Witnessing a Galaxy Cluster Merger with JWST and a Chandra X-ray Temperature Map

The first James Webb Space Telescope (JWST) image released was of galaxy cluster SMACSJ0723.3- 7327, a lensing cluster at z=0.39 showing detail only JWST can provide. While the majority of the focus has been on the brilliantly lensed galaxies at redshifts far beyond it, there is more to the story than it being just a lensing cluster. The Chandra X-ray temperature map tells a tale of a merging cluster with a significant subcluster leaving a wake in the intracluster medium (ICM). This paper presents a high fidelity temperature map of SMACSJ0723.3-7327 using adaptive circular binning, overlaid with the JWST image, showing clear signs of merger activity. As the ICM extends well past the boundaries of the JWST imagery, and no low-frequency radio observations are yet published, a fuller story of this cluster remains to be told. This new X-ray temperature map reveals new details of a moderately distant actively merging cluster.Comment: 4 Pages, 1 Figure, Submitted to Research Notes

Dominance of grain size impacts on seasonal snow albedo at deforested sites in New Hampshire

Snow cover serves as a major control on the surface energy budget in temperate regions due to its high reflectivity compared to underlying surfaces. Winter in the northeastern United States has changed over the last several decades, resulting in shallower snowpacks, fewer days of snow cover, and increasing precipitation falling as rain in the winter. As these climatic changes occur, it is imperative that we understand current controls on the evolution of seasonal snow albedo in the region. Over three winter seasons between 2013 and 2015, snow characterization measurements were made at three open sites across New Hampshire. These near-daily measurements include spectral albedo, snow optical grain size determined through contact spectroscopy, snow depth, snow density, black carbon content, local meteorological parameters, and analysis of storm trajectories using the Hybrid Single-Particle Lagrangian Integrated Trajectory model. Using analysis of variance, we determine that land-based winter storms result in marginally higher albedo than coastal storms or storms from the Atlantic Ocean. Through multiple regression analysis, we determine that snow grain size is significantly more important in albedo reduction than black carbon content or snow density. And finally, we present a parameterization of albedo based on days since snowfall and temperature that accounts for 52% of variance in albedo over all three sites and years. Our improved understanding of current controls on snow albedo in the region will allow for better assessment of potential response of seasonal snow albedo and snow cover to changing climate

Light incoherence due to quantum-gravitational fluctuations of the background space

Based on the theory of mutual coherence of light from an extended incoherent quasi-monochromatic source (providing a basis of stellar interferometry) we estimate the degree of light incoherence due to quantum-gravitational fluctuations of the background metric. It is shown that the stellar interferometry observational data considered in the literature for a last few years as a manifestation against the Planck scale quantum-gravitational fluctuations of the background metric have no chance for detecting such an effect.Comment: 5 pages; Version to appear in Astroparticle Physic

A longer vernal window: The role of winter coldness and snowpack in driving spring thresholds and lags

Climate change is altering the timing and duration of the vernal window, a period that marks the end of winter and the start of the growing season when rapid transitions in ecosystem energy, water, nutrient, and carbon dynamics take place. Research on this period typically captures only a portion of the ecosystem in transition and focuses largely on the dates by which the system wakes up. Previous work has not addressed lags between transitions that represent delays in energy, water, nutrient, and carbon flows. The objectives of this study were to establish the sequence of physical and biogeochemical transitions and lags during the vernal window period and to understand how climate change may alter them. We synthesized observations from a statewide sensor network in New Hampshire, USA, that concurrently monitored climate, snow, soils, and streams over a three-year period and supplemented these observations with climate reanalysis data, snow data assimilation model output, and satellite spectral data. We found that some of the transitions that occurred within the vernal window were sequential, with air temperatures warming prior to snow melt, which preceded forest canopy closure. Other transitions were simultaneous with one another and had zero-length lags, such as snowpack disappearance, rapid soil warming, and peak stream discharge. We modeled lags as a function of both winter coldness and snow depth, both of which are expected to decline with climate change. Warmer winters with less snow resulted in longer lags and a more protracted vernal window. This lengthening of individual lags and of the entire vernal window carries important consequences for the thermodynamics and biogeochemistry of ecosystems, both during the winter-to-spring transition and throughout the rest of the year

