We present and analyze follow-up, higher resolution ($R$ $\sim$ 70) $H$ and $K$ band integral field spectroscopy of the superjovian exoplanet HIP 99770 b with SCExAO/CHARIS. Our new data recover the companion at a high signal-to-noise ratio in both bandpasses and more than double the astrometric baseline for its orbital motion. Jointly modeling HIP 99770 b's position and the star's astrometry from \textit{Hipparcos} and \textit{Gaia} yields orbital parameters consistent with those from the discovery paper, albeit with smaller errors, and a slight preference for a smaller semimajor axis ($\sim$15.7--15.8 au)and a larger eccentricity ($\sim$0.28--0.29), disfavoring a circular orbit. We revise its dynamical mass slightly downwards to 15.0$_{-4.4}^{+4.5}$ $M_{\rm Jup}$ for a flat prior and 13.1$_{-5.2}^{+4.8}$ $M_{\rm Jup}$ for a more standard log-uniform mass prior, where the inclusion of its relative radial-velocity measurement is primarily responsible for these changes. \textcolor{red}{We find consistent results for HIP 99770 b's dynamical mass including recent VLTI/GRAVITY astrometry, albeit with a slightly smaller, better constrained eccentricity of $e$ $\sim$ 0.22$^{+0.10}_{-0.13}$}. HIP 99770 b is a $\sim$ 1300 K object at the L/T transition with a gravity intermediate between that of the HR 8799 planets and older, more massive field brown dwarfs with similar temperatures but with hints of equilibrium chemistry. HIP 99770 b is particularly well suited for spectroscopic follow up with Roman CGI during the technology demonstration phase at 730 nm to further constrain its metallicity and chemistry; JWST thermal infrared observations could likewise explore the planet's carbon chemistry, metallicity, and clouds.

Results from a study of Fe K-alpha emission lines for a sample of six non-magnetic Cataclysmic Variables (CVs) using the high resolution X-ray data from the Chandra High Energy Transmission Grating (HETG) are presented. Two of the sources, SS Cyg and U Gem are observed in both quiescent and outburst states whereas V603 Aql, V426 Oph, WX Hyi and SU UMa are observed only in quiescence. The fluorescent Fe line is prominent in V603 Aql, V426 Oph and SS Cyg during quiescence indicating the presence of a conspicuous reflection component in these sources. The observed equivalent width of the fluorescent Fe line is consistent with reflection from a white dwarf surface that subtends 2pi solid angle at the X-ray source. During the outburst in SS Cyg, the fluorescent line is red-shifted by about 2300 km/s. The Fe XXV triplet at 6.7 keV is found to be dominant in all sources. The value of the G-ratio derived from the Fe XXV triplet indicates that the plasma is in collisional ionization equilibrium during the quiescent state. The Fe XXV line is significantly broadened in U Gem and SS Cyg during the outbursts compared to quiescence, indicating the presence of a high velocity material near the white dwarf during the outburst. The ratio of Fe XXVI/XXV indicates a higher ionization temperature during quiescence than in outburst in U Gem and SS Cyg.

For one of the first set of Roman Coronagraph project images, we propose to target AB Aurigae. AB Aurigae is a complex and visually stunning system, surrounded by a gas rich protoplanetary disk showing numerous spiral arms, an enigmatic embedded protoplanet (AB Aurigae b) at 0\farcs{}6 separation, and hints of potential additional sites of planet formation. Even a marginally-successful dark hole generation (e.g. 10$^{-5}$--10$^{-6}$ contrast) with CGI would yield a vastly improved view of AB Aur b at optical wavelengths where current ground-based and HST data struggle to yield a high SNR detection and parameters (astrometry, photometry) unbiased by processing artifacts. Total intensity imaging and polarimetry together will provide new constraints on the disk's dust properties and the range of emission sources for AB Aur b. AB Aur images with the Roman Coronagraph will provide a striking, inspiring demonstrations of the instrument's power and promise for detecting fainter planets and disks.

