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At least 649 records · Page 36

INTERPRETING THE DISTANCE CORRELATION RESULTS FOR THE COMBO-17 SURVEY

The accurate classification of galaxies in large-sample astrophysical databases of galaxy clusters depends sensitively on the ability to distinguish between morphological types, especially at higher redshifts. This capability can be enhanced through a new statistical measure of association and correlation, called the distance correlation coefficient, which has more statistical power to detect associations than does the classical Pearson measure of linear relationships between two variables. The distance correlation measure offers a more precise alternative to the classical measure since it is capable of detecting nonlinear relationships that may appear in astrophysical applications. We showed recently that the comparison between the distance and Pearson correlation coefficients can be used effectively to isolate potential outliers in various galaxy data sets, and this comparison has the ability to confirm the level of accuracy associated with the data. In this work, we elucidate the advantages of distance correlation when applied to large databases. We illustrate how the distance correlation measure can be used effectively as a tool to confirm nonlinear relationships between various variables in the COMBO-17 database, including the lengths of the major and minor axes, and the alternative redshift distribution. For these outlier pairs, the distance correlation coefficient is routinely higher than the Pearson coefficient since it is easier to detect nonlinear relationships with distance correlation. The V-shaped scatter plots of Pearson versus distance correlation coefficients also reveal the patterns with increasing redshift and the contributions of different galaxy types within each redshift range.

79 ASTRONOMY AND ASTROPHYSICS↗

Testing the Froggatt-Nielsen mechanism with lepton flavor and number violating processes

The Froggatt-Nielsen (FN) mechanism offers an elegant explanation for the observed masses and mixings of Standard Model fermions. In this work, we systematically study FN models in the lepton sector, identifying a broad range of charge assignments (“textures”) that naturally yield viable masses and mixings for various neutrino mass generation mechanisms. Using these textures, we consider higher-dimensional operators consistent with a FN origin and find that natural realizations predict distinct patterns in lepton flavor- and number-violating observables. For Dirac and Majorana neutrinos, FN-related correlations can lead to detectable rates of charged lepton flavor violation at next-generation low-energy experiments. Majorana and type-I seesaw models predict measurable rates of neutrinoless double beta decay. Determination of inverted neutrino mass ordering would exclude the Dirac neutrino FN scenario. Only a small minority of purely leptonic FN models predict detectable flavor violation at future muon colliders, though it is possible that a combined analysis with the quark sector will reveal motivated signals. These findings highlight the power of the FN mechanism to link neutrino mass generation to testable leptonic observables, offering new pathways for the experimental exploration of lepton number and underscoring the importance of next-generation low-energy probes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Symmetry breaking and Landau quantization in topological crystalline insulators

In the recently discovered topological crystalline insulators SnTe and Pb 1–x Sn x (Te, Se), crystal symmetry and electronic topology intertwine to create topological surface states with many interesting features including Lifshitz transition, Van-Hove singularity, and fermion mass generation. These surface states are protected by mirror symmetry with respect to the (110) plane. In this work we present a comprehensive study of the effects of different mirror-symmetry-breaking perturbations on the (001) surface band structure. Pristine (001) surface states have four branches of Dirac fermions at low energy. We show that ferroelectric-type structural distortion generates a mass and gaps out some or all of these Dirac points, while strain shifts Dirac points in the Brillouin zone. An in-plane magnetic field leaves the surface state gapless, but introduces asymmetry between Dirac points. Finally, an out-of-plane magnetic field leads to discrete Landau levels. We show that the Landau level spectrum has an unusual pattern of degeneracy and interesting features due to the unique underlying band structure. Furthermore this suggests that Landau level spectroscopy can detect and distinguish between different mechanisms of symmetry breaking in topological crystalline insulators.

