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At least 685 records · Page 38

How open data and interdisciplinary collaboration improve our understanding of space weather: A risk and resiliency perspective

Space weather refers to conditions around a star, like our Sun, and its interplanetary space that may affect space- and ground-based assets as well as human life. Space weather can manifest as many different phenomena, often simultaneously, and can create complex and sometimes dangerous conditions. The study of space weather is inherently trans-disciplinary, including subfields of solar, magnetospheric, ionospheric, and atmospheric research communities, but benefiting from collaborations with policymakers, industry, astrophysics, software engineering, and many more. Effective communication is required between scientists, the end-user community, and government organizations to ensure that we are prepared for any adverse space weather effects. With the rapid growth of the field in recent years, the upcoming Solar Cycle 25 maximum, and the evolution of research-ready technologies, we believe that space weather deserves a reexamination in terms of a “risk and resiliency” framework. By utilizing open data science, cross-disciplinary collaborations, information systems, and citizen science, we can forge stronger partnerships between science and industry and improve our readiness as a society to mitigate space weather impacts. The objective of this manuscript is to raise awareness of these concepts as we approach a solar maximum that coincides with an increasingly technology-dependent society, and introduce a unique way of approaching space weather through the lens of a risk and resiliency framework that can be used to further assess areas of improvement in the field.

79 ASTRONOMY AND ASTROPHYSICS↗

Protein Data Bank: A Comprehensive Review of 3D Structure Holdings and Worldwide Utilization by Researchers, Educators, and Students

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), funded by the United States National Science Foundation, National Institutes of Health, and Department of Energy, supports structural biologists and Protein Data Bank (PDB) data users around the world. The RCSB PDB, a founding member of the Worldwide Protein Data Bank (wwPDB) partnership, serves as the US data center for the global PDB archive housing experimentally-determined three-dimensional (3D) structure data for biological macromolecules. As the wwPDB-designated Archive Keeper, RCSB PDB is also responsible for the security of PDB data and weekly update of the archive. RCSB PDB serves tens of thousands of data depositors (using macromolecular crystallography, nuclear magnetic resonance spectroscopy, electron microscopy, and micro-electron diffraction) annually working on all permanently inhabited continents. RCSB PDB makes PDB data available from its research-focused web portal at no charge and without usage restrictions to many millions of PDB data consumers around the globe. It also provides educators, students, and the general public with an introduction to the PDB and related training materials through its outreach and education-focused web portal. This review article describes growth of the PDB, examines evolution of experimental methods for structure determination viewed through the lens of the PDB archive, and provides a detailed accounting of PDB archival holdings and their utilization by researchers, educators, and students worldwide.

59 BASIC BIOLOGICAL SCIENCES↗

Mining Thermophile Photosynthesis Genes: A Synthetic Operon Expressing Chloroflexota Species Reaction Center Genes in Rhodobacter sphaeroides

Photosynthesis is the foundation of the vast majority of life systems, and is therefore the most important bioenergetic process on earth. The greatest diversity of photosynthetic systems is found in microorganisms. However, our understanding of the biophysical and biochemical processes that transduce light into chemical energy is derived from a relatively small subset of proteins from microbes that are amenable to cultivation, in contrast to the huge number of predicted proteins that catalyze the initial photochemical reactions deposited in databases, such as from metagenomics. We describe the use of a Rhodobacter sphaeroides laboratory strain for the expression of heterologous photosynthesis genes to demonstrate the feasibility of mining this resource, focusing on hot spring Chloroflexota gene sequences. Using a synthetic operon of genes, we produced a photochemically active complex of reaction center proteins in our biological system. We also present bioinformatic analyses of anoxygenic type II reaction center sequences from metagenomic samples collected from hot (42–90 °C) springs available through the JGI IMG database, to generate a resource of diverse sequences that are potentially adapted to photosynthesis at such temperatures. These data provide a view into the natural diversity of anoxygenic photosynthesis, through a lens focused on high-temperature environments. The approach we took to express such genes can be applied for potential biotechnology purposes as well as for studies of fundamental catalytic properties of these heretofore inaccessible protein complexes.

Chloroflexota↗

A Convex Data-Driven Approach for Nonlinear Control Synthesis

We consider a class of nonlinear control synthesis problems where the underlying mathematical models are not explicitly known. We propose a data-driven approach to stabilize the systems when only sample trajectories of the dynamics are accessible. Our method is built on the density-function-based stability certificate that is the dual to the Lyapunov function for dynamic systems. Unlike Lyapunov-based methods, density functions lead to a convex formulation for a joint search of the control strategy and the stability certificate. This type of convex problem can be solved efficiently using the machinery of the sum of squares (SOS). For the data-driven part, we exploit the fact that the duality results in the stability theory can be understood through the lens of Perron–Frobenius and Koopman operators. This allows us to use data-driven methods to approximate these operators and combine them with the SOS techniques to establish a convex formulation of control synthesis. The efficacy of the proposed approach is demonstrated through several examples.

