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An Airborne Communications Roadmap for the U.S. Federal Air Marshal Service: Overview and Status

Following the events of September 11, 2001, the responsibilities, operations and numbers of the U.S. Federal Air Marshal Service (FAMS) wer e greatly expanded. With this expansion, new critical research and te chnology needs were identified, including the need for air to ground telecommunications capabilities. To address this need, the FAMS has cr eated a working group to develop, deploy and enhance aviation communi cations with respect to security and law enforcement. This paper presents the working group's progress to date in generating a FAMS air-gro und communications roadmap identifying expected communications servic es, technology maturity, and technology gaps over a timeline. The paper includes a communications preliminary requirements summary and syst em performance characteristics needed to meet identified operational needs. The system engineering process utilized is presented beginning with the identification of users, their operational needs and relevant constraints. The operational needs are translated to desired airbor ne communications services. System technical performance requirements associated with the identified services are summarized. In addition, notional communications architectures addressing the requirements are presented. Finally, future plans to identify and assess potential ca ndidate systems and their associated technical architectures, gaps and barriers to implementation are discussed. The paper addresses the cu rrent, near term (within 5 years) and far term (10 years) timeframes for such an airborne communications system.

Martzaklis, Konstantinos S.↗

Non-Intrusive Appliance Identification with Appliance-Specific Networks

The problem of noninstrusive load monitoring (NILM) is usually formulated as a single-channel blind source separation task, whose successful solution enable fast and convenient load identification and energy disaggregation. When applied at test time, NILM algorithms aim to identify the operating characteristics of individual appliances from an aggregate power measurement of the entire house. Recent advances in deep learning gave rise to many methods that mostly focus on learning a direct mapping from aggregate measurement to individual appliance power. However, these methods are not only computationally expensive, but they often suffer from overfitting and do not generalize very well. In this article, we propose a novel NILM method that leverages advances in statistical learning that have not been properly applied in this domain before. The proposed method consists of three stages: first, a Bayesian nonparametric learning-based approach for appliance state extraction; second, synthetic minority oversampling technique for data augmentation and mitigating the heavy imbalance in switching events; and third, appliance-specific lightweight long short-term memory networks for status classification for each appliance. Here, we adopt a “differential” input (the difference before and after the switching event) to reduce the complexity of network training and make the proposed method robust to multiappliance switching events. Experiments are conducted to demonstrate the effectiveness of the proposed method, achieving superior performance when compared to recent methods. An ablation study is conducted to demonstrate the effectiveness of each module of our method. Finally, we investigate the quality of generated synthetic samples.

42 ENGINEERING↗

Macro-physical Properties of Shallow Cumulus from Integrated ARM Observations (Final Report)

