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At least 469 records · Page 26

Cooking methods and kitchen ventilation availability, usage, perceived performance and potential in Canadian homes

Cooking is a substantial contributor to air pollutant exposures in many residences. Effective use of kitchen ventilation can mitigate exposure; however, information on its availability, usage, and potential to increase its use across the population has been limited. This study aimed to obtain nationally representative information on cooking methods, kitchen ventilation availability and usage, and the potential for education to increase effective usage. An online survey was sent to a representative sample of Canadian homes to collect data on cooking methods, the presence and use of mechanical kitchen ventilation devices, perceived device performance, and willingness to implement mitigation strategies. Responses were weighted to match key demographic factors and analyzed using non-parametric statistics. Among the 4500 respondents, 90% had mechanical ventilation devices over the cooktop (66% of which were vented to the outside), and 30% reported regularly using their devices. Devices were used most often for deep-frying, followed by stir-frying, sautéing or pan-frying, indoor grilling, boiling or steaming. Almost half reported rarely or never using their ventilation devices during baking or oven self-cleaning. Only 10% were fully satisfied with their devices. More frequent use was associated with the device being vented to the outdoors, having more than two speed settings, quiet operation if only one speed, covering over half of the cooktop, and higher perceived effectiveness. After being informed of the benefits of kitchen ventilation, 64% indicated they would consider using their devices more often, preferentially using back burners with ventilation, and/or using higher ventilation device settings when needed. This study provides population-representative data on the most used cooking methods, kitchen ventilation availability and usage, and influencing factors in Canadian homes. Such data are needed for exposure assessments and evaluating the potential to mitigate cooking-related pollutant exposures via more effective use of kitchen ventilation. The data can be reasonably extrapolated to the United States, given the similarities in residential construction practices and cultural norms between the two countries.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Minimizing Cache Misses Using Minimum-Surface Bodies

A number of known techniques for improving cache performance in scientific computations involve the reordering of the iteration space. Some of these reorderings can be considered as coverings of the iteration space with the sets having good surface-to-volume ratio. Use of such sets reduces the number of cache misses in computations of local operators having the iteration space as a domain. First, we derive lower bounds which any algorithm must suffer while computing a local operator on a grid. Then we explore coverings of iteration spaces represented by structured and unstructured grids which allow us to approach these lower bounds. For structured grids we introduce a covering by successive minima tiles of the interference lattice of the grid. We show that the covering has low surface-to-volume ratio and present a computer experiment showing actual reduction of the cache misses achieved by using these tiles. For planar unstructured grids we show existence of a covering which reduces the number of cache misses to the level of structured grids. On the other hand, we present a triangulation of a 3-dimensional cube such that any local operator on the corresponding grid has significantly larger number of cache misses than a similar operator on a structured grid.

Frumkin, Michael↗

Check-Cases for Verification of 6-Degree-of-Freedom Flight Vehicle Simulations

The rise of innovative unmanned aeronautical systems and the emergence of commercial space activities have resulted in a number of relatively new aerospace organizations that are designing innovative systems and solutions. These organizations use a variety of commercial off-the-shelf and in-house-developed simulation and analysis tools including 6-degree-of-freedom (6-DOF) flight simulation tools. The increased affordability of computing capability has made highfidelity flight simulation practical for all participants. Verification of the tools' equations-of-motion and environment models (e.g., atmosphere, gravitation, and geodesy) is desirable to assure accuracy of results. However, aside from simple textbook examples, minimal verification data exists in open literature for 6-DOF flight simulation problems. This assessment compared multiple solution trajectories to a set of verification check-cases that covered atmospheric and exo-atmospheric (i.e., orbital) flight. Each scenario consisted of predefined flight vehicles, initial conditions, and maneuvers. These scenarios were implemented and executed in a variety of analytical and real-time simulation tools. This tool-set included simulation tools in a variety of programming languages based on modified flat-Earth, round- Earth, and rotating oblate spheroidal Earth geodesy and gravitation models, and independently derived equations-of-motion and propagation techniques. The resulting simulated parameter trajectories were compared by over-plotting and difference-plotting to yield a family of solutions. In total, seven simulation tools were exercised.

