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Surveying Clay Mineral Diversity in the Murray Formation, Gale Crater, Mars
One of the primary science goals of Mars Science Laboratory (MSL) is to investigate layered clay mineral-bearing deposits outcropping in the lower NW slopes of Aeolis Mons (Mt. Sharp) detected from orbit. Martian clay mineral-bearing layered rocks are of particular interest because they are potential markers of sedimentary deposits formed in habitable aqueous environments. The CheMin X-ray diffraction (XRD) instrument aboard MSL has documented clay minerals in various drill samples during its traverse of Gale Crater's floor and ascent of Mt. Sharp. Previously, the high concentrations of clay minerals (approximately 20 wt.%) detected in drill powders of mudstone (Sheepbed member) at Yellowknife Bay (YKB) allowed their detailed characterization. Drill powders recovered from lacustrine mudstones of the Sheepbed member at YKB contain smectite clay minerals. Based on the position of 02l reflections in XRD patterns, which serve as an indicator of octahedral occupancy, the smectites are Fe-bearing, trioctahedral species analogous to ferrian saponites from terrestrial deposits. The smectites are thought to have been formed through a process of isochemical aqueous alteration of detrital olivine close to the time of sediment deposition under anoxic to poorly oxidizing conditions. The clay minerals are key indicators that the lake waters were benign and habitable at the time. Clay minerals were detected at other locations during MSL's traverse, including samples from the Pahrump Hills, but lower abundances and overlapping peaks from crystalline phases in XRD patterns hamper in-depth analysis.
Neutrino event selection in the MicroBooNE liquid argon time projection chamber using Wire-Cell 3D imaging, clustering, and charge-light matching
An accurate and efficient event reconstruction is required to realize the full scientific capability of liquid argon time projection chambers (LArTPCs). The current and future neutrino experiments that rely on massive LArTPCs create a need for new ideas and reconstruction approaches. Wire-Cell, proposed in recent years, is a novel tomographic event reconstruction method for LArTPCs. The Wire-Cell 3D imaging approach capitalizes on charge, sparsity, time, and geometry information to reconstruct a topology-agnostic 3D image of the ionization electrons prior to pattern recognition. A second novel method, the many-to-many charge-light matching, then pairs the TPC charge activity to the detected scintillation light signal, thus enabling a powerful rejection of cosmic-ray muons in the MicroBooNE detector. A robust processing of the scintillation light signal and an appropriate clustering of the reconstructed 3D image are fundamental to this technique. In this paper, we describe the principles and algorithms of these techniques and their successful application in the MicroBooNE experiment. A quantitative evaluation of the performance of these techniques is presented. Using these techniques, a 95% efficient pre-selection of neutrino charged-current events is achieved with a 30-fold reduction of non-beam-coincident cosmic-ray muons, and about 80% of the selected neutrino charged-current events are reconstructed with at least 70% completeness and 80% purity.
Chloro-Modified Magnetic Fe{sub 3}O{sub 4}@MCM-41 Core–Shell Nanoparticles for L-Asparaginase Immobilization with Improved Catalytic Activity, Reusability, and Storage Stability
This paper describes a new support that permits to efficient immobilization of L-asparaginase (L-ASNase). For this purpose, Fe{sub 3}O{sub 4} magnetic nanoparticles were synthesized and coated by MCM-41. 3-chloropropyltrimethoxysilane (CPTMS) was used as a surface modifying agent for covalent immobilization of L-ASNase on the magnetic nanoparticles. The chemical structure; thermal, morphological, and magnetic properties; chemical composition; and zeta potential value of Fe{sub 3}O{sub 4}@MCM-41-Cl were characterized by Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), differential thermal analysis (DTA), differential scanning calorimetry (DSC), vibrating sample magnetometer (VSM), scanning electron microscope (SEM), energy dispersive X-ray (EDX), X-ray diffraction patterns (XRD), and zeta-potential measurement. The immobilization efficiency onto Fe{sub 3}O{sub 4}@MCM-41-Cl was detected as 63%. The reusability, storage, pH, and thermal stabilities of the immobilized L-ASNase were investigated and compared to that of soluble one. The immobilized enzyme maintained 42.2% of its original activity after 18 cycles of reuse. Furthermore, it was more stable towards pH and temperature compared with soluble enzyme. The Michaelis–Menten kinetic properties of immobilized L-ASNase showed a lower V{sub max} and a similar K{sub m} compared to soluble L-ASNase. Immobilized enzyme had around 47 and 32.5% residual activity upon storage a period of 28 days at 4 and 25 °C, respectively. In conclusion, the Fe{sub 3}O{sub 4}@MCM-41-Cl@L-ASNase core–shell nanoparticles could successfully be used in industrial and medical applications.
