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Detection sensitivities of the chemical elements following thermal-neutron activation have been compiled from the available experimental cross sections and nuclear properties and presented in a concise and usable form. The report also includes the equations and nuclear parameters used in the calculations.
Through a series of measurements with a high purity germanium detector, we have established that the past presence of neutron emitting material can be detected by the decay of activation products in aluminum containers, tungsten shielding, and concrete floors even several days after last exposure. The time since last exposure can also be estimated by the gamma-ray detection rate. These findings may lead to interesting new CONOPS in the detection of illicit SNM or the verification of the absence (or presence) of SNM containing objects in facilities and/or transit even after the material has been removed.
Active regions are a source of various phenomena responsible for Space Weather disturbances; therefore, developing a technology for early warning about upcoming magnetic activity is crucial to mitigate its impact. However, observational limitations and the high nonlinearity of processes associated with the accumulation of magnetic flux and its interaction with the surrounding plasma during the emergence through the convection zone make early activity detection a challenging problem. To address these challenges, we developed a physics-driven machine learning model that allows us to detect active regions (ARs) before they become visible on the solar surface by analyzing the power spectra of acoustic oscillations observed by the SDO/HMI instrument. This study is based on a time series of Doppler shift maps of 31x31-degree areas tracked with the Carrington rotation rate for four days before and after the emergence. The Doppler shift time series are processed into the oscillation power maps for four frequency ranges and accompanied by line-of-sight magnetograms and the continuum intensity maps from SDO/HMI. The resulting data are converted into a 1D time series representing the mean temporal variations of these quantities. The redacted time series are used as input to predict AR emergence using the Long Short Term Memory (LSTM) method. The training of the LSTM model is based on 40 ARs, which includes an independent analysis for each sub region that exhibits AR emergence or remains quiet. The emergence of magnetic flux (defined as a decrease of the continuum intensity) was detected with the developed LSTM algorithm from 5 to 48 hours before the reported time by NOAA. The developed model is capable of pointing to the time and location of active region formation. In this presentation, we discuss reasons that impact how early in advance the model can identify the upcoming activity and the possibility of improving the current predictive skills and steps to transition to the operational forecast.
The work performed in this project has demonstrated the ability to construct proteolytic enzyme substrates that are PCR and sequencing-readable reporter molecules. Specifically, the goal was to detect those reporter molecules via PCR and Oxford Nanopore Technologies MinION sequencing methods following exposure to the biomarker protease thrombin. The assay development focused on binding the constructed peptide-oligonucleotide chimera to immobilized streptavidin. The action of thrombin on the peptide portion of the molecule released the oligonucleotide for detection. Detection of protease activity was demonstrated in a concentration-dependent manner using MALDI-MS, RT-PCR and DNA sequencing. Additional steps to remove background release of reporter molecules during the assay was used to improve the difference in detected oligonucleotide reporter following protease activity. Additional steps in assay development will be to (1) test the assay in an appropriate matrix, (2) investigate detection using additional DNA sequencing platforms and (3) demonstrate multiplexed detection of multiple protease markers in a single reaction.
The development of an accurate forecast for solar eruptive activity has become increasingly important in order to prevent any potential impact on activities in space and the Earth's environment. It is therefore crucial to detect active regions before they appear on the solar surface and create early warning capabilities for upcoming Space Weather disturbances. In this work, 9TB of solar data (SDO/HMI dopplergrams, magnetograms and continuum intensity maps) involving the emergence of 61 NOAA solar active regions since 2010 were processed using the NASA HECC capabilities. An acoustic power maps time-series dataset was created (for four different frequency ranges and processed to take into account the solar sphere geometric effect ) which can be used for understanding the dynamics of the solar surface and train a variety of ML models. The calculated acoustic power maps carry precursor information associated with the decrease in continuum intensity on the solar surface, verifying older helioseismology research. Our results show that a Long Short-Term Memory (LSTMs) model, with a modest layer depth and the right hyperparameters tuned, when trained on this solar acoustic power maps dataset can predict without false negatives a drop in intensity (associated with the emergence of the active region), up to 18 hours in advance.
