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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Dual-Frequency Observations of 140 Compact, Flat-Spectrum Active Galactic Nuclei for Scintillation-Induced Variability

The 4.9 GHz Micro-Arcsecond Scintillation-Induced Variability (MASIV) Survey detected a drop in Interstellar Scintillation (ISS) for sources at red shifts z > or approx. 2, indicating an apparent increase in angular diameter or a decrease in flux density of the most compact components of these sources, relative to their extended emission. This can result from intrinsic source size effects or scatter broadening in the Intergalactic Medium (IGM) , in excess of the expected (1+z)1/2 angular diameter scaling of brightness temperature limited sources resulting from cosmological expansion. We report here 4.9 GHz and 8.4 GHz observations and data analysis for a sample of 140 compact, fiat-spectrum sources which may allow us to determine the origin of this angular diameter-redshift relation by exploiting their different wavelength dependences. In addition to using ISS as a cosmological probe, the observations provide additional insight into source morphologies and the characteristics of ISS. As in the MASIV Survey, the variability of the sources is found to be significantly correlated with line-of-sight H(alpha) intensities, confirming its link with ISS. For 25 sources, time delays of about 0.15 to 3 days are observed between the scintillation patterns at both frequencies, interpreted as being caused by a shift in core positions when probed at different optical depths. Significant correlation is found between ISS amplitudes and source spectral index; in particular, a large drop in ISS amplitudes is observed at alpha < -0.4 confirming that steep spectrum sources scintillate less. We detect a weakened redshift dependence of ISS at 8.4 GHz over that at 4.9 GHz, with the mean variance at 4-day timescales reduced by a factor of 1.8 in the z > 2 sources relative to the z < 2 sources, as opposed to the factor of 3 decrease observed at 4.9 GHz. This suggests scatter broadening in the IGM, but the interpretation is complicated by subtle selection effects that will be explored further in a follow-up paper.

Koay, J. Y.↗
DOE OSTI2015

ANS complex of St John’s wort PR-10 protein with 28 copies in the asymmetric unit: a fiendish combination of pseudosymmetry with tetartohedral twinning

Hyp-1, a pathogenesis-related class 10 (PR-10) protein from H. perforatum, was crystallized in complex with the fluorescent probe 8-anilino-1-naphthalene sulfonate (ANS). The asymmetric unit of the tetartohedrally twinned crystal contains 28 copies of the protein arranged in columns with noncrystallographic sevenfold translational symmetry and with additional pseudotetragonal rotational NCS. Hyp-1, a pathogenesis-related class 10 (PR-10) protein from St John’s wort (Hypericum perforatum), was crystallized in complex with the fluorescent probe 8-anilino-1-naphthalene sulfonate (ANS). The highly pseudosymmetric crystal has 28 unique protein molecules arranged in columns with sevenfold translational noncrystallographic symmetry (tNCS) along c and modulated X-ray diffraction with intensity crests at l = 7n and l = 7n ± 3. The translational NCS is combined with pseudotetragonal rotational NCS. The crystal was a perfect tetartohedral twin, although detection of twinning was severely hindered by the pseudosymmetry. The structure determined at 2.4 Å resolution reveals that the Hyp-1 molecules (packed as β-sheet dimers) have three novel ligand-binding sites (two internal and one in a surface pocket), which was confirmed by solution studies. In addition to 60 Hyp-1-docked ligands, there are 29 interstitial ANS molecules distributed in a pattern that violates the arrangement of the protein molecules and is likely to be the generator of the structural modulation. In particular, whenever the stacked Hyp-1 molecules are found closer together there is an ANS molecule bridging them.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Wintertime Brine Discharge at the Surface of a Cold Polar Glacier and the Unexpected Absence of Associated Seismicity

