AMP based sensitive and rapid spore detection assay
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AMP PPDK spore detection↗
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Rapid Corner Detection Using FPGAs
In order to perform precision landings for space missions, a control system must be accurate to within ten meters. Feature detection applied against images taken during descent and correlated against the provided base image is computationally expensive and requires tens of seconds of processing time to do just one image while the goal is to process multiple images per second. To solve this problem, this algorithm takes that processing load from the central processing unit (CPU) and gives it to a reconfigurable field programmable gate array (FPGA), which is able to compute data in parallel at very high clock speeds. The workload of the processor then becomes simpler; to read an image from a camera, it is transferred into the FPGA, and the results are read back from the FPGA. The Harris Corner Detector uses the determinant and trace to find a corner score, with each step of the computation occurring on independent clock cycles. Essentially, the image is converted into an x and y derivative map. Once three lines of pixel information have been queued up, valid pixel derivatives are clocked into the product and averaging phase of the pipeline. Each x and y derivative is squared against itself, as well as the product of the ix and iy derivative, and each value is stored in a WxN size buffer, where W represents the size of the integration window and N is the width of the image. In this particular case, a window size of 5 was chosen, and the image is 640 480. Over a WxN size window, an equidistance Gaussian is applied (to bring out the stronger corners), and then each value in the entire window is summed and stored. The required components of the equation are in place, and it is just a matter of taking the determinant and trace. It should be noted that the trace is being weighted by a constant k, a value that is found empirically to be within 0.04 to 0.15 (and in this implementation is 0.05). The constant k determines the number of corners available to be compared against a threshold sigma to mark a valid corner. After a fixed delay from when the first pixel is clocked in (to fill the pipeline), a score is achieved after each successive clock. This score corresponds with an (x,y) location within the image. If the score is higher than the predetermined threshold sigma, then a flag is set high and the location is recorded.
Morfopoulos, Arin C.↗
H31G-1596: DeepSAT's CloudCNN: A Deep Neural Network for Rapid Cloud Detection from Geostationary Satellites
Cloud and cloud shadow detection has important applications in weather and climate studies. It is even more crucial when we introduce geostationary satellites into the field of terrestrial remote sensing. With the challenges associated with data acquired in very high frequency (10-15 mins per scan), the ability to derive an accurate cloud shadow mask from geostationary satellite data is critical. The key to the success for most of the existing algorithms depends on spatially and temporally varying thresholds,which better capture local atmospheric and surface effects.However, the selection of proper threshold is difficult and may lead to erroneous results. In this work, we propose a deep neural network based approach called CloudCNN to classify cloudshadow from Himawari-8 AHI and GOES-16 ABI multispectral data. DeepSAT's CloudCNN consists of an encoderdecoder based architecture for binary-class pixel wise segmentation. We train CloudCNN on multi-GPU Nvidia Devbox cluster, and deploy the prediction pipeline on NASA Earth Exchange (NEX) Pleiades supercomputer. We achieved an overall accuracy of 93.29% on test samples. Since, the predictions take only a few seconds to segment a full multispectral GOES-16 or Himawari-8 Full Disk image, the developed framework can be used for real-time cloud detection, cyclone detection, or extreme weather event predictions.
GOES-1↗
Colorimetric detection of actinides
A method for rapid detection of actinides including the steps of having a support including a colorimetric complexation, placing the support in communication with a sample through urinalysis, and receiving a visual indicator from the colorimetric complexation. The sample having an unknown concentration of at least one actinide within it. The colorimetric complexation is configured to activate when contacted by a threshold concentration of an actinide.
Riddle, Catherine↗
Adenosine Monophosphate-Based Detection of Bacterial Spores
A method of rapid detection of bacterial spores is based on the discovery that a heat shock consisting of exposure to a temperature of 100 C for 10 minutes causes the complete release of adenosine monophosphate (AMP) from the spores. This method could be an alternative to the method described in the immediately preceding article. Unlike that method and related prior methods, the present method does not involve germination and cultivation; this feature is an important advantage because in cases in which the spores are those of pathogens, delays involved in germination and cultivation could increase risks of infection. Also, in comparison with other prior methods that do not involve germination, the present method affords greater sensitivity. At present, the method is embodied in a laboratory procedure, though it would be desirable to implement the method by means of a miniaturized apparatus in order to make it convenient and economical enough to encourage widespread use.