Highlights: • The first archaeal dimeric structures of Methanosarcina mazei Rib7 are reported. • Our studies show the divergences between archaeal and eubacterial Rib7 reductases. • Asp33 together with Arg36, had been evolved to ensure the substrate specificity. • Unexpectedly, an endogenous NADPH cofactor is observed in M. mazei Rib7. • The endogenous NADPH greatly enhances the structural stability of archaeal Rib7. Archaeal/fungal Rib7 and eubacterial RibG possess a reductase domain for ribosyl reduction in the second and third steps, respectively, of riboflavin biosynthesis. These enzymes are specific for an amino and a carbonyl group of the pyrimidine ring, respectively. Here, several crystal structures of Methanosarcina mazei Rib7 are reported at 2.27–1.95 Å resolution, which are the first archaeal dimeric Rib7 structures. Mutational analysis displayed that no detectable activity was observed for the Bacillus subtilis RibG K151A, K151D, and K151E mutants, and the M. mazei Rib7 D33N, D33K, and E156Q variants, while 0.1–0.6% of the activity was detected for the M. mazei Rib7 N9A, S29A, D33A, and D57N variants. Our results suggest that Lys151 in B. subtilis RibG, while Asp33 together with Arg36 in M. mazei Rib7, ensure the specific substrate recognition. Unexpectedly, an endogenous NADPH cofactor is observed in M. mazei Rib7, in which the 2′-phosphate group interacts with Ser88, and Arg91. Replacement of Ser88 with glutamate eliminates the endogenous NADPH binding and switches preference to NADH. The lower melting temperature of ∼10 °C for the S88E and R91A mutants suggests that nature had evolved a tightly bound NADPH to greatly enhance the structural stability of archaeal Rib7.
Proteases include clinically relevant markers for clotting disorders, certain cancers as well as toxins. Assays for protease activity often use designed peptides mimicking natural substrates and detection with colorometric and fluorescence-based detection that is difficult to multiplex without expensive and resource demanding instruments. This work demonstrates detection of proteolytic activity using PCR and sequencing-readable reporter molecules. The assay development focused on binding the constructed peptide-oligonucleotide chimera to immobilized streptavidin. Thrombin, an essential component of the clotting cascade, was used as a model system for testing peptide substrate recognition and release of a designed oligonucleotide for detection. Detection of protease activity was demonstrated in a concentration-dependent manner using MALDI-MS, RT-PCR and DNA sequencing.
This paper considers the development of information flow analyses to support resilient design and active detection of adversaries in cyber physical systems (CPS). CPS security, though well studied, suffers from fragmentation. In this paper, we consider control systems as an abstraction of CPS. Here, we use information flow analysis, a well established set of methods developed in software security, to obtain a unified framework that captures and extends results in control system security. Specifically, we propose the Kullback Liebler (KL) divergence as a causal measure of information flow, which quantifies the effect of adversarial inputs on sensor outputs. We show that the proposed measure characterizes the resilience of control systems to specific attack strategies by relating the KL divergence to optimal detection. We then relate information flows to stealthy attack scenarios where an adversary can bypass detection. Finally, this article examines active detection mechanisms where a defender intelligently manipulates control inputs or the system itself to elicit information flows from an attacker's malicious behavior. In all previous cases, we demonstrate an ability to investigate and extend existing results through the proposed information flow analyses.
Background : Accurately estimating burned area from satellites is key to improving biomass burning emission models, studying fire evolution and assessing environmental impact. Previous studies have found that current methods for estimating burned area of fires from satellite active-fire data do not always provide an accurate estimate. Aims and Methods : In this work, we develop a novel algorithm to estimate hourly accumulated burned area based on the area from boundaries of non-convex polygons containing the accumulated Visible Infrared Imaging Radiometer Suite (VIIRS)active-fire detections. Hourly time series are created by combining VIIRS estimates with fire radiative power (FRP) estimates from GOES-17 data. Conclusions, Key Results and Implication : We evaluate the performance of the algorithm for both accumulated and change in burned area between airborne observations, and specifically examine sensitivity to the choice of the parameter controlling how much the boundary can shrink towards the interior of the area polygon. Results of the hourly accumulation of burned area for multiple fires from 2019 and 2020 generally correlate strongly with airborne infrared (IR) observations collected by the United States Forest Service National Infrared Operations (NIROPS), exhibiting correlation coefficient values usually greater than 0.95 and errors <20%.