A subglacial groundwater system beneath Taylor Glacier, Antarctica, discharges hypersaline, iron-rich brine episodically at the glacier surface to create Blood Falls. However, the triggering mechanism for these brine release events is not yet understood. Identifying which fracture processes are observed seismically can help us better characterize the hydrological system at Taylor Glacier, and more generally, provide us with a broader understanding of englacial hydrologic activity in cold glaciers. We document wintertime brine discharge using time-lapse photography. Subfreezing air temperatures during the brine discharge indicate that surface melt-induced hydrofracture is an unlikely trigger for brine release. Further, we analyze local seismic data to test a hypothesis that fracturing generates elevated surface wave energy preceding and/or coinciding with brine release events. Our results show no discernible elevated Rayleigh wave activity prior to or during Blood Falls brine release. Instead, we find a pattern of seismic events dominated by a seasonal signal, with more Rayleigh events occurring in the summer than the winter from the Blood Falls source area. We calculate that the volumetric opening of cracks that would generate Rayleigh waves at our detection limits are of similar size to myriad cracks in glacier ice, lake ice, and frozen sediment in the terminus area. We therefore propose that any fracturing coincident with brine release activity likely consists of a series of smaller opening events that are masked by other seismicity in the local environment.

58 GEOSCIENCES↗
DOE OSTI2025

GRUMDN: A Multi-Task Model for Predicting Human Patterns-of-Life from Stay Transition Data

Understanding human patterns-of-life (PoL) is essential towards ensuring safe and secure indoor facility environment as well as outdoor urban environment. Prediction of human movement in between places of interest is vital in understanding human PoL. Movement between spaces maybe represented and detected in one of the two forms: 1) trajectories: locations measured at regular time intervals by mobile sensors, bluetooth or GPS sensors; or 2) stay transitions: semantic PoI (points of interest) and stay duration data measurable by eventbased sensors that collect data when a check-in or check-out event is detected. Stay transition data provides a more compressed data format compared to trajectories data, especially in situations with longer stay durations, while preserving the information necessary for PoL analysis. Now as introduced briefly in the paper, our deployed end application (Digital Twin of a facility with non-player characters, besides the interactive user in virtual reality) needed a well-performing and validated AI/ML model for simulating high quality stay transitions behavior. In this study we thus primarily present our findings with developing and validating that model, which is a multi-task neural network for stay transition prediction. The neural network consists of two heads, for corresponding two tasks of stay category prediction and stay duration prediction. We evaluated gated recurrent units and multi-layer perceptrons of varying network sizes for stay category prediction; while mixture density networks, noisy generator-only networks, and generative adversarial networks of varying network sizes for stay duration prediction. We have then evaluated four multi-task models, constructed by combining these specialized models, on their ability to predict stay transition data. We tested our models on datasets from two different cases: 1) a simulation-generated dataset of indoor movement within the HFIR (high flux isotope reactor) nuclear reactor facility at Oak Ridge National Laboratory (ORNL); and 2) the GeoLife human mobility dataset of outdoor urban movement available in literature. Our results indicate that GRUMDN, which combines gated recurrent units (GRU) for stay category prediction task, and mixture density networks (MDN) for stay duration prediction task, did overall outperform other multitask models and the current state-of-the-art.

Gunaratne, Chathika [ORNL] (ORCID:0000000225088745↗
DOE OSTI2025

ATTNChecker: Highly-Optimized Fault Tolerant Attention for Large Language Model Training

Large Language Models (LLMs) have demonstrated remarkable performance in various natural language processing tasks. However, the training of these models is computationally intensive and susceptible to faults, particularly in the attention mechanism, which is a critical component of transformer-based LLMs. In this paper, we investigate the impact of faults on LLM training, focusing on INF, NaN, and near-INF values in the computation results with systematic fault injection experiments. We observe the propagation patterns of these errors, which can trigger non-trainable states in the model and disrupt training, forcing the procedure to load from checkpoints. To mitigate the impact of these faults, we propose ATTNChecker, the first Algorithm-Based Fault Tolerance (ABFT) technique tailored for the attention mechanism in LLMs. ATTNChecker is designed based on fault propagation patterns of LLM and incorporates performance optimization to adapt to both system reliability and model vulnerability while providing lightweight protection for fast LLM training. Evaluations on four LLMs show that ATTNChecker on average incurs on average 7% overhead on training while detecting and correcting all extreme errors. Compared with the state-of-the-art checkpoint/restore approach, ATTNChecker reduces recovery overhead by up to 49×.