Fair-weather shallow cumuli (ShCu) play an important role in many climate-related processes. Irregular geometry of ShCu and their strong temporal and spatial variability make it challenging to observe ShCu holistically and to represent them correctly in climate models. To improve ShCu parameterizations, information on both vertically and horizontally resolved cloud properties is required. Commonly, the vertically resolved cloud properties are provided by zenith pointing lidar-radar observations with a very narrow field of view (FOV). Thus, these “pencil-beam” properties may not be representative of a larger surrounding area. Limited number of areal-averaged cloud properties, such as fractional sky cover (FSC), are offered typically by wide-FOV observations. The main goal of our project was to integrate advantages of the narrow-FOV (vertical structure of clouds) and wide-FOV (spatial arrangement of clouds) observations for an improved characterization of single-layer ShCu observed at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site for an 18-yr period (2000-2017). There are four major accomplishments of our project, First, an updated operational cloud classification for days with ShCu has been suggested and evaluated through a detailed comparison with the manually curated records. Our classification extends successfully the latest ARM cloud type Value Added Product (VAP) based on the Active Remote Sensing of Clouds (ARSCL) cloud product by incorporating both cloud fraction (CF) provided by narrow-FOV ceilometer data and FSC from wide-FOV images offered by a Total Sky Imager (TSI). Moreover, our classification allows one to identify impact of instrumentation changes at the SGP site, namely the transition to KAZRARSCL with the updated cloud radar, on the identification of periods with single-layer ShCu. Second, a new approach that resolves cloud area distributions for a given region (up to 4x4 km 2 ) has been suggested and cloud equivalent diameters (CEDs) have been estimated for the first time. These estimations have been performed over a wide range of cloud sizes (about 0.01–3.5 km) with high temporal resolution (30s) using wide-FOV TSI images and cloud base height (CBH) provided by complementary narrow-FOV lidar measurements. Our simple and computationally inexpensive approach offers a previously unavailable dataset for process studies in the convective boundary layer and evaluation of ShCu parameterizations in cloud-resolving models. Third, a long-term integrated record of ShCu macrophysical properties has been developed. The developed record represents the longest available compilation of events with ShCu and includes (i) a novel visualization of the spatial variability in cloud cover both along- and across-wind directions, (ii) updated estimates of narrow-FOV CF and wide-FOV FSC, (iii) updated narrow-FOV CBH, and (iv) complementary data, such as wind speed and direction from the 915-MHz Radar Wind Profiler (RWP) data. The developed record has been used successfully to assess conventional observational estimates of cloud cover and their sensitivity to the following two factors: (i) instrument-dependent cloud detection and data merging criteria and (ii) FOV configuration. Fourth, co-variability of the ShCu macrophysical properties and environmental parameters has been analyzed for a 3-yr period (2016-2018). Our initial analysis includes diurnal changes of FSCs obtained for clouds with small, moderate and large CEDs and several environmental parameters, such as lifted condensation level (LCL) and mixed layer height (zi). Preliminary results of our analysis suggest that the horizontal extent of ShCu is controlled substantially by the sign and magnitude of difference between these two parameters (zi-LCL): the CED tends to grow with increase of this difference (zi exceeds LCL). We have initiated relationships between the ShCu and key atmospheric parameters that control both the development and evolution of ShCu using our new data product, which combines effectively the advantages of narrow-FOV data offered by zenith pointing cloud radars and lidars and wide-FOV TSI images. While the latest instrumentation at the ARM sites may address these challenging relationships in the future, we believe that the historical ARM data at the SGP site has not yet been fully utilized. Overall, our data product can be used by researchers working on a wide range of climate-related projects. These projects may include (i) a comprehensive evaluation of outputs from the Large-Eddy Simulation (LES) and single-column models for their future improvement, (ii) the representativeness of “short-period” results obtained from the previous model and observational studies and (iii) the planning of future field campaigns with focus on improved understanding of the diurnal cycle of cumulus convection.

54 ENVIRONMENTAL SCIENCES↗

Commissioning the DIRC Detector and Searching for Axion-like Particles at GlueX

This thesis centers around problems in the study of the strong nuclear force. The GlueX DIRC, a Cherenkov radiation-based detector, was proposed to upgrade the particle identification capability of the GlueX experiment, which aims to perform quantitative tests of Quantum Chromodynamics in the nonperturbative regime by searching for and studying hybrid mesons. This thesis describes the construction, commissioning, reconstruction, and calibration of the GlueX DIRC detector. Originally proposed to solve the strong CP problem, axions and axion-like particles are hypothetical pseudoscalar particles found in many proposed extensions to the Standard Model of particle physics. This thesis presents a search for photoproduction of axion-like particles using data in photon-proton interactions collected by the GlueX experiment at Jefferson Laboratory in the $\gamma\gamma$ and $\pi^+\pi^-\pi^0$ final states of the axion-like particles. In addition, the Monte Carlo modeling of the strong interaction at low energies leads to challenges known as the event generator tuning problem. This thesis presents a novel approach to the Monte Carlo event generator tuning problem using Bayesian optimization.

