new challenge for biomedical research. We describe a strategy that marries performance and security by borrowing from and redefining the concept of a Science DMZ, a framework that is used in physical sciences and engineering research to manage high-capacity data flows. Conclusion By implementing a Medical Science DMZ architecture, biomedical researchers can leverage the scale provided by high-performance computer and cloud storage facilities and national high-speed research networks while preserving privacy and meeting regulatory requirements.

Peisert, Sean↗

DOE OSTI2020

Updated design of the CMB polarization experiment satellite LiteBIRD

Recent developments of transition-edge sensors (TESs), based on extensive experience in ground-based experiments, have been making the sensor techniques mature enough for their application on future satellite CMB polarization experiments. LiteBIRD is in the most advanced phase among such future satellites, targeting its launch in Japanese Fiscal Year 2027 (2027FY) with JAXA's H3 rocket. It will accommodate more than 4000 TESs in focal planes of reflective low-frequency and refractive medium-and-high-frequency telescopes in order to detect a signature imprinted on the cosmic microwave background (CMB) by the primordial gravitational waves predicted in cosmic inflation. The total wide frequency coverage between 34GHz and 448GHz enables us to extract such weak spiral polarization patterns through the precise subtraction of our Galaxy's foreground emission by using spectral differences among CMB and foreground signals. Telescopes are cooled down to 5Kelvin for suppressing thermal noise and contain polarization modulators with transmissive half-wave plates at individual apertures for separating sky polarization signals from artificial polarization and for mitigating from instrumental 1/f noise. Passive cooling by using V-grooves supports active cooling with mechanical coolers as well as adiabatic demagnetization refrigerators. Sky observations from the second Sun-Earth Lagrangian point, L2, are planned for three years. An international collaboration between Japan, USA, Canada, and Europe is sharing various roles. In May 2019, the Institute of Space and Astronautical Science (ISAS), JAXA selected LiteBIRD as the strategic large mission No. 2.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Population-level control of two manganese oxidases expands the niche for bacterial manganese biomineralization

Abstract The enzymatic oxidation of aqueous divalent manganese (Mn) is a widespread microbial trait that produces reactive Mn(III, IV) oxide minerals. These biominerals drive carbon, nutrient, and trace metal cycles, thus playing important environmental and ecological roles. However, the regulatory mechanisms and physiological functions of Mn biomineralization are unknown. This challenge arises from the common occurrence of multiple Mn oxidases within the same organism and the use of Mn oxides as indicators of combined gene activity. Through the detection of gene activation in individual cells, we discover that expression ofmnxGandmcoA, two Mn oxidase-encoding genes inPseudomonas putidaGB-1, is confined to subsets of cells within the population, with each gene showing distinct spatiotemporal patterns that reflect local microenvironments. These coordinated intra-population dynamics control Mn biomineralization and illuminate the strategies used by microbial communities to dictate the extent, location, and timing of biogeochemical transformations.

Biotechnology & Applied Microbiology↗

DOE OSTI2020

A spherical crystal diffraction imager for Sandia’s Z Pulsed Power Facility

Sandia’s Z Pulsed Power Facility is able to dynamically compress matter to extreme states with exceptional uniformity, duration, and size, which are ideal for investigating fundamental material properties of high energy density conditions. X-ray diffraction (XRD) is a key atomic scale probe since it provides direct observation of the compression and strain of the crystal lattice and is used to detect, identify, and quantify phase transitions. Because of the destructive nature of Z-Dynamic Material Property (DMP) experiments and low signal vs background emission levels of XRD, it is very challenging to detect a diffraction signal close to the Z-DMP load and to recover the data. We have developed a new Spherical Crystal Diffraction Imager (SCDI) diagnostic to relay and image the diffracted x-ray pattern away from the load debris field. The SCDI diagnostic utilizes the Z-Beamlet laser to generate 6.2-keV Mn–He α x rays to probe a shock-compressed material on the Z-DMP load. Finally, a spherically bent crystal composed of highly oriented pyrolytic graphite is used to collect and focus the diffracted x rays into a 1-in. thick tungsten housing, where an image plate is used to record the data.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Ultrafast x-ray and electron scattering of free molecules: A comparative evaluation

Resolving gas phase molecular motions with simultaneous spatial and temporal resolution is rapidly coming within the reach of x-ray Free Electron Lasers (XFELs) and Mega-electron-Volt (MeV) electron beams. These two methods enable scattering experiments that have yielded fascinating new results, and while both are important methods for determining transient molecular structures in photochemical reactions, it is important to understand their relative merits. In the present study, we evaluate the respective scattering cross sections of the two methods and simulate their ability to determine excited state molecular structures in light of currently existing XFEL and MeV source parameters. Using the example of optically excited N-methyl morpholine and simulating the scattering patterns with shot noise, we find that the currently achievable signals are superior with x-ray scattering for equal samples and on a per-shot basis and that x-ray scattering requires fewer detected signal counts for an equal fidelity structure determination. Importantly, within the independent atom model, excellent structure determinations can be achieved for scattering vectors only to about 5 Å−1, leaving larger scattering vector ranges for investigating vibrational motions and wavepackets. Electron scattering has a comparatively higher sensitivity toward hydrogen atoms, which may point to applications where electron scattering is inherently the preferred choice, provided that excellent signals can be achieved at large scattering angles that are currently difficult to access.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2022

