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At least 109 records · Page 6

Sensitivity properties of a biosphere model based on BATS and a statistical-dynamical climate model

A biosphere model based on the Biosphere-Atmosphere Transfer Scheme (BATS) and the Saltzman-Vernekar (SV) statistical-dynamical climate model is developed. Some equations of BATS are adopted either intact or with modifications, some are conceptually modified, and still others are replaced with equations of the SV model. The model is designed so that it can be run independently as long as the parameters related to the physiology and physiognomy of the vegetation, the atmospheric conditions, solar radiation, and soil conditions are given. With this stand-alone biosphere model, a series of sensitivity investigations, particularly the model sensitivity to fractional area of vegetation cover, soil surface water availability, and solar radiation for different types of vegetation, were conducted as a first step. These numerical experiments indicate that the presence of a vegetation cover greatly enhances the exchanges of momentum, water vapor, and energy between the atmosphere and the surface of the earth. An interesting result is that a dense and thick vegetation cover tends to serve as an environment conditioner or, more specifically, a thermostat and a humidistat, since the soil surface temperature, foliage temperature, and temperature and vapor pressure of air within the foliage are practically insensitive to variation of soil surface water availability and even solar radiation within a wide range. An attempt is also made to simulate the gradual deterioration of environment accompanying gradual degradation of a tropical forest to grasslands. Comparison with field data shows that this model can realistically simulate the land surface processes involving biospheric variations.

Zhang, Taiping↗

Thermal Design to Meet Stringent Temperature Gradient/Stability Requirements of SWIFT BAT Detectors

The Burst Alert Telescope (BAT) is an instrument on the National Aeronautics and Space Administration (NASA) SWIFT spacecraft. It is designed to detect gamma ray burst over a broad region of the sky and quickly align the telescopes on the spacecraft to the gamma ray source. The thermal requirements for the BAT detector arrays are very stringent. The maximum allowable temperature gradient of the 256 cadmium zinc telluride (CZT) detectors is PC. Also, the maximum allowable rate of temperature change of the ASICs of the 256 Detector Modules (DMs) is PC on any time scale. The total power dissipation of the DMs and Block Command & Data Handling (BCDH) is 180 W. This paper presents a thermal design that uses constant conductance heat pipes (CCHPs) to minimize the temperature gradient of the DMs, and loop heat pipes (LHPs) to transport the waste heat to the radiator. The LHPs vary the effective thermal conductance from the DMs to the radiator to minimize heater power to meet the heater power budget, and to improve the temperature stability. The DMs are cold biased, and active heater control is used to meet the temperature gradient and stability requirements.

Choi, Michael K.↗

Swift Observations Of High-z Radio-loud Quasars Detected With Bat

We present follow-up Swift observations of 4 high-z radio-loud quasars detected with the BAT during the 15-month survey in 15-150 keV. The 0.5-8-keV spectra are best fitted either with a power law with no excess absorption over the Galactic value (0212+735, 0836+710, 2149--307 in higher state) or by a downward-curved broken power law model (0537--286, 2149--307 in lower state). The BAT spectra integrated over the whole 15 months of the survey are fitted with a single power law, with a range of spectral slopes, Gamma=l.3-2.3. Comparison with previous SAX observations shows that there is a trend for the 15-150-keV continuum to soften with fading intensity; on the contrary, little or no spectral variations are observed at medium-hard X-rays. This may suggest either/both dramatic variability above 10-keV, or/and two separate spectral components.

Sambruna, Rita M.↗

XMM Observations of 'New' Swift BAT Sources

Because the E> 15 keV band is unaffected by absorption this band offers the best hope of obtaining an unbiased sample of AGN. The Swift BAT survey has produced the first large sample of hard x-ray bright AGN in the local universe providing the data necessary to determine the true characteristics of the AGN population. However to use this data one needs to obtain the x-ray spectral properties of these objects.We will present the complete sample of x-ray spectra of the BAT objects and the implications of these data.