Murri, Daniel G.↗

To Exascale and Beyond—The Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM), a Performance Portable Global Atmosphere Model for Cloud-Resolving Scales

The new generation of heterogeneous CPU/GPU computer systems offer much greater computational performance but are not yet widely used for climate modeling. One reason for this is that traditional climate models were written before GPUs were available and would require an extensive overhaul to run on these new machines. In addition, even conventional “high–resolution” simulations don't currently provide enough parallel work to keep GPUs busy, so the benefits of such overhaul would be limited for the types of simulations climate scientists are accustomed to. The vision of the Simple Cloud-Resolving Energy Exascale Earth System (E3SM) Atmosphere Model (SCREAM) project is to create a global atmospheric model with the architecture to efficiently use GPUs and horizontal resolution sufficient to fully take advantage of GPU parallelism. After 5 years of model development, SCREAM is finally ready for use. In this paper, we describe the design of this new code, its performance on both CPU and heterogeneous machines, and its ability to simulate real-world climate via a set of four 40 day simulations covering all 4 seasons of the year.

54 ENVIRONMENTAL SCIENCES↗

First results from COPSS: The CO power spectrum survey

We present constraints on the abundance of carbon monoxide in the early universe from the CO Power Spectrum Survey. We utilize a data set collected between 2005 and 2008 using the Sunyaev–Zel’dovich Array (SZA), which was previously used to measure arcminute-scale fluctuations of the cosmic microwave background. This data set features observations of 44 fields, covering an effective area of 1.7 square degrees, over a frequency range of 27–35 GHz. Using the technique of intensity mapping, we are able to probe the CO(1–0) transition, with sensitivity to spatial modes between k = 0.5–2 h Mpc{sup −1} over a range in redshift of z = 2.3–3.3, spanning a comoving volume of 3.6 × 10{sup 6} h{sup −3} Mpc{sup 3}. We demonstrate our ability to mitigate foregrounds, and present estimates of the impact of continuum sources on our measurement. We constrain the CO power spectrum to P{sub CO} < 2.6 × 10{sup 4} μK{sup 2} (h{sup −1} Mpc){sup 3}, or Δ{sup 2}{sub CO}(k = 1 h Mpc{sup −1}) < 1.3 × 10{sup 3} μK{sup 2}, at 95% confidence. This limit resides near optimistic predictions for the CO power spectrum. Under the assumption that CO emission is proportional to halo mass during bursts of active star formation, this corresponds to a limit on the ratio of CO(1–0) luminosity to host halo mass of A{sub CO} < 1.2 × 10{sup −5} L{sub ⊙} M{sub ⊙}{sup −1}. Further assuming a Milky Way-like conversion factor between CO luminosity and molecular gas mass (α{sub CO} = 4.3 M{sub ⊙} (K km s{sup −1} pc{sup −2}){sup −1}), we constrain the global density of molecular gas to ρ{sub z∼3}(M{sub H{sub 2}})⩽2.8×10{sup 8} M{sub ⊙} Mpc{sup −3}.

79 ASTRONOMY AND ASTROPHYSICS↗

MINE 2.0: enhanced biochemical coverage for peak identification in untargeted metabolomics