GSoFa: Scalable Sparse Symbolic LU Factorization on GPUs

Decomposing a matrix $\mathbf {A}$ into a lower matrix $\mathbf {L}$ and an upper matrix $\mathbf {U}$, which is also known as LU decomposition, is an essential operation in numerical linear algebra. For a sparse matrix, LU decomposition often introduces more nonzero entries in the $\mathbf {L}$ and $\mathbf {U}$ factors than in the original matrix. A symbolic factorization step is needed to identify the nonzero structures of $\mathbf {L}$ and $\mathbf {U}$ matrices. Attracted by the enormous potentials of the Graphics Processing Units (GPUs), an array of efforts have surged to deploy various LU factorization steps except for the symbolic factorization, to the best of our knowledge, on GPUs. This article introduces gSoFa, the first GPU-based symbolic factorization design with the following three optimizations to enable scalable LU symbolic factorization for nonsymmetric pattern sparse matrices on GPUs. First, here we introduce a novel fine-grained parallel symbolic factorization algorithm that is well suited for the Single Instruction Multiple Thread (SIMT) architecture of GPUs. Second, we tailor supernode detection into a SIMT friendly process and strive to balance the workload, minimize the communication and saturate the GPU computing resources during supernode detection. Third, we introduce a three-pronged optimization to reduce the excessive space consumption problem faced by multi-source concurrent symbolic factorization. Taken together, gSoFa achieves up to 31× speedup from 1 to 44 Summit nodes (6 to 264 GPUs) and outperforms the state-of-the-art CPU project, on average, by 5×. Notably, gSoFa also achieves up to 47 percent of the peak memory throughput of a V100 GPU in the Summit Supercomputer.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

The Oral and Skin Microbiomes of Captive Komodo Dragons Are Significantly Shared with Their Habitat

Animals, including humans, have evolved in the context of exposure to a variety of microbial organisms present in the environment. Only recently have humans, and some animals, begun to spend a significant amount of time in enclosed artificial environments, rather than in the more natural spaces in which most of evolution took place. The consequences of this radical change in lifestyle likely extend to the microbes residing in and on our bodies and may have important implications for health and disease. A full characterization of host-microbe sharing in both closed and open environments will provide crucial information that may enable the improvement of health in humans and in captive animals, both of which experience a greater incidence of disease (including chronic illness) than counterparts living under more ecologically natural conditions. Examining the way in which animals, including those in captivity, interact with their environment is extremely important for studying ecological processes and developing sophisticated animal husbandry. Here we use the Komodo dragon (Varanus komodoensis) to quantify the degree of sharing of salivary, skin, and fecal microbiota with their environment in captivity. Both species richness and microbial community composition of most surfaces in the Komodo dragon’s environment are similar to the Komodo dragon’s salivary and skin microbiota but less similar to the stool-associated microbiota. We additionally compared host-environment microbiome sharing between captive Komodo dragons and their enclosures, humans and pets and their homes, and wild amphibians and their environments. We observed similar host-environment microbiome sharing patterns among humans and their pets and Komodo dragons, with high levels of human/pet- and Komodo dragon-associated microbes on home and enclosure surfaces. In contrast, only small amounts of amphibian-associated microbes were detected in the animals’ environments. We suggest that the degree of sharing between the Komodo dragon microbiota and its enclosure surfaces has important implications for animal health. These animals evolved in the context of constant exposure to a complex environmental microbiota, which likely shaped their physiological development; in captivity, these animals will not receive significant exposure to microbes not already in their enclosure, with unknown consequences for their health. Animals, including humans, have evolved in the context of exposure to a variety of microbial organisms present in the environment. Only recently have humans, and some animals, begun to spend a significant amount of time in enclosed artificial environments, rather than in the more natural spaces in which most of evolution took place. The consequences of this radical change in lifestyle likely extend to the microbes residing in and on our bodies and may have important implications for health and disease. A full characterization of host-microbe sharing in both closed and open environments will provide crucial information that may enable the improvement of health in humans and in captive animals, both of which experience a greater incidence of disease (including chronic illness) than counterparts living under more ecologically natural conditions.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2016

Modeling magnetic fields from a DC power cable buried beneath San Francisco Bay based on empirical measurements

