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At least 253 records · Page 14

Quasar energy distributions. I - Soft X-ray spectra of quasars

As the initial stage of a study of quasar energy distributions (QEDs), Einstein IPC spectra of 24 quasars are presented. These are combined with previously reported IPC spectra to form a sample of 33 quasars with well-determined soft X-ray slopes. A correlation analysis shows that radio loudness, rather than redshift or luminosity, is fundamentally related to the X-ray slope. This correlation is not followed by higher energy spectra of active galaxies. Two components are required to explain both sets of results. The best-fit column densities are systematically smaller than the Galactic values. The same effect is not present in a sample of BL Lac objects, implying that the effect is intrinsic to the quasars and is caused by a low-energy turnup in the quasar spectra.

Wilkes, Belinda J.↗

The Correlation of Active and Passive Microwave Outputs for the Skylab S-193 Sensor

This paper presents the results of the correlation analysis of the Skylab S-193 13.9 GHz Radiometer/Scatterometer data. Computer analysis of the S-193 data shows more than 50 percent of the radiometer and scatterometer data are uncorrelated. The correlation coefficients computed for the data gathered over various ground scenes indicates the desirability of using both active and passive sensors for the determination of various Earth phenomena.

Krishen, K.↗

The correlation of active and passive microwave data for the Skylab S-193 sensor

This paper presents the results of the correlation analysis of the Skylab S-193 13.9 GHz Radiometer/Scatterometer data. Computer analysis of the S-193 data shows more than 50 percent of the radiometer and scatterometer data are uncorrelated. The correlation coefficients computed for the data gathered over various ground scenes indicates the desirability of using both active and passive sensors for the determination of various Earth phenomena.

Krishen, Kumar↗

A Cross-correlation Study between IceCube Neutrino Events and the FERMI Unresolved Gamma-Ray Sky

With the coincident detections of electromagnetic radiation together with gravitational waves (GW170817) or neutrinos (TXS 0506+056), the new era of multimessenger astrophysics has begun. Of particular interest are the searches for correlation between the high-energy astrophysical neutrinos detected by the IceCube Observatory and gamma-ray photons detected by the Fermi Large Area Telescope (LAT). So far, only sources detected by the LAT have been considered in correlation with IceCube neutrinos, neglecting any emission from sources too faint to be resolved individually. Here we present the first cross-correlation analysis considering the unresolved gamma-ray background (UGRB) and IceCube events. We perform a thorough sensitivity study, and, given the lack of identified correlation, we place upper limits on the fraction of the observed neutrinos that would be produced in proton–proton or proton–$γ$ interactions from the population of sources contributing to the UGRB emission and dominating its spatial anisotropy (aka blazars). Our analysis suggests that, under the assumption that there is no intrinsic cutoff and/or hardening of the spectrum above Fermi-LAT energies, and that all gamma rays from the unresolved blazars dominating the UGRB fluctuation field are produced by neutral pions from $p–p$ ($p–γ$) interactions, up to 60% (30%) of such a population may contribute to the total neutrino events observed by IceCube. This translates into an O (1%) maximum contribution to the astrophysical high-energy neutrino flux observed by IceCube at 100 TeV.

79 ASTRONOMY AND ASTROPHYSICS↗

Sensor selection and tool wear prediction with data‐driven models for precision machining

Abstract Estimation of tool wear in precision machining is vital in the traditional subtractive machining industry to reduce processing cost, improve manufacturing efficiency and product quality. In this vein, fusion of time and frequency‐domain features of commonly sensed signals can provide an early indication of tool wear and improve its prediction accuracy for prognostics and health management. This paper presents a data‐driven methodology and a complete tool chain for the inference of precision machining tool wear from fused machine measurements, such as cutting force, power, audio and vibration signals, and quantify the usefulness of each measurement. Indicators of tool wear are extracted from time‐domain signal statistics, frequency‐domain analysis, and time‐frequency domain analysis. Correlation coefficients between the extracted features (indicators) and the tool wear are used to select the most informative features. Principal Component Analysis and Partial Least‐Squares are used to reduce the dimensionality of the feature space. Regression models, including linear regression, support vector regression, Decision tree regression, neural network regression and Gaussian process regression, are used to predict the tool wear using data from a Haas milling machine performing spiral boss face milling. The performance of the regression models based on subsets of sensors validates the preliminary estimates about the saliency of the sensors. The experimental results show that the proposed methods can predict the machine tool wear precisely, with readily available sensor measurements. Neural network and Gaussian process regression were able to achieve good estimates of tool wear at different machine operating conditions. The most informative signal in predicting tool wear was shown to be the vibration signal. Time‐frequency domain features were the most informative features among the combination of features of three domains. In addition, using partial least squares components extracted from the original features of signals led to higher prediction accuracy.