Mushotzky, Richard F.↗

SWIFT BAT Survey of AGN

We present the results1 of the analysis of the first 9 months of data of the Swift BAT survey of AGN in the 14-195 keV band. Using archival X-ray data or follow-up Swift XRT observations, we have identified 129 (103 AGN) of 130 objects detected at [b] > 15deg and with significance > 4.8-delta. One source remains unidentified. These same X-ray data have allowed measurement of the X-ray properties of the objects. We fit a power law to the logN - log S distribution, and find the slope to be 1.42+/-0.14. Characterizing the differential luminosity function data as a broken power law, we find a break luminosity logL*(ergs/s)= 43.85+/-0.26. We obtain a mean photon index 1.98 in the 14-195 keV band, with an rms spread of 0.27. Integration of our luminosity function gives a local volume density of AGN above 10(exp 41) erg/s of 2.4x10(exp -3) Mpc(sup -3), which is about 10% of the total luminous local galaxy density above M* = -19.75. We have obtained X-ray spectra from the literature and from Swift XRT follow-up observations. These show that the distribution of log nH is essentially flat from nH = 10(exp 20)/sq cm to 10(exp 24)/sq cm, with 50% of the objects having column densities of less than 10(exp 22)/sq cm. BAT Seyfert galaxies have a median redshift of 0.03, a maximum log luminosity of 45.1, and approximately half have log nH > 22.

Tueller, J.↗

Modeling the Swift BAT Trigger Algorithm with Machine Learning

To draw inferences about gamma-ray burst (GRB) source populations based on Swift observations, it is essential to understand the detection efficiency of the Swift burst alert telescope (BAT). This study considers the problem of modeling the Swift BAT triggering algorithm for long GRBs, a computationally expensive procedure, and models it using machine learning algorithms. A large sample of simulated GRBs from Lien et al. (2014) is used to train various models: random forests, boosted decision trees (with AdaBoost), support vector machines, and artificial neural networks. The best models have accuracies of approximately greater than 97% (approximately less than 3% error), which is a significant improvement on a cut in GRB flux which has an accuracy of 89:6% (10:4% error). These models are then used to measure the detection efficiency of Swift as a function of redshift z, which is used to perform Bayesian parameter estimation on the GRB rate distribution. We find a local GRB rate density of eta(sub 0) approximately 0.48(+0.41/-0.23) Gpc(exp -3) yr(exp -1) with power-law indices of eta(sub 1) approximately 1.7(+0.6/-0.5) and eta(sub 2) approximately -5.9(+5.7/-0.1) for GRBs above and below a break point of z(sub 1) approximately 6.8(+2.8/-3.2). This methodology is able to improve upon earlier studies by more accurately modeling Swift detection and using this for fully Bayesian model fitting. The code used in this is analysis is publicly available online.

gamma rays: general↗

Modeling the Swift Bat Trigger Algorithm with Machine Learning

To draw inferences about gamma-ray burst (GRB) source populations based on Swift observations, it is essential to understand the detection efficiency of the Swift burst alert telescope (BAT). This study considers the problem of modeling the Swift / BAT triggering algorithm for long GRBs, a computationally expensive procedure, and models it using machine learning algorithms. A large sample of simulated GRBs from Lien et al. is used to train various models: random forests, boosted decision trees (with AdaBoost), support vector machines, and artificial neural networks. The best models have accuracies of greater than or equal to 97 percent (less than or equal to 3 percent error), which is a significant improvement on a cut in GRB flux, which has an accuracy of 89.6 percent (10.4 percent error). These models are then used to measure the detection efficiency of Swift as a function of redshift z, which is used to perform Bayesian parameter estimation on the GRB rate distribution. We find a local GRB rate density of n (sub 0) approaching 0.48 (sup plus 0.41) (sub minus 0.23) per cubic gigaparsecs per year with power-law indices of n (sub 1) approaching 1.7 (sup plus 0.6) (sub minus 0.5) and n (sub 2) approaching minus 5.9 (sup plus 5.7) (sub minus 0.1) for GRBs above and below a break point of z (redshift) (sub 1) approaching 6.8 (sup plus 2.8) (sub minus 3.2). This methodology is able to improve upon earlier studies by more accurately modeling Swift detection and using this for fully Bayesian model fitting.

gamma-ray burst: general – gamma-rays: general â↗

Searching for GRB Counterparts to GW Events from the Third Gravitational Wave Observing Run with Fermi-GBM and Swift-BAT