Yang, Yunjie↗

Study of the Mu2e sensitivity to the $\mu^-\rightarrow e^+$ conversion process

The Mu2e experiment at Fermilab (Batavia, IL) will search for the coherent neutrinoless conversion of a muon into an electron in the electric field of an aluminum atom. The conversion process results in a monochromatic electron with energy slightly below the muon rest mass ($E_e= 104.97$ MeV). The experiment goal is to improve the previous measurement by four orders of magnitude and reach a single event sensitivity of $3 \times 10^{-17} $ on the conversion rate with respect to the muon capture rate. \\ The experiment will deliver a very intense pulsed negative muon beam to an aluminum target to achieve a total number of $10^{18}$ stopped muons in three years of running. Production and transport of the muons are accomplished with a sophisticated magnetic system comprised of a Production, a Transport and a Detector solenoid, with the last one hosting a Straw-tube Tracker and a Crystal Calorimeter. The entire detector region is surrounded by a Cosmic Ray Veto system. Mu2e is und er construction at the Muon Campus of Fermilab. \\ The INFN italian group is responsible for the design and construction of the crystal calorimeter, which plays a crucial role in the Mu2e measurement, providing particle identification capabilities fundamental for the rejection of the different background sources that can mimic a conversion electron. The calorimeter information allows also to improve the tracking performances it provides a fast standalone trigger for the experiment.\\ After a long R\&D phase, the final drawings see a calorimeter comprised of 1348 pure CsI crystals arranged in two annular disks. Each crystal is readout by two custom UV-extended Silicon Photomultipliers (SiPMs). Performances of the selected components were verified with an electron beam test, carried out in 2017 at the Beam Test Facility (BTF) at the National Laboratories of Frascati, on a large size prototype of 51 crystals and 102 SiPMs, confirming excellent energy ($\sigma_{E}/E = \mathcal{O }(10\%)$) and timing ($\sigma_{T} <500$ ps) resolutions in a! greement with the Mu2e specifications.\\ In the first chapters of this thesis, I describe my involvement in the calorimeter activities, with particular emphasis on the data analysis of the prototype energy response and resolution, that I was personally leading. Moreover, a description of the tuning of the simulation and the careful data-MC comparison is also reported.\\ An auxiliary measurement that can be performed with Mu2e is the search for a Lepton Number Violation (LNV) process where the negatively charged muon converts, without neutrinos, into a positron, $\mu ^{-} +N(A,Z) \rightarrow $ e$^+ +N(A,Z-2)$. At the moment of writing, Neutrinoless Double Beta Decay (0$\nu \beta \beta$) has set the most stringent limit on the LNV processes (T$^{0\nu \beta \beta}_{1/2} > 1.1 \times 10^{26} $ yr at 90$\%$ CL) with the GERDA experiment. In 0$\nu \beta \beta$ a pair of free electrons is created in the transformation from a nucleus $(A, Z)$ into its daughter $(A, Z + 2)$, namely: $(A,Z)\rightarrow (A, Z+2) =2 e^-$. Similar transitions could proceed through the emission of a pair of positrons, double electron capture (EC), or EC and single emission of a positron, with the nucleus changing from $(A, Z)$ to $(A, Z - 2)$. All these variations are equally interesting when discussing of new Physics, since they all manifest a non-conservation of the number of leptons.\\ Moreover, recent studies show that, because of flavor effect, off-diagonal processes, such as the $\mu^- -e^+$ conversion, can have their rate enhanced with respect to processes occurring in the $e-e$ sector.\\ Mu2e will search for $\mu^- + Al(27,13) \rightarrow e^+ +Na(27,11)$, only considering ground state transition, producing a conversion positron with energy $E_{e^+}= 92.32 $ MeV.\\ This thesis is focused on this search. In particular, I developed an algorithm to account for the radiative corrections to be applied to the conversion positrons that resulted in a few percent reduction in s ignal acceptance.\\ One of the most prominent background to ! this sear! ch is the Radiative Muon Capture (RMC) $ \mu+ N(Z,A)\rightarrow \gamma + \nu_{\mu} + N(Z-1,A)$. The produced photon can convert, virtually or in the detector materials (in the following referred as internal or external conversion respectively) in an electron-positron pair, producing positrons with energies approaching the expected conversion energy. Experimental results from previous experiments indicate the RMC endpoint ($\kmax$) to be of $\sim$ 90 MeV. A precise modeling of this background is relevant due to the proximity of the photon spectrum endpoint to the positron conversion energy. The calorimeter group is obviously interested to reconstruct the RMC distribution having also the opportunity to improve the current knowledge of the process. \\ A toy MC has been developed to evaluate the number of $e^+$ from external RMC background in the signal window. Knowing this value and ev...

