Forecasting influenza activity using meteorological and Google Flu Trends data.
Abstract not provided.
Lefantzi, Sophia↗
SEARCH · Engineering Papers
Results for “active data”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Metatranscriptomics reveals a shift in microbial community composition and function during summer months in a coastal marine environment
Abstract Temperate coastal marine waters are often thermally stratified from spring through fall but can be dynamic and disrupted by tidal currents and wind‐driven upwelling. These mixing events introduce deeper, cooler water with a higher partial pressure of CO 2 (pCO2) and its associated microbial communities to the surface. Anecdotally, these events impact shellfish hatcheries and farms, warranting improved understanding of changes in composition and activity of marine microbial communities in relation to environmental processes. To characterize both compositional and functional changes associated with abiotic factors, here, we generate a reference metatranscriptome from the Strait of Georgia over representative seasons and analyze metatranscriptomic profiles of the microorganisms present within intake water containing different pCO 2 levels at a shellfish hatchery in British Columbia from June through October. Abiotic factors studied include pH, temperature, alkalinity, aragonite, calcite, and pCO 2 . Community composition changes were observed to occur at broad taxonomic levels and most notably to vary with temperature and pCO 2 . Functional gene expression profiles indicated a strong difference between early (June–July) and late summer (August–October) associated with viral activity. The taxonomic data suggest this could be due to the termination of cyanobacteria and phytoplankton blooms by viral lysis in the late season. Functional analysis indicated fewer differentially expressed transcripts associated with abiotic variables (e.g., pCO 2 ) than with the temporal effect. Microbial composition and activity in these waters vary with both short‐term effects observed alongside abiotic variation and long‐term effects observed across seasons. The analysis of both taxonomy and functional gene expression simultaneously in the same samples by environmental RNA (eRNA metatranscriptomics) provided a more comprehensive view for monitoring water bodies than either would in isolation.
Sutherland, Ben J. G.↗
Activity coefficient acquisition with thermodynamics–informed active learning for phase diagram construction
This work explores the use of thermodynamics-informed Gaussian processes (GPs) and active learning (AL) to model activity coefficients and construct phase diagrams. Relying on synthetic data generated from an excess Gibbs energy model, GPs were found to accurately describe the activity coefficients of several binary mixtures across large composition and temperature ranges. Moreover, GPs could estimate their own uncertainty and identify composition/temperature regions where activity coefficient data provide the most information to the models. This was leveraged to build AL algorithms targeted at modeling phase equilibria. In many cases, a single active-learning-acquired data point was sufficient to describe the phase diagrams studied. Lastly, the ability of AL to greatly reduce the amount of data needed to obtain accurate models was further verified on experimental case studies, namely individual ion activity coefficients, the solid–liquid and vapor–liquid equilibrium of deep eutectic solvents, and phase equilibria in ternary mixtures.
25 ENERGY STORAGE↗
Structure-Based Alteration of Substrate Specificity and Catalytic Activity of Sulfite Oxidase from Sulfite Oxidation to Nitrate Reduction
Eukaryotic sulfite oxidase is a dimeric protein that contains the molybdenum cofactor and catalyzes the metabolically essential conversion of sulfite to sulfate as the terminal step in the metabolism of cysteine and methionine. Nitrate reductase is an evolutionarily related molybdoprotein in lower organisms that is essential for growth on nitrate. In this study, we describe human and chicken sulfite oxidase variants in which the active site has been modified to alter substrate specificity and activity from sulfite oxidation to nitrate reduction. On the basis of sequence alignments and the known crystal structure of chicken sulfite oxidase, two residues are conserved in nitrate reductases that align with residues in the active site of sulfite oxidase. On the basis of the crystal structure of yeast nitrate reductase, both positions were mutated in human sulfite oxidase and chicken sulfite oxidase. The resulting double-mutant variants demonstrated a marked decrease in sulfite oxidase activity but gained nitrate reductase activity. An additional methionine residue in the active site was proposed to be important in nitrate catalysis, and therefore, the triple variant was also produced. The nitrate reducing ability of the human sulfite oxidase triple mutant was nearly 3-fold greater than that of the double mutant. To obtain detailed structural data for the active site of these variants, we introduced the analogous mutations into chicken sulfite oxidase to perform crystallographic analysis. The crystal structures of the Mo domains of the double and triple mutants were determined to 2.4 and 2.1 {angstrom} resolution, respectively.