We present Fermi Gamma-ray Burst Monitor (Fermi-GBM) and Swift Burst Alert Telescope (Swift-BAT) observations of gravitational-wave (GW) events detected during the third LIGO/Virgo/KAGRA Collaboration observing run (O3). Using Fermi-GBM on-board triggers as well as sub-threshold searches in both Fermi-GBM and Swift-BAT ground data, we search for coincident gamma-ray transients associated with the GW events. No new joint events beyond GRB 170817A and GW170817 were found. We therefore calculate flux upper limits for the associated gamma-ray luminosity of each GW event. Using the lack of electromagnetic (EM) emission from binary black hole (BBH) mergers, we begin to constrain theoretical models of any such emission.

Joshua Wood↗

Searching for GRB Counterparts to GW Events from the Third Gravitational Wave Observing Run with Fermi-GBM and Swift-BAT

We present Fermi Gamma-ray Burst Monitor (Fermi-GBM) and Swift Burst Alert Telescope (Swift-BAT) observations of gravitational-wave (GW) events detected during the third LIGO/Virgo/KAGRA Collaboration observing run (O3). Using Fermi-GBM on-board triggers as well as sub-threshold searches in both Fermi-GBM and Swift-BAT ground data, we search for coincident gamma-ray transients associated with the GW events. No new joint events were found. We therefore calculate flux upper limits for the associated gamma-ray luminosity of each GW event. Using the lack of electromagnetic (EM) emission from binary black hole (BBH) mergers, we begin to constrain theoretical models of any such emission.

GRB↗

Searching for GRB Counterparts to GW Events from the Third Gravitational Wave Observing Run with Fermi-GBM and Swift-BAT

We present Fermi Gamma-ray Burst Monitor (Fermi-GBM) and Swift Burst Alert Telescope (Swift-BAT) observations of gravitational-wave (GW) events detected during the third LIGO/Virgo/KAGRA Collaboration observing run (O3). Using Fermi-GBM on-board triggers as well as sub-threshold searches in both Fermi-GBM and Swift-BAT ground data, we search for coincident gamma-ray transients associated with the GW events. No new joint events were found. We therefore calculate flux upper limits for the associated gamma-ray luminosity of each GW event. Using the lack of electromagnetic (EM) emission from binary black hole (BBH) mergers, we begin to constrain theoretical models of any such emission.

GRB↗

Accelerating technology development to monitor and minimize effects from land‐based wind energy on birds and bats

While wind energy is a key sector of domestic energy production for the United States, operation of wind turbines directly and indirectly adversely affects certain species of birds and bats. The cumulative effect of wind turbine strikes can have both biological and regulatory consequences, and, in some cases, delay permitting and construction or affect ongoing operations. Technology can help quantify and minimize these effects, but the pace of development, acceptance, and adoption of technological solutions is slow. Although adopting cost‐effective technologies may reduce negative effects on wildlife and help achieve both energy production and conservation goals, consensus is lacking among developers, regulators, and the conservation community regarding how to define technology effectiveness and acceptance and how to develop a standardized process for doing so. Removing barriers to technology advancement requires deviating from the status quo. Changes include 1) creating incentives to mitigate impacts, 2) establishing options for research as mitigation, 3) rethinking how research is funded, 4) increasing stakeholder coordination, and 5) increasing the efficiency of research and development. We recommend the creation of a national framework to establish clear criteria and protocols for technology evaluation and adoption.

17 WIND ENERGY↗

Migratory Strategy is a Key Factor Driving Interactions at Wind Energy Facilities in At-Risk North American Bats

Animal migration remains poorly understood for many organisms, impeding understanding of movement dynamics and limiting conservation actions. We develop a framework that scales from movements of individuals to the dynamics of continental migration using data synthesis of endogenous markers, which we apply to three North American bat species with unexplained high rates of fatalities at wind energy facilities. The two species experiencing the highest fatality rates exhibit a "pell-mell" migration strategy in which individuals move from summer habitats in multiple directions, both to higher and lower latitudes, during autumn. We link movements to higher latitudes to encounters with wind energy facilities and report that the timing of pell-mell migration strongly overlaps with that of fatalities at the continental level. These findings support the hypothesis that migration distance and strategy are drivers of increased interactions with wind energy facilities, highlighting the significance of understanding migratory strategy to achieve conservation goals.

