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L-band radar scattering from grass

A radar system based on a network analyzer has been developed to study the backscatter from vegetation. The radar is operated at L-band. Radar measurements of a grass field were made in 1991. The radar returns from the grass were measured at three incidence angles. Ground truth and canopy parameters such as blade and stem dimensions, moisture content of the grass and the soil, and blade and stem density, were measured. These parameters are used in a distorted Born approximation model to compute the backscatter coefficients from the grass layer. The model results are compared with the radar data.

Chauhan, N.

Assimilative modeling of low latitude ionosphere

In this paper we present an observation system simulation experiment for modeling low-latitude ionosphere using a 3-dimensional (3-D) global assimilative ionospheric model (GAIM). The experiment is conducted to test the effectiveness of GAIM with a 4-D variational approach (4DVAR) in estimation of the ExB drift and thermospheric wind in the magnetic meridional planes simultaneously for all longitude or local time sectors. The operational Global Positioning System (GPS) satellites and the ground-based global GPS receiver network of the International GPS Service are used in the experiment as the data assimilation source. 'The optimization of the ionospheric state (electron density) modeling is performed through a nonlinear least-squares minimization process that adjusts the dynamical forces to reduce the difference between the modeled and observed slant total electron content in the entire modeled region. The present experiment for multiple force estimations reinforces our previous assessment made through single driver estimations conducted for the ExB drift only.

data assimilation

An intercomparison of ground-based total ozone instruments

Five ground-based total ozone spectrophotometers were intercompared at Wallops Island, VA between October 1979 and January 1981. The tests were conducted to evaluate the stability and accuracy of each instrument over an extended time period. Acceptable performance regarding these two characteristics is essential if an instrument is to be useful in field measurements and network monitoring of the atmospheric total ozone content. The Dobson spectrophotometer was used as the standard of comparison for the Brewer grating spectrophotometer, the USSR M-83 ozonometer, the Canterbury filter photometer, and the SenTran filter photometer. The grating instrument was found to be potentially the equal of the Dobson but was subject to unreliable performance by its rather sophisticated electronic components. The filter photometers performed acceptably for short periods but filter aging and eventual degradation rendered both units unusable before the end of the intercomparison. Finally, the M-83 results were found to be in acceptable agreement with the Dobson throughout the period when certain qualifications are invoked. The accuracy of a single M-83 ozone measurement may be low. Averages tend to improve its agreement with the Dobson.

Parsons, C. L.

Deploying a Route Optimization EFB Application for Commercial Airline Operational Trials

The Traffic Aware Planner (TAP), developed for NASA Langley Research Center to support the Traffic Aware Strategic Aircrew Requests (TASAR) project, is a flight-efficiency software application developed for an Electronic Flight Bag (EFB). Tested in two flight trials and planned for operational testing by two commercial airlines, TAP is a real-time trajectory optimization application that leverages connectivity with onboard avionics and broadband Internet sources to compute and recommend route modifications to flight crews to improve fuel and time performance. The application utilizes a wide range of data, including Automatic Dependent Surveillance Broadcast (ADS-B) traffic, Flight Management System (FMS) guidance and intent, on-board sensors, published winds and weather, and Special Use Airspace (SUA) schedules. This paper discusses the challenges of developing and deploying TAP to various EFB platforms, our solutions to some of these challenges, and lessons learned, to assist commercial software developers and hardware manufacturers in their efforts to implement and extend TAP functionality in their environments. EFB applications (such as TAP) typically access avionics data via an ARINC 834 Simple Text Avionics Protocol (STAP) server hosted by an Aircraft Interface Device (AID) or other installed hardware. While the protocol is standardized, the data sources, content, and transmission rates can vary from aircraft to aircraft. Additionally, the method of communicating with the AID may vary depending on EFB hardware and/or the availability of onboard networking services, such as Ethernet, WIFI, Bluetooth, or other mechanisms. EFBs with portable and installed components can be implemented using a variety of operating systems, and cockpits are increasingly incorporating tablet-based technologies, further expanding the number of platforms the application may need to support. Supporting multiple EFB platforms, AIDs, avionics datasets, and user interfaces presents a challenge for software developers and the management of their code baselines. Maintaining multiple baselines to support all deployment targets can be extremely cumbersome and expensive. Certification also needs to be considered when developing the application. Regardless of whether the software is itself destined to be certified, data requirements in support of the application and user interface elements may introduce certification requirements for EFB manufacturers and the airlines. The example of TAP, the challenges faced, solutions implemented, and lessons learned will give EFB application and hardware developers insight into future potential requirements in deploying TAP or similar flight-deck EFB applications.

