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In emergency response scenarios, autonomous small Unmanned Aerial Systems (sUAS) must be configured and deployed quickly and safely to perform mission-specific tasks. In this paper, we present \DR, a Software Product Line for rapidly configuring and deploying a multi-role, multi-sUAS mission whilst guaranteeing a set of safety properties related to the sequencing of tasks within the mission. Individual sUAS behavior is governed by an onboard state machine, combined with coordination handlers which are configured dynamically within seconds of launch and ultimately determine the sUAS' behaviors, transition decisions, and interactions with other sUAS, as well as human operators. The just-in-time manner in which missions are configured precludes robust upfront testing of all conceivable combinations of features -- both within individual sUAS and across cohorts of collaborating ones. To ensure the absence of common types of configuration failures and to promote safe deployments, we check vital properties of the dynamically generated sUAS specifications and coordination handlers before sUAS are assigned their missions. We evaluate our approach in two ways. First, we perform validation tests to show that the end-to-end configuration process results in correctly executed missions, and second, we apply fault-based mutation testing to show that our safety checks successfully detect incorrect task sequences. 

The MAPE-K feedback loop has been established as the primary reference model for self-adaptive and autonomous systems in domains such as autonomous driving, robotics, and Cyber-Physical Systems. At the same time, the Human Machine Teaming (HMT) paradigm is designed to promote partnerships between humans and autonomous machines. It goes far beyond the degree of collaboration expected in human-on-the-loop and human-in-the-loop systems and emphasizes interactions, partnership, and teamwork between humans and machines. However, while MAPE-K enables fully autonomous behavior, it does not explicitly address the interactions between humans and machines as intended by HMT. In this paper, we present the MAPE-K-HMT framework which augments the traditional MAPE-K loop with support for HMT. We identify critical human-machine teaming factors and describe the infrastructure needed across the various phases of the MAPE-K loop in order to effectively support HMT. This includes runtime models that are constructed and populated dynamically across monitoring, analysis, planning, and execution phases to support human-machine partnerships. We illustrate MAPE-KHMT using examples from an autonomous multi-UAV emergency response system, and present guidelines for integrating HMT into MAPE-K. 

Abstract We report the first direct measurement of the helium isotope ratio, 3 He/ 4 He, outside of the Local Interstellar Cloud, as part of science-verification observations with the upgraded CRyogenic InfraRed Echelle Spectrograph. Our determination of 3 He/ 4 He is based on metastable He i * absorption along the line of sight toward Θ 2 A Ori in the Orion Nebula. We measure a value 3 He/ 4 He = (1.77 ± 0.13) × 10 −4 , which is just ∼40% above the primordial relative abundance of these isotopes, assuming the Standard Model of particle physics and cosmology, ( 3 He/ 4 He) p = (1.257 ± 0.017) × 10 −4 . We calculate a suite of galactic chemical evolution simulations to study the Galactic build up of these isotopes, using the yields from Limongi & Chieffi for stars in the mass range M = 8–100 M ⊙ and Lagarde et al. for M = 0.8–8 M ⊙ . We find that these simulations simultaneously reproduce the Orion and protosolar 3 He/ 4 He values if the calculations are initialized with a primordial ratio 3 He / 4 He p = ( 1.043 ± 0.089 ) × 10 − 4 . Even though the quoted error does not include the model uncertainty, this determination agrees with the Standard Model value to within ∼2 σ . We also use the present-day Galactic abundance of deuterium (D/H), helium (He/H), and 3 He/ 4 He to infer an empirical limit on the primordial 3 He abundance, 3 He / H p ≤ ( 1.09 ± 0.18 ) × 10 − 5 , which also agrees with the Standard Model value. We point out that it is becoming increasingly difficult to explain the discrepant primordial 7 Li/H abundance with nonstandard physics, without breaking the remarkable simultaneous agreement of three primordial element ratios (D/H, 4 He/H, and 3 He/ 4 He) with the Standard Model values. 