Liang, Yuhang [University of Alabama - Birmingham]↗
DOE OSTI2023

Using Eye-Tracking to Quantify Reverse Engineering Expertise

Software reverse engineering (RE) requires analysts to closely read and make decisions about code. Little is known about what makes an analyst successful, making it difficult to train new analysts or design tools to augment existing ones. The goal of this project was to quantify the eye movement behaviors supporting RE and code comprehension more generally. We applied eye-tracking methods from the language comprehension literature to understand where analysts direct their attention over time when completing tasks (e.g., function identification, bug detection). Across three studies, we manipulated aspects of code hypothesized to impact comprehension (e.g., variable name meaningfulness, code complexity) and presentation methods (e.g., line-by-line, free viewing, gaze-contingent moving window) to understand effects on accuracy and gaze patterns. Results showed clear benefits of meaningful variable names, and effects of expertise on global and line-specific viewing patterns. Findings could inspire empirically-supported tool or analytic adaptations that help to reduce analyst workload.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Analyzing Risks of Virtual Private Network Connections

The use of Splunk for analyzing VPN logs is an effective approach for identifying vulnerabilities in network endpoints. Splunk, a powerful platform for searching, monitoring, and analyzing machine-generated data, enables organizations to aggregate VPN logs in real-time, providing insights into network activity, user behavior, and potential security risks. By indexing VPN traffic and authentication logs, security teams can track abnormal patterns such as multiple failed login attempts, unusual IP addresses, or unexpected changes in bandwidth usage, all of which could indicate potential vulnerabilities or breaches. With Splunk’s advanced search and reporting capabilities, users can create custom dashboards and alerts to detect suspicious activities. Automated searches can flag endpoints exhibiting unusual behavior, while correlation analysis can identify links between compromised devices and broader network vulnerabilities. In particular, Splunk's machine learning capabilities can be leveraged to predict and prevent threats by identifying trends that might otherwise be missed in traditional log analysis. This proactive approach to monitoring VPN logs allows for the early detection of security weaknesses, enabling rapid response and minimizing potential damage to network integrity. By enhancing endpoint visibility, Splunk plays a crucial role in securing remote connections and safeguarding sensitive information. Additionally, Splunk’s automation and alerting features allow teams to create custom workflows that notify them of vulnerable or misconfigured endpoints identified through Shodan. This synergy between Splunk’s log analysis and Shodan’s device intelligence enhances an organization’s ability to proactively identify and mitigate security risks, improving the overall resilience of their VPN infrastructure.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Towards a Counting Point Detector for Nanosecond Coherent X-ray Science

We present the technical realization of a high-speed hard X-ray single-photon counting-detection scheme based on a commercial avalanche silicon photodiode and high-speed oscilloscope. The development is motivated by the need to perform pulse-resolved photon-correlation and pump-probe studies at synchrotron sources with densely packed pulse patterns that result in high repetition rate pulses on the order of hundreds of MHz. Commissioning experiments are performed at the 1C PAL-KRISS beamline at PLS-II of South Korea operating at a burst mode maximum repetition rate of 500 MHz. In such a high count-rate measurement, detector dead-time can lead to a distortion of counting statistics. We are able to model the counting behavior of our detector under these conditions with a detector dead-time comparable to time between X-ray pulses, implying that nanosecond X-ray photon correlation spectroscopy should be possible at diffraction-limited light sources.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Quaternary slip rates and most recent surface rupture of the Bitterroot fault, western Montana