Kern, Roger G.↗
Strengthening Cybersecurity for Industrial Control Systems: Innovations in Protecting PLC-Based Infrastructure
In this paper, we propose two new approaches aimed at enhancing the security of industrial control systems (ICS) that utilize programmable logic controllers (PLCs) for the control of critical processes. The first approach involves the addition of a unique digital watermark to the PWM control that adjusts the motor speed to control the critical process. This enables efficient detection and identification of any unauthorized modifications to the sensor signals responsible for controlling the plant. The second approach focuses on monitoring the input current (i.e power) drawn by the PLC during the execution of critical process control tasks. Malicious intrusions to change the PLC parameters and/or unauthorized firmware updates can be rapidly detected. Both approaches demonstrate a substantial improvement in the security of ICS, effectively safeguarding against potential cyber-attacks. Experimental results from a laboratory scale water tank level controlled via PLC showcases rapid intrusion detection capabilities.
Huang, Peng-Hao↗
Accelerated acquisition of wideline solid-state NMR spectra of spin 3/2 nuclei by frequency-stepped indirect detection experiments
1 H{X} DE-RESPDOR pulse sequences enable the rapid detection of wideline solid-state nuclear magnetic resonance spectra of spin 3/2 half-integer quadrupolar nuclei.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
A Review of Twenty-Six Years of U.S. Weather Radar Detection of Meteorite Falls
Weather radars have proven to be a valuable tool for detection, rapid recovery, and analysis of meteorite falls and fall statistics. The U.S. operates a nationwide weather radar network (NEXRAD) which will be discussed here, but it is important to acknowledge that weather radars operate worldwide and efforts are underway to utilize this rich resource. By the author’s count, since the NEXRAD system came online in the late 1990s it has detected 34 recovered meteorite falls and another 33 unrecovered probable falls. Weather radars are powerful tools because they directly detect meteorites falling after the end of their luminous flight, during the "dark flight" period. This allows rapid recovery through detection and modeling of fall locations down to as little as tens of meters. They are also the only tool that analyzes meteorites that survive their parent fireball, before many or all of them are lost to terrain. This allows direct measurement of meteorite mass, particle size distribution, and with additional work should allow calculation of pre-atmospheric mass and a measure of whole-body strength.
M D Fries↗
Rapid adaptation (or not) in restored plant populations
Abstract Mismatches between the traits of a colonizing population and a novel habitat can generate strong selection, potentially resulting in rapid adaptation. However, for most colonization events, it can be difficult to detect rapid adaptation or distinguish it from nonadaptive evolutionary changes. Here, I take advantage of a replicated prairie restoration experiment to compare recently established plant populations in two closely located restored prairies to each other and to their shared source population to test for rapid adaptation. Using a reciprocal transplant experiment six years after the populations were established, I found that one restored plant population showed evidence of adaptation, outperforming the other restored population when grown at its home site. In contrast, I detected no evidence for adaptation at the other site. These findings demonstrate that while rapid adaptation can occur in colonizing plant populations, it may not be the rule. Better understanding of when adaptation may or may not occur in these contexts may help us use evolution to our advantage, potentially improving establishment of desirable species in restored habitats.
59 BASIC BIOLOGICAL SCIENCES↗
The influence of laser energy on deuterium emission characteristics from a Zircaloy-4 plasma
Laser-produced plasma coupled with optical emission spectroscopy (OES) is a promising technique for detecting certain isotopes, with unique capabilities such as standoff and rapid detection and minimal to no sample preparation requirements. The key figure-of-merit for isotopic analysis using optical spectroscopy tools is the linewidth relative to the isotope shift. Although the isotopes of hydrogen (1H, 2H, and 3H) possess large isotopic shifts (1H–2H ≈ 180 pm, 1H–3H ≈ 240 pm), being a light element, the H transitions are susceptible to various broadening mechanisms in the plasma environment. One of the critical parameters that influence the linewidth of a transition in an LPP is the incident laser energy. In the present study, we evaluated the role of laser energy on plume expansion dynamics, deuterium emission intensity, and linewidth in a nanosecond laser-produced Zircaloy-4 plasma. The changes in 2Hα emission intensity and linewidth were investigated for varying laser fluence and time after plasma onset. Spatially resolved and spatially integrated OES were performed and compared to investigate the emission spectral features and linewidth of 2Hα. Monochromatic two-dimensional time-resolved imaging was also performed to understand the morphology of the deuterium and protium emission relative to all species in the plume. Our results showed that 1Hα and 2Hα emissions predominantly occur closer to the target. Measurements of 2Hα linewidth approached similar values at later times of plasma evolution regardless of the laser energy. The linewidths of the 2Hα transition showed insignificant differences between spatially resolved and spatially integrated measurements.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Real-Time Leaky Lamb Wave Spectrum Measurement and Its Application to NDE of Composites
Numerous analytical and theoretical studies of the behavior of leaky Lamb waves (LLW) in composite materials were documented in the literature. One of the key issues that are constraining the application of this method as a practical tool is the amount of data that needs to be acquired and the slow process that is involved with such experiments. Recently, a methodology that allows quasi real-time acquisition of LLW dispersion data was developed. At each angle of incidence the reflection spectrum is available in real time from the experimental setup and it can be used for rapid detection of the defects. This technique can be used to rapidly acquire the various plate wave modes along various angles of incidence for the characterization of the material elastic properties. The experimental method and data acquisition technique will be described in this paper. Experimental data was used to examine a series of flaws including porosity and delaminations and demonstrated the efficiency of the developed technique.