Roscoe, David A.

Comparative genomic analysis of thermophilic fungi reveals convergent evolutionary adaptations and gene losses

Thermophily is a trait scattered across the fungal tree of life, with its highest prevalence within three fungal families (Chaetomiaceae, Thermoascaceae, and Trichocomaceae), as well as some members of the phylum Mucoromycota. We examined 37 thermophilic and thermotolerant species and 42 mesophilic species for this study and identified thermophily as the ancestral state of all three prominent families of thermophilic fungi. Thermophilic fungal genomes were found to encode various thermostable enzymes, including carbohydrate-active enzymes such as endoxylanases, which are useful for many industrial applications. At the same time, the overall gene counts, especially in gene families responsible for microbial defense such as secondary metabolism, are reduced in thermophiles compared to mesophiles. We also found a reduction in the core genome size of thermophiles in both the Chaetomiaceae family and the Eurotiomycetes class. The Gene Ontology terms lost in thermophilic fungi include primary metabolism, transporters, UV response, and O-methyltransferases. Comparative genomics analysis also revealed higher GC content in the third base of codons (GC3) and a lower effective number of codons in fungal thermophiles than in both thermotolerant and mesophilic fungi. Furthermore, using the Support Vector Machine classifier, we identified several Pfam domains capable of discriminating between genomes of thermophiles and mesophiles with 94% accuracy. Using AlphaFold2 to predict protein structures of endoxylanases (GH10), we built a similarity network based on the structures. We found that the number of disulfide bonds appears important for protein structure, and the network clusters based on protein structures correlate with the optimal activity temperature. Thus, comparative genomics offers new insights into the biology, adaptation, and evolutionary history of thermophilic fungi while providing a parts list for bioengineering applications.

59 BASIC BIOLOGICAL SCIENCES

Millimeter-Wave Radar Field Measurements and Inversion of Cloud Parameters for the 1999 Mt. Washington Icing Sensors Project

The Mount Washington Icing Sensors Project (MWISP) was a multi-investigator experiment with participants from Quadrant Engineering, NOAA Environmental Technology Laboratory (NOAA/ETL), the Microwave Remote Sensing Laboratory (MIRSL) of the University of Massachusetts (UMass), and others. Radar systems from UMass and NOAA/ETL were used to measure X-, Ka-, and W-band backscatter data from the base of Mt. Washington, while simultaneous in-situ particle measurements were made from aircraft and from the observatory at the summit. This report presents range and time profiles of liquid water content and particle size parameters derived from range profiles of radar reflectivity as measured at X-, Ka-, and W-band (9.3, 33.1, and 94.9 GHz) using an artificial neural network inversion algorithm. In this report, we provide a brief description of the experiment configuration, radar systems, and a review of the artificial neural network used to extract cloud parameters from the radar data. Time histories of liquid water content (LWC), mean volume diameter (MVD) and mean Z diameter (MZD) are plotted at 300 m range intervals for slant ranges between 1.1 and 4 km. Appendix A provides details on the extraction of radar reflectivity from measured radar power, and Appendix B provides summary logs of the weather conditions for each day in which we processed data.

Pazmany, Andrew L.

Aircraft Operations Classification System

Accurate data is important in the aviation planning process. In this project we consider systems for measuring aircraft activity at airports. This would include determining the type of aircraft such as jet, helicopter, single engine, and multiengine propeller. Some of the issues involved in deploying technologies for monitoring aircraft operations are cost, reliability, and accuracy. In addition, the system must be field portable and acceptable at airports. A comparison of technologies was conducted and it was decided that an aircraft monitoring system should be based upon acoustic technology. A multimedia relational database was established for the study. The information contained in the database consists of airport information, runway information, acoustic records, photographic records, a description of the event (takeoff, landing), aircraft type, and environmental information. We extracted features from the time signal and the frequency content of the signal. A multi-layer feed-forward neural network was chosen as the classifier. Training and testing results were obtained. We were able to obtain classification results of over 90 percent for training and testing for takeoff events.