As part of our program to identify host galaxies of known z = 2–3 Mg ii absorbers with the Keck Cosmic Web Imager (KCWI), we discovered a compact group giving rise to a z = 2.431 DLA with ultrastrong Mg ii absorption in quasar field J234628+124859. The group consists of four star-forming galaxies within 8–28 kpc and v ∼ 40–340 km s−1 of each other, where tidal streams are weakly visible in deep HST imaging. The group geometric centre is D = 25 kpc from the quasar (D = 20–40 kpc for each galaxy). Galaxy G1 dominates the group (1.66L*, SFRFUV = 11.6 M⊙ yr−1) while G2, G3, and G4 are less massive (0.1–0.3L*, SFRFUV = 1.4–2.0 M⊙ yr−1). Using a VLT/UVES quasar spectrum covering the H i Lyman series and metal lines such as Mg ii, Si iii, and C iv, we characterized the kinematic structure and physical conditions along the line of sight with cloud-by-cloud multiphase Bayesian modelling. The absorption system has a total $\log (N({{{\rm H}\,\rm{\small I}}})/{\rm cm}^{-2})=20.53$ and an $N({{{\rm H}\,\rm{\small I}}})$-weighted mean metallicity of log (Z/Z⊙) = −0.68, with a very large Mg ii linewidth of Δv ∼ 700 km s−1. The highly kinematically complex profile is well modelled with 30 clouds across low- and intermediate-ionization phases with values ${13\lesssim \log (N({{{\rm H}\,\rm{\small I}}})/{\rm cm}^{-2})\lesssim 20}$ and −3 ≲ log (Z/Z⊙) ≲ 1. Comparing these properties to the galaxy properties, we infer a wide range of gaseous environments, including metal-rich outflows, metal-poor IGM accretion, and tidal streams from galaxy–galaxy interactions. This diversity of structures forms the intragroup medium around a complex compact group environment at the epoch of peak star formation activity. Surveys of low-redshift compact groups would benefit from obtaining a more complete census of this medium for characterizing evolutionary pathways.

 

Several recent works have focused on the search for bright, high-z quasars (QSOs) in the South. Among them, the QUasars as BRIght beacons for Cosmology in the Southern hemisphere (QUBRICS) survey has now delivered hundreds of new spectroscopically confirmed QSOs selected by means of machine learning algorithms. Building upon the results obtained by introducing the probabilistic random forest (PRF) for the QUBRICS selection, we explore in this work the feasibility of training the algorithm on synthetic data to improve the completeness in the higher redshift bins. We also compare the performances of the algorithm if colours are used as primary features instead of magnitudes. We generate synthetic data based on a composite QSO spectral energy distribution. We first train the PRF to identify QSOs among stars and galaxies, then separate high-z quasar from low-z contaminants. We apply the algorithm on an updated data set, based on SkyMapper DR3, combined with Gaia eDR3, 2MASS, and WISE magnitudes. We find that employing colours as features slightly improves the results with respect to the algorithm trained on magnitude data. Adding synthetic data to the training set provides significantly better results with respect to the PRF trained only on spectroscopically confirmed QSOs. We estimate, on a testing data set, a completeness of $\sim 86{{\ \rm per\ cent}}$ and a contamination of $\sim 36{{\ \rm per\ cent}}$. Finally, 206 PRF-selected candidates were observed: 149/206 turned out to be genuine QSOs with z > 2.5, 41 with z < 2.5, 3 galaxies and 13 stars. The result confirms the ability of the PRF to select high-z quasars in large data sets.