Effects of the Grazing Incidence Geometry on X-ray Photon Correlation Spectroscopy Measurements
X-ray photon correlation spectroscopy (XPCS) is a versatile tool to measure dynamics on the nanometer to micrometer scale in bulk samples. XPCS has also been applied in grazing incidence (GI) geometry to examine the dynamics of surface layers. However, considering GI scattering experiments more universally, the GI geometry leads to a superposition of signals due to reflection and refraction effects, also known from the distorted-wave Born approximation (DWBA). In this paper, the impact of these reflection and refraction effects on the correlation analysis is determined experimentally by measuring grazing incidence transmission XPCS (GT-XPCS) and grazing incidence XPCS (GI-XPCS) simultaneously for a thin film sample, showing non-equilibrium dynamics. Here the results of the GI and GT geometry comparisons are combined within the framework of the standardly applied, simplified DWBA. These calculations allow identifying the main contributions of the detected signal from the leading scattering terms along the out-of-plane direction q z , which dominate the measured intensity pattern on the detector. In combination with the calculation of the non-linear effect of refraction in GTSAXS and GISAXS, it is possible to identify experimental conditions that can be chosen to run experiments and data analysis as close as possible to transmission XPCS and to explain which limitations for data interpretations are observed. Consequently, the beam exposure can be significantly reduced by using GI geometry only. Calculations of experimental settings prior to experiments are detailed to determine suitable q z regions for a variety of material systems measured in bulk-sensitive GI-XPCS experiments, allowing us to determine the scaling behavior of typical decay times as a function of q that is comparable to the scaling behavior obtained in distortion-free GT-XPCS or transmission XPCS experiments.
Mechanistic Understanding of the Growth Kinetics and Dynamics of Nanoparticle Superlattices by Coupling Interparticle Forces from Real-Time Measurements
Superlattice structures formed by nanoparticle (NP) self-assembly have attracted increasing attention due to their potential as a novel class of nanomaterials with enhanced physicochemical properties tailored by the assembly structure. However, many key questions remain regarding the correlation between the dynamics of individual NPs and the emerging superlattice patterns. Here we investigated the self-assembly of gold NPs by employing in situ transmission electron microscopy equipped with direct detection camera capabilities, which enabled us to track the rapid motion of individual nanoparticles in real time. By calculating the contributions of Brownian, van der Waals, hydrodynamic, and steric hindrance forces, we obtained a quantitative evaluation of the competitive interactions that drive the assembly process. Such competition between forces over various separations is critical for the kinetics of cluster growth, as well as the superlattice formation. Brownian motion resulted in random particle motions to form small-sized clusters, whose growth dynamics was characterized as reaction-limited aggregation. Subsequently, at relative short-range particle separation, van der Waals force overrode the Brownian force and dominantly drove the assembly process. In the close proximity, a delicate balance between van der Waals and steric hindrance forces surprisingly led to a unique dynamic nature of the assembled superlattice. Our study provides a fundamental understanding of coupling energetics and dynamics of NPs involved in the assembly process, enabling the control and design of the structure of nanoparticle superlattices.