59 BASIC BIOLOGICAL SCIENCES↗
Application-driven Privacy-preserving Data Publishing with Correlated Attributes
Recent advances in computing have allowed for the possibility to collect large amounts of data on personal activities and private living spaces. To address the privacy concerns of users in this environment, we propose a novel framework called PR-GAN that offers privacy-preserving mechanism using generative adversarial networks. Given a target application, PR-GAN automatically modifies the data to hide sensitive attributes - which may be hidden and can be inferred by machine learning algorithms - while preserving the data utility in the target application. Unlike prior works, the public's possible knowledge of the correlation between the target application and sensitive attributes is built into our modeling. We formulate our problem as an optimization problem, show that an optimal solution exists and use generative adversarial networks (GAN) to create perturbations. We further show that our method provides privacy guarantees under the Pufferfish framework, an elegant generalization of the differential privacy that allows for the modeling of prior knowledge on data and correlations. Through experiments, we show that our method outperforms conventional methods in effectively hiding the sensitive attributes while guaranteeing high performance in the target application, for both property inference and training purposes. Finally, we demonstrate through further experiments that once our model learns a privacy-preserving task, such as hiding subjects' identity, on a group of individuals, it can perform the same task on a separate group with minimal performance drops.
97 MATHEMATICS AND COMPUTING↗
FORMATION OF MOLECULAR HYDROGEN FROM METHANE ICE
To study the formation of molecular hydrogen in the wake of the processing of interstellar ices by energetic cosmic-ray particles, we investigated the interaction of energetic electrons, as formed in the track of galactic cosmic-ray particles, with deuterated methane ices (CD{sub 4}) at 11 K. The energetic electrons mimic energy-transfer processes that occur in the track of the trajectories of energetic cosmic-ray particles; deuterated methane ice was utilized to discriminate the molecular deuterium (m/z = 4) formed during the radiation exposure from the residual molecular hydrogen gas (m/z = 2) released inside the ultrahigh vacuum scattering chamber from outgassing of the stainless steel material. The ices were characterized online and in situ using Fourier transform infrared spectroscopy, while the evolution of the molecular deuterium (D{sub 2}) into the gas phase was monitored using a mass spectrometer. A mass spectrometric signal proportional to the number density of the deuterium molecules generated inside the ice and released during the irradiation was analyzed kinetically using a set of coupled rate equations. From the fit to the experimental data, we obtain activation energies for the diffusion of atomic deuterium (E{sub 0} = 37 {+-} 1 meV), and for the desorption of atomic (E{sub 1} = 32 {+-} 1 meV) and molecular deuterium (E{sub 2} = 32 {+-} 1 meV). These energies are placed in context and then transferred to atomic and molecular hydrogen to yield astrophysically relevant data. The experimental yield of molecular deuterium is then used to calculate the formation rate of molecular hydrogen due to cosmic-ray interaction with ice-covered grains in dense clouds.