In this paper we present the stellar Value-Added Catalogue (VAC) based on the DESI Data Release 1. This VAC contains stellar parameter, abundance and radial velocity measurements for more than 4 million stars. It also contains, for the first time, measurements from individual epochs for more than a million stars with at least two observations. The main contribution to the catalogue comes from the bright program of the main survey, which includes $\sim$2.5 million stars, and the backup program, which includes $\sim$ 1 million stars. The combined magnitude range for the stars in the catalogue extends from Gaia G $\sim 12$ to G $\sim 21$. For the magnitude range $17.5

Recent years have witnessed the remarkable progress of applying deep learning models in video person re-identification (Re-ID). A key factor for video person Re-ID is to effectively construct discriminative and robust video feature representations for many complicated situations. Part-based approaches employ spatial and temporal attention to extract representative local features. While correlations between parts are ignored in the previous methods, to leverage the relations of different parts, we propose an innovative adaptive graph representation learning scheme for video person Re-ID, which enables the contextual interactions between relevant regional features. Specifically, we exploit the pose alignment connection and the feature affinity connection to construct an adaptive structure-aware adjacency graph, which models the intrinsic relations between graph nodes. We perform feature propagation on the adjacency graph to refine regional features iteratively, and the neighbor nodes' information is taken into account for part feature representation. To learn compact and discriminative representations, we further propose a novel temporal resolution-aware regularization, which enforces the consistency among different temporal resolutions for the same identities. We conduct extensive evaluations on four benchmarks, i.e. iLIDS-VID, PRID2011, MARS, and DukeMTMC-VideoReID, experimental results achieve the competitive performance which demonstrates the effectiveness of our proposed method. The code is available at this https URL.

We consider equations of M\"uller-Israel-Stewart type describing a relativistic viscous fluid with bulk viscosity in four-dimensional Minkowski space. We show that there exists a class of smooth initial data that are localized perturbations of constant states for which the corresponding unique solutions to the Cauchy problem break down in finite time. Specifically, we prove that in finite time such solutions develop a singularity or become unphysical in a sense that we make precise. We also show that in general Riemann invariants do not exist in 1+1 dimensions for physically relevant equations of state and viscosity coefficients. Finally, we present a more general version of a result by Y. Guo and A.S. Tahvildar-Zadeh: we prove large-data singularity formation results for perfect fluids under very general assumptions on the equation of state, allowing any value for the fluid sound speed strictly less than the speed of light.

Human activity recognition (HAR) using drone-mounted cameras has attracted considerable interest from the computer vision research community in recent years. A robust and efficient HAR system has a pivotal role in fields like video surveillance, crowd behavior analysis, sports analysis, and human-computer interaction. What makes it challenging are the complex poses, understanding different viewpoints, and the environmental scenarios where the action is taking place. To address such complexities, in this paper, we propose a novel Sparse Weighted Temporal Attention (SWTA) module to utilize sparsely sampled video frames for obtaining global weighted temporal attention. The proposed SWTA is comprised of two parts. First, temporal segment network that sparsely samples a given set of frames. Second, weighted temporal attention, which incorporates a fusion of attention maps derived from optical flow, with raw RGB images. This is followed by a basenet network, which comprises a convolutional neural network (CNN) module along with fully connected layers that provide us with activity recognition. The SWTA network can be used as a plug-in module to the existing deep CNN architectures, for optimizing them to learn temporal information by eliminating the need for a separate temporal stream. It has been evaluated on three publicly available benchmark datasets, namely Okutama, MOD20, and Drone-Action. The proposed model has received an accuracy of 72.76%, 92.56%, and 78.86% on the respective datasets thereby surpassing the previous state-of-the-art performances by a margin of 25.26%, 18.56%, and 2.94%, respectively.