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Identifying Urban Pluvial Frequency Flooding Hotspots Using the Topographic Control Index and Remote Sensing Radar Images for Early Warning Systems

Identifying areas that frequently experience post-rainfall ponding is essential for effective flood mitigation and planning. This study integrates Sentinel-1 radar imagery and the Topographic Control Index (TCI) to identify 378 flood-prone urban depressions in Beaumont, Texas. Out of 159 major rainfall events, only six had Sentinel-1 radar imagery acquired within six hours of peak rainfall, and these were used to generate the flood frequency map; the ground-based flood sensor data were used to verify that these selected events corresponded to actual peak rainfall and to validate radar-detected water pixels. Validation results showed 100% precision, 70.87% recall, an F1-score of 82.95%, and 71.32% overall accuracy. Approximately 84% of medium-to-high TCI depressions overlapped with Beaumont’s two-year inundation map, confirming a strong relationship between TCI and observed flooding. A total of 124 depressions retained significant water, and after excluding 25 engineered detention ponds, 99 natural depressions remained flood vulnerable. Among these, 74 depressions with medium or high TCI were identified as the highest-priority nuisance flooding hotspots. The results demonstrate that combining TCI with radar imagery provides a reliable and cost-effective approach for identifying areas prone to frequent urban ponding. This framework supports practical decision-making for drainage improvements, hotspot identification, and early-warning system development in urban flood-prone regions.

Sentinel-1 radar imagery↗

Introduction, Investigation, and Experimental Validation of a Novel Passive Neutron Spectrometer

Unfolding neutron energy spectra are instrumental for determining personal health effects and calculating dose received. This area of study is heavily researched, and Lawrence Livermore National Laboratory (LLNL) is investigating a passive neutron spectrometer for the purpose of acquiring the information needed to determine personnel dose in the event of a criticality accident. A part of this investigation is presented in this article through the examination of four experimental detector responses (DRs). These four DRs were acquired in the presence of 252 Cf, AmBe, GODIVA, and National Ignition Facility (NIF) neutron sources. An algorithm developed at LLNL was used to unfold the neutron fluence from each of the four DRs, and subsequently, fluence-to-dose conversion factors provided by the American National Standards Institute were used to calculate dose. Additionally, a multistep unfolding process was developed and employed to calculate the effects of both direct (from the source) and indirect (from room return) neutrons. The average error when unfolding the direct DR was less than 8%. The dose from 252 Cf was predicted with only 8% error. The multistep approach allowed for the identification of the low-energy neutrons in the 252 Cf, AmBe, and NIF DRs.

Nuclear Criticality Safety Program (NCSP)↗

Ion Composition of Titan's Ionosphere Observed During T9 Magnetotail Crossing

In a recent paper, Sittler et al., (2010) presented new results on the T9 encounter by the Cassini spacecraft when it passed through Titan s induced magnetotail. Two crossings were observed, but the first crossing, event 1, is thought to be out flowing ionosphere plasma. T9 is ideal for CAPS IMS probing of the ionosphere, since the ion densities at the higher altitudes of the T9 flyby approx. 10,000 km, allows measurements to be made down to 1 eV without saturating its detectors. Sittler et al., (2010) reported possible detection of NH4+ ions, but favored the detection of CH5+ and C2H5+ ions. In this report we investigate both the medium mass resolution (straight through (ST)) and high mass resolution (linear electric field (LEF)) composition data from the Cassini Plasma Spectrometer (CAPS) Ion Mass Spectrometer (IMS). We present a more in depth analysis of the composition data and make comparisons with ionospheric models including nitrogen chemistry such as that by Vuitton et al. (2007). The LEF data does not support NH4+ identification, but favors a CH5+ and C2H5+ identification, but also molecular ions C2N+ and CH2NH2+ are chemically allowed possibilities.