Abstract Summary Although advances in untargeted metabolomics have made it possible to gather data on thousands of cellular metabolites in parallel, identification of novel metabolites from these datasets remains challenging. To address this need, Metabolic in silico Network Expansions (MINEs) were developed. A MINE is an expansion of known biochemistry which can be used as a list of potential structures for unannotated metabolomics peaks. Here, we present MINE 2.0, which utilizes a new set of biochemical transformation rules that covers 93% of MetaCyc reactions (compared to 25% in MINE 1.0). This results in a 17-fold increase in database size and a 40% increase in MINE database compounds matching unannotated peaks from an untargeted metabolomics dataset. MINE 2.0 is thus a significant improvement to this community resource. Availability and implementation The MINE 2.0 website can be accessed at https://minedatabase.ci.northwestern.edu. The MINE 2.0 web API documentation can be accessed at https://mine-api.readthedocs.io/en/latest/. The data and code underlying this article are available in the MINE-2.0-Paper repository at https://github.com/tyo-nu/MINE-2.0-Paper. MINE 2.0 source code can be accessed at https://github.com/tyo-nu/MINE-Database (MINE construction), https://github.com/tyo-nu/MINE-Server (backend web API) and https://github.com/tyo-nu/MINE-app (web app). Supplementary information Supplementary data are available at Bioinformatics online.

59 BASIC BIOLOGICAL SCIENCES↗

Massively parallel and universal approximation of nonlinear functions using diffractive processors

Nonlinear computation is essential for a wide range of information processing tasks, yet implementing nonlinear functions using optical systems remains a challenge due to the weak and power-intensive nature of optical nonlinearities. Overcoming this limitation without relying on nonlinear optical materials could unlock unprecedented opportunities for ultrafast and parallel optical computing systems. Here, we demonstrate that large-scale nonlinear computation can be performed using linear optics through optimized diffractive processors composed of passive phase-only surfaces. In this framework, the input variables of nonlinear functions are encoded into the phase of an optical wavefront—e.g., via a spatial light modulator (SLM)—and transformed by an optimized diffractive structure with spatially varying point-spread functions to yield output intensities that approximate a large set of unique nonlinear functions–all in parallel. We provide proof establishing that this architecture serves as a universal function approximator for an arbitrary set of bandlimited nonlinear functions, also covering wavelength-multiplexed nonlinear functions as well as multi-variate and complex-valued functions that are all-optically cascadable. Our analysis also indicates the successful approximation of typical nonlinear activation functions commonly used in neural networks, including the sigmoid, tanh, ReLU (rectified linear unit), and softplus. We numerically demonstrate the parallel computation of one million distinct nonlinear functions, accurately executed at wavelength-scale spatial density at the output of a diffractive optical processor. Furthermore, we experimentally validated this framework using in situ optical learning and approximated 35 unique nonlinear functions in a single shot using a compact setup consisting of an SLM and an image sensor. These results establish diffractive optical processors as a scalable platform for massively parallel universal nonlinear function approximation, paving the way for new capabilities in analog optical computing based on linear materials.

Rahman, Md Sadman Sakib [University of California,↗

Search for the Rare Decay $B_s^0 \to \mu^+\mu^-$ at D0

Results of the search for the rare decay B 0 s → μ + μ - using data collected by the D0 detector at the Fermilab Tevatron collider are presented. This analysis covers the full Run II data set, corresponding to approximately 10.4 fb -1 of integrated luminosity in p¯p collisions at a center of mass energy of 1.96 TeV. The analysis used new variables and a multivariate technique to improve the background reduction. After seeing fewer events than expected from background, a new Tevatron best observed limit was set on the branching fraction of the decay at B(B 0 s → μ + μ - ) < 15 x 10 -9 (12 x 10 -9 ) at the 95% (90%) C.L.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Research Needs for Trusted Analytics in National Security Settings

As artificial intelligence, machine learning, and statistical modeling methods become commonplace in national security applications, the drive to create trusted analytics becomes increasingly important. The goal of this report is to identify areas of research that can provide the foundational understanding and technical prerequisites for the development and deployment of trusted analytics in national security settings. Our review of the literature covered several disjoint research communities, including computer science, statistics, human factors, and several branches of psychology and cognitive science, which tend not to interact with one another or cite each other's literatures. As a result, there exists no agreed-upon theoretical framework for understanding how various factors influence trust and no well-established empirical paradigm for studying these effects. This report therefore takes three steps. First, we define several key terms in an effort to provide a unifying language for trusted analytics and to manage the scope of the problem. Second, we outline an empirical perspective that identifies key independent, moderating, and dependent variables in assessing trusted analytics. Though not a substitute for a theoretical framework, the empirical perspective does support research and development of trusted analytics in the national security domain. Finally, we discuss several research gaps relevant to developing trusted analytics for the national security mission space.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A Correction for IUE UV Flux Distributions from Comparisons with CALSPEC