Harlow, Charles

A Data-Driven Framework for Predicting the Sorting and Screening Performance of an Integrated Biomass Feedstock Preprocessing System

The characteristics of mechanically sorted and screened lignocellulosic biomass, such as the mass contents of corn stover anatomical fractions (leaves, husks, stalks, cobs, etc.), can be used to calculate the intermediate feedstock quality attributes “yield” and “purity” that indicate the conversion efficiency of biocrude. No prior study has investigated the correlations from the characteristics of raw biomass and preprocessing unit operation parameters to those intermediate feedstock quality attributes. This work presents a data-driven framework for assessing and predicting the intermediate feedstock quality attributes in an integrated biomass feedstock preprocessing system. Our study used corn stover as a typical type of herbaceous biomass because of its abundance in the U.S. It began with data acquisition of moisture content, particle size distribution, and anatomical fractions of the materials after each unit operation in the system. The objective of this preprocessing system is to minimize husks and leaves and maximizing cobs and stalks by mechanically separating the materials into three streams via disc screen and air separator. Prototype neural network models were then developed to evaluate the feasibility of predicting process outcomes based on measurable parameters. It is found that incorporating physical constraints into these prediction models significantly enhances the accuracy of the predicted yield and purity against the ground truth data. The experimental data and model predictions indicate that decreasing throughput increases purity, while higher throughput results in lower purity. Finally, an optimization problem was introduced to search optimal combinations of feed material properties and preprocessing unit operation parameters, as the intermediate feedstock quality attributes – yield and purity, appeared to be competing factors. The study also suggests the continual need to improve the data-driven framework’s predictability by incorporating more accurate physical models to describe the dynamics in the preprocessing units such as the air separator.

09 - BIOMASS FUELS

Ionosphere Delay Calibration and Calibration Errors for Satellite Navigation of Aircraft

The Federal Aviation Administration (FAA) is implementing a satellite-based navigation system for aircraft using the Global Positioning System (GPS). Positioning accuracy of a few meters will be achieved by broadcasting corrections to the direct GPS signal. These corrections are derived using the wide-area augmentation system (WAAS), which includes a ground network of at least 24 GPS receivers across the Continental US (CONUS). WAAS will provide real-time total electron content (TEC) measurements that can be mapped to fixed grid points using a real-time mapping algorithm. These TECs will be converted into vertical delay corrections for the GPS L1 frequency and broadcast to users every five minutes via geosynchronous satellite. Users will convert these delays to slant calibrations along their own lines-of-sight (LOS) to GPS satellites. Uncertainties in the delay calibrations will also be broadcast, allowing users to estimate the uncertainty of their position. To maintain user safety without reverting to excessive safety margins an empirical model of user calibration errors has been developed. WAAS performance depends on factors that include geographic location (errors increase near WAAS borders), and ionospheric conditions, such as the enhanced spatial electron density gradients found during ionospheric storms.