Han, Seulki↗

Multimodal Chemical Characterization of Brown Carbon in Atmosphere and Snowpack during SAIL Field Campaign Report

The main goal of this field project was to characterize the chemical and physical properties of light-absorbing particles (LAP) present in the atmosphere and snowpack. The specific field efforts included: 1) online measurement and sampling of light-absorbing particles using a Magee Scientific model AE33 aethalometer (AE33) and a time-resolved aerosol collector (TRAC); and 2) sampling of snowpack during observed events of LAP deposition on snow, confirmed by onsite U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility measurements and meteorological data. The ongoing research objectives of our follow-up sample and data analysis include: 1) Characterization of aerosol regimes and sources, identifying particle-type populations, mixing states, and atmospheric transformations based on correlative analysis of our detailed chemical imaging and chemical characterization measurements and real-time records from the second ARM Mobile Facility (AMF2) and other instruments available from the Surface Atmosphere Integrated Field Laboratory (SAIL) experiment; 2) Assessment of the optical and chemical properties of snowpack deposits to investigate how aerosol deposition influences snowpack lifetime.

54 ENVIRONMENTAL SCIENCES↗

Assessing individual movement, habitat use, and behavior of non-breeding marine birds in relation to prey availability in the US Atlantic

Resource availability is a key factor driving marine bird movements and distributions, but direct information on prey availability is difficult to obtain at relevant scales. We present novel methods for describing multi-scale trophic associations, combining movement analyses of marine birds with estimates of forage fish surface aggregations from digital aerial survey data and species occupancy from bottom trawl survey data. We analyzed satellite telemetry data from northern gannets Morus bassanus , red-throated loons Gavia stellata , and long-tailed ducks Clangula hyemalis in the US Atlantic during the non-breeding period. Using discrete-time hidden Markov models to distinguish area-restricted (i.e. putative foraging) from transit movements, we examined how environmental factors influence movement, and how forage fish species distributions and surface aggregations influence habitat use by gannets and loons that have greater dietary reliance. Our results suggest that chlorophyll a concentration significantly affected movement behavior across species, highlighting the importance of higher-productivity areas around estuaries during colder months when regional productivity is low. Though variable across species and seasons, spatial cross-correlation analysis revealed that herring species (Family Clupeidae), including Atlantic menhaden Brevoortia tyrannus , may be important resources; it also showed positive spatial correlations with forage fish aggregations. This suggests that prey patch dynamics and factors driving aggregation formation may be as important as species composition. However, spatial patterns were generally low (<0.3), suggesting a mismatch in spatiotemporal resolution, exemplifying the challenges in quantifying trophic relationships in marine systems. Disentangling predator-prey relationships is critical to understanding the mechanisms driving marine bird behavior in rapidly changing marine systems.

Environmental Sciences & Ecology↗

Search for correlated radio and optical events in long-term studies of extragalactic sources

For the first time, long-term records of radio and optical fluxes of a large sample of variable extragalactic sources have been assembled and compared, with linear cross-correlation analysis being used to reinforce the visual comparisons. Only in the case of the BL Lac object OJ 287 is the correlation between radio and optical records strong. In the majority of cases there is no evidence of significant correlation, although nine sources show limited or weak evidence of correlation. The results do not support naive extrapolation of the expanding source model. The general absence of strong correlation between the radio and optical regions has important implications for the energetics of events occurring in such sources.