79 ASTRONOMY AND ASTROPHYSICS↗
Characterization of the Pulsed Radiation Environment in FREC-II at the ACRR
Ongoing tests at the Annular Core Research Reactor (ACRR) at Sandia National Laboratories aim to measure temperature and strain in materials exposed to a transient neutron-photon environment. Radiation transport and finite element analysis codes are used to predict the thermal-structural response of test articles exposed in the reactor. Strain and temperature sensors fielded on test articles provide validation data for finite element models, while active and passive radiation dosimetry provides data for MCNP models. The ACRR is able to provide pulse energies of 40 - 300 MJ per pulse with pulse times of 7 - 100 milliseconds. The pulse power is higher than many of the other research reactors due to its unique high heat capacity UO{sub 2}-BeO fuel in the central reactor. Additionally, the Fuel Ringed External Cavity (FREC-II) contains U-ZrH fuel. Future tests at the ACRR plan to field test assemblies in the Fuel Ringed External Cavity (FREC-II) and expose the test articles to the transient anisotropic radiation field experienced in the cavity. The FREC-II is coupled with the ACRR core and is used to test larger specimens, and the radiation environment can be shaped/modified to the needs of the experiment. The FREC-II was designed to provide an irradiation cavity with a strong flux gradient favoring the central cavity side. Neutron fluence also varies by height in the cavity, with a peak level slightly below the fuel rod vertical centerline. Tests were conducted in 2014 to measure the thermal-structural response of test articles exposed in the central cavity. Those tests in the central cavity fielded Nickel activation foils to record the neutron fluence at various locations around the test assembly. Foil data was later used to highlight uncertainties between thermo-structural response models and the measured temperature and strain. Studies performed in 2015 exposed large arrays of activation foils and thermo-luminescent dosimeters (TLD) in the FREC-II cavity in order to map out the neutron and photon spectrum at many locations. This type of passive measurement was shown to be too simple for performing thermo-structural simulations of a test article in response to multiple pulsed-reactor exposures. The Depleted Uranium Strain and Temperature - Enhanced Response (DUSTER-II) experiments will expose test assemblies to reactor pulses in the FREC-II cavity. To prepare for these experiments, the MCNP model will be compared with June 2016 experimental results from the pulses with the FREC-II coupled with the ACRR. These comparisons will provide an accurate model to be implemented in further studies. (authors)
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
Genome dependent Cas9/gRNA search time underlies sequence dependent gRNA activity
Abstract CRISPR-Cas9 is a powerful DNA editing tool. A gRNA directs Cas9 to cleave any DNA sequence with a PAM. However, some gRNA sequences mediate cleavage at higher efficiencies than others. To understand this, numerous studies have screened large gRNA libraries and developed algorithms to predict gRNA sequence dependent activity. These algorithms do not predict other datasets as well as their training dataset and do not predict well between species. Here, to better understand these discrepancies, we retrospectively examine sequence features that impact gRNA activity in 44 published data sets. We find strong evidence that gRNA sequence dependent activity is largely influenced by the ability of the Cas9/gRNA complex to find the target site rather than activity at the target site and that this drives sequence dependent differences in gRNA activity between different species. This understanding will help guide future work to understand Cas9 activity as well as efforts to identify optimal gRNAs and improve Cas9 variants.
59 BASIC BIOLOGICAL SCIENCES↗
1995 OKI Household Activity and Travel Report Survey
The OKI Household Activity and Travel Report Survey 1995, conducted by Market Opinion Research, gathered household activity and travel data from 3,000 households within the OKI region (Ohio, Kentucky, and Indiana Council of Governments' service area). The region covers over 2,615 square miles and is home to 697,468 households (over 1.75 million people). The primary purpose of this study was to provide OKI with a new database of travel patterns and behavior to assist in updating the region's transportation models. Respondents were asked to report their activities for a 24-hour period from 3:00 a.m. to 3:00 a.m. on an assigned activity day. The survey included weekday assignments only from October 4, 1995, to November 30, 1995.
1Hz data↗
Evaluation of oxygen reduction activity by the thin-film rotating disk electrode methodology: The effects of potentiodynamic parameters
Here, an accurate and efficient assessment of activity is critical for the research and development of electrocatalysts for oxygen reduction reaction (ORR). Currently, the methodology combining the thin-film rotating disk electrode (TF-RDE) and potentiodynamic polarization is the most commonly used to pre-evaluate ORR activity, acquire kinetic data (i.e., kinetic current, Tafel slope, etc.), and gain understanding of the ORR mechanism. However, it is often neglected that appropriate potentiodynamic parameters have to be chosen to obtain reliable results. We first evaluate the potentiodynamic and potentiostatic polarization measurements with TF-RDE to examine the ORR activity of Pt nanoelectrocatalyst. Furthermore, our results demonstrate that besides depending on the nature of electrocatalyst, the apparent ORR kinetics also strongly depends on the associated potentiodynamic parameters, such as scan rate and scan region, which have a great effect on the coverage of adsorbed OH ad /O ad on Pt surface, thereby affecting the ORR activities of both nanosized and bulk Pt. However, the apparent Tafel slopes remained nearly the same, indicating that the ORR mechanism in all the measurements was not affected by different potentiodynamic parameters.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Remediation strategy, capping construction and ongoing monitoring for the mill tailings pond, Ningyo-Toge uranium mine, Japan