08 HYDROGEN↗

The star formation properties of the observed and simulated AGN Universe: BAT versus EAGLE

ABSTRACT In this paper, we present data from 72 low-redshift, hard X-ray selected active galactic nucleus (AGN) taken from the Swift–BAT 58 month catalogue. We utilize spectral energy distribution fitting to the optical to infrared photometry in order to estimate host galaxy properties. We compare this observational sample to a volume- and flux-matched sample of AGN from the Evolution and Assembly of GaLaxies and their Environments (EAGLE) hydrodynamical simulations in order to verify how accurately the simulations can reproduce observed AGN host galaxy properties. After correcting for the known +0.2 dex offset in the SFRs between EAGLE and previous observations, we find agreement in the star formation rate (SFR) and X-ray luminosity distributions; however, we find that the stellar masses in EAGLE are 0.2–0.4 dex greater than the observational sample, which consequently leads to lower specific star formation rates (sSFRs). We compare these results to our previous study at high redshift, finding agreement in both the observations and simulations, whereby the widths of sSFR distributions are similar (∼0.4–0.6 dex) and the median of the SFR distributions lie below the star-forming main sequence by ∼0.3–0.5 dex across all samples. We also use EAGLE to select a sample of AGN host galaxies at high and low redshift and follow their characteristic evolution from z = 8 to z = 0. We find similar behaviour between these two samples, whereby star formation is quenched when the black hole goes through its phase of most rapid growth. Utilizing EAGLE we find that 23 per cent of AGN selected at z ∼ 0 are also AGN at high redshift, and that their host galaxies are among the most massive objects in the simulation. Overall, we find EAGLE reproduces the observations well, with some minor inconsistencies (∼0.2 dex in stellar masses and ∼0.4 dex in sSFRs).

Jackson, Thomas M.↗

2018 Bat Maternity Roosts at the 183-F and 183-D Clearwells

The 183-F and 183-D Water Treatment Plants served three of the historic reactors at the Hanford Site for a combined 45 years, assisting in the production of weapons grade plutonium. These once massive facilities have been remediated to near unrecognizable landscape with limited infrastructure remaining. Although small in proportion to the pre-demolished facilities, the associated 183-F and 183-D Clearwells played a critical role during the operating years of the site and continue to serve as an unintended highpriority habitat for breeding bat populations.

54 ENVIRONMENTAL SCIENCES↗

Genomic Surveillance Detection of SARS-CoV-1–Like Viruses in Rhinolophidae Bats, Bandarban Region, Bangladesh

We sequenced sarbecovirus from Rhinolophus spp. bats in Bandarban District, Bangladesh, in a genomic surveillance campaign during 2022–2023. Sequences shared identity with SARS-CoV-1 Tor2, which caused an outbreak of human illnesses in 2003. Describing the genetic diversity and zoonotic potential of reservoir pathogens can aid in identifying sources of future spillovers.

Angiotensin Converting Enzyme 2↗

Neurophysiological analysis of echolocation in bats

An analysis of echolocation and signal processing in brown bats is presented. Data cover echo detection, echo ranging, echolocalization, and echo analysis. Efforts were also made to identify the part of the brain that carries out the most essential processing function for echolocation. Results indicate the inferior colliculus and the auditory nuclei function together to process this information.

Suga, N.↗

Individual recognition between mother and infant bats (Myotis)

The recognition process and the basis for that recognition, in brown bats, between mother and infant are analyzed. Two parameters, ultrasonic communication and olfactory stimuli, are investigated. The test animals were not allowed any visual contact. It was concluded that individual recognition between mother and infant occurred. However, it could not be determined if the recognition was based on ultrasonic signals or olfactory stimuli.

Turner, D.↗

Evolution: bats, radar, and science (The Remote Sensing Award Lecture)

A parallel is drawn between the evolution of the bat and the evolution of the science and technology of radar and remote sensing to illustrate the importance of the role of Darwinian processes in the culture and practice of science and technology, and thus in the survival of their vitality. The lecture touches on several themes of interest to the science community, such as the relation between basic and applied science and engineering; research in academia, industry, and government laboratories; elite scientists; and the survival of a scientific institution.

Atlas, David↗