A collection of spectral energy distributions (SEDs) is available in the Hubble Space Telescope (HST) CALSPEC database that is based on calculated model atmospheres for pure hydrogen white dwarfs (WDs). A much larger set (∼100,000) of UV SEDs covering the range (1150–3350 Å) with somewhat lower quality are available in the IUE database. IUE low-dispersion flux distributions are compared with CALSPEC to provide a correction that places IUE fluxes on the CALSPEC scale. While IUE observations are repeatable to only 4%–10% in regions of good sensitivity, the average flux corrections have a precision of 2%–3%. Our re-calibration places the IUE flux scale on the current UV reference standard and is relevant for any project based on IUE archival data, including our planned comparison of GALEX to the corrected IUE fluxes. IUE SEDs may be used to plan observations and cross-calibrate data from future missions, so the IUE flux calibration must be consistent with HST instrumental calibrations to the best possible precision.

79 ASTRONOMY AND ASTROPHYSICS↗

A Gigaparsec-scale Hydrodynamic Volume Reconstructed with Deep Learning

The next generation of spectroscopic surveys will map the large-scale structure of the Universe at high redshifts (2 ≤ z ≤ 5) using millions of quasar spectra, enabling major advances in constraining both the standard cosmological model and its extensions. Robust cosmological analyses of these data sets require numerical simulations that both cover gigaparsec volumes and resolve features on ∼10 kpc scales and smaller. However, running such large-volume, high-resolution hydrodynamic simulations is computationally prohibitive. We present a generative deep learning model that enhances a low-resolution, gigaparsec-scale (960 h −1 Mpc) hydrodynamic simulation using a smaller (80 h −1 Mpc) high-resolution input hydrodynamic simulation as training data. The resulting enhanced simulation reproduces the line-of-sight power spectrum to within ∼10% and the three-dimensional power spectrum at the ∼20% level at intermediate to small scales (k ≲ 2 h Mpc −1 ). Our method shows strong promise for producing realistic simulations for cosmological analyses with current surveys such as the Dark Energy Spectroscopic Instrument and upcoming next-generation experiments, but further improvements are needed to accurately recover the large-scale modes. We publicly release the enhanced hydrodynamic simulation, along with a halo catalog from a companion N-body dark matter simulation to support the calibration of data analysis pipelines for these large-scale surveys.

Convolutional neural networks↗

Analysis of PV Fleet Performance in Western United States During August 2020 Extreme Heat Wave

Starting in June 2020 through the end of that year, the western and central United States experienced a widespread heat wave and drought, which resulted in US$5.44 billion (CPI-adjusted) worth of damages. The ongoing heat and drought produced record large wildfires across the region, responsible for an additional US$19.9 billion in damage. These natural disasters directly impacted the energy system in the western US, leading to power blackouts in August 2020. In this work, we analyze the NLR PV Fleets data set, focusing on the geographic area covered by the Western Coordinating Council (WECC). We find that over the 10-day period from August 14 through 24, the median PV system produced 12% lower energy than expected, with some locations experiencing total losses of around 30%. Analyzing the spatial-temporal structure of the data and supplementing with limited operational current and voltage data where available, we find that system underperformance was more strongly impacted by irradiance reduction from wildfire smoke rather than by the high heat itself.