Pomphrey, R. B.↗

Detection and attribution of long-term and fine-scale changes in spring phenology over urban areas: A case study in New York State

Spring phenology plays an essential role in climate change, terrestrial ecosystem, and public health. Field-based monitoring and understanding of changes in spring phenology for long periods and in large regions are challenging due to the limited in-site observations. Space-based remotely sensed observations offer great potentials for monitoring decadal spring phenology changes from regional to global scales. However, the coarse-scale remotely sensed observations are insufficient to capture fine-scale spring phenology dynamics, especially in urban areas, and this makes it challenging for understanding the combined effects of climate change and urbanization on spring phenology. We derived the start of phenology season (SOS) in New York State using 30 m Landsat observations from 1990 to 2015 to understand the impact of the environment and urbanization on SOS. The results show that SOS for different years reveals heterogeneous spatial distribution. Most regions of New York State have been experiencing significant spring phenology changes in form of earlier onset of vegetation greening, ranging from 0.2 to 0.6 day/year during 1990 to 2015, and this trend varies slightly with latitudes and urbanization levels. Further, spatial correlation analysis shows that the increase in temperature and urbanization could both promote the advancement of SOS. However, the effect of urbanization (partial correlation coefficient (R) ranges from −0.289 to −0.542) on SOS is greater than the effect of temperature (R ranges from 0.006 to −0.192). The study generates a high spatio-temporal resolution spring phenology dataset for ecological, environmental and public health studies, especially in urban areas, and reveals the importance of better accounting for the urbanization effects when quantifying the SOS dynamics in phenology models.

Landsat↗

The concentration of BTEX in selected urban areas of Malaysia during the COVID-19 pandemic lockdown

Volatile organic compounds (VOCs) such as benzene, toluene, ethylbenzene and xylene (BTEX) are air pollutants that harm human health. This study aims to identify BTEX concentrations before the lockdown known as the Movement Control Order was imposed (BMCO), during the implementation of the Movement Control Order (MCO), and then during the Conditional Movement Control Order (CMCO). These orders were introduced during the COVID-19 pandemic in Malaysia. The study utilised data measured by the continuous monitoring of BTEX using online gas chromatography instruments located at three urban area stations. Here, the results showed that the BTEX concentrations reduced by between –38% and –46% during the MCO compared to the BMCO period. The reduction of human mobility during the MCO and CMCO influenced the lower BTEX concentrations recorded at a station within the Kuala Lumpur area. The results of the BTEX diagnostic ratios and principal component analysis showed that the major source of BTEX, especially during the BMCO and CMCO periods, was motor vehicle emissions. Further investigation, using correlation analysis and polar plots, showed that the BTEX concentrations were also influenced by meteorological variables such as wind speed, air temperature and relative humidity.

54 ENVIRONMENTAL SCIENCES↗

Characterizing the Oscillatory Properties of Bulk Electric Systems

This paper presents a process for characterizing the oscillatory dynamics of a large bulk power system. As a demonstration, the process is applied to the Western Interconnection of North America. Several complementary analysis approaches, both new and existing, are employed to provide a comprehensive understanding of the oscillatory properties of the system. Established modal analysis techniques based on ringdown and mode-meter algorithms are utilized. In addition, we derive and apply methods based on spectral correlation analysis to identify modal frequencies, distinguish between modes that are closely spaced in frequency, and determine locations at which the modes are observable. Critical interarea modes are identified and characterized using actual-system synchrophasor measurements taken over several years of operation in concert with industry-standard simulation models. This includes 145 hours of PMU data and two planning base cases.

42 ENGINEERING↗

A mechanistic study of cellulase adsorption onto lignin

To explore the effect of lignin composition on cellulase adsorption, here dehydrogenation polymers (DHPs) were prepared from p-glucocoumaryl alcohol/coniferin/syringin, giving rise to H-DHP, G-DHP, and S-DHP, respectively. The structures of DHPs were thoroughly characterized and compared by GPC and NMR techniques, and the Langmuir isotherm protocol was applied to determine the cellulase adsorption behaviors of these different types of DHPs. The adsorption study indicated that the binding strength between the DHPs and cellulase varied in the following order: G-DHP > H-DHP > S-DHP. The inhibition of different types of DHPs on enzymatic hydrolysis of cellulose was in the same order as the cellulase adsorption, indicating that non-productive adsorption was the main way to influence cellulase. The correlation analysis results showed a positive association between the phenolic hydroxyl group content in DHPs and their maximum adsorption capacity toward enzymes. A negative correlation between the PDI and binding strength was also observed. It was also found that the adsorbed cellulase could be desorbed and retained normal enzyme activity, and so it was presumed that DHPs and cellulase were mainly linked by physisorption such as hydrogen bonding. This study clearly showed that the composition of lignin had a great impact on cellulase, and that G-type lignin exhibited the most detrimental effect. The results could provide useful information on the mechanism of cellulase adsorption onto lignin using DHPs as lignin model compounds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Comparison of the X-Ray and Radio Light Curves of Quasar PKS 1510--089