36 MATERIALS SCIENCE↗

Desert camouflage and what wildlife see

Desert, desert-scrub, savanna and sandy beach and lakeshore environments can be particularly tricky in terms of camouflage selection due to their low vegetative density. Therefore many companies focus on the development of paint color schemes that match the vegetation and the desert soils/sands. However another factor in the consideration of which camouflage to purchase may lie in what the animal can see. White-tailed deer and similar large mammals have been shown to have three classes of photo pigments that are sensitive to the range of blue to yellowgreen during day light hours and blue to blue-green at night. Six commercially-available camouflage patterns were investigated to determine if the reflectance characteristics measured in the laboratory and under field conditions were elevated in the blue range and perhaps more likely to be seen by wildlife. The camouflage patterns were evaluated against standard vegetation indices including NDVI, SAVI, EVI, and SR. Only two of the patterns (S4 and S5) possessed a reflectance more like vegetation. Patterns S4, S6, S3, and S2 all showed only slight elevations in the blue wavelength range which could only have been detected by NIR measurements instead of visual observation by the human eye.

59 BASIC BIOLOGICAL SCIENCES↗

Notos - a galaxy tool to analyze CpN observed expected ratios for inferring DNA methylation types

Background: DNA methylation patterns store epigenetic information in the vast majority of eukaryotic species. The relatively high costs and technical challenges associated with the detection of DNA methylation however have created a bias in the number of methylation studies towards model organisms. Consequently, it remains challenging to infer kingdom-wide general rules about the functions and evolutionary conservation of DNA methylation. Methylated cytosine is often found in specific CpN dinucleotides, and the frequency distributions of, for instance, CpG observed/expected (CpG o/e) ratios have been used to infer DNA methylation types based on higher mutability of methylated CpG. Results: Predominantly model-based approaches essentially founded on mixtures of Gaussian distributions are currently used to investigate questions related to the number and position of modes of CpG o/e ratios. These approaches require the selection of an appropriate criterion for determining the best model and will fail if empirical distributions are complex or even merely moderately skewed. We use a kernel density estimation (KDE) based technique for robust and precise characterization of complex CpN o/e distributions without a priori assumptions about the underlying distributions. Conclusions: We show that KDE delivers robust descriptions of CpN o/e distributions. For straightforward processing, we have developed a Galaxy tool, called Notos and available at the ToolShed, that calculates these ratios of input FASTA files and fits a density to their empirical distribution. Based on the estimated density the number and shape of modes of the distribution is determined, providing a rational for the prediction of the number and the types of different methylation classes. Notos is written in R and Perl.

59 BASIC BIOLOGICAL SCIENCES↗

Summary Report: NMSBA CY 2016 - AEgis Technologies Group Inc. #12458.

AEgis requires large area partial mirror optics consisting of partially reflecting optical coatings on large dimension substrates for high energy laser (HEL) applications. The partial mirrors should transmit nearly the same small fraction of HEL radiation incident from a wide range of angles of incidence (AOIs), and the laser-induced damage threshold (LIDT) of the coatings should be high enough for them to be able to withstand direct exposure to near infrared CW HEL radiation at multi-kilowatt/cm2 power levels. The transmitted fraction of incident HEL radiation should reach an array of detectors at power levels high enough for reliable detection but low enough to not damage the detectors. The reflected fraction of incident HEL radiation should scatter into a divergent pattern so as to be eye safe at a distance of ~ 200 m from the mirror in the case of 100 kilowatt incident laser power. The detector array together with the partial mirror optic and possible additional optics that provide divergent scattering of reflected HEL radiation constitute what AEgis refers to as a target board. The target board use environment may vary from benign, indoor laboratory conditions to harsh, outdoor conditions in tests on the ground as well as in air. Under this NMSBA project, Sandia agreed to apply its extensive expertise and capability in the design and production of high LIDT coatings on large dimension optics for high power pulsed laser radiation to advise and assist AEgis in the design and development of high LIDT coatings for the partial mirror optic. Sandia and AEgis met several times to discuss the partial mirror and target board requirements, and Sandia was guided in its work by these discussions as well as by the partial mirror and target board requirement summaries of Tables 1 and 2, respectively, that were provided by AEgis.