History, College of Medicine: 1959-1968. Chapter 2: College Administration

Prepared for the Centennial of The Ohio State University

DECISIVE Benchmarking Data Report: sUAS Performance Results from Phase I

This report reviews all results derived from performance benchmarking conducted during Phase I of the Development and Execution of Comprehensive and Integrated Subterranean Intelligent Vehicle Evaluations (DECISIVE) project by the University of Massachusetts Lowell, using the test methods specified in the DECISIVE Test Methods Handbook v1.1 for evaluating small unmanned aerial systems (sUAS) performance in subterranean and constrained indoor environments, spanning communications, field readiness, interface, obstacle avoidance, navigation, mapping, autonomy, trust, and situation awareness. Using those 20 test methods, over 230 tests were conducted across 8 sUAS platforms: Cleo Robotics Dronut X1P (P = prototype), FLIR Black Hornet PRS, Flyability Elios 2 GOV, Lumenier Nighthawk V3, Parrot ANAFI USA GOV, Skydio X2D, Teal Golden Eagle, and Vantage Robotics Vesper. Best in class criteria is specified for each applicable test method and the sUAS that match this criteria are named for each test method, including a high-level executive summary of their performance.Comment: Approved for public release: PAO #PR2023_74172; arXiv admin note: substantial text overlap with arXiv:2211.0180

DECISIVE Test Methods Handbook: Test Methods for Evaluating sUAS in Subterranean and Constrained Indoor Environments, Version 1.1

This handbook outlines all test methods developed under the Development and Execution of Comprehensive and Integrated Subterranean Intelligent Vehicle Evaluations (DECISIVE) project by the University of Massachusetts Lowell for evaluating small unmanned aerial systems (sUAS) performance in subterranean and constrained indoor environments, spanning communications, field readiness, interface, obstacle avoidance, navigation, mapping, autonomy, trust, and situation awareness. For sUAS deployment in subterranean and constrained indoor environments, this puts forth two assumptions about applicable sUAS to be evaluated using these test methods: (1) able to operate without access to GPS signal, and (2) width from prop top to prop tip does not exceed 91 cm (36 in) wide (i.e., can physically fit through a typical doorway, although successful navigation through is not guaranteed). All test methods are specified using a common format: Purpose, Summary of Test Method, Apparatus and Artifacts, Equipment, Metrics, Procedure, and Example Data. All test methods are designed to be run in real-world environments (e.g., MOUT sites) or using fabricated apparatuses (e.g., test bays built from wood, or contained inside of one or more shipping containers).Comment: Approved for public release: PAO #PR2022_4705

Neuropathology of wild-type and nef-attenuated T cell tropic simian immunodeficiency virus (SIVmac32H) and macrophage tropic neurovirulent SIVmac17E-Fr in cynomolgus macaques

The neuropathology of simian immunodeficiency (SIV) infection in cynomolgus macaques (Macaca fascicularis) was investigated following infection with either T cell tropic SIVmacJ5, SIVmacC8 or macrophage tropic SIVmac17E-Fr. Formalin fixed, paraffin embedded brain tissue sections were analysed using a combination of in situ techniques. Macaques infected with either wild-type SIVmacJ5 or neurovirulent SIVmac17E-Fr showed evidence of neuronal dephosphorylation, loss of oligodendrocyte and CCR5 staining, lack of microglial MHC II expression, infiltration by CD4+ and CD8+ T cells and mild astrocytosis. SIVmacJ5-infected animals exhibited activation of microglia whilst those infected with SIVmac17E-Fr demonstrated a loss of microglia staining. These results are suggestive of impaired central nervous system (CNS) physiology. Furthermore, infiltration by T cells into the brain parenchyma indicated disruption of the blood brain barrier (BBB). Animals infected with the Δnef-attenuated SIVmacC8 showed microglial activation and astrogliosis indicative of an inflammatory response, lack of MHC II and CCR5 staining and infiltration by CD8+ T cells. These results demonstrate that the SIV infection of cynomolgus macaque can be used as a model to replicate the range of CNS pathologies observed following HIV infection of humans and to investigate the pathogenesis of HIV associated neuropathology