Illicit maritime activity, such as piracy and smuggling, is a global issue that often occurs in areas where interdiction authorities are sparse, ground-based monitoring technologies like radar lack range and coverage, and dark vessels abound. Our objective was to assess vessel congregation patterns, identify likely beaching areas based on terrain maps, and use them to narrow the search for potential smuggling transfer and overland routes in a specific region along the Puntland coast of Somalia. To accomplish this goal, we developed automated protocols applied to WorldView satellite imagery for (1) vessel detection and size classification, (2) shallow-water bathymetric characterization, and (3) coastal topography mapping. Utilizing a single sensor for vessel detection and topographic and bathymetric extraction at high spatial resolution and at a high re-visit rate provides a simplification to near-shore characterization for monitoring purposes. The extracted topography and bathymetry are then presented as a single, comprehensive perspective of a coastal region. The vessel-detection algorithm identified all vessels larger than approximately 15 metres in length (35 of 35), but misidentified six artefacts (i.e. false positives), resulting in an overall accuracy of 85%. The combined vessel and terrain maps facilitated the identification of a potential beaching and overland transportation route location.
NADH-dependent persulfide reductase (Npsr) has been proposed to facilitate dissimilatory sulfur respiration by reducing persulfide or sulfane sulfur-containing substrates to H2S. The presence of this gene in the sulfate and thiosulfate-reducing Archaeoglobus fulgidus DSM 4304 and other hyperthermophilic Archaeoglobales appears anomalous, as A. fulgidus is unable to respire S0 and grow in the presence of elemental sulfur. To assess the role of Npsr in the sulfur metabolism of A. fulgidus DSM 4304, the Npsr from A. fulgidus was characterized. AfNpsr is specific for persulfide and polysulfide as substrates in the oxidative half-reaction, exhibiting k cat / K m on the order of 104 M-1 s-1, which is similar to the kinetic parameters observed for hyperthermophilic CoA persulfide reductases. In contrast to the bacterial Npsr, AfNpsr exhibits low disulfide reductase activity with DTNB; however, similar to the bacterial enzymes, it does not show detectable activity with CoA-disulfide, oxidized glutathione, or cystine. The 3.1 Å X-ray structure of AfNpsr reveals access to the tightly bound catalytic CoA, and the active site Cys 42 is restricted by a flexible loop (residues 60-66) that is not seen in the bacterial homologs from Shewanella loihica PV-4 and Bacillus anthracis. Unlike the bacterial enzymes, AfNpsr exhibits NADH oxidase activity and also shows no detectable activity with NADPH. Models suggest steric and electrostatic repulsions of the NADPH 2 ′ -phosphate account for the strong preference for NADH. The presence of Npsr in the nonsulfur-reducing A. fulgidus suggests that the enzyme may offer some protection against S0 or serve in another metabolic role that has yet to be identified.
Developments in radioxenon monitoring since the implementation of the International Monitoring System are reviewed with emphasis on the most current technologies to improve detector sensitivity and resolution. The nuclear detectors reviewed include combinations of plastic and NaI(Tl) detectors, high purity germanium detectors, silicon detectors, and phoswich detectors. The minimum detectable activity and calibration methods for the various detectors are also discussed.
The present invention relates to methods of detecting one or more targets of interest in a sample. In one instance, the target can be correlated to an active infection (e.g., by a virus and/or a bacterium). Methods can include treating the sample with a dissociation agent, thereby releasing the target of interest for more accurate detection (e.g., by use of a sedimentation-based centrifugal microfluidic devices). Also described herein are microfluidic devices and systems for use with a dissociation agent.
This poster summarizes work completed for the NA-22 STILGAR project using seismic cross-correlation to detect human-generated subsurface activity. It will be presented at the 2024 American Geophysical Union Fall Meeting.
