In The Concise Evolutionary Essays, Robert B. Graber, ed.

https://www.berghahnbooks.com/title/GraberCarneir

Animated Sequences Showing the Ejecta Produced in the DART Impact of Asteroid (65803) Didymos

The data consist of 11 animated sequences, each with a leading panel that provides a summary of what is portrayed in that sequence. Additional information is given in the accompanying text for each file. Identical sequences are provided in both MOV and MP4 formats. Displaying with Quicktime or a similar app allows the user to play the movie at different speeds, and also to step through the sequence a frame at a time, which is helpful for following the details as the ejecta evolves. Time tags (seconds since the time of impact) are incorporated to help identify the images in the sequence. Zip files containing all 11 animated sequences are included for both MOV and MP4 versions.This data collection contains animated sequences showing different aspects of the ejecta that were observed after the Double Asteroid Impact Test (DART) spacecraft crashed into Dimorphos, the moon of asteroid (65803) Didymos on September 26, 2022. The images comprising the sequences were obtained with the LICIACube Unit Key Explorer (LUKE) instrument on board the LICIACube spacecraft that flew by the Didymos system about 3 minutes after the impact event. Although the sequences are comprised of the same observations they are presented in different ways to emphasize various aspects of the ejecta field. These animations are intended as a supplement to the individual LUKE images, to provide insight and to help in the interpretation of the data in support of studies that address spatial and temporal changes in the DART ejecta field. Note that in some of the sequences, black sections may encroach in from the sides. These are gaps in the data where the asteroids moved to the edge of the camera's detector.This study was supported in part by the DART mission, National Aeronautics and Space Administration (NASA) contract No. 80MSFC20D0004 to JHU/APL

Supplementary material for Applying Wearable Sensors and Machine Learning to the Diagnostic Challenge of Distinguishing Parkinson's Disease from Other Forms of Parkinsonism

Parkinson's Disease (PD) and other forms of parkinsonism share motor symptoms, including tremor, bradykinesia, and rigidity. This overlap in the clinical presentation creates a diagnostic challenge, underscoring the need for objective differentiation. However, applying machine learning (ML) to clinical datasets faces challenges such as imbalanced class distributions, small sample sizes for non-PD parkinsonism, and heterogeneity within the non-PD group. This study analyzed wearable sensor data from 260 PD participants and 18 individuals with etiologically diverse forms of non-PD parkinsonism during clinical mobility tasks, using a single sensor placed on the lower-back. We evaluated the performance of ML models in distinguishing these two groups and identified the most informative mobility tasks for classification. Additionally, we examined clinical characteristics of misclassified participants and presented case studies of common challenges in clinical practice, including diagnostic uncertainty at the initial visit and changes in diagnosis over time. We also suggested potential steps to address dataset challenges which limited the models' performance. We demonstrate that ML-based analysis is a promising approach for distinguishing idiopathic PD from non-PD parkinsonism, though its accuracy remains below that of expert clinicians. Using the Timed Up and Go test as a single mobility task outperformed the use of all tasks combined, achieving a balanced accuracy of 78.2%. We also identified differences in some clinical scores between participants correctly and falsely classified by our models. These findings demonstrate the feasibility of using ML and wearable sensors for differentiating PD from other parkinsonian disorders, addressing key challenges in diagnosis, and streamlining diagnostic workflows.Funding was provided by a University of Maryland MPower Seed Grant Award (R.v.C. and M.P.C), the Rosalyn Newman Foundation (L.M.S), and the University of Maryland Claude D. Pepper Older Americans Independence Center (P30-AG028747; R.v.C)

Identity Documents and Trans People in Maryland: Experiences with Name and Gender Markers

The Maryland Trans Survey is a community-based research project conducted by Trans Maryland and the Queer/Trans Collective for Research on Equity and Wellness examining experiences of trans people in the State of Maryland in areas such as health and healthcare, employment and economic wellbeing, and legal and policy experiences. To date, it is the largest survey of trans people in the State, with 750 trans people representing all 23 counties in Maryland and Baltimore City. Data were collected from June to December 2023 through in-person and online community outreach. The project was approved by Towson University’s Institutional Review Board (Protocol #1897) and used Transgender Research Informed Consent (TRICON) Disclosures to provide trans community members with additional transparency on the project, recognizing long histories of harmful practices in trans research from scientific institutions. This brief contains information from the survey related to name and gender on identity documents to help advocates, policymakers, and community-serving entities better understand and support the current needs of trans people in Maryland.University System of Maryland - Wilson H. Elkins Professorship (2021-2023); Washington University in St. Louis - Audre Lorde Distinguished Professorship (2023-present)https://transmaryland.org