Multi-access edge computing (MEC) is a promising architecture to provide low-latency applications for future Internet of Things (IoT)-based network systems. Together with the increasing scholarly attention on task offloading, the problem of edge servers' resource allocation has been widely studied. Most of previous works focus on a single edge server (ES) serving multiple terminal entities (TEs), which restricts their access to sufficient resources. In this paper, we consider a MEC resource transaction market with multiple ESs and multiple TEs, which are interdependent and mutually influence each other. However, this many-to-many interaction requires resolving several problems, including task allocation, TEs' selection on ESs and conflicting interests of both parties. Game theory can be used as an effective tool to realize the interests of two or more conflicting individuals in the trading market. Therefore, we propose a bilateral game framework among multiple ESs and multiple TEs by modeling the task outsourcing problem as two noncooperative games: the supplier and customer side games. In the first game, the supply function bidding mechanism is employed to model the ESs' profit maximization problem. The ESs submit their bids to the scheduler, where the computing service price is computed and sent to the TEs. While in the second game, TEs determine the optimal demand profiles according to ESs' bids to maximize their payoff. The existence and uniqueness of the Nash equilibrium in the aforementioned games are proved. A distributed task outsourcing algorithm (DTOA) is designed to determine the equilibrium. Simulation results have demonstrated the superior performance of DTOA in increasing the ESs' profit and TEs' payoff, as well as flattening the peak and off-peak load.

Surface roughness is primary measure of pavement performance that has been associated with ride quality and vehicle operating costs. Of all the surface roughness indicators, the International Roughness Index (IRI) is the most widely used. However, it is costly to measure IRI, and for this reason, certain road classes are excluded from IRI measurements at a network level. Higher levels of distresses are generally associated with higher roughness. However, for a given roughness level, pavement data typically exhibits a great deal of variability in the distress types, density, and severity. It is hypothesized that it is feasible to estimate the IRI of a pavement section given its distress types and their respective densities and severities. To investigate this hypothesis, this paper uses data from in-service pavements and machine learning methods to ascertain the extent to which IRI can be predicted given a set of pavement attributes. The results suggest that machine learning can be used reliably to estimate IRI based on the measured distress types and their respective densities and severities. The analysis also showed that IRI estimated this way depends on the pavement type and functional class. The paper also includes an exploratory section that addresses the reverse situation, that is, estimating the probability of pavement distress type distribution and occurrence severity/extent based on a given roughness level.

We analyze near-infrared integral field spectropolarimetry of the AB Aurigae protoplanetary disk and protoplanet (AB Aur b), obtained with SCExAO/CHARIS in 22 wavelength channels covering the J, H, and K passbands ($\lambda_{\rm o}$ = 1.1--2.4 $\mu m$) over angular separations of $\rho$ $\approx$ 0.13" to 1.1" ($\sim$20--175 au). Our images resolve spiral structures in the disk in each CHARIS channel. At the longest wavelengths, the data may reveal an extension of the western spiral seen in previous polarimetric data at $\rho$ < 0.3" out to larger distances clockwise from the protoplanet AB Aur b, coincident with the ALMA-detected $CO$ gas spiral. While AB Aur b is detectable in complementary total intensity data, it is a non-detection in polarized light at $\lambda$ > 1.3 $\mu$m. While the observed disk color is extremely red across $JHK$, the disk has a blue intrinsic scattering color consistent with small dust grains. The disk's polarization spectrum is redder than AB Aur b's total intensity spectrum. The polarization fraction peaks at $\sim$ 0.6 along the major disk axis. Radiative transfer modeling of the CHARIS data shows that small, porous dust grains with a porosity of $p$ = 0.6--0.8 better reproduce the scattered-light appearance of the disk than more compact spheres ($p$ = 0.3), especially the polarization fraction. This work demonstrates the utility of integral field spectropolarimetry to characterize structures in protoplanetary disks and elucidate the properties of the disks' dust.

We demonstrate how a target model's generalization gap leads directly to an effective deterministic black box membership inference attack (MIA). This provides an upper bound on how secure a model can be to MIA based on a simple metric. Moreover, this attack is shown to be optimal in the expected sense given access to only certain likely obtainable metrics regarding the network's training and performance. Experimentally, this attack is shown to be comparable in accuracy to state-of-art MIAs in many cases.