97 MATHEMATICS AND COMPUTING↗

Optimize Electron Beam Energy toward In Situ Imaging of Thick Frozen Bio-Samples with Nanometer Resolution Using MeV-STEM

To optimize electron energy for in situ imaging of large biological samples up to 10 μm in thickness with nanoscale resolutions, we implemented an analytical model based on elastic and inelastic characteristic angles. This model has been benchmarked by Monte Carlo simulations and can be used to predict the transverse beam size broadening as a function of electron energy while the probe beam traverses through the sample. As a result, the optimal choice of the electron beam energy can be realized. In addition, the impact of the dose-limited resolution was analysed. While the sample thickness is less than 10 μm, there exists an optimal electron beam energy below 10 MeV regarding a specific sample thickness. However, for samples thicker than 10 μm, the optimal beam energy is 10 MeV or higher depending on the sample thickness, and the ultimate resolution could become worse with the increase in the sample thickness. Moreover, a MeV-STEM column based on a two-stage lens system can be applied to reduce the beam size from one micron at aperture to one nanometre at the sample with the energy tuning range from 3 to 10 MeV. In conjunction with the state-of-the-art ultralow emittance electron source that we recently implemented, the maximum size of an electron beam when it traverses through an up to 10 μm thick bio-sample can be kept less than 10 nm . This is a critical step toward the in situ imaging of large, thick biological samples with nanometer resolution.

36 MATERIALS SCIENCE↗

Enhancing Camera Calibration for Traffic Surveillance with an Integrated Approach of Genetic Algorithm and Particle Swarm Optimization

Recent advancements in sensor technologies, coupled with signal processing and machine learning, have enabled real-time traffic control systems to effectively adapt to changing traffic conditions. Cameras, as sensors, offer a cost-effective means to determine the number, location, type, and speed of vehicles, aiding decision-making at traffic intersections. However, the effective use of cameras for traffic surveillance requires proper calibration. This paper proposes a new optimization-based method for camera calibration. In this approach, initial calibration parameters are established using the Direct Linear Transformation (DLT) method. Then, optimization algorithms are applied to further refine the calibration parameters for the correction of nonlinear lens distortions. A significant enhancement in the optimization process is achieved through the integration of the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) into a combined Integrated GA and PSO (IGAPSO) technique. The effectiveness of this method is demonstrated through the calibration of eleven roadside cameras at three different intersections. The experimental results show that when compared to the baseline DLT method, the vehicle localization error is reduced by 22.30% with GA, 22.31% with PSO, and 25.51% with IGAPSO.

47 OTHER INSTRUMENTATION↗

A Causal Approach to Integrate Component Health Data into System Reliability Models

Two of the challenges of current plant reliability approaches are the ability to integrate plant health data, and to support decision making. Condition based data and diagnostic/prognostic information are in fact not considered into plant reliability models to inform system engineers on the most critical components. Currently, the propagation of quantitative health data from the component to the system level is a challenge given the diverse nature/structure of the data. On the other hand, plant reliability methods (which are typically based on fault-trees or reliability block diagrams) can effectively propagate data from the component to the system level, but values of failure rates or failure probabilities are an approximated integral representation of the past industry-wide operational experience, and it neglects the present component health status (e.g., diagnostic and condition-based data) and health projection (when available from prognostic data). Our first claim is that system reliability models should propagate health information from the component to the system/plant level in order to provide a quantitative snapshot of system/plant health and identify the most critical components. Our second claim is that component health should be informed solely by that specific component current and historical performance data and should not be an approximated integral representation of the past industry-wide operational experience. This paper is directly supporting these two claims by proposing a different approach to perform reliability modeling which relies on available component diagnostic, prognostic and condition-based data to measure component health, and it propagates this information through fault tree models. The propagation of health data from the component to the system level is performed not in terms of probability, but in terms of margins where margin is defined as the “distance” between the present actual status and an undesired event (e.g., failure or unacceptable performance). Through a cause-effect lens, while classical reliability models target the effect associated to a component performance, a margin-based approach focuses on the cause of an undesired component performance (i.e., component health). Hence, thinking of reliability in terms of margins implies decision making based on causal reasoning. We will show how fault tree models can be solved using a margin language and how this process can effectively assist system engineers to identify the most critical components.