Lih, Shyh-Shiuh↗
A microarray immunoassay for simultaneous detection of proteins and bacteria
We report the development and characterization of an antibody microarray biosensor for the rapid detection of both protein and bacterial analytes under flow conditions. Using a noncontact microarray printer, biotinylated capture antibodies were immobilized at discrete locations on the surface of an avidin-coated glass microscope slide. Preservation of capture antibody function during the deposition process was accomplished with the use of a low-salt buffer containing sucrose and bovine serum albumin. The slide was fitted with a six-channel flow module that conducted analyte-containing solutions over the array of capture antibody microspots. Detection of bound analyte was subsequently achieved using fluorescent tracer antibodies. The pattern of fluorescent complexes was interrogated using a scanning confocal microscope equipped with a 635-nm laser. This microarray system was employed to detect protein and bacterial analytes both individually and in samples containing mixtures of analytes. Assays were completed in 15 min, and detection of cholera toxin, staphylococcal enterotoxin B, ricin, and Bacillus globigii was demonstrated at levels as low as 8 ng/mL, 4 ng/mL, 10 ng/mL, and 6.2 x 10(4) cfu/mL, respectively. The assays presented here are very fast, as compared to previously published methods for measuring antibody-antigen interactions using microarrays (minutes versus hours).
Non-NASA Center↗
Microelectrode-based technology for the detection of low levels of bacteria
A microelectrode-based electrochemical detection method was used for quantitation of bacteria in water samples. The redox mediator, benzoquinone, was used to accept electrons from the bacterial metabolic pathway to create a flow of electrons by reducing the mediator. Electrochemical monitoring electrodes detected the reduced mediator as it diffused out of the cells and produced a small electrical current. By using a combination of microelectrodes and monitoring instrumentation, the cumulative current generated by a particular bacterial population could be monitored. Using commercially available components, an electrochemical detection system was assembled and tested to evaluate its potential as an emerging technology for rapid detection and quantitation of bacteria in water samples.
Rogers, Tom D.↗
Manipulating cobalt oxide on N-doped aligned electrospun carbon nanofibers towards instant electrochemical detection of dopamine secreted by living cells
A demand exists for the development of miniaturized biosensors with high sensitivity and a wide dynamic range for rapid detecting dopamine (DA) levels. Here, an electrochemical sensor is created by decorating closely packed cobalt oxide (Co 3 O 4 ) nanograins on nitrogen-doped electrospun carbon nanofibers (NECNFs) via a facile electrodeposition method. The carbon nanofiber matrix provides both a scaffold with ultrahigh surface area for homogeneous dispersion of cobalt oxide nanostructures and facilitates the electrochemical conductivity for the hybrid electrode. The sensing principle is based on the redox reaction between DA and DA quinone that generates electrical signal, which is detectable via differential pulse voltammetry (DPV) and chronoamperometry (CA). Owing to a high electroactive surface area and facilitating electron transfer between electrode surface and the target molecule, the electrical sensing platform exhibits superior sensitivity and selectivity toward DA, with an excellent limit of detection (9 nM) over a wide range of concentrations (0.01 to 100 μM). Moreover, based on its excellent sensing properties and biocompatibility, the sensor has been used for the real-time monitoring exogeneous DA released from pheochromocytoma (PC12) cells. This work demonstrates promise of a novel sensor technology that may render rapid point-of-care testing of DA towards early clinical diagnosis.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
BurstCube: Behind the Scenes of a Do-No-Harm I&T Production
BurstCube is one of the most recent 6-U CubeSats built and developed by NASA Goddard Spaceflight Center (GSFC). As an astrophysics mission, BurstCube will be a rapid detection alert end-to-end mission system for short astrophysical gamma-ray bursts with the aim of increasing the chance of coincident detection of gamma-ray bursts. In addition, the mission is intended to augment the current fleet of gamma-ray astronomy satellites. The payload instrument includes 4 scintillator heads read out by arrays of silicon photomultipliers which will detect short astrophysical gamma-ray bursts. BurstCube provides a high field of view previously unavailable to larger missions and is intended to provide rapid alerts for follow up observations with other assets, increasing the chance of a coincident detection of an event. From the design to the integration and test phases, the project aimed to provide realistic test plans and stimulus to help verify and validate reachable areas of this innovative payload/instrument system and even spacecraft performance. Typical robust integration and test phases for space missions are unaligned with the budget and risk postures of small satellite or CubeSat missions, often designated as “Do No Harm” projects where the primary requirement is not harming the host platform or other payloads. Despite this status, CubeSats are complex missions that mix new and prior technologies. Integration and test for these missions requires responsible engineering, creative collaboration, and careful observation to deliver a reliable mission. This paper will provide an overview of the payload instrument and mission system, areas of injected automation (current and future), environmental testing results, and lessons learned during the integration and test phase.