Ground-based telescopes coupled with adaptive optics (AO) have been playing a leading role in exoplanet direct imaging science and technological development for the past two decades and will continue to have an indispensable role for the next decade and beyond. Over the next decade, extreme AO systems on 8-10m telescopes will 1) mitigate risk for WFIRST-CGI by identifying numerous planets the mission can spectrally characterize, 2) validate performance requirements and motivate improvements to atmosphere models needed to unambiguously characterize solar system-analogues from space, and 3) mature novel technological innovations useful for space. Extremely Large Telescopes can deliver the first thermal infrared (10 $\mu m$) images of rocky planets around Sun-like stars and identify biomarkers. These data provide a future NASA direct imaging flagship mission (i.e. HabEx, LUVOIR) with numerous exo-Earth candidates and critical ancillary information to help clarify whether these planets are habitable.

We introduce an approach to improve team performance in a Multi-Agent Multi-Armed Bandit (MAMAB) framework using Fastest Mixing Markov Chain (FMMC) and Fastest Distributed Linear Averaging (FDLA) optimization algorithms. The multi-agent team is represented using a fixed relational network and simulated using the Coop-UCB2 algorithm. The edge weights of the communication network directly impact the time taken to reach distributed consensus. Our goal is to shrink the timescale on which the convergence of the consensus occurs to achieve optimal team performance and maximize reward. Through our experiments, we show that the convergence to team consensus occurs slightly faster in large constrained networks.

The unified model of active galactic nuclei (AGN) claims that the properties of AGN depend on the viewing angle of the observer with respect to a toroidal distribution of dust surrounding the nucleus. Both the mid-infrared (MIR) attenuation and continuum luminosity are expected to be related to dust associated with the torus. Therefore, isolating the nuclear component is essential to study the MIR emission of AGN. We have compiled all the T-ReCS spectra (Gemini observatory) available in the N-band for 22 AGN: 5 Type-1 and 17 Type-2 AGN. The high angular resolution of the T-ReCs spectra allows us to probe physical regions of 57 pc (median). We have used a novel pipeline called RedCan capable of producing flux- and wavelength-calibrated spectra for the CanariCam (GTC) and T-ReCS (Gemini) instruments. We have measured the fine-structure [SIV] at 10.5 microns and the PAH at 11.3 microns line strengths together with the silicate absorption/emission features. We have also compiled Spitzer/IRS spectra to understand how spatial resolution influences the results. The 11.3 microns PAH feature is only clearly detected in the nuclear spectra of two AGN, while it is more common in the Spitzer data. For those two objects the AGN emission in NGC7130 accounts for more than 80% of the MIR continuum at 12 microns while in the case of NGC1808 the AGN is not dominating the MIR emission. This is confirmed by the correlation between the MIR and X-ray continuum luminosities. The [SIV] emission line at 10.5 microns, which is believed to originate in the narrow line region, is detected in most AGN. We have found an enhancement of the optical depth at 9.7 microns in the high-angular resolution data for higher values of NH. Clumpy torus models reproduce the observed values only if the host-galaxy properties are taken into account.

In the framework of Supersymmetric Grand Unified Theories (SUSY GUTs), the universe undergoes a cascade of symmetry breakings, during which topological defects can be formed. We address the question of the probability of cosmic string formation after a phase of hybrid inflation within a large number of models of SUSY GUTs in agreement with particle and cosmological data. We show that cosmic strings are extremely generic and should be used to relate cosmology and high energy physics. This conclusion is employed together with the WMAP CMB data to strongly constrain SUSY hybrid inflation models. F-term and D-term inflation are studied in the SUSY and minimal SUGRA framework. They are both found to agree with data but suffer from fine tuning of their superpotential coupling (\lambda \lesssim 3\times 10^(-5) or less). Mass scales of inflation are also constrained to be less than M \lesssim 3\times 10^(15) GeV.