 

Abstract. Current climate models have difficulty representing realistic wave–mean flow interactions, partly because the contribution from waves with fine vertical scales is poorly known. There are few direct observations of these waves, and most models have difficulty resolving them. This observational challenge cannot be addressed by satellite or sparse ground-based methods. The Strateole-2 long-duration stratospheric superpressure balloons that float with the horizontal wind on constant-density surfaces provide a unique platform for wave observations across a broad range of spatial and temporal scales. For the first time, balloon-borne Global Navigation Satellite System (GNSS) radio occultation (RO) is used to provide high-vertical-resolution equatorial wave observations. By tracking navigation signal refractive delays from GPS satellites near the horizon, 40–50 temperature profiles were retrieved daily, from balloon flight altitude (∼20 km) down to 6–8 km altitude, forming an orthogonal pattern of observations over a broad area (±400–500 km) surrounding the flight track. The refractivity profiles show an excellent agreement of better than 0.2 % with co-located radiosonde, spaceborne COSMIC-2 RO, and reanalysis products. The 200–500 m vertical resolution and the spatial and temporal continuity of sampling make it possible to extract properties of Kelvin waves and gravity waves with vertical wavelengths as short as 2–3 km. The results illustrate the difference in the Kelvin wave period (20 vs. 16 d) in the Lagrangian versus ground-fixed reference and as much as a 20 % difference in amplitude compared to COSMIC-2, both of which impact estimates of momentum flux. A small dataset from the extra Galileo, GLONASS, and BeiDou constellations demonstrates the feasibility of nearly doubling the sampling density in planned follow-on campaigns when data with full equatorial coverage will contribute to a better estimate of wave forcing on the quasi-biennial oscillation (QBO) and improved QBO representation in models. 

In this study, we use published geologic maps and cross-sections to construct a three-dimensional geologic model of major shear zones that make up the Himalayan orogenic wedge. The model incorporates microseismicity, megathrust coupling, and various derivatives of the topography to address several questions regarding observed crustal strain patterns and how they are expressed in the landscape. These questions include: (1) How does vertical thickening vary along strike of the orogen? (2) What is the role of oblique convergence in contributing to along-strike thickness variations and the style of deformation? (3) How do variations in the coupling along the megathrust affect the overlying structural style? (4) Do lateral ramps exist along the megathrust? (5) What structural styles underlie and are possibly responsible for the generation of high-elevation, low-relief landscapes? Our model shows that the orogenic core of the western and central Himalaya displays significant along-strike variation in its thickness, from ∼25−26 km in the western Himalaya to ∼34−42 km in the central Himalaya. The thickness of the orogenic core changes abruptly across the western bounding shear zone of the Gurla Mandhata metamorphic core complex, demonstrating a change in the style of strain there. Pressure-temperature-time results indicate that the thickness of the orogenic core at 37 Ma is 17 km. Assuming this is constant along strike from 81°E to 85°E indicates that, the western and central Nepal Himalaya have been thickened by 0.5 and 1−1.5 times, respectively. West of Gurla Mandhata the orogenic core is significantly thinner and underlies a large 11,000 km2 Neogene basin (Zhada). A broad, thick orogenic core associated with thrust duplexing is collocated with an 8500 km2 high-elevation, low-relief surface in the Mugu-Dolpa region of west Nepal. We propose that these results can be explained by oblique convergence along a megathrust with an along-strike and down-dip heterogeneous coupling pattern influenced by frontal and oblique ramps along the megathrust. 

We report an angle-tilted, wavelength-multiplexed ptychographic modulation approach for multispectral lensless on-chip microscopy. In this approach, we illuminate the specimen with lights at five wavelengths simultaneously. A prism is added at the illumination path for spectral dispersion. Thus, lightwaves at different wavelengths hit the specimen at slightly different incident angles, breaking the ambiguities in mixed-state ptychographic reconstruction. At the detection path, we place a thin diffuser between the specimen and the monochromatic image sensor for encoding the spectral information into 2D intensity measurements. By scanning the sample to different$x-<\#comment/>y$positions, we acquire a sequence of monochromatic images for reconstructing the five complex object profiles at the five wavelengths. An up-sampling procedure is integrated into the recovery process to bypass the resolution limit imposed by the imager pixel size. We demonstrate a half-pitch resolution of 0.55 µm using an image sensor with 1.85 µm pixel size. We also demonstrate quantitative and high-quality multispectral reconstructions of stained tissue sections for digital pathology applications.