The Bitterroot fault is a ~100-km-long Quaternary active normal fault that bounds the eastern margin of the north–south-trending Bitterroot Mountains and accommodates extension near the Intermountain Seismic Belt. Here, new detailed mapping using high-resolution topographic data derived from light detection and ranging (lidar) along the southern Bitterroot Range documents multiple generations of fault scarps in Holocene–Pleistocene deposits with vertical off sets that increase in magnitude with age. Fault mapping indicates a complex fault geometry characterized by an en echelon pattern of discontinuous segments of 41–78° east-dipping normal faults that appear to cut the older Eocene detachment fault, and locally 70–88° west-dipping antithetic normal faults. 10 Be cosmogenic exposure dating provides in situ age control for 32 surface boulders (>1 m) sampled in glacial deposits. Near Como Dam, two Pinedale-age glacial moraine sequences yield peak age distributions of 15.0 ± 0.4 ka and 16.4 ± 0.6 ka as apparent exposure ages (e = 0), and 15.4 ± 0.4 ka and 16.8 ± 0.6 ka based on the maximum allowed boulder surface erosion rate (e = 2 mm/ka). Vertical separation of 3.5 ± 0.2 m across the ~16–17 ka glacial moraine off set by the Bitterroot fault scarp yields a fault slip rate of 0.2–0.3 mm/yr. Glacial Lake Missoula highstand shorelines, inset into the ~15 ka glacial moraine and vertically off set 4.6 ± 1.6 m by an antithetic strand of the Bitterroot fault, yield fault slip rates of 0.2–0.5 mm/yr that overlap with fault slip rates on the main strand near Lake Como (0.2–0.3 mm/yr). At the Ward Creek fan located ~15 km to the north of Lake Como, two glacial debris fan sequences yield peak age distributions of 16.6 ± 0.4 ka and 62.8 ± 1.7 ka (e = 0), and 17.0 ± 0.4 ka and 69.9 ± 2.2 ka (e = 2 mm/ka). Vertical separations of 2.4 ± 0.3 m and 4.5 ± 0.2 m on the ~17 ka and ~63–70 ka fan surfaces off set by the Bitterroot fault yield fault slip rates of 0.2–0.3 mm/yr and 0.1 mm/yr, respectively. Our results indicate broadly consistent fault slip rates for the main fault segments at Lake Como (0.2–0.3 mm/yr) and the Ward Creek fan (0.1–0.3 mm/yr) with an along-strike range of 0.1–0.3 mm/yr for the southern Bitterroot fault. Fault scaling relations and evidence of multiple late Quaternary fault surface ruptures suggest the Bitterroot fault could produce a Mw ~7.2 earthquake. Structural model constraints and our slip rate results indicate both high-angle or low-angle fault geometries are possible at depth. A seismogenic low-angle fault model could generate a larger earthquake of Mw >7.2. Earthquake history is unknown for the Bitterroot fault, but fault scarps in young glacial deposits demonstrate its seismogenic potential. Data from this study suggest seismic hazards from the Bitterroot fault may pose a high level of risk to the Missoula metropolitan area, the State’s second most populous region, and major infrastructures across the Missoula and Bitterroot Valleys.

58 GEOSCIENCES↗
NASA NTRS1979

Preliminary results of a gamma-ray burst study in the Konus experiment on the Venera-11 and Venera-12 space probes

Twenty-one gamma-ray bursts and 68 solar flares in the hard X-ray range were detected on Venera-11 and Venera-12 space probes during the initial 50-day observation period. Major characteristics of the equipment used and preliminary data on the temporal structure and energy spectra of the gamma-ray bursts are considered. The pattern of gamma-ray burst frequency distribution vs. intensity, N(S), is established.

Mazets, Y. P.↗
NASA NTRS1990

Velocity and pressure fields associated with near-wall turbulence structures

Computer generated databases containing velocity and pressure fields in three-dimensional space at a sequence of time-steps, were used for the investigation of near-wall turbulence structures, their space-time evolution, and their associated pressure fields. The main body of the results were obtained from simulation data for turbulent channel flow at a Reynolds number of 180 (based on half-channel height and friction velocity) with a grid of 128 x 129 x and 128 points. The flow was followed over a total time of 141 viscous time units. Spanwise centering of the detected structures was found to be essential in order to obtain a correct magnitude of the associated Reynolds stress contribution. A positive wall-pressure peak is found immediately beneath the center of the structure. The maximum amplitude of the pressure pattern was, however, found in the buffer region at the center of the shear-layer. It was also found that these flow structures often reach a maximum strength in connection with an asymmetric spanwise motion, which motivated the construction of a conditional sampling scheme that preserved this asymmetry.