Sittler, Edward↗

The NASA Soil Moisture Active Passive (SMAP) Mission - Science and Data Product Development Status

The Soil Moisture Active Passive (SMAP) mission, planned for launch in late 2014, has the objective of frequent, global mapping of near-surface soil moisture and its freeze-thaw state. The SMAP measurement system utilizes an L-band radar and radiometer sharing a rotating 6-meter mesh reflector antenna. The instruments will operate on a spacecraft in a 685 km polar orbit with 6am/6pm nodal crossings, viewing the surface at a constant 40-degree incidence angle with a 1000-km swath width, providing 3-day global coverage. Data from the instruments will yield global maps of soil moisture and freeze/thaw state at 10 km and 3 km resolutions, respectively, every two to three days. The 10-km soil moisture product will be generated using a combined radar and radiometer retrieval algorithm. SMAP will also provide a radiometer-only soil moisture product at 40-km spatial resolution and a radar-only soil moisture product at 3-km resolution. The relative accuracies of these products will vary regionally and will depend on surface characteristics such as vegetation water content, vegetation type, surface roughness, and landscape heterogeneity. The SMAP soil moisture and freeze/thaw measurements will enable significantly improved estimates of the fluxes of water, energy and carbon between the land and atmosphere. Soil moisture and freeze/thaw controls of these fluxes are key factors in the performance of models used for weather and climate predictions and for quantifYing the global carbon balance. Soil moisture measurements are also of importance in modeling and predicting extreme events such as floods and droughts. The algorithms and data products for SMAP are being developed in the SMAP Science Data System (SDS) Testbed. In the Testbed algorithms are developed and evaluated using simulated SMAP observations as well as observational data from current airborne and spaceborne L-band sensors including data from the SMOS and Aquarius missions. We report here on the development status of the SMAP data products. The Testbed simulations are designed to capture various sources of errors in the products including environment effects, instrument effects (nonideal aspects of the measurement system), and retrieval algorithm errors. The SMAP project has developed a Calibration and Validation (Cal/Val) Plan that is designed to support algorithm development (pre-launch) and data product validation (post-launch). A key component of the Cal/Val Plan is the identification, characterization, and instrumentation of sites that can be used to calibrate and validate the sensor data (Level l) and derived geophysical products (Level 2 and higher).

Nloku, E.↗

A Burst and Simultaneous Short-Term Pulsed Flux Enhancement From The Magnetar Candidate 1E 1048.1-5937

We report on the 2004 June 29 X-ray burst detected from the direction of the AXP 1E 1048.1-5937 using the RXTE. We find a simultaneous increase of approx. 3.5 times the quiescent value in the 2-10 keV pulsed flux of 1E 1048.1-5937 during the tail of the burst, which identifies the AXP as the burst s origin. The burst was overall very similar to the two others reported from the direction of this source in 2001. The unambiguous identification of 1E 1048.1-5937 as the burster here confirms that it was the origin of the 2001 bursts as well. The epoch of the burst peak was very close to the arrival time of 1E 1048.1-5937 s pulse peak. The burst exhibited significant spectral evolution, with the trend going from hard to soft. Although the average spectrum of the burst was comparable in hardness (Lambda approx. 1.6) to those,of the 2001 bursts, the peak of this burst was much harder (Lambda approx. 0.3). During the 11 days following the burst, the AXP was observed further with RXTE, XMM-Newton, and Chandra. Pre- and post-burst observations revealed no change in the total flux or spectrum of the quiescent emission. Comparing all three bursts detected thus far from this source, we find that this event was the most fluent (>3.3 x 10(exp-8 ergs/sq cm) in the 2-20 keV band), had the highest peak flux (59+/-9 x 10(exp -10)ergs/s/sq cm) in the 2-20 keV band), and had the longest duration (>699 s). The long duration of the burst difFerentiates it from SGR bursts, which have typical durations of approx.0.1 s. Bursts that occur preferentially at pulse maximum, have fast rises, and long X-tails containing the majority of the total burst energy have been seen uniquely from AXPs. The marked differences between AXP and SGRs bursts may provide new clues to help understand the physical differences between these objects.