Harris, Ian

NASA Tech Briefs, January 2012

Contents of this issue are: (1) Energy-Based Tetrahedron Sensor for High-Temperature, High-Pressure Environments (2) Handheld Universal Diagnostic Sensor (3) Large-Area Vacuum Ultraviolet Sensors (4) Fiber Bragg Grating Sensor System for Monitoring Smart Composite Aerospace Structures (5) Health-Enabled Smart Sensor Fusion Technology (6) Extended-Range Passive RFID and Sensor Tags (7) Hybrid Collaborative Learning for Classification and Clustering in Sensor Networks (8) Self-Healing, Inflatable, Rigidizable Shelter (9) Improvements in Cold-Plate Fabrication (10) Technique for Radiometer and Antenna Array Calibration - TRAAC (11) Real-Time Cognitive Computing Architecture for Data Fusion in a Dynamic Environment (12) Programmable Digital Controller (13) Use of CCSDS Packets Over SpaceWire to Control Hardware (14) Key Decision Record Creation and Approval Module (15) Enhanced Graphics for Extended Scale Range (16) Debris Examination Using Ballistic and Radar Integrated Software (17) Data Distribution System (DDS) and Solar Dynamic Observatory Ground Station (SDOGS) (18) Integration Manager (19) Eclipse-Free-Time Assessment Tool for IRIS (20) Automated and Manual Rocket Crater Measurement Software (21) MATLAB Stability and Control Toolbox Trim and Static Stability Module (22) Patched Conic Trajectory Code (23) Ring Image Analyzer (24) SureTrak Probability of Impact Display (25) Implementation of a Non-Metallic Barrier in an Electric Motor (26) Multi-Mission Radioisotope Thermoelectric Generator Heat Exchangers for the Mars Science Laboratory Rover (27) Uniform Dust Distributor for Testing Radiative Emittance of Dust-Coated Surfaces (28) MicroProbe Small Unmanned Aerial System (29) Highly Stable and Active Catalyst for Sabatier Reactions (30) Better Proton-Conducting Polymers for Fuel-Cell Membranes (31) CCD Camera Lens Interface for Real-Time Theodolite Alignment (32) Peregrine 100-km Sounding Rocket Project (33) SOFIA Closed- and Open-Door Aerodynamic Analyses (34) Sonic Thermometer for High-Altitude Balloons (35) Near-Infrared Photon-Counting Camera for High-Sensitivity Observations (36) Integrated Optics Achromatic Nuller for Stellar Interferometry (37) High-Speed Digital Interferometry (38) Ultra-Miniature Lidar Scanner for Launch Range Data Collection (39) Shape and Color Features for Object Recognition Search (40) Explanation Capabilities for Behavior-Based Robot Control (41) A DNA-Inspired Encryption Methodology for Secure, Mobile Ad Hoc Networks (42) Quality Control Method for a Micro-Nano-Channel Microfabricated Device (43) Corner-Cube Retroreflector Instrument for Advanced Lunar Laser Ranging (44) Electrospray Collection of Lunar Dust (45) Fabrication of a Kilopixel Array of Superconducting Microcalorimeters with Microstripline Wiring Spacecraft Attitude Tracking and Maneuver Using Combined Magnetic Actuators (46) Coherent Detector for Near-Angle Scattering and Polarization Characterization of Telescope Mirror Coatings

Source record

Investigation Organizer

Contents include the folloving:Overview of the Application; Input Data; Analytical Process; Tool's Output; and Application of the Results of the Analysis.The tool enables the first element through a Web-based application that can be accessed by distributed teams to store and retrieve any type of digital investigation material in a secure environment. The second is accomplished by making the relationships between information explicit through the use of a semantic network-a structure that literally allows an investigator or team to "connect -the-dots." The third element, the significance of the correlated information, is established through causality and consistency tests using a number of different methods embedded within the tool, including fault trees, event sequences, and other accident models. And finally, the evidence gathered and structured within the tool can be directly, electronically archived to preserve the evidence and investigative reasoning.

Panontin, Tina

Estimating Total Electron Content Using 1,000+ GPS Receivers

A computer program uses data from more than 1,000 Global Positioning System (GPS) receivers in an Internet-accessible global network to generate daily estimates of the global distribution of vertical total electron content (VTEC) of the ionosphere. This program supersedes an older program capable of processing readings from only about 200 GPS receivers. This program downloads the data via the Internet, then processes the data in three stages. In the first stage, raw data from a global subnetwork of about 200 receivers are preprocessed, station by station, in a Kalman-filter-based least-squares estimation scheme that estimates satellite and receiver differential biases for these receivers and for satellites. In the second stage, an observation equation that incorporates the results from the first stage and the raw data from the remaining 800 receivers is solved to obtain the differential biases for these receivers. The only remaining error sources for which an account cannot be given are multipath and receiver noise contributions. The third stage is a postprocessing stage in which all the processed data are combined and used to generate new data products, including receiver differential biases and global and regional VTEC maps and animations.