Johansson, Arne V.↗
NASA NTRS1992

Possibilistic clustering for shape recognition

Clustering methods have been used extensively in computer vision and pattern recognition. Fuzzy clustering has been shown to be advantageous over crisp (or traditional) clustering in that total commitment of a vector to a given class is not required at each iteration. Recently fuzzy clustering methods have shown spectacular ability to detect not only hypervolume clusters, but also clusters which are actually 'thin shells', i.e., curves and surfaces. Most analytic fuzzy clustering approaches are derived from Bezdek's Fuzzy C-Means (FCM) algorithm. The FCM uses the probabilistic constraint that the memberships of a data point across classes sum to one. This constraint was used to generate the membership update equations for an iterative algorithm. Unfortunately, the memberships resulting from FCM and its derivatives do not correspond to the intuitive concept of degree of belonging, and moreover, the algorithms have considerable trouble in noisy environments. Recently, we cast the clustering problem into the framework of possibility theory. Our approach was radically different from the existing clustering methods in that the resulting partition of the data can be interpreted as a possibilistic partition, and the membership values may be interpreted as degrees of possibility of the points belonging to the classes. We constructed an appropriate objective function whose minimum will characterize a good possibilistic partition of the data, and we derived the membership and prototype update equations from necessary conditions for minimization of our criterion function. In this paper, we show the ability of this approach to detect linear and quartic curves in the presence of considerable noise.

Keller, James M.↗
NASA NTRS1993

Possibilistic clustering for shape recognition

Clustering methods have been used extensively in computer vision and pattern recognition. Fuzzy clustering has been shown to be advantageous over crisp (or traditional) clustering in that total commitment of a vector to a given class is not required at each iteration. Recently fuzzy clustering methods have shown spectacular ability to detect not only hypervolume clusters, but also clusters which are actually 'thin shells', i.e., curves and surfaces. Most analytic fuzzy clustering approaches are derived from Bezdek's Fuzzy C-Means (FCM) algorithm. The FCM uses the probabilistic constraint that the memberships of a data point across classes sum to one. This constraint was used to generate the membership update equations for an iterative algorithm. Unfortunately, the memberships resulting from FCM and its derivatives do not correspond to the intuitive concept of degree of belonging, and moreover, the algorithms have considerable trouble in noisy environments. Recently, the clustering problem was cast into the framework of possibility theory. Our approach was radically different from the existing clustering methods in that the resulting partition of the data can be interpreted as a possibilistic partition, and the membership values may be interpreted as degrees of possibility of the points belonging to the classes. An appropriate objective function whose minimum will characterize a good possibilistic partition of the data was constructed, and the membership and prototype update equations from necessary conditions for minimization of our criterion function were derived. The ability of this approach to detect linear and quartic curves in the presence of considerable noise is shown.

Keller, James M.↗
NASA NTRS2004

Antigenic Protein In Microgravity-Grown Human Mixed Mullerian Tumor (LN1) Cells Preserved In RNA Stabilizing Agent