47 OTHER INSTRUMENTATION↗

Experimental Report: Multi-Instrument Comparison of AAF Condensation Particle Counters

Condensation particle counters (CPCs), also known as condensation nucleus counters (CNCs) are sophisticated instruments designed to measure the concentration of aerosol particles in the atmosphere. These devices are pivotal in environmental monitoring, industrial applications, and scientific research, particularly in atmospheric studies. CPCs are vital for understanding the role of aerosols in climate systems. Aerosols influence cloud formation, radiative forcing, and atmospheric chemistry. By providing accurate measurements of particle concentrations and distributions, CPCs contribute to models that predict atmospheric impact and weather patterns (Mei et al. 2021). CPCs operate by enlarging submicron particles, including those as small as a few nanometers, to sizes detectable by optical methods. This report delves into the mechanisms, importance, and contributions of CPCs to atmospheric research at the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Aerial Facility (AAF), highlighting their role in advancing air quality assessment, pollution control, and atmospheric studies.

54 ENVIRONMENTAL SCIENCES↗

Creation of a Robust and Generalizable Machine Learning Classifier for Patient Ventilator Asynchrony

Background: As healthcare increasingly digitizes, streaming waveform data is being made available from an variety of sources, but there still remains a paucity of performant clinical decision support systems. For example, in the intensive care unit (ICU) existing automated alarm systems typically rely on simple thresholding that result in frequent false positives. Recurrent false positive alerts create distrust of alarm mechanisms that can be directly detrimental to patient health. To improve patient care in the ICU, we need alert systems that are both pervasive, and accurate so as to be informative and trusted by providers. Objective: We aimed to develop a machine learning-based classifier to detect abnormal waveform events using the use case of mechanical ventilation waveform analysis, and the detection of harmful forms of ventilation delivery to patients. We specifically focused on detecting injurious subtypes of patient-ventilator asynchrony (PVA).Methods: Using a dataset of breaths recorded from 35 different patients, we used machine learning to create computational models to automatically detect, and classify two types of injurious PVA, double trigger asynchrony (DTA), breath stacking asynchrony (BSA). We examined the use of synthetic minority over-sampling technique (SMOTE) to overcome class imbalance problems, varied methods for feature selection, and use of ensemble methods to optimize the performance of our model. Results: We created an ensemble classifier that is able to accurately detect DTA at a sensitivity/specificity of 0.960/0.975, BSA at sensitivity/specificity of 0.944/0.987, and non-PVA events at sensitivity/specificity of .967/.980. Conclusions: Our results suggest that it is possible to create a high-performing machine learning-based model for detecting PVA in mechanical ventilator waveform data in spite of both intra-patient, and inter-patient variability in waveform patterns, and the presence of clinical artifacts like cough and suction procedures. Our work highlights the importance of addressing class imbalance in clinical data sets, and the combined use of statistical methods and expert knowledge in feature selection.

97 MATHEMATICS AND COMPUTING↗

IMAGING ANALYSIS OF THE HARD X-RAY TELESCOPE ProtoEXIST2 AND NEW TECHNIQUES FOR HIGH-RESOLUTION CODED-APERTURE TELESCOPES

Wide-field (≳100 deg{sup 2}) hard X-ray coded-aperture telescopes with high angular resolution (≲2′) will enable a wide range of time domain astrophysics. For instance, transient sources such as gamma-ray bursts can be precisely localized without the assistance of secondary focusing X-ray telescopes to enable rapid followup studies. On the other hand, high angular resolution in coded-aperture imaging introduces a new challenge in handling the systematic uncertainty: the average photon count per pixel is often too small to establish a proper background pattern or model the systematic uncertainty in a timescale where the model remains invariant. We introduce two new techniques to improve detection sensitivity, which are designed for, but not limited to, a high-resolution coded-aperture system: a self-background modeling scheme which utilizes continuous scan or dithering operations, and a Poisson-statistics based probabilistic approach to evaluate the significance of source detection without subtraction in handling the background. We illustrate these new imaging analysis techniques in high resolution coded-aperture telescope using the data acquired by the wide-field hard X-ray telescope ProtoEXIST2 during a high-altitude balloon flight in fall 2012. We review the imaging sensitivity of ProtoEXIST2 during the flight, and demonstrate the performance of the new techniques using our balloon flight data in comparison with a simulated ideal Poisson background.