Gavriil, Fotis P.↗

Planetary Candidates from K2 Campaign 16

Given that Campaign 16 of the K2 mission is one of just two K2 campaigns observed so far in "forward-facing" mode, which enables immediate follow-up observations from the ground, we present a catalog of interesting targets identified through photometry alone. Our catalog includes 30 high-quality planet candidates (showing no signs of being non-planetary in nature), 48 more ambiguous events that may be either planets or false positives, 164 eclipsing binaries, and 231 other regularly periodic variable sources. We have released light curves for all targets in C16 and have also released system parameters and transit vetting plots for all interesting candidates identified in this paper. Of particular interest is a candidate planet orbiting the bright F dwarf HD 73344 (V = 6.9, K = 5.6) with an orbital period of 15 days. If confirmed, this object would correspond to a 2.56 +/- 0.18 R⊕ planet and would likely be a favorable target for radial velocity characterization. This paper is intended as a rapid release of planet candidates, eclipsing binaries, and other interesting periodic variables to maximize the scientific yield of this campaign, and as a test run for the upcoming TESS mission, whose frequent data releases call for similarly rapid candidate identification and efficient follow up.

bright F dwarf↗

Deep Learning for Fish Identification from Sonar Data (CRADA 481 Final Report)

In eastern regions of the United States, the American eel is a species of management and regulatory concern because of significant population declines, despite the species’ previous abundance in all tributaries of rivers flowing into the Atlantic Ocean. The American eel is also a candidate for listing under the U.S. Endangered Species Act. While hydropower construction and operation are only one of several factors contributing to this population decline, such a listing could impose additional regulatory challenges for a large number of hydropower projects. In this CRADA project, we improved technologies for identifying migrating eels with the goal of reducing the cost and time required for future American eel hydropower impact assessment and mitigation studies, while maintaining accuracy. We built on results from a previous FOA project (FOA# DE-FOA-0001662), led by the Electric Power Research Institute (EPRI), which developed a highly accurate, deep-learning method for identifying migrating eels from imaging sonar data. The current study aimed to further optimize this deep-learning model, originally designed for image classification, and to develop an object detection software capable of identifying fish from sonar videos in real time, enabling the detection of events like fish migrations and specific species, such as the American eel, at hydropower dams. The data conversion algorithms were packaged as software with a graphical user interface, and the software is evaluated by external collaborators. We focused on the American eel in this project and explored the transferability of the developed deep learning models to the sea lamprey, given the similar body shape and swimming behavior between the two species.

13 HYDRO ENERGY↗

Design, building, and testing of the postlanding systems for the assured crew return vehicle

