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NASA NTRS1999

NASA/NOAA: Earth Science Electronic Theater 1999

The Electronic Theater (E-theater) presents visualizations which span the period from the original Suomi/Hasler animations of the first ATS-1 GEO weather satellite images in 1966 to the latest 1999 NASA Earth Science Vision for the next 25 years. Hot off the SGI-Onyx Graphics-Supercomputer are NASA's visualizations of Hurricanes Mitch, Georges, Fran and Linda. These storms have been recently featured on the covers of National Geographic, Time, Newsweek and Popular Science. Highlights will be shown from the NASA hurricane visualization resource video tape that has been used repeatedly this season on National and International network TV. Results will be presented from a new paper on automatic wind measurements in Hurricane Luis from 1-min GOES images that appeared in the November BAMS. The visualizations are produced by the NASA Goddard Visualization and Analysis Laboratory (VAL/912), and Scientific Visualization Studio (SVS/930), as well as other Goddard and NASA groups using NASA, NOAA, ESA, and NASDA Earth science datasets. Visualizations will be shown from the Earth Science E-Theater 1999 recently presented in Tokyo, Paris, Munich, Sydney, Melbourne, Honolulu, Washington, New York, and Dallas. The presentation Jan 11-14 at the AMS meeting in Dallas used a 4-CPU SGI/CRAY Onyx Infinite Reality Super Graphics Workstation with 8 GB RAM and a Terabyte Disk at 3840 X 1024 resolution with triple synchronized BarcoReality 9200 projectors on a 60ft wide screen. Visualizations will also be featured from the new Earth Today Exhibit which was opened by Vice President Gore on July 2, 1998 at the Smithsonian Air & Space museum in Washington, as well as those presented for possible use at the American Museum of Natural History (NYC), Disney EPCOT, and other venues. New methods are demonstrated for visualizing, interpreting, comparing, organizing and analyzing immense HyperImage remote sensing datasets and three dimensional numerical model results. We call the data from many new Earth sensing satellites, HyperImage datasets, because they have such high resolution in the spectral, temporal, spatial, and dynamic range domains. The traditional numerical spreadsheet paradigm has been extended to develop a scientific visualization approach for processing HyperImage datasets and 3D model results interactively. The advantages of extending the powerful spreadsheet style of computation to multiple sets of images and organizing image processing were demonstrated using the Distributed image SpreadSheet (DISS). The DISS is being used as a high performance testbed Next Generation Internet (NGI) VisAnalysis of: 1) El Nino SSTs and NDVI response 2) Latest GOES 10 5-min rapid Scans of 26 day 5000 frame movie of March & April '98 weather and tornadic storms 3) TRMM rainfall and lightning 4)GOES 9 satellite images/winds and NOAA aircraft radar of hurricane Luis, 5) lightning detector data merged with GOES image sequences, 6) Japanese GMS, TRMM, & ADEOS data 7) Chinese FY2 data 8) Meteosat & ERS/ATSR data 9) synchronized manipulation of multiple 3D numerical model views; and others will be illustrated. The Image SpreadSheet has been highly successful in producing Earth science visualizations for public outreach. Many of these visualizations have been widely disseminated through the world wide web pages of the HPCC/LTP/RSD program which can be found at http://rsd.gsfc.nasa.gov/rsd The one min interval animations of Hurricane Luis on ABC Nightline and the color perspective rendering of Hurricane Fran published by TIME, LIFE, Newsweek, Popular Science, National Geographic, Scientific American, and the "Weekly Reader" are some of the examples which will be shown.