14 SOLAR ENERGY↗

Experimental and Analytical Investigation of the Coolant Flow Characteristics in Cooled Turbine Airfoils

The flow characteristics of turbine airfoil cooling system components were experimentally investigated. Flow models representative of leading edge impingement, impingement with crossflow (midchord cooling), pin fins, feeder supply tube, and a composite model of a complete airfoil flow system were tested. Test conditions were set by varying pressure level to cover the Mach number and Reynolds number range of interest in advanced turbine applications. Selected geometrical variations were studied on each component model to determine these effects. Results of these tests were correlated and compared with data available in the literature. Orifice flow was correlated in terms of discharge coefficients. For the leading edge model this was found to be a weak function of hole Mach number and orifice-to-impinged wall spacing. In the impingement with crossflow tests, the discharge coefficient was found to be constant and thus independent of orifice Mach number, Reynolds number, crossflow rate, and impingement geometry. Crossflow channel pressure drop showed reasonable agreement with a simple one-dimensional momentum balance. Feeder tube orifice discharge coefficients correlated as a function of orifice Mach number and the ratio of the orifice-to-approach velocity heads. Pin fin data was correlated in terms of equivalent friction factor, which was found to be a function of Reynolds number and pin spacing but independent of pin height in the range tested.

Damerow, W. P.↗

Infrared Spectrometer Investigations of the Planets and Planetary Satellites

A set of cooled filter wheel spectrometers covering the wavelength range 2.8-24 micron have been constructed and tested. The two short wavelength systems (2.8-5.6 micron and 7-14 micron) have been found to be very useful and provide a substantial increase in signal to noise over previous systems. The 12-24 micron system, although still very useful, suffers from a low transmittance filter wheel and possibly poor wavelength resolution, intrinsic to the filter wheel.

Gillett, E. C.↗

LACIE performance predictor final operational capability program description, volume 2

Given the swath table files, the segment set for one country and cloud cover data, the SAGE program determines how many times and under what conditions each segment is accessed by satellites. The program writes a record for each segment on a data file which contains the pertinent acquisition data. The weather data file can also be generated from a NASA supplied tape. The Segment Acquisition Selector Program (SACS) selects data from the segment reference file based upon data input manually and from a crop window file. It writes the extracted data to a data acquisition file and prints two summary reports. The POUT program reads from associated LACIE files and produces printed reports. The major types of reports that can be produced are: (1) Substrate Reference Data Reports, (2) Population Mean, Standard Deviation and Histogram Reports, (3) Histograms of Monte Carlo Statistics Reports, and (4) Frequency of Sample Segment Acquisitions Reports.

Source record↗

Spectral decomposition of a matrix using the generalized sign matrix

An algorithm for spectral decomposition is presented which does not require knowledge of eigenvalues and eigenvectors. A set of eigenprojectors are defined which covers the entire spectrum of a matrix, and special attention is given to the projection on the zero eigenvalue. Some useful applications are discussed in the paper.

Denman, E. D.↗

Mapping and monitoring renewable resources with space SAR

The SEASAT-A SAR and SIR-A imagery was examined to evaluate the quality and type of information that can be extracted and used to monitor renewable resources on Earth. Two tasks were carried out: (1) a land cover classification study which utilized two sets of imagery acquired by the SEASAT-A SAR, one set by SIR-A, and one LANDSAT set (4 bands); and (2) a change detection to examine differences between pairs of SEASAT-A SAR images and relates them to hydrologic and/or agronomic variations in the scene.

Ulaby, F. T.↗

Theoretical and experimental studies in support of the geophysical fluid flow experiment

Computer programming was completed for digital acquisition of temperature and velocity data generated by the Geophysical Fluid Flow Cell (GFFC) during the upcoming Spacelab 3 mission. A set of scenarios was developed which covers basic electro-hydrodynamic instability, highly supercritical convection with isothermal boundaries, convection with imposed thermal forcing, and some stably stratified runs to look at large-scale thermohaline ocean circulations. The extent to which the GFFC experimental results apply to more complicated circumstances within the Sun or giant planets was assessed.

Hart, J.↗