79 ASTRONOMY AND ASTROPHYSICS↗

Testing the Cosmological Principle: Astrometric Limits on Systemic Motion of Quasars at Different Cosmological Epochs

A sample of 60,410 bona fide optical quasars with astrometric proper motions in Gaia Early Data Release 3 and spectroscopic redshifts above 0.5 in an oval 8400 square degree area of the sky is constructed. Using orthogonal Zernike functions of polar coordinates, the proper motion fields are fitted in a weighted least-squares adjustment of the entire sample and of six equal bins of sorted redshifts. The overall fit with 37 Zernike functions reveals a statistically significant pattern, which is likely to be of instrumental origin. The main feature of this pattern is a chain of peaks and dips mostly in the R.A. component with an amplitude of 25 μ as yr -1 . This field is subtracted from each of the six analogous fits for quasars grouped by redshifts covering the range 0.5 through 7.03, with median values of 0.72, 1.00, 1.25, 1.52, 1.83, 2.34. The resulting residual patterns are noisier, with formal uncertainties up to 8 μ as yr -1 in the central part of the area. We detect a single high-confidence Zernike term for the R.A. proper motion components of quasars with redshifts around 1.52 representing a general gradient of 30 μ as yr -1 over 150° on the sky. We do not find any small- or medium-scale systemic variations of the residual proper motion field as functions of redshift above the 2.5 σ significance level.

79 ASTRONOMY AND ASTROPHYSICS↗

Forward Drift Chambers for the GlueX experiment

The GlueX experiment will search for exotic mesons produced by 9 GeV linearly polarized photon beam from the 12 GeV CEBAF machine. A hermetic solenoid-based detector system that includes tracking and calorimetry has been constructed. The Forward Drift Chamber (FDC) system consists of 24 circular planar drift chambers of 1 m diameter. Additional information from cathode strips, placed at both sides of the wire planes, is required to achieve efficient pattern recognition in the presence of high background rates in forward direction, resulting in 12,500 readout channels in total. The detection of relatively low energy photons by the electro-magnetic calorimeters imposes severe constraints on the amount of the material used in the FDC. Challenges in the production of this low-mass detector will be discussed. The FDC has been completed and recently installed in the bore of the solenoid magnet. Results from the tests of the whole detector system will be presented.

Pentchev, Lubomir↗

Enhanced Propagating Surface Plasmon Signal Detection

Overcoming the dissipative nature of propagating surface plasmons (PSPs) is pre-requisite to realizing functional plasmonic circuitry, in which large bandwidth signals can be manipulated over length scales far-below the diffraction limit of light. To this end, we report on a novel PSP enhanced signal detection technique achieved in an all-metallic substrate. We take advantage of two strategically spatio-temporally separated phase-locked femtosecond laser pulses, incident onto lithographically patterned PSP coupling structures. We follow PSP propagation with joint femtosecond temporal and nanometer spatial resolution in a time-resolved non-linear photoemission electron microscopy scheme. Initially, a PSP signal wave packet is launched from a hole etched into the silver surface from where it propagates through an open trench structure and is decoded through the use of a timed probe pulse. FDTD calculations demonstrate that PSP signal waves may traverse open trenches in excess of 10 microns in diameter, thereby allowing remote detection even through vacuum regions. This arrangement results in a 10X enhancement in photoemission relative to readout from the bare metal surface. The enhancement is attributed to an all-optical homodyne detection technique that mixes signal and reference PSP waves in a non-linear scheme. Larger readout trenches achieve higher readout levels, however reduced transmission through the trench limits the trench size to 6 microns for maximum readout levels. However, the use of an array of trenches increases the maximum enhancement to near 30X. The attainable enhancement factor may be harnessed to achieve extended coherent PSP propagation in ultrafast plasmonic circuitry.