97 MATHEMATICS AND COMPUTING↗

KMT-2016-BLG-1836Lb: A Super-Jovian Planet from a High-cadence Microlensing Field

We report the discovery of a super-Jovian planet in the microlensing event KMT-2016-BLG-1836, which was found by the Korea Microlensing Telescope Network (KMTNet) high-cadence observations (Γ~4 hr -1 ). The planet–host mass ratio q ~ 0.004. A Bayesian analysis indicates that the planetary system is composed of a super-Jovian M{ planet =2.2 -1.1 +1.9 M J planet orbiting an M or K dwarf, M{ host =0.49 -0.25 0.38 M ⊙ , at a distance of D L =7.1 -2.4} +0.8 kpc. The projected planet–host separation is 3.5 -0.9 +1.1 au, implying that the planet is located beyond the snow line of the host star. Future high-resolution images can potentially strongly constrain the lens brightness and thus the mass and distance of the planetary system. Without considering detailed detection efficiency, selection, or publication biases, we find a potential mass-ratio desert at -3.7 ≲ log q ≲ -3.0 for the 31 published KMTNet planets.

79 ASTRONOMY AND ASTROPHYSICS↗

OGLE-2018-BLG-0677Lb: A Super-Earth Near the Galactic Bulge

We report the analysis of the microlensing event OGLE-2018-BLG-0677. A small feature in the light curve of the event leads to the discovery that the lens is a star–planet system. Although there are two degenerate solutions that could not be distinguished for this event, both lead to a similar planet-host mass ratio. We perform a Bayesian analysis based on a Galactic model to obtain the properties of the system and find that the planet corresponds to a super-Earth/sub-Neptune with a mass of M{sub planet}=3.96{sub −2.66}{sup +5.88}M{sub ⊕}. The host star has a mass of M{sub host}=0.12{sub −0.08}{sup +0.14} M{sub ⊙}. The projected separation for the inner and outer solutions are 0.63{sub −0.17}{sup +0.20} au and 0.72{sub −0.19}{sup +0.23} au respectively. At Δχ{sup 2}=χ{sup 2}(1L1S)−χ{sup 2}(2L1S)=46, this is by far the lowest Δχ {sup 2} for any securely detected microlensing planet to date, a feature that is closely connected to the fact that it is detected primarily via a “dip” rather than a “bump.”.

79 ASTRONOMY AND ASTROPHYSICS↗

KMT-2019-BLG-0842Lb: A Cold Planet below the Uranus/Sun Mass Ratio

We report the discovery of a cold planet with a very low planet/host mass ratio of q = (4.09 ± 0.27) × 10 -5 , which is similar to the ratio of Uranus/Sun (q = 4.37 × 10 -5 ) in the solar system. The Bayesian estimates for the host mass, planet mass, system distance, and planet–host projected separation are M {sub host} = 0.76 ± 0.40M ⊙ , M planet = 10.3 ± 5.5M ⊕ , D L = 3.3 ± 1.3 kpc, and a ⊥ = 3.3 ± 1.4 au, respectively. The consistency of the color and brightness expected from the estimated lens mass and distance with those of the blend suggests the possibility that the most blended light comes from the planet host, and this hypothesis can be established if high-resolution images are taken during the next (2020) bulge season. We discuss the importance of conducting optimized photometry and aggressive follow-up observations for moderately or very high magnification events to maximize the detection rate of planets with very low mass ratios.

79 ASTRONOMY AND ASTROPHYSICS↗

A New Method for Aerosol Measurement Using Wide-field Photometry

We present a new method to measure the vertical aerosol optical depth (VAOD) during clear nights using a wide-field imager—a CCD camera with a photographic lens on an equatorial mount. A series of 30 s exposures taken at different altitudes above the horizon can be used to measure the VAOD with a precision better than 0.008 optical depths within a few minutes. Such a measurement does not produce any light and is thus suitable for use at sites where other astronomical instruments are located. The precision of the VAOD measurement depends on the laboratory calibration of spectral properties of the system and of the response of the camera electronics to varying illumination levels, as well as careful considerations of the details of stellar photometry and modeling of the dependence of the measured stellar flux, the star color, and the position within the field of view. The results obtained with robotic setups at the future sites of the Cerenkov Telescope Array show good internal consistency and agreement with simultaneous measurements from a Sun/Moon photometer located at the same sites.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