Human Mobility to Parks Under the COVID-19 Pandemic and Wildfire Seasons in the Western and Central United States
In 2020, people's health suffered a great crisis under the dual effects of the COVID-19 pandemic and the extensive, severe wildfires in the western and central United States. Parks, including city, national, and cultural parks, offer a unique opportunity for people to maintain their recreation behaviors following the social distancing protocols during the pandemic. However, massive forest wildfires in western and central US, producing harmful toxic gases and smoke, pose significant threats to human health and affect their recreation behaviors and mobility to parks. In this study, we employed the geographically and temporally weighted regression (GTWR) Models to investigate how COVID-19 and wildfires jointly shaped human mobility to parks, regarding the number of visits per capita, dwell time, and travel distance to parks, during June - September 2020. We detected strong correlations between visitations and COVID-19 incidence in southern Montana, western Wyoming, Colorado, and Utah before August. However, the pattern was weakened over time, indicating the decreasing trend of the degree of concern regarding the pandemic. Moreover, more park visits and lower dwell time were found in parks further away from wildfires and less air pollution in Washington, Oregon, California, Colorado, and New Mexico, during the wildfire season, suggesting the potential avoidance of wildfires when visiting parks. This study provides important insights on people's responses in recreation and social behaviors when facing multiple severe crises that impact their health and wellbeing, which could support the preparation and mitigation of the health impacts from future pandemics and natural hazards.
Warning signals for eruptive events in spreading fires
Significance As flames spread through forests, buildings, or other complex environments, they can erupt, unexpectedly, into fast-moving conflagrations. This study presents evidence that characteristic patterns in the behavior of spreading flames may indicate when such eruptions are likely to occur. Our results rely on the detection of a phenomenon termed “critical slowing down”—the slowed recovery of multistable systems from perturbations as those systems approach tipping points. Using a bistable combustion system in which flames propagate either as small, slowly moving flames, or as large, rapidly moving flames stabilized by feedback between wind and fire, we provide evidence that slowing responses of spreading flames to sudden changes in environment (e.g., wind, terrain) may anticipate the onset of intense, feedback-stabilized modes of propagation.
FOREGROUND MODEL AND ANTENNA CALIBRATION ERRORS IN THE MEASUREMENT OF THE SKY-AVERAGED λ21 cm SIGNAL AT z∼ 20
The most promising near-term observable of the cosmic dark age prior to widespread reionization (z ∼ 15-200) is the sky-averaged λ21 cm background arising from hydrogen in the intergalactic medium. Though an individual antenna could in principle detect the line signature, data analysis must separate foregrounds that are orders of magnitude brighter than the λ21 cm background (but that are anticipated to vary monotonically and gradually with frequency, e.g., they are considered {sup s}pectrally smooth{sup )}. Using more physically motivated models for foregrounds than in previous studies, we show that the intrinsic spectral smoothness of the foregrounds is likely not a concern, and that data analysis for an ideal antenna should be able to detect the λ21 cm signal after subtracting a ∼fifth-order polynomial in log ν. However, we find that the foreground signal is corrupted by the angular and frequency-dependent response of a real antenna. The frequency dependence complicates modeling of foregrounds commonly based on the assumption of spectral smoothness. Our calculations focus on the Large-aperture Experiment to detect the Dark Age, which combines both radiometric and interferometric measurements. We show that statistical uncertainty remaining after fitting antenna gain patterns to interferometric measurements is not anticipated to compromise extraction of the λ21 cm signal for a range of cosmological models after fitting a seventh-order polynomial to radiometric data. Our results generalize to most efforts to measure the sky-averaged spectrum.
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.
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.
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.
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.
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.
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.
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.
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.
Application of computer processed multispectral data to the discrimination of land collapse (sinkhole) prone areas in Florida
Data were collected near Bartow, Florida, for the purpose of studying land collapse phenomena using remote sensing techniques. Data obtained using the multispectral scanner system consisted of various combinations of 18 spectral bands ranging from 0.4-14.0 microns and several types of photography. The multispectral data were processed on a special-purpose analog computer in order to detect moisture-stressed vegetation and to enhance terrain surface temperatures. The processed results were printed on film to show the patterns of distribution of the proposed hydrogeologic indicators.