Environmental Molecular Sciences Laboratory↗

CMed: Crowd Analytics for Medical Imaging Data

In this work, we present a visual analytics framework, CMed, for exploring medical image data annotations acquired from crowdsourcing. CMed can be used to visualize, classify, and filter crowdsourced clinical data based on a number of different metrics such as detection rate, logged events, and clustering of the annotations. CMed provides several interactive linked visualization components to analyze the crowd annotation results for a particular video and the associated workers. Additionally, all results of an individual worker can be inspected using multiple linked views in our CMed framework. We allow a crowdsourcing application analyst to observe patterns and gather insights into the crowdsourced medical data, helping him/her design future crowdsourcing applications for optimal output from the workers. We demonstrate the efficacy of our framework with two medical crowdsourcing studies: polyp detection in virtual colonoscopy videos and lung nodule detection in CT thin-slab maximum intensity projection videos. We also provide experts' feedback to show the effectiveness of our framework. Lastly, we share the lessons we learned from our framework with suggestions for integrating our framework into a clinical workflow.

97 MATHEMATICS AND COMPUTING↗

2013 R&D 100 Award: DNATrax could revolutionize air quality detection and tracking

A team of LLNL scientists and engineers has developed a safe and versatile material, known as DNA Tagged Reagents for Aerosol Experiments (DNATrax), that can be used to reliably and rapidly diagnose airflow patterns and problems in both indoor and outdoor venues. Until DNATrax particles were developed, no rapid or safe way existed to validate air transport models with realistic particles in the range of 1-10 microns. Successful DNATrax testing was conducted at the Pentagon in November 2012 in conjunction with the Pentagon Force Protection Agency. This study enhanced the team's understanding of indoor ventilation environments created by heating, ventilation and air conditioning (HVAC) systems. DNATrax are particles comprised of sugar and synthetic DNA that serve as a bar code for the particle. The potential for creating unique bar-coded particles is virtually unlimited, thus allowing for simultaneous and repeated releases, which dramatically reduces the costs associated with conducting tests for contaminants. Among the applications for the new material are indoor air quality detection, for homes, offices, ships and airplanes; urban particulate tracking, for subway stations, train stations, and convention centers; environmental release tracking; and oil and gas uses, including fracking, to better track fluid flow.

54 ENVIRONMENTAL SCIENCES↗

Searching for primordial non-Gaussianity in Planck CMB maps using a combined estimator

The extensive search for deviations from Gaussianity in cosmic microwave background radiation (CMB) data is very important due to the information about the very early moments of the universe encoded there. Recent analyses from Planck CMB data do not exclude the presence of non-Gaussianity of small amplitude, although they are consistent with the Gaussian hypothesis. The use of different techniques is essential to provide information about types and amplitudes of non-Gaussianities in the CMB data. In particular, we find interesting to construct an estimator based upon the combination of two powerful statistical tools that appears to be sensitive enough to detect tiny deviations from Gaussianity in CMB maps. This estimator combines the Minkowski functionals with a Neural Network, maximizing a tool widely used to study non-Gaussian signals with a reinforcement of another tool designed to identify patterns in a data set. We test our estimator by analyzing simulated CMB maps contaminated with different amounts of local primordial non-Gaussianity quantified by the dimensionless parameter f{sub NL}. We apply it to these sets of CMB maps and find ∼> 98% of chance of positive detection, even for small intensity local non-Gaussianity like f{sub NL} = 38±18, the current limit from Planck data for large angular scales. Additionally, we test the suitability to distinguish between primary and secondary non-Gaussianities: first we train the Neural Network with two sets, one of nearly Gaussian CMB maps (|f{sub NL}| ≤ 10) but contaminated with realistic inhomogeneous Planck noise (i.e., secondary non-Gaussianity) and the other of non-Gaussian CMB maps, that is, maps endowed with weak primordial non-Gaussianity (28 ≤ f{sub NL} ≤ 48); after that we test an ensemble composed of CMB maps either with one of these non-Gaussian contaminations, and find out that our method successfully classifies ∼ 95% of the tested maps as being CMB maps containing primordial or secondary non-Gaussianity. Furthermore, we analyze the foreground-cleaned Planck maps obtaining constraints for non-Gaussianity at large-angles that are in good agreement with recent constraints. Finally, we also test the robustness of our estimator including cut-sky masks and realistic noise maps measured by Planck, obtaining successful results as well.