Hasler, A. Fritz↗
NASA NTRS2001

Electronic-Theater 2001: Visions of Our Planet's Atmosphere, Land and Oceans

The NASA/NOAA/AMS Electronic Theater presents Earth science observations and visualizations in a historical perspective. Fly in from outer space to Wisconsin, Madison and the Monona Terrace Center. Drop in on the Kennedy Space Center and Park City Utah, site of the 2002 Olympics using I m IKONOS "Spy Satellite" data. Go back to the early weather satellite images from the 1960s pioneered by UW. Scientists and see them contrasted with the latest US and International global satellite weather movies including hurricanes & tornadoes. See the latest spectacular images from NASA/NOAA remote sensing missions like Terra GOES, TRMM, SeaWiFS, Landsat 7 that are visualized & explained. See how High Definition Television (HDTV) is revolutionizing the way we communicate science in cooperation with the American Museum of Natural History in NYC. See dust storms in Africa and smoke plumes from fires in Mexico. See visualizations featured on Newsweek, TIME, National Geographic, Popular Science covers & National & International Network TV. New visualization tools allow us to roam & zoom through massive global images eg Landsat tours of the US, Africa, & New Zealand showing desert and mountain geology as well as seasonal changes in vegetation. See animations of the polar ice packs and the motion of gigantic Antarctic Icebergs from SeaWinds data. Spectacular new visualizations of the global atmosphere & oceans are shown. See massive dust storms sweeping across Africa. See vortices and currents in the global oceans that bring up the nutrients to feed tiny plankton and draw the fish, whales and fisherman. See the how the ocean blooms in response to these currents and El Nina/La Nina climate changes. The demonstration is interactively driven by a SGI Onyx 11 Graphics Supercomputer with four CPUs, 8 Gigabytes of RAM and Terabyte of disk. With five projectors on a giant IMAX sized 18 x 72 ft screen. See the city lights, fishing fleets, gas flares and bio-mass burning of the Earth at night observed by the "nightvision" DMSP military satellite.

Hasler, Authur↗
NASA NTRS2013

Rapid Assessment of Contrast Sensitivity with Mobile Touch-screens

The availability of low-cost high-quality touch-screen displays in modern mobile devices has created opportunities for new approaches to routine visual measurements. Here we describe a novel method in which subjects use a finger swipe to indicate the transition from visible to invisible on a grating which is swept in both contrast and frequency. Because a single image can be swiped in about a second, it is practical to use a series of images to zoom in on particular ranges of contrast or frequency, both to increase the accuracy of the measurements and to obtain an estimate of the reliability of the subject. Sensitivities to chromatic and spatio-temporal modulations are easily measured using the same method. We will demonstrate a prototype for Apple Computer's iPad-iPod-iPhone family of devices, implemented using an open-source scripting environment known as QuIP (QUick Image Processing,

mobile devices↗
DOE OSTI2025

Dataset for Leveraging CryoEM and AI-Driven Morphological Feature Analysis for Insights on Bacterial Structures

This repository hosts an AI-assisted image segmentation and analysis pipeline for Pantoea sp. YR343 cryo-electron microscopy (cryoEM) datasets. The workflow automates membrane thickness measurements, flagella detection, and field-of-view (FOV) screening from low-dose, high-resolution cryoEM micrographs eliminating the need for slow manual annotation. By integrating deep-learning based segmentation (YOLOv11) with quantitative post-processing, this toolkit provides a scalable and reproducible way to study bacterial morphology under hydrated, near-native conditions. The GitHub repository for AI-based tools for cryoEM bacteria ultrastructures can be found here: https://github.com/Sireesiru/Cryo-EM-Ultrastructures/tree/main

60 APPLIED LIFE SCIENCES↗
NASA NTRS2017

VIIP 2017 Clinical Update

INTRODUCTION: NASA's Space Medicine community knowledge regarding the "Vision Impairment Intracranial Pressure", or VIIP.has been evolving over time.. Various measures of occupational health related to this condition had to be determined and then plans/processes put into place. The most robust of these processes were inititated in 2010. This presentation will provide a clinic update of the astronaut occupational health data related to VIIP. METHODS: NASA and its international partners require its astronauts to undergo routine health measures deemed important to monitoring VIIP. The concern is that the spaceflight environment aboard ISS could cause some astronauts to have physiologic changes detrimental to either ongoing mission operations or long-term health related to the ocular system and possibly the CNS. Specific medical tests include but are not limited to brain/orbit MRI (NASA unique protocol), OCT, fundoscopy and ocular ultrasound. Measures are taken prior to spaceflight, in-flight and post-flight. Measures to be reported include incidence of disc edema, globe flattening, choroidal folds, ONSD and change in refractive error. RESULTS: 73 ISS astronauts have been evaluated at least partially for VIIP related measures. Of these individuals, approximately 1 in 7 have experienced disc edema. The prevalence of the other findings is more complicated as the medical testing has changed over time. Overall, 26 separate individuals have experienced at least one of the findings NASA has associated with VIIP Another confounding factor is most of the astronauts have prior spaceflight experience at the time of the "pre-flight" testing. DISCUSSION: In 2010 NASA and its US operating segment (USOS) partners (CSA, ESA and JAXA) began routine occupational monitoring and data collection for most VIIP related changes. Interpretation of that data is extremely challenging for several reasons. For example, the determination of disc edema is the most complete finding as we have had highly qualified optometrists routinely and competently performing post-flight funduscopic exams for the entirety of the ISS program. Yet in 2013 NASA added OCT to our in-flight suite of eye exams. Shortly after routine screening with the OCT, a new term appeared within VIIP vernacular - "subclinical disc edema". OCT has much greater ability to measure change within the retina and provides significantly more data to analyze, understand and communicate out. Communicating VIIP data clearly adds even more challenge. Historically we've reported data per eye and not necessarily per person. This has led to difficulty in understanding how many individuals have experienced "VIIP" within the aerospace medicine community. The presenter will attempt to provide clear and concise communication of VIIP findings.