Komjathy, Attila

Global Soil Moisture from the Aquarius/SAC-D Satellite: Description and Initial Assessment

Aquarius satellite observations over land offer a new resource for measuring soil moisture from space. Although Aquarius was designed for ocean salinity mapping, our objective in this investigation is to exploit the large amount of land observations that Aquarius acquires and extend the mission scope to include the retrieval of surface soil moisture. The soil moisture retrieval algorithm development focused on using only the radiometer data because of the extensive heritage of passive microwave retrieval of soil moisture. The single channel algorithm (SCA) was implemented using the Aquarius observations to estimate surface soil moisture. Aquarius radiometer observations from three beams (after bias/gain modification) along with the National Centers for Environmental Prediction model forecast surface temperatures were then used to retrieve soil moisture. Ancillary data inputs required for using the SCA are vegetation water content, land surface temperature, and several soil and vegetation parameters based on land cover classes. The resulting global spatial patterns of soil moisture were consistent with the precipitation climatology and with soil moisture from other satellite missions (Advanced Microwave Scanning Radiometer for the Earth Observing System and Soil Moisture Ocean Salinity). Initial assessments were performed using in situ observations from the U.S. Department of Agriculture Little Washita and Little River watershed soil moisture networks. Results showed good performance by the algorithm for these land surface conditions for the period of August 2011-June 2013 (rmse = 0.031 m(exp 3)/m(exp 3), Bias = −0.007 m(exp 3)/m(exp 3), and R = 0.855). This radiometer-only soil moisture product will serve as a baseline for continuing research on both active and combined passive-active soil moisture algorithms. The products are routinely available through the National Aeronautics and Space Administration data archive at the National Snow and Ice Data Center.

Soil MOisture

Populus PtrbHLH011 Is a Transcriptional Co‐Regulator Involved in the Activation of Cell Wall Biosynthesis by Iron Deprivation

The lack of a mechanistic understanding of the environmental plasticity of secondary cell wall (SCW) biosynthesis restricts large-scale biomass and bioenergy production on marginal lands. Using Populus (poplar), a key bioenergy crop, we discovered that iron deprivation, a prevalent abiotic stress on marginal lands, stimulates SCW biosynthesis in stems. We identified the transcription factor PtrbHLH011 as a critical regulator underlying this response. Through integrated analyses involving phenotypic characterisation of PtrbHLH011 knockout and overexpression plants, functional genomics and molecular investigations, we established that PtrbHLH011 functions as a central regulator of SCW biosynthesis, iron homeostasis and flavonoid biosynthesis by directly repressing essential genes in these pathways. Iron deprivation downregulates PtrbHLH011 expression, subsequently activating these biosynthetic pathways. Notably, cytosine base editing-based knockout of PtrbHLH011 significantly enhanced plant growth, yielding up to a 110% increase in stem diameter and a 300% increase in leaf iron content. These findings present a novel regulatory mechanism linking environmental iron availability to SCW biosynthesis and illustrate a practical strategy to improve biomass yield on iron-deficient marginal lands. Furthermore, our mechanistic insights into PtrbHLH011 target recognition and regulation provide a valuable foundation for precise manipulation of gene regulatory networks, facilitating the development of high-performance bioenergy crops adapted to marginal environments.

59 BASIC BIOLOGICAL SCIENCES

Towards Content Authenticity: Multimodal Fake News Detection and AI-Generated Text Identification

In today’s digital world, the spread of fake news and the rise of AI-generated text have become major threats to content authenticity and public trust. This thesis addresses both challenges through two complementary research directions: detecting fake news using multimodal features, and identifying AI-generated text using semantic and structural reasoning. The first part of the work focuses on fake news detection by introducing a novel model that combines text and image features through a unique rotational attention mechanism. Unlike traditional attention methods, this approach rotates the roles of query, key, and value across modalities to capture deeper interactions. Additionally, the model incorporates external domain information by linking news posts to top-ranked websites from Google search results, which helps assess the credibility of content based on its broader web context. This results in a more reliable and accurate fake news detection system that outperforms existing state-of-the-art methods. The second part presents SGG-ATD, a new framework for detecting AI-generated text. It uses masked language modeling to measure sentence coherence, followed by constructing a graph where keywords—both original and predicted—are connected based on semantic and contextual similarity. A Graph Convolutional Network (GCN) is then used to learn structural relationships within the text for final classification. Experimental results demonstrate that SGG-ATD achieves high F1-scores and consistently outperforms strong baselines. This method contributes to robust AI text detection, supporting accountability and resilience against AI-driven misinformation.