Ningyo-toge Uranium Mine is subject to the environmental remediation. The main purposes are to take measures to ensure the radiation protection from the exposure pathways to humans in future, and to prevent the occurrence of mining pollution. The Yotsugi Mill Tailings Pond in the Ningyo-toge Uranium Mine has deposited mining waste and impounded water as a buffer reservoir before it is transferred to the Water Treatment Facility. It is located at the upstream of the water-source river and as the impact on its environment in case of earthquake is estimated significant, the highest priority has been put to it among mine-related facilities in the Mine. So far, basic concept has been examined and a great number of data has been acquired, and using the data, some remediation activities have already done, including capping construction for the upstream part of the Mill Tailings Pond. The capping is to reduce rainwater penetration to lower the burden of water treatment, and to reduce radon exhalation and dose rates. Only natural materials are used to alleviate the future maintenance. Data, including settlement amount and underground temperature is now being acquired and accumulated to verify the effectiveness of the capping, and used for the future remediation of the Downstream with revision of its specifications if necessary. (authors)
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Advanced Manufacturing Basic Entity Relationships Ontology
A data ontology defined using the W3C Web Ontology Language (OWL) format. It defines classes and attributes for objects directly implicated in manufacturing such as materials, preform geometries, and manufacturing processes and settings. It also includes classes to describe entities that are instrumental to making digital twins and performing predictive activities on manufacturing data such as designs of experiment and predictive models.
Harris, BrennanKay↗
Efficient kinetic thermal inverse modeling for organic material decomposition
The prevalent use of organic materials in manufacturing is a fire safety concern, and motivates the need for predictive thermal decomposition models. A critical component of predictive modeling is numerical inference of kinetic parameters from bench scale data. Currently, an active area of computational pyrolysis research focuses on identifying efficient, robust methods for optimization. This paper demonstrates that kinetic parameter calibration problems can successfully be solved using classical gradient-based optimization. We explore calibration examples that exhibit characteristics of concern: high nonlinearity, high dimensionality, complicated schemes, overlapping reactions, noisy data, and poor initial guesses. The examples demonstrate that a simple, non-invasive change to the problem formulation can simultaneously avoid local minima, avoid computation of derivative matrices, achieve a computational efficiency speedup of 10x, and make optimization robust to perturbations of parameter components. Techniques from the mathematical optimization and inverse problem communities are employed. By re-examining gradient-based algorithms, we highlight opportunities to develop kinetic parameter calibration methods that should outperform current methods.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Factorization Machine‐Based Active Learning for Functional Materials Design with Optimal Initial Data
The optimization of functional materials is important to enhance their properties, but their complex geometries pose great challenges to optimization. Data-driven algorithms efficiently navigate such complex design spaces by learning relationships between material structures and performance metrics to discover high-performance functional materials. Surrogate-based active learning, continually improving its surrogate model by iteratively including high-quality data points, has emerged as a cost-effective data-driven approach. Furthermore, it can be coupled with quantum computing to enhance optimization processes, especially when paired with a special form of surrogate model (i.e., quadratic unconstrained binary optimization), formulated by factorization machine (FM). However, current practices often overlook the variability in design space sizes when determining the initial data size for optimization. In this work, we investigate the optimal initial data sizes required for efficient convergence across various design space sizes. By employing averaged piecewise linear regression, we identify initiation points where convergence begins, highlighting the crucial role of employing adequate initial data in achieving efficient optimization. These results contribute to the efficient optimization of functional materials by ensuring faster convergence and reducing computational costs in FM-based active learning.
active learning↗
Accelerating CO2 Storage Site Characterization through a New Understanding of Favorable Formation Properties and the Impact of Core-Scale Heterogeneities
CO2 sequestration in deep geologic formations can permanently reduce atmospheric CO2 emissions and help to abate climate change. Target formations must undergo a time- and resource-intensive site evaluation process, assessing storage capacity, environmental safety, and suitability for CO2 trapping via reactive transport models based on data from a limited number of core samples. As such, simulations are often simplified and omit heterogeneities in formation properties that may be significant but are not well understood. To facilitate more rapid site assessment, this work first defines the aquifer properties of favorable storage formations through the analysis of promising and active storage sites. Data show quartz is the most prevalent formation mineral with carbonate minerals, highly reactive with injected CO2, present in over 75% of formations. Porosity and permeability data are highly clustered at 10–30% and 10–1000 mD. Field-scale reactive transport simulations are then constructed and used to analyze CO2 trapping efficiency. The models consider porosity and carbonate mineral heterogeneity as well as the impacts of typical temperature gradients. Simulated sequestration efficiencies are compared to results from a comparable homogenous model to understand the implications of aquifer non-uniformities. The results show a lower sequestration efficiency in the homogeneous model during the injection phase. During the post-injection phase, the homogenization of porosity and carbonate mineralogy results in a higher sequestration efficiency. Incorporating the temperature gradient also increases the sequestration efficiency. Importantly, the maximum deviation between the homogeneous and heterogeneous simulations at the end of the 50-year study period is only ~10%. Larger impacts may be incurred for properties outside the defined, promising ranges suggested here.