The presence of active oxygen species (O(-), O2(-), O3(-)) and other strong oxidants (Fe2O3 and Fe3O4) was invoked in interpretations of the Viking biological experiments and a model was also suggested for Martian surface chemistry. The non-biological interpretations of the biological results gain futher support as no organic compounds were detected in the Viking pyrolysis-gas chromatography mass spectrometer (GCSM) experiments at concentrations as low as 10 ppb. Electron spin resonance (ESR) measures the absorption of microwaves by a paramagnetic and/or ferromagnetic center in the presence of an external field. In many instances, ESR has the advantage of detailed submicroscopic identification of the transient species and/or unstable reaction intermediates in their environments. Since the higly active oxygen species (O(-), O2(-), O3(-), and R-O-O(-)) are all paramagnetic in nature, they can be readily detected in native form by the ESR method. Active oxygen species likely to occur in the Martian surface samples were detected by ESR in UV-irradiated samples containing MgO. A miniaturized ESR spectrometer system can be developed for the Mars Rover Sample Return Mission. The instrument can perform the following in situ Martian samples analyses: detection of active oxygen species; characterization of Martian surface chemistry and photooxidation processes; and searching for organic compounds in the form of free radicals preserved in subsoils, and detection of microfossils with Martian carbonate sediments.
We discuss a current, ongoing demonstration of insitu onboard detection in which the Earth Observing-1 spacecraft detects surface sulfur deposits that originate from underlying springs by distinguishing the sulfur from the ice-rich glacial background, a good analogue for the Europan surface. In this paper, we describe the process of developing the onboard classifier for detecting the presence of sulfur in a hyperspectral scene, including the use of a training/testing set that is not exhaustively labeled, i.e.not all true positives are marked, and the selection of 12, out of 242, Hyperion instrument wavelength bands to use in the onboard detector. This study aims to demonstrate the potential for future missions to capture short-lived science events, make decisions onboard, identify high priority data for downlink and perform onboard change detection. In the future, such capability could help maximize the science return of downlink bandwidth-limited missions, addressing a significant constraint in all deep-space missions.
We studied adaptation to spectral light distribution in undisturbed benthic communities of cyanobacterial mats growing in hypersaline ponds at Guerrero Negro, Baja California, Mexico. Microscale measurements of oxygen photosynthesis and action spectra were performed with microelectrodes; spectral radiance was measured with fiber-optic microprobes. The spatial resolution of all measurements was 0.1 mm, and the spectral resolution was 10 to 15 nm. Light attenuation spectra showed absorption predominantly by chlorophyll a (Chl a) (430 and 670 nm), phycocyanin (620 nm), and carotenoids (440 to 500 nm). Blue light (450 nm) was attenuated 10-fold more strongly than red light (600 nm). The action spectra of the surface film of diatoms accordingly showed activity over the whole spectrum, with maxima for Chl a and carotenoids. The underlying dense Microcoleus population showed almost exclusively activity dependent upon light harvesting by phycobilins at 550 to 660 nm. Maximum activity was at 580 and 650 nm, indicating absorption by phycoerythrin and phycocyanin as well as by allophycocyanin. Very little Chl a-dependent activity could be detected in the cyanobacterial action spectrum, even with additional 600-nm light to excite photosystem II. The depth distribution of photosynthesis showed detectable activity down to a depth of 0.8 to 2.5 mm, where the downwelling radiant flux at 600 nm was reduced to 0.2 to 0.6% of the surface flux.
With the upgrading of communication technology, cyber threats to power converters are increasing. In this paper, a model-based cyber-attack detection methodology is proposed for the interleaved Active neutral point clamped (ANPC) Photovoltaic (PV) converter. The proposed methodology identifies cyber-attacks using two estimations based on the Kalman filter and the state-space model of the ANPC PV converter. The residual between the two estimations is analyzed from a statistical perspective. Based on the Cumulative Sum (CUSUM) Control Chart, the standard errors shift of the residual is used to identify cyber-attacks. Besides, to validate the feasibility of the proposed methodology, several conditions are considered in the simulation, including white noise in the sensor, irradiance variation, and cyber-attacks in the PV converter. Furthermore, the simulation result demonstrates the proposed method can identify cyber-attacks in the ANPC PV converter.