KMT-2019-BLG-0371 and the Limits of Bayesian Analysis

We show that the perturbation at the peak of the light curve of microlensing event KMT-2019-BLG-0371 is explained by a model with a mass ratio between the host star and planet of q ∼ 0.08. Due to the short event duration (t {sub E} ∼ 6.5 days), the secondary object in this system could potentially be a massive giant planet. A Bayesian analysis shows that the system most likely consists of a host star with a mass M{sub h}=0.09{sub −0.05}{sup +0.14}M{sub ⊙} and a massive giant planet with a mass M{sub p}=7.70{sub −3.90}{sup +11.34}M{sub Jup}. However, the interpretation of the secondary as a planet (i.e., as having M {sub p} < 13M {sub Jup}) rests entirely on the Bayesian analysis. Motivated by this event, we conduct an investigation to determine which constraints meaningfully affect Bayesian analyses for microlensing events. We find that the masses inferred from such a Bayesian analysis are determined almost entirely by the measured value of θ {sub E} and are relatively insensitive to other factors such as the direction of the event (ℓ, b), the lens–source relative proper motion μ {sub rel}, or the specific Galactic model prior.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Shortest Microlensing Event with a Bound Planet: KMT-2016-BLG-2605

With a planet–host mass ratio q = 0.012 ± 0.001, KMT-2016-BLG-2605 has the shortest Einstein timescale, t {sub E} = 3.41 ± 0.13 days, of any planetary microlensing event to date. This prompts us to examine the full sample of seven short (t {sub E} < 7 days) planetary events with good q measurements. We find that six have clustered Einstein radii θ {sub E} = 115 ± 20 μas and lens–source relative proper motions μ {sub rel} ≃ 9.5 ± 2.5 mas yr{sup -1}. For the seventh, these two quantities could not be measured. These distributions are consistent with a Galactic bulge population of very low mass (VLM) hosts near the hydrogen-burning limit. This conjecture could be verified by imaging at first adaptive optics light on next-generation (30 m) telescopes. Based on a preliminary assessment of the sample, “planetary” companions (i.e., below the deuterium-burning limit) are divided into “genuine planets,” formed in their disks by core accretion, and VLM brown dwarfs, which form like stars. We discuss techniques for expanding the sample, which include taking account of the peculiar “anomaly-dominated” morphology of the KMT-2016-BLG-2605 light curve.

74 ATOMIC AND MOLECULAR PHYSICS↗

Gems of the Galaxy Zoos—A Wide-ranging Hubble Space Telescope Gap-filler Program*

We describe the Gems of the Galaxy Zoos (Zoo Gems) project, a gap-filler project using short windows in the Hubble Space Telescope's schedule. As with previous snapshot programs, targets are taken from a pool based on position; we combine objects selected by volunteers in both the Galaxy Zoo and Radio Galaxy Zoo citizen-science projects. Zoo Gems uses exposures with the Advanced Camera for Surveys to address a broad range of topics in galaxy morphology, interstellar-medium content, host galaxies of active galactic nuclei, and galaxy evolution. Science cases include studying galaxy interactions, backlit dust in galaxies, post-starburst systems, rings and peculiar spiral patterns, outliers from the usual color–morphology relation, Green Pea compact starburst systems, double radio sources with spiral host galaxies, and extended emission-line regions around active galactic nuclei. For many of these science categories, final selection of targets from a larger list used public input via a voting process. Highlights to date include the prevalence of tightly wound spiral structure in blue, apparently early-type galaxies, a nearly complete Einstein ring from a group lens, redder components at lower surface brightness surrounding compact Green Pea starbursts, and high-probability examples of spiral galaxies hosting large double radio sources.

79 ASTRONOMY AND ASTROPHYSICS↗

PopSyCLE: A New Population Synthesis Code for Compact Object Microlensing Events

We present a new Milky Way microlensing simulation code, dubbed PopSyCLE (Population Synthesis for Compact object Lensing Events). PopSyCLE is the first resolved microlensing simulation to include a compact object distribution derived from numerical supernovae explosion models and both astrometric and photometric microlensing effects. We demonstrate the capabilities of PopSyCLE by investigating the optimal way to find black holes (BHs) with microlensing. Candidate BHs have typically been selected from wide-field photometric microlensing surveys, such as OGLE, by selecting events with long Einstein crossing times (tE > 120 days). These events can be selected at closest approach and monitored astrometrically in order to constrain the mass of each lens; PopSyCLE predicts a BH detection rate of ~40% for such a program. We find that the detection rate can be enhanced to ~ 85% by selecting events with both tE > 120 days and a microlensing parallax of πE < 0.08. Unfortunately, such a selection criterion cannot be applied during the event as πE requires both pre- and post-peak photometry. However, historical microlensing events from photometric surveys can be revisited using this new selection criteria in order to statistically constrain the abundance of BHs in the Milky Way. The future WFIRST microlensing survey provides both precise photometry and astrometry and will yield individual masses of O(100 - 1000) black holes, which is at least an order of magnitude more than is possible with individual candidate follow-up with current facilities. The resulting sample of BH masses from WFIRST will begin to constrain the shape of the black hole present-day mass function, BH multiplicity, and BH kick velocity distributions