The design, building, and testing of the postlanding support systems for a water-landing Assured Crew Return Vehicle (ACRV) are presented. One ACRV will be permanently docked to Space Station Freedom, fulfilling NASA's commitment to Assured Crew Return Capability in the event of an accident or illness. The configuration of the ACRV is based on an Apollo Command Module (ACM) derivative. The 1990-1991 effort concentrated on the design, building, and testing of a one-fifth scale model of the egress and stabilization systems. The objective was to determine the feasibility of (1) stabilizing the ACM out of the range of motions that cause seasickness and (2) the safe and rapid removal of a sick or injured crew member from the ACRV. The development of the ACRV postlanding systems model was performed at the University of Central Florida with guidance from the Kennedy Space Center ACRV program managers. Emphasis was placed on four major areas. First was design and construction of a one-fifth scale model of the ACM derivative to accommodate the egress and stabilization systems for testing. Second was the identification of a water test facility suitable for testing the model in all possible configurations. Third was the construction of the rapid egress mechanism designed in the previous academic year for incorporation into the ACRV model. The fourth area was construction and motion response testing of the attitude ring and underwater parachute systems.

Hosterman, Kenneth C.↗

Development of a Near Real-Time Hail Damage Swath Identification Algorithm for Vegetation

Every year in the Midwest and Great Plains, widespread greenness forms in conjunction with the latter part of the spring-summer growing season. This prevalent greenness forms as a result of the high concentration of agricultural areas having their crops reach their maturity before the fall harvest. This time of year also coincides with an enhanced hail frequency for the Great Plains (Cintineo et al. 2012). These severe thunderstorms can bring damaging winds and large hail that can result in damage to the surface vegetation. The spatial extent of the damage can relatively small concentrated area or be a vast swath of damage that is visible from space. These large areas of damage have been well documented over the years. In the late 1960s aerial photography was used to evaluate crop damage caused by hail. As satellite remote sensing technology has evolved, the identification of these hail damage streaks has increased. Satellites have made it possible to view these streaks in additional spectrums. Parker et al. (2005) documented two streaks using the Moderate Resolution Imaging Spectroradiometer (MODIS) that occurred in South Dakota. He noted the potential impact that these streaks had on the surface temperature and associated surface fluxes that are impacted by a change in temperature. Gallo et al. (2012) examined at the correlation between radar signatures and ground observations from storms that produced a hail damage swath in Central Iowa also using MODIS. Finally, Molthan et al. (2013) identified hail damage streaks through MODIS, Landsat-7, and SPOT observations of different resolutions for the development of a potential near-real time applications. The manual analysis of hail damage streaks in satellite imagery is both tedious and time consuming, and may be inconsistent from event to event. This study focuses on development of an objective and automatic algorithm to detect these areas of damage in a more efficient and timely manner. This study utilizes the MODIS sensor aboard the NASA Aqua satellite. Aqua was chosen due to an afternoon orbit over the United States when land surface temperatures are relatively warm and improve the contrast between damaged and undamaged areas. This orbit is also similar to the orbit of the Suomi-National Polar-orbiting Partnership (NPP) satellite. The Suomi NPP satellite hosts the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument, which is the next generation of a MODIS-like sensor in polar orbit.

MODIS VIIRS↗

The Archaeology of Little Wood Creek: New Chronometric Evidence

This study reports on the establishment of viable dates for several major cultural components at the Little Wood Creek site on the upper Hudson in Fort Edward, New York. The original excavation in the mid-1980s (Grossman et al. 1990) resulted in the identification of two major periods of occupation, a deeply buried Transitional period sequence of living floors, and closer to the surface, and separated by circa five feet of sterile alluvium, a series of Late Woodland period pits and features. Both are overlain by the discovery of the southern bastion of Revolutionary War-era Fort Edward. Ambiguities in the original bulk radiocarbon dating of the site left it in chronological limbo with widely divergent determinations for both prehistoric occupation periods. New AMS dates from 10 samples, four Transitional period and six Late Woodland period assays, both refined the absolute chronology of the site complex and clarified several major issues in the cultural and environmental history of the region. Together, these two sets of dates, combined with recent high resolution environmental sequences, provide sufficient resolution to correlate the newly defined periods of occupation with major events in the pollen and climate record of eastern New York State.