Environmental Sciences & Ecology↗
Rock Valley Accelerated Weight Drop Seismic Data Processing and Picking of P-wave and S-wave Arrival Times
Rock Valley, in the southern end of the Nevada National Security Site, hosts a fault system that was responsible for a shallow (< 3 km below surface ) magnitude 3.7 earthquake in May 1993. In order to better understand this system, seismic properties of the shallow subsurface need to be better constrained. In April and May of 2021, accelerated weight drop (AWD) active-source seismic data were recorded in order to measure P- and S-wave travel-times for the area. This report describes the processing and phase picking of the recorded seismic waveforms. In total, we picked 7,982 P-wave arrivals at offsets up to ~2500 m, and 4,369 S-wave arrivals at offsets up to ~2200 m. These travel-time picks can be inverted for shallow P-wave and S-wave velocity structure in future studies.
58 GEOSCIENCES↗
C/2010 U3 (Boattini): A Bizarre Comet Active at Record Heliocentric Distance
We present a photometric and dynamical study of comet C/2010 U3 (Boattini), which was seen active in prediscovery data as early as 2005 November at a new inbound record heliocentric distance of r {sub H} = 25.8 au. Two outburst events around 2009 and 2017 were observed. The coma and tail of the comet consist of dust grains of ~10 μm in radius, ejected protractedly at speeds ≲50 m s{sup -1} near the subsolar point, and are subjected to the Lorentz force, solar gravitation, and radiation pressure force all together. The prolonged activity indicates that sublimation of supervolatiles (e.g., CO, CO{sub 2}) is at play, causing a net mass-loss rate ≳1 kg s{sup -1}. To sustain the mass loss, the nucleus radius has to be ≳0.1 km. The color of the cometary dust, similar to other long-period comets, is redder than the solar colors, but we also observed potential color variations when the comet was at 10 < r {sub H} < 15 au, concurrent with the onset of crystallization of amorphous water ice, if at all. Using publicly available and our refined astrometric measurements, we estimated the precise trajectory of the comet and propagated it backward to its previous perihelion. We found that the comet visited the planetary region 1.96 ± 0.04 Myr ago, with barycentric perihelion distance q = 8.364 ± 0.004 au. Thus, C/2010 U3 (Boattini) is almost certainly a dynamically old comet from the Oort cloud, and the observed activity cannot be caused by retained heat from the previous apparition.
79 ASTRONOMY AND ASTROPHYSICS↗
Diagnosing United States hurricane landfall risk: An alternative to count-based methodologies: Diagnosing U.S. Hurricane Landfall Risk
Assessing hurricane landfall risk is of immense public utility, yet extant methods of diagnosing annual tropical cyclone (TC) activity demonstrate no skill in diagnosing U.S. hurricane landfalls. Atlantic TC count itself has limited skill, explaining less than 20% of interannual variance in landfall incidence. Using extended landfall activity and reanalysis data sets, we employed empirical Poisson modeling to produce a landfall diagnostic index (LDI), incorporating spatially and temporally averaged upper level divergence, relative sea surface temperature, meridional wind, and zonal shear vorticity. LDI captures 31% of interannual variability of U.S. hurricane landfalls and offers physical insight into why indices that successfully capture TC activity fail to diagnose landfalls: there is inherent tension between conditions likely to steer hurricanes toward the U.S. and conditions favorable for TC development. Given this tension, attempting to diagnose, predict, or understand TC count is inadequate for quantifying societal impacts due to landfalling hurricanes.
Geology↗