Here, the Trans Bay Cable (TBC) is a ±200-kilovolt (kV), 400 MW 85-km long High Voltage Direct Current (DC) buried transmission line linking Pittsburg, CA with San Francisco, CA (SF) beneath the San Francisco Estuary. The TBC runs parallel to the migratory route of various marine species, including green sturgeon, Chinook salmon, and steelhead trout. In July and August 2014, an extensive series of magnetic field measurements were taken using a pair of submerged Geometrics magnetometers towed behind a survey vessel in four locations in the San Francisco estuary along profiles that cross the cable’s path; these included the San Francisco-Oakland Bay Bridge (BB), the Richmond-San Rafael Bridge (RSR), the Benicia- Martinez Bridge (Ben) and an area in San Pablo Bay (SP) in which a bridge is not present. In this paper, we apply basic formulas that ideally describe the magnetic field from a DC cable summed vectorially with the background geomagnetic field (in the absence of other sources that would perturb the ambient field) to derive characteristics of the cable that are otherwise not immediately observable. Magnetic field profiles from measurements taken along 170 survey lines were inspected visually for evidence of a distinct pattern representing the presence of the cable. Many profiles were dominated by field distortions unrelated to the cable caused by bridge structures or other submerged objects, and the cable’s contribution to the field was not detectable. BB, with 40 of the survey lines, did not yield usable data for these reasons. The unrelated anomalies could be up to 100 times greater than those from the cable. In total, discernible magnetic field profiles measured from 76 survey lines were regressed against the equations, representing eight days of measurement. The modeled field anomalies due to the cable (the difference between the maximum and minimum field along the survey line at the cable crossing) were virtually identical to the measured values. The modeling yielded a pooled cable depth below the bay floor of 2.06 m (±1.46 std dev), and estimated the angle to the horizontal of the imaginary line connecting the crosssectional center of the cable’s two conductors (0.1143 m apart) as 178.9° ±61.9° (std dev) for Ben, 78.6°±37.0° (std dev) for RSR, and 139.9°±27.4° (std dev) for SP. The mean of the eight daily average currents derived from the regressions was 986 ±185 amperes (A) (std dev), as compared to 722 ±95 A (std dev) provided by Trans Bay Cable LLC. Overall, the regressions based on fundamental principles (Biot Savart law) and the vectorial summation of cable and geomagnetic fields provide estimates of cable characteristics consistent with plausible expectations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

A renewed model of pancreatic cancer evolution based on genomic rearrangement patterns

Pancreatic cancer, a highly aggressive tumour type with uniformly poor prognosis, exemplifies the classically held view of stepwise cancer development. The current model of tumorigenesis, based on analyses of precursor lesions, termed pancreatic intraepithelial neoplasm (PanINs) lesions, makes two predictions: first, that pancreatic cancer develops through a particular sequence of genetic alterations (KRAS, followed by CDKN2A, then TP53 and SMAD4); and second, that the evolutionary trajectory of pancreatic cancer progression is gradual because each alteration is acquired independently. A shortcoming of this model is that clonally expanded precursor lesions do not always belong to the tumour lineage, indicating that the evolutionary trajectory of the tumour lineage and precursor lesions can be divergent. This prevailing model of tumorigenesis has contributed to the clinical notion that pancreatic cancer evolves slowly and presents at a late stage. However, the propensity for this disease to rapidly metastasize and the inability to improve patient outcomes, despite efforts aimed at early detection, suggest that pancreatic cancer progression is not gradual. Here, using newly developed informatics tools, we tracked changes in DNA copy number and their associated rearrangements in tumour-enriched genomes and found that pancreatic cancer tumorigenesis is neither gradual nor follows the accepted mutation order. Two-thirds of tumours harbour complex rearrangement patterns associated with mitotic errors, consistent with punctuated equilibrium as the principal evolutionary trajectory. In a subset of cases, the consequence of such errors is the simultaneous, rather than sequential, knockout of canonical preneoplastic genetic drivers that are likely to set-off invasive cancer growth. These findings challenge the current progression model of pancreatic cancer and provide insights into the mutational processes that give rise to these aggressive tumours.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Deep learning for visualization and novelty detection in large X-ray diffraction datasets

Abstract We apply variational autoencoders (VAE) to X-ray diffraction (XRD) data analysis on both simulated and experimental thin-film data. We show that crystal structure representations learned by a VAE reveal latent information, such as the structural similarity of textured diffraction patterns. While other artificial intelligence (AI) agents are effective at classifying XRD data into known phases, a similarly conditioned VAE is uniquely effective at knowing what it doesn’t know: it can rapidly identify data outside the distribution it was trained on, such as novel phases and mixtures. These capabilities demonstrate that a VAE is a valuable AI agent for aiding materials discovery and understanding XRD measurements both ‘on-the-fly’ and during post hoc analysis.

36 MATERIALS SCIENCE↗