We present results for the X-ray-bright superluminal AGN PKS 1510-089 (z=0.36) monitored weekly with the Rossi X-Ray Timing Explorer for the past four years in order to study the origin of X-ray emission from this extremely variable blazer. These RXTE data are compared with weekly cm-band flux and polarization observations from the Michigan Diameter telescope, to identify correlated activity and associated frequency-dependent time delays for constraining X-ray emission models; and bimonthly 7mm VLBA total and linearly polarized intensity imaging to identify temporal associations between X-ray events and the ejection of superluminal components and disturbances in the magnetic field, to test if the X-ray energy release is related to changes in the inner jet flow. Both the X-ray (2-20 keV) and radio flux are highly variable on timescales of weeks. The VLBA mas structure is dominated by a bright core with a weak jet; both the ejection of very fast superluminal knots and changes in the fractional polarization and EVPA of the core on timescales of one to four months are identified. Two outbursts in 1997 are well-resolved in both the centimeter and X-ray bands. Both the strong temporal association and the similar outburst shape support a causal relation, and a discrete cross-correlation analysis identifies that the X-ray lags the radio by 16 days during the bursts. Starting in 1998 the behavior changes: the correlation is weaker with the X-ray possibly leading the radio by six days. During the full time window there is a correlation between bands as expected if the radio photons are upscattered to X-ray energies. The time correlations and difference between the flat X-ray spectral index (0.0 <= alpha <= 0.5 where F(sub v) is proportional to v(exp -alpha)), and the mm-wave synchrotron spectrum (alpha = 0.8) are discussed within the framework of viable SSC models.

Aller, M. F.↗

Comparison of ALE and SPH Simulations of Vertical Drop Tests of a Composite Fuselage Section into Water

Simulation of multi-terrain impact has been identified as an important research area for improved prediction of rotorcraft crashworthiness within the NASA Subsonic Rotary Wing Aeronautics Program on Rotorcraft Crashworthiness. As part of this effort, two vertical drop tests were conducted of a 5-ft-diameter composite fuselage section into water. For the first test, the fuselage section was impacted in a baseline configuration without energy absorbers. For the second test, the fuselage section was retrofitted with a composite honeycomb energy absorber. Both tests were conducted at a nominal velocity of 25-ft/s. A detailed finite element model was developed to represent each test article and water impact was simulated using both Arbitrary Lagrangian Eulerian (ALE) and Smooth Particle Hydrodynamics (SPH) approaches in LS-DYNA, a nonlinear, explicit transient dynamic finite element code. Analytical predictions were correlated with experimental data for both test configurations. In addition, studies were performed to evaluate the influence of mesh density on test-analysis correlation.

Jackson, Karen E.↗

Continuously varying skin potentials elicited by sinusoidally varying electric shock potentials

An investigation was carried out to determine whether a form of quasi-linear systems analysis can be applied to electrodormal responses to yield new insights into the nature of the response mechanisms and their interrelationships. The response investigated was the electrodermal response (galvanic skin potential, GSP) as elicited by an electric shock stimulus applied to the skin. The response subsequent to this stimulation was examined and its characteristics measured. A series of experimental runs on three Ss was accomplished, using sinusoidal modulation envelopes of frequencies. Results showed that it was possible to drive the GSP and to achieve relatively high coherence between the driving frequency and the response itself. The analysis was limited to Fourier analysis of the response in order to determine the relative energies at the driving frequency and at successive harmonics of that driving frequency, and correlational analysis in order to determine the degree of linear relationship between the driving frequency and the driven response.