Gupta, Nidhi

Developing Flexible, High Performance Polymers with Self-Healing Capabilities

Flexible, high performance polymers such as polyimides are often employed in aerospace applications. They typically find uses in areas where improved physical characteristics such as fire resistance, long term thermal stability, and solvent resistance are required. It is anticipated that such polymers could find uses in future long duration exploration missions as well. Their use would be even more advantageous if self-healing capability or mechanisms could be incorporated into these polymers. Such innovative approaches are currently being studied at the NASA Kennedy Space Center for use in high performance wiring systems or inflatable and habitation structures. Self-healing or self-sealing capability would significantly reduce maintenance requirements, and increase the safety and reliability performance of the systems into which these polymers would be incorporated. Many unique challenges need to be overcome in order to incorporate a self-healing mechanism into flexible, high performance polymers. Significant research into the incorporation of a self-healing mechanism into structural composites has been carried out over the past decade by a number of groups, notable among them being the University of I1linois [I]. Various mechanisms for the introduction of self-healing have been investigated. Examples of these are: 1) Microcapsule-based healant delivery. 2) Vascular network delivery. 3) Damage induced triggering of latent substrate properties. Successful self-healing has been demonstrated in structural epoxy systems with almost complete reestablishment of composite strength being achieved through the use of microcapsulation technology. However, the incorporation of a self-healing mechanism into a system in which the material is flexible, or a thin film, is much more challenging. In the case of using microencapsulation, healant core content must be small enough to reside in films less than 0.1 millimeters thick, and must overcome significant capillary and surface tension forces to flow, mix and react to achieve healing. Vascular networks small enough to fit into such films must also overcome these same flow limitations. Self-healing has also been demonstrated in ionomeric substrates such as Surlyn , wherein the heat generated by a projectile impact triggers the latent ability of this substrate to flow back to its original shape. Recent work using Diels-Alder reactions have shown promise in bringing about actual reforming of broken chemical bonds to achieve self-healing [2]. All self-healing mechanisms that rely on the use of inherent latent substrate properties require some degree of polymer chain flow to achieve any significant level of healing.

Jolley, Scott T.

Characterizing the Relationships Among Lightning and Storm Parameters: Lightning as a Proxy Variable

We have gained important insights from prior studies that have suggested relationships between lightning and storm growth, decay, convective rain flux, vertical distribution of storm mass and echo volume in the region, and storm energetics. A study was initiated in the Summer of 1996 to determine how total (in-cloud plus ground) lightning observations might provide added knowledge to the forecaster in the determination and identification of severe thunderstorms and weather hazards in real-time. The Melbourne Weather Office was selected as a primary site to conduct this study because Melbourne is the only site in the world with continuous and open access to total lightning (LDAR) data and a Doppler (WSR-88D) radar. A Lightning Imaging Sensor Data Applications Demonstration (LISDAD) system was integrated into the forecaster's workstation during the Summer 1996 to allow the forecaster to interact in real-time with the multi-sensor data being displayed. LISDAD currently ingests LDAR data, the cloud-to-ground National Lightning Detection Network (NLDN) data, and the Melbourne radar data in f real-time. The interactive features provide the duty forecaster the ability to perform quick diagnostics on storm cells of interest. Upon selection of a storm cell, a pop-up box appears displaying the time-history of various storm parameters (e.g., maximum radar reflectivity, height of maximum reflectivity, echo-top height, NLDN and LDAR lightning flash rates, storm-based vertically integrated liquid water content). This product is archived to aid on detailed post-analysis.

Goodman, S. J.