79 ASTRONOMY AND ASTROPHYSICS↗

COOL-LAMPS. I. An Extraordinarily Bright Lensed Galaxy at Redshift 5.04

In this paper, we report the discovery of COOL J1241+2219, a strongly lensed galaxy at redshift z = 5.043 ± 0.002 with observed magnitude z AB = 20.47, lensed by a moderate-mass galaxy cluster at z = 1.001 ± 0.001. COOL J1241+2219 is the brightest lensed galaxy currently known at optical and near-infrared wavelengths at z $\gtrsim$ 5; it is ~5 times brighter than the prior record-holder lensed galaxy, and several magnitudes brighter than the brightest unlensed galaxies known at these redshifts. It was discovered as part of COOL-LAMPS, a collaboration initiated to find strongly lensed systems in recent public optical imaging data. We characterize the lensed galaxy, as well as the central galaxy of the lensing cluster using ground-based grizJH imaging and optical spectroscopy. We report model-based magnitudes, and derive stellar masses, dust content, metallicity, and star-formation rates via stellar-population synthesis modeling. Our lens mass modeling, based on ground-based imaging, implies a median source magnification of ~30, which puts the stellar mass and star-formation rate (in the youngest age bin, closest to the epoch of observation) at logM* = ${10.11}_{-0.26}^{+0.21}$ and SFR = ${27}_{-9}^{+13} M_⊙$ yr –1 , respectively. We constrain a star-formation history for COOL J1241+2219 consistent with constant star formation across ~1 Gyr of cosmic time, and that places this galaxy on the high-mass end of the star-forming main sequence. COOL J1241+2219 is two to four times more luminous than a galaxy with the characteristic UV luminosity at these redshifts. The UV continuum slope β = –2.2 ± 0.2 places this galaxy on the blue side of the observed distribution of galaxies at z = 5, although the lack of Lyα emission indicates dust sufficient to suppress this emission.

79 ASTRONOMY AND ASTROPHYSICS↗

Discovering New Strong Gravitational Lenses in the DESI Legacy Imaging Surveys

We have conducted a search for new strong gravitational lensing systems in the Dark Energy Spectroscopic Instrument Legacy Imaging Surveys' Data Release 8. We use deep residual neural networks, building on previous work presented by Huang et al. These surveys together cover approximately one-third of the sky visible from the Northern Hemisphere, reaching a z-band AB magnitude of ~22.5. We compile a training sample that consists of known lensing systems as well as non-lenses in the Legacy Surveys and the Dark Energy Survey. After applying our trained neural networks to the survey data, we visually inspect and rank images with probabilities above a threshold. In this work, we present 1210 new strong lens candidates.

79 ASTRONOMY AND ASTROPHYSICS↗

The Hubble Constant from Strongly Lensed Supernovae with Standardizable Magnifications

The dominant uncertainty in the current measurement of the Hubble constant (H 0 ) with strong gravitational lensing time delays is attributed to uncertainties in the mass profiles of the main deflector galaxies. Strongly lensed supernovae (glSNe) can provide, in addition to measurable time delays, lensing magnification constraints when knowledge about the unlensed apparent brightness of the explosion is imposed. We present a hierarchical Bayesian framework to combine a data set of SNe that are not strongly lensed and a data set of strongly lensed SNe with measured time delays. We jointly constrain (i) H 0 using the time delays as an absolute distance indicator, (ii) the lens model profiles using the magnification ratio of lensed and unlensed fluxes on the population level, and (iii) the unlensed apparent magnitude distribution of the SN population and the redshift–luminosity relation of the relative expansion history of the universe. We apply our joint inference framework on a future expected data set of glSNe and forecast that a sample of 144 glSNe of Type Ia with well-measured time series and imaging data will measure H 0 to 1.5%. We discuss strategies to mitigate systematics associated with using absolute flux measurements of glSNe to constrain the mass density profiles. Using the magnification of SN images is a promising and complementary alternative to using stellar kinematics. Future surveys, such as the Rubin and Roman observatories, will be able to discover the necessary number of glSNe, and with additional follow-up observations, this methodology will provide precise constraints on mass profiles and H 0 .

79 ASTRONOMY AND ASTROPHYSICS↗