Senders, J. W.↗

Synchronization of Human Autonomic Nervous System Rhythms with Geomagnetic Activity in Human Subjects

A coupling between geomagnetic activity and the human nervous system's function was identified by virtue of continuous monitoring of heart rate variability (HRV) and the time-varying geomagnetic field over a 31-day period in a group of 10 individuals who went about their normal day-to-day lives. A time series correlation analysis identified a response of the group's autonomic nervous systems to various dynamic changes in the solar, cosmic ray, and ambient magnetic field. Correlation coefficients and p values were calculated between the HRV variables and environmental measures during three distinct time periods of environmental activity. There were significant correlations between the group's HRV and solar wind speed, Kp, Ap, solar radio flux, cosmic ray counts, Schumann resonance power, and the total variations in the magnetic field. In addition, the time series data were time synchronized and normalized, after which all circadian rhythms were removed. It was found that the participants' HRV rhythms synchronized across the 31-day period at a period of approximately 2.5 days, even though all participants were in separate locations. Overall, this suggests that daily autonomic nervous system activity not only responds to changes in solar and geomagnetic activity, but is synchronized with the time-varying magnetic fields associated with geomagnetic field-line resonances and Schumann resonances.

Magnetic Fields↗

Discovering the Multisectoral Impacts of Global Energy Sector Outcomes Through Multiple Ensemble Aggregation Measures

Understanding complex human-Earth system interactions often involves analyzing large scenario ensembles that encompass a wide range of plausible futures. These ensembles often require aggregation to summarize information based on specific criteria or conditions. However, previous research using global change scenario ensembles has largely overlooked how the choice of aggregation method influences the interpretation of results. To address this gap, we leverage a large ensemble data set designed to capture broad energy system dynamics generated using the Global Change Analysis Model. We first explore how energy-related uncertainties are propagated to both global and regional water-energy-food sectors. We then conduct a rank correlation analysis across seven ensemble aggregation measures and demonstrate the need to consider multiple measures in global change scenarios. Our results suggest that global water and food sector outcomes in the 21st century vary widely depending on different scenario assumptions. The global energy productivity is projected to improve by the end of the century across all scenarios. Moreover, regions facing water scarcity challenges in 2100 do not always overlap with those facing extreme energy and food sector outcomes. Although rank correlations across seven aggregation measures are relatively stable across sectors, we identify cases where relying on a single measure leads to losing critical information in the full ensemble. Reliance on a single aggregation measure can distort the interpretation of global change scenario outcomes. Instead, adopting multiple ensemble aggregation measures provides a more holistic understanding of global change scenario ensembles.

Kim, Gijoo↗

Quantitative Analysis of Origin of Lithium Inventory Loss and Interface Evolution over Extended Fast Charge Aging in Li Ion Batteries

During the extreme fast charging (XFC) of lithium-ion batteries, lithium inventory loss (LLI) and reaction mechanisms at the anode/electrolyte interface are crucial factors in performance and safety. Determining the causes of LLI and quantifying them remain an essential challenge. We present mechanistic research on the evolution and interactions of aging mechanisms at the anode/electrolyte interface. We used NMC 532 /graphite pouch cells charged at rates of 1, 6, and 9 C up to 1000 cycles for our investigation. The cell components were characterized after cycling using electrochemical measurements, inductively coupled plasma optical emission spectroscopy, 7 Li solid-state nuclear magnetic resonance spectroscopy, and high-performance liquid chromatography/mass spectrometry. The results indicate that cells charged at 1 C exhibit no Li plating, and the increase of SEI thickness is the dominant source of the Li loss. In contrast, Li loss in cells charged at 9 C is related to the formation of the metallic plating layers (42%) the SEI layer (38.1%) and irreversible intercalation into the bulk graphite (19%). XPS analysis suggests that the charging rate has little influence on the evolution of SEI composition. The interactions between competing aging mechanisms were evaluated by a correlation analysis. In conclusion, the quantitative method established in this work provides a comprehensive analytical framework for understanding the synergistic coupling of anodic degradation mechanisms, forecasting SEI failure scenarios, and assessing the XFC lithium-ion battery capacity fade.

25 ENERGY STORAGE↗