CubeSats↗
On-Line Loss of Control Detection Using Wavelets
Wavelet transforms are used for on-line detection of aircraft loss of control. Wavelet transforms are compared with Fourier transform methods and shown to more rapidly detect changes in the vehicle dynamics. This faster response is due to a time window that decreases in length as the frequency increases. New wavelets are defined that further decrease the detection time by skewing the shape of the envelope. The wavelets are used for power spectrum and transfer function estimation. Smoothing is used to tradeoff the variance of the estimate with detection time. Wavelets are also used as front-end to the eigensystem reconstruction algorithm. Stability metrics are estimated from the frequency response and models, and it is these metrics that are used for loss of control detection. A Matlab toolbox was developed for post-processing simulation and flight data using the wavelet analysis methods. A subset of these methods was implemented in real time and named the Loss of Control Analysis Tool Set or LOCATS. A manual control experiment was conducted using a hardware-in-the-loop simulator for a large transport aircraft, in which the real time performance of LOCATS was demonstrated. The next step is to use these wavelet analysis tools for flight test support.
Brenner, Martin J.↗
FY 2026 Midyear Report: Seismic Monitoring of Underground Vibration Sources Using Distributed Acoustic Sensing and Seismometers
Safeguards-relevant temporal changes in underground facilities can be observed using geophysical monitoring techniques. Seismic waves, in particular, provide valuable insights into subsurface activities and can serve as an important tool for detecting anomalous events that may indicate containment breaches at geological repositories. This midyear report summarizes ongoing efforts to automatically and rapidly detect and locate anomalous vibration signals that could be indicative of potential containment breaches. Previous work during FY25 focused on compiling continuous seismic datasets from two underground sites and developing a database of continuous waveforms and ground-truth event data derived from multiple sensing modalities. Building on this foundation, we are adapting anomaly detection and geolocation algorithms to explore methods for monitoring underground activities using two relatively low-maintenance sensing technologies: a dense surface geophone array deployed at the Pleasant Gap mine in Pennsylvania, and a three-dimensional fiber-optic cable array for distributed acoustic sensing (DAS) installed in the subsurface at the Sanford Underground Research Facility (SURF) in South Dakota. This report summarizes work conducted during the first two quarters of FY26, during which we refined a dynamic power spectral density (PSD)-based detector, applied it independently to each geophone station, and then combined the per‑station detections with density-based spatial clustering of applications with noise (DBSCAN) to cluster events and produce spatial maps over a nine‑day interval. In addition, we outline plans for a field trial at the Waste Isolation Pilot Plant (WIPP) in New Mexico to compare traditional seismic monitoring approaches with DAS techniques and to evaluate the benefits of combined data analysis. Activities during the past two quarters have included the preparation and submission of a Field Test Plan to WIPP for approval, as well as submission to headquarters for review and feedback.
58 GEOSCIENCES↗
Development and Evaluation of Ensemble Learning-based Environmental Methane Detection and Intensity Prediction Models
The environmental impacts of global warming driven by methane (CH 4 ) emissions have catalyzed significant research initiatives in developing novel technologies that enable proactive and rapid detection of CH 4 . Several data-driven machine learning (ML) models were tested to determine how well they identified fugitive CH 4 and its related intensity in the affected areas. Various meteorological characteristics, including wind speed, temperature, pressure, relative humidity, water vapor, and heat flux, were included in the simulation. We used the ensemble learning method to determine the best-performing weighted ensemble ML models built upon several weaker lower-layer ML models to (i) detect the presence of CH 4 as a classification problem and (ii) predict the intensity of CH 4 as a regression problem. The classification model performance for CH 4 detection was evaluated using accuracy, F1 score, Matthew’s Correlation Coefficient (MCC), and the area under the receiver operating characteristic curve (AUC ROC), with the top-performing model being 97.2%, 0.972, 0.945 and 0.995, respectively. The R 2 score was used to evaluate the regression model performance for CH 4 intensity prediction, with the R 2 score of the best-performing model being 0.858. The ML models developed in this study for fugitive CH 4 detection and intensity prediction can be used with fixed environmental sensors deployed on the ground or with sensors mounted on unmanned aerial vehicles (UAVs) for mobile detection.
Majumder, Reek↗