We analyze high-contrast, medium-spectral-resolution $H_{\rm \alpha}$ observations of the star AB Aurigae using the Very Large Telescope's Multi Unit Spectroscopic Explorer (MUSE). In multiple epochs, MUSE detects the AB Aur b protoplanet discovered from Subaru/SCExAO data in emission at wavelengths slightly blue-shifted from the $H_{\rm \alpha}$ line center (i.e. at 6558.88--6560.13 Å; $\sim$ -100 km s$^{-1}$) and in absorption at redshifted wavelengths (6562.8--6565.1 Å; $\sim$ 75 km s$^{-1}$). AB Aur b's $H_{\rm \alpha}$ spectrum is inconsistent with that of the host star or the average residual disk spectrum and is dissimilar to that of PDS 70 b and c. Instead, the spectrum's shape resembles that of an inverse P Cygni profile seen in some accreting T Tauri stars and interpreted as evidence of infalling cold gas from accretion, although we cannot formally rule out all other nonaccretion origins for AB Aur b's MUSE detection. AB Aurigae hosts only the second protoplanetary system detected in $H_{\rm \alpha}$ thus far and the first with a source showing a spectrum resembling an inverse P Cygni profile. Future modeling and new optical data will be needed to assess how much of AB Aur b's emission source(s) originates from protoplanet accretion reprocessed by the disk, a localized scattered-light feature with a unique $H_{\rm \alpha}$ profile, or another mechanism.

The New Horizons spacecraft's encounter with the cold classical Kuiper belt object (486958) Arrokoth (formerly 2014 MU69) revealed a contact-binary planetesimal. We investigate how it formed, finding it is the product of a gentle, low-speed merger in the early Solar System. Its two lenticular lobes suggest low-velocity accumulation of numerous smaller planetesimals within a gravitationally collapsing, solid particle cloud. The geometric alignment of the lobes indicates the lobes were a co-orbiting binary that experienced angular momentum loss and subsequent merger, possibly due to dynamical friction and collisions within the cloud or later gas drag. Arrokoth's contact-binary shape was preserved by the benign dynamical and collisional environment of the cold classical Kuiper belt, and so informs the accretion processes that operated in the early Solar System.

The Planet Formation Imager (PFI) project aims to provide a strong scientific vision for ground-based optical astronomy beyond the upcoming generation of Extremely Large Telescopes. We make the case that a breakthrough in angular resolution imaging capabilities is required in order to unravel the processes involved in planet formation. PFI will be optimised to provide a complete census of the protoplanet population at all stellocentric radii and over the age range from 0.1 to about 100 Myr. Within this age period, planetary systems undergo dramatic changes and the final architecture of planetary systems is determined. Our goal is to study the planetary birth on the natural spatial scale where the material is assembled, which is the "Hill Sphere" of the forming planet, and to characterise the protoplanetary cores by measuring their masses and physical properties. Our science working group has investigated the observational characteristics of these young protoplanets as well as the migration mechanisms that might alter the system architecture. We simulated the imprints that the planets leave in the disk and study how PFI could revolutionise areas ranging from exoplanet to extragalactic science. In this contribution we outline the key science drivers of PFI and discuss the requirements that will guide the technology choices, the site selection, and potential science/technology tradeoffs.

We describe the motivation, design, and early results for our 42-night, 125 star Subaru/SCExAO direct imaging survey for planets around accelerating stars. Unlike prior large surveys, ours focuses only on stars showing evidence for an astrometric acceleration plausibly due to the dynamical pull of an unseen planet or brown dwarf. Our program is motivated by results from a recent pilot program that found the first planet jointly discovered from direct imaging and astrometry and resulted in a planet and brown dwarf discovery rate substantially higher than previous unbiased surveys like GPIES. The first preliminary results from our program reveal multiple new companions; discovered planets and brown dwarfs can be further characterized with follow-up data, including higher-resolution spectra. Finally, we describe the critical role this program plays in supporting the Roman Space Telescope Coronagraphic Instrument, providing a currently-missing list of targets suitable for the CGI technological demonstration without which the CGI tech demo risks failure.