Dataset for Constraining Wetland and Landfill Methane Emission Signatures Through Atmospheric Methane Clumped Isotopologue Measurements" [Paper #2024JG008249-T]

Described in methods section of primary paperFrom Primary Paper: Microbial methane emissions are associated with a wide range of isotopic signatures, providing information about the sources and sinks of methane. Methods of directly sampling methane from environments such as wetlands may fail to capture the temporal and spatial variations in emissions at a specific site and time. The Keeling plot method is commonly used to infer the overarching isotopic signatures of methane sources. In this study, we have expanded the application of the Keeling plot from conventional stable isotope ratios to include novel clumped isotopologue compositions of methane. This advancement aims to provide more robust constraints on regional methane emission signatures. We analyzed methane isotopologue compositions from air samples collected above wetlands and landfills across Maryland, USA, and determined the endmember compositions for background air, wetland, and landfill sources. Our findings indicate that the isotopologue compositions of methane from regional wetland emissions exhibit seasonal variations — δ13C and δD values become less positive as winter approaches, reflecting changes in methane oxidation and production rates. The continuous monitoring of air methane isotopologue signatures will deepen our understanding of the seasonal patterns in methane emissions and contribute to refining the global methane budget, as valuable insights can be extracted from these measurements.JS was supported by NOAA grant NA19NES4320002 (Cooperative Institute for Satellite Earth System Studies -CISESS) at UMD. Funding to support MH was provided by U.S. National Science Foundation grant (EAR-PF: 2052834)

Measurements of boulders ejected in the Double Asteroid Redirection Test (DART) impact

The data consist of two machine readable tables, with headers that describe the format of the data. The positions table lists the X and Y (row and column) pixel where the boulder is observed in each image where it is detected. The photometry table gives the brightness (irradiance) of a boulder in a 3-pixel radius in each image where it is measured, along with the uncertainty in that measurement. The brightness is normalized to a spacecraft range of 57.63 km (the LICIACue close approach distance).This data collection contains tables that provide measurements of the positions and brightnesses of meter-sized boulders that were ejected when the Double Asteroid Impact Test (DART) spacecraft crashed into Dimorphos, the moon of asteroid (65803) Didymos on September 26, 2022. The measurements come from the LICIACube Unit Key Explorer (LUKE) instrument on board the LICIACube spacecraft that flew by the Didymos system about 3 minutes after the impact event. The positions table provides the pixel locations of each boulder in the images where it was detected, while the photometry table gives the brightness for each boulder in each of the images where it was measured.This study was supported in part by the DART mission, National Aeronautics and Space Administration (NASA) contract No. 80MSFC20D0004 to JHU/APL

Acyclic Cucurbit[n]uril Bearing Alkyl Sulfate Ionic Groups - Electronic Supporting Data

The methodology is detailed in the published paper and the supporting information file.This dataset contains the electronic data files that support the publication.National Science Foundation (CHE-1807486); National Institute of General Medical Sciences of the National Institutes of Health (R35GM153362)

Active Seismic Exploration of Planetary Subsurfaces via Compressive Sensing

The software supports the following study: We present a method for improving seismic data collection on planetary surfaces such as the Moon and Mars. This approach is based on recent advances in compressive sensing technology to reduce the number of data collection points required compared to conventional methods without sacrificing the quality of the resulting subsurface images. We demonstrate its effectiveness using both synthetic and field data from locations with similarities to planetary surface environments. The method is then applied to reanalyze seismic data collected by the crew of the Apollo 14 and 16 missions. Our study has implications for mission planning, as this method can make space missions more efficient by reducing the equipment and time to collect geophysical data on planetary surfaces. It also makes it possible to reconstruct missing or damaged data, improving the quality of imagery and enhancing our understanding of the interior of other worlds.https://doi.org/10.1029/2024EA00382

Experimental data for Efficacy of sodium hypochlorite and peracetic acid in reducing cross‐contamination during washing of baby spinach at different water quality levels

This is the dataset for manuscript titled Efficacy of sodium hypochlorite and peracetic acid in reducing cross‐contamination during washing of baby spinach at different water quality levels that has the DOI of https://doi.org/10.1111/1750-3841.17657USDA-NIFAhttps://doi.org/10.1111/1750-3841.1765