chronology↗

Supernova 1998bw In ESO 184-G82

Over the wavelength range 390-750 nm, we measure intrinsic linear polarization of 0.53 +/- 0.08 percent at position angle 49 +/- 3 deg, after correcting for Galactic interstellar polarization using the star HD 184100, which has polarization of 0.75 +/- 0.01 percent at p.a. 176.5 +/- 2.5 deg. This measured interstellar polarization is consistent with the Galactic extinction in this direction, estimated to be E(B-V) = 0.059 from IRAS maps, or E(B-V) = 0.079 from 21-cm H I. Interstellar polarization in the host galaxy ESO 184-G82 is expected to be negligible based on the relative absence of Na I D absorption at z = 0.00841 +/- 0.00005, the redshift of the environment of the supernova from narrow H II region emission lines in its spectrum. Polarization appears highest in between emission features in the total flux spectrum, which strengthens the interpretation of the polarization as intrinsic to the supernova. This modest polarization is less than that of some type-II supernovae, but greater than that of type-Ia supernovae, which are generally unpolarized. This supports the interpretation of SN 1998bw, a peculiar type-Ic supernova, as a core-collapse event in which the observed polarization is due to moderate asymmetry in either the photosphere of the ejecta or an overlying scattering envelope. However, this result does not strongly constrain arguments about whether some supernovae emit gamma-ray bursts, since such emission may come from a mildly relativistic shock associated with the radio emission and above the optical photosphere, without any requirements on beaming or orientation." A. V. Filippenko, University of California at Berkeley, comments on the total flux spectrum obtained above: "The spectrum most closely resembles those of the peculiar SN 1997ef, but perhaps evolving more slowly. It is not typical of type-Ic supernovae; indeed, the spectrum does not match any of the known spectral classes, but perhaps 'peculiar type Ic' is the best choice at this time. The object appears to be starting a transition to the nebular phase, but identifications of the broad emission features are uncertain. The feature at 650 nm is probably [Fe III], as is the one at 455 nm (perhaps with some contribution from Mg I]). That at 590 nm may be a mixture of [Co III] and Na D. The strongest feature, at 545 nm, may consist of Fe, Co, and Ti lines."

Kay, L. E.↗

A Machine Learning Approach to Objective Identification of Dust in Satellite Imagery

Airborne dust has broad adverse effects on human activity, including aviation, human health, and agriculture. Remote sensing observations are used to detect dust and aerosols in the atmosphere using long established techniques. False color Red-Green-Blue (RGB) imagery using band differences sensitive to dust absorption (Dust RGB) is currently used operationally to assist forecasters and decision-makers in identifying dust at night, but there are still limitations, subjectivity, and nuances to image interpretation making night-time dust identification difficult even for experts. This study applies machine learning to the problem of night-time dust detection with a simple random forest (RF) model using Geostationary Operational Environmental Satellite-16 (GOES-16) Advanced Baseline Imager (ABI) infrared imagery, band differences sensitive to dust absorption, and Dust RGB color components as inputs to the model. The RF model achieves an Area-Under-Curve (AUC) of 0.97 with a standard deviation of 0.04 for dust cases. For images with dust present, the model correctly labels 85% of dust pixels and 99.96% of no-dust pixels for all dust images in the validation data set. The addition of a single null case to the training data set drastically reduces error in labeling no-dust pixels as dust from 45% to 14.5%. Application of the machine learning model to the April 13–14, 2019 dust event demonstrates the ability of the model to identify dust during night-time hours when visual dust detection is limited by the cooling ground surface characteristics.

dust↗

Normalizing flows for domain adaptation when identifying Λ hyperon events

Here this study focuses on the application of a normalizing flow as a method of domain adaptation when classifying physics data. Normalizing flows offer a way to transform data points between two different distributions. The present study investigates a novel method of transforming latent representations of physics data to a normal distribution and then to a physics distribution again. The final distribution models a simulated distribution. After being transformed, the data can be classified by a neural network trained on labeled simulation data. The present study succeeds in training two normalizing flows that can transform between data (or simulation) and a Gaussian distribution.

47 OTHER INSTRUMENTATION↗