79 ASTRONOMY AND ASTROPHYSICS↗

Substation Secondary Asset Health Monitoring and Management System (SSHM)

Electric Power Group, LLC (EPG) was awarded DOE OE0000850 to design, develop, and demonstrate a real-time software application for substation secondary equipment health monitoring and management at host utility American Electric Power (AEP), a cost share partner. This project addresses the need for monitoring substation equipment health and providing operators with tools to identify and take pre-emptive action to avoid catastrophic equipment failure. By monitoring synchrophasor data in real time, data anomalies that indicate potential asset failure can be detected and alerts can be sent to operators in time to take corrective actions. EPG developed two data driven algorithms to identify abnormal equipment signature patterns as well as a method using substation linear state estimation (SLSE). The software has been deployed on hardened PC’s and tested and validated for cost share partner AEP’s substations - 138kV and 765 kV. The SSHM software has been accepted by AEP and final demonstration of DOE - OE0000850 for AEP and DOE was successfully completed on March 17th, 2020. EPG developed the Substation Secondary Asset Health Monitoring (SSHM) Platform to analyze equipment failure signatures in PMU data and alert substation personnel when pre-emptive inspection, repairs and other actions are warranted to prevent potential catastrophic failures. This is the first system that automatically monitors the health of substation secondary assets and alerts users to emerging failures using synchrophasor measurements. SSHM uses high resolution PMU data from PTs, CTs, and CCVTs to analyze equipment signatures and identify anomalies that are precursor indicators of potential equipment failure. When an anomaly is detected, there is a likelihood of potential failure of monitored equipment, the system alerts the user with visual alarms including alarm trend charts and indicator lights on a oneline diagram of the substation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Population genomic analysis reveals differential evolutionary histories and patterns of diversity across subgenomes and subpopulations of Brassica napus L.

The allotetraploid species Brassica napus L. is a global crop of major economic importance, providing canola oil (seed) and vegetables for human consumption and fodder and meal for livestock feed. Characterizing the genetic diversity present in the extant germplasm pool of B. napus is fundamental to better conserve, manage and utilize the genetic resources of this species. We used sequence-based genotyping to identify and genotype 30,881 SNPs in a diversity panel of 782 B. napus accessions, representing samples of winter and spring growth habits originating from 33 countries across Europe, Asia, and America. We detected strong population structure broadly concordant with growth habit and geography, and identified three major genetic groups: spring (SP), winter Europe (WE), and winter Asia (WA). Subpopulation-specific polymorphism patterns suggest enriched genetic diversity within the WA group and a smaller effective breeding population for the SP group compared to WE. Interestingly, the two subgenomes of B. napus appear to have different geographic origins, with phylogenetic analysis placing WE and WA as basal clades for the other subpopulations in the C and A subgenomes, respectively. Finally, we identified 16 genomic regions where the patterns of diversity differed markedly from the genome-wide average, several of which are suggestive of genomic inversions. The results obtained in this study constitute a valuable resource for worldwide breeding efforts and the genetic dissection and prediction of complex B. napus traits.

58 GEOSCIENCES↗

HOT CORE, OUTFLOWS, AND MAGNETIC FIELDS IN W43-MM1 (G30.79 FIR 10)

We present submillimeter spectral line and dust continuum polarization observations of a remarkable hot core and multiple outflows in the high-mass, star-forming region W43-MM1 (G30.79 FIR 10), obtained using the Submillimeter Array. A temperature of ∼400 K is estimated for the hot core using CH{sub 3}CN (J = 19-18) lines, with detections of 11 K-ladder components. The high temperature and the mass estimates for the outflows indicate high-mass star formation. The continuum polarization pattern shows an ordered distribution, and its orientation over the main outflow appears to be aligned with the outflow. The derived magnetic field indicates slightly super-critical conditions. While the magnetic and outflow energies are comparable, the B-field orientation appears to have changed from parsec scales to ∼0.1 pc scales during the core/star formation process.

79 ASTRONOMY AND ASTROPHYSICS↗