Tarver, William↗
DOE OSTI2026

Dataset for Top Model Decision Tree: Selecting Segmentation Models for Reliable Quantitative Analysis in Low- and Ultralow-Dose CryoEM

Motivation Multiple deep learning model architectures can be used to segment bacterial membranes in cryoEM images. However, an AI-based tool advancement is often presented with only a single segmentation model for broad use, and this single model may show inconsistent results across datasets from different users. Here, we present the Top Model Decision Tree, a model screening framework to screen for the best model to generate bacterial inner and outer membrane masks based on user priorities. We use pre-trained segmentation models from YOLOv11, YOLO26, U-Net, Detectron2 and SAM3 fine-tuned on bacterial inner and outer membranes imaged with cryoEM. Run the Framework This notebook must be opened in Google Colab. Mount Google Drive and run with a GPU-based runtime. Open the notebook and follow steps to git clone in folders and files within this repository. There will be a repeating top_model_decision_tree.ipynb (notebook clone) that will not be used. Save your .png binary mask files and .csv table outputs within your Google Drive or download before closing the notebook. The models and all analysis/training scripts are available at [GitHub: https://github.com/Lynnicia/CryoEM_membranes_top_model_decision_tree and https://github.com/Sireesiru/Semantic-Segmentation-of-bacterial-cell-envelope-using-U-Nets.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

The Art of Automation: Translating Electron Microscopy Workflows Into Automated Processes

Acquiring data using a scanning transmission electron microscope (STEM) is a complex, multi-step process. The intricacy of the process depends on the type of sample, composition of the material, desired results of the experiment, resolution requirement and other experimental factors. Each experiment presents unique complications, such as sample drift and contamination, that the microscopist must consider when acquiring data. All these challenges are handled fluidly and expertly by experienced microscopists, but to reach new levels of innovation in material development, including greater reproducibility, throughput, and precision, the automation of these workflows is essential. The initial phase of this work involved translating intuition-based workflows into discrete, programmable steps. Some common key stages in STEM workflows are the initial tuning, scanning the sample for areas of interest, and then acquiring the data. Each stage can be broken further into specific parameter adjustments, such as aberration correction and dwell time optimization, depending on the experiment. When deconstructing various experiments each step was assessed for automation feasibility based on the amount of real time operator decisions. There are steps that lend themselves to automation more readily than others, such as course focusing and sample screening, but there is potential for full automation of all stages with time. As an initial step, an automated montage routine was developed, allowing for the efficient acquisition of large portions of the sample without requiring continuous intervention from the operator. The automation of this small process of the procedure demonstrates the value of this capability. A major challenge in automation arises from discrepancies between commanded, reported and actual stage movements. Using systematic tests, stage movement was quantified. This error can be corrected algorithmically for more accurate workflows in the future. Expanding automation capabilities would result in larger, more efficient data acquisition which allows for more robust statistical analysis. Additionally, this work lays the groundwork for a closed loop system where machine learning algorithms would intake automatically acquired data and make real time decisions. By progressively automating this instrument, this work establishes the foundation for fully automated experimentation in transmission electron microscopy.

97 MATHEMATICS AND COMPUTING↗