Cells treated with RNAlater(TradeMark) have previously been shown to contain antigenic proteins that can be visualized using Western blot analysis. These proteins seem to be stable for several months when stored in RNA stabilizer at 4 C. Antigenic protein can be recovered from cells that have been processed using an Ambion RNAqueous(Registered TradeMark) kit to remove RNA. In this set of experiments, human mixed Mullerian tumor (LNI) cells grown on the International Space Station during Expedition 3 were examined for antigenic stability after removal of RNA. The cells were stored for three months in RNAlater(TradeMark) and RNA was extracted. The RNA filtrate containing the protein was precipitated, washed, and suspended in buffer containing sodium dodecyl sulfate (SDS). Samples containing equal concentrations of protein were loaded onto SDS-polyacrylamide gels. Proteins were separated by electrophoresis and transferred by Western blot to polyvinylidene fluoride (PVDF) membrane. The Western blots were stained with an enhanced chemiluminescent ECL(Registered Trademark) Plus detection kit (Amersham) and scanned using a Storm 840 gel image analyzer (Amersham, Molecular Dynamics). ImageQuant(Registered TradeMark) software was used to quantify the densities of the protein bands. The ground control and flight LN1 cell samples showed a similar staining pattern over time with antibodies to vimentin, glyceraldehyde-3-phosphate dehydrogenase, and epithelial membrane antigens.

Hammond, Dianne K.↗
NASA NTRS2014

Vision Algorithm for the Solar Aspect System of the High Energy Replicated Optics to Explore the Sun Mission

This work covers the design and test of a machine vision algorithm for generating high- accuracy pitch and yaw pointing solutions relative to the sun on a high altitude balloon. It describes how images were constructed by focusing an image of the sun onto a plate printed with a pattern of small cross-shaped fiducial markers. Images of this plate taken with an off-the-shelf camera were processed to determine relative position of the balloon payload to the sun. The algorithm is broken into four problems: circle detection, fiducial detection, fiducial identification, and image registration. Circle detection is handled by an "Average Intersection" method, fiducial detection by a matched filter approach, and identification with an ad-hoc method based on the spacing between fiducials. Performance is verified on real test data where possible, but otherwise uses artificially generated data. Pointing knowledge is ultimately verified to meet the 20 arcsecond requirement.

0000000↗
NASA NTRS2019

The Seismic Signatures of Recently Formed Impact Craters on Mars

We investigated the seismic signatures of recent impact crater clusters on Mars that would be recorded by the Interior Exploration using Seismic Investigations, Geodesy and Heat Transport (InSight)seismometers. We used a database of 77 measured and dated impact sites, with craters with diameters between 2.1 and 33.8 m, along with inferred impact angle, bolide trajectory, and varying target material properties to empirically scale for the momentum, expected seismic source function, and radiation pattern of impacts. The impact source is simulated in a local 3‐Dfinite difference wave propagation code and coupled to teleseismic distances by scaling the spectra of 1‐D global synthetic seismograms. We use the InSight seismometer noise floors to estimate detectability of impact(s) across azimuth and distance. Our experiments reveal that impact clusters have a higher peak corner frequency resulting from energy contributed by smaller craters to the power spectrum. We also find that the time separation between individual impacts in a cluster is small (<10–15 ms) and requires a seismometer closely situated to the source (<10 km) and a high sampling rate (>100 Hz) to resolve individual impacts within the cluster. Two of the clusters in our database(>20‐m effective diameter) would have been detectable by InSight, with the assumptions that the Martian background noise and seismic attenuation are both low. Joint detection of surface changes from newly formed crater(s) in images and by InSight will provide precise source locations that are crucial for constraining the internal structure of Mars

N. C. Schmerra↗
DOE OSTI2017

The Biogeographic Pattern of Microbial Functional Genes along an Altitudinal Gradient of the Tibetan Pasture

As the highest place of the world, the Tibetan plateau is a fragile ecosystem. Given the importance of microbial communities in driving soil nutrient cycling, it is of interest to document the microbial biogeographic pattern here. We adopted a microarray-based tool named GeoChip 4.0 to investigate grassland microbial functional genes along an elevation gradient from 3200 to 3800 m above sea level open to free grazing by local herdsmen and wild animals. Interestingly, microbial functional diversities increase with elevation, so does the relative abundances of genes associated with carbon degradation, nitrogen cycling, methane production, cold shock and oxygen limitation. The range of Shannon diversities (10.27-10.58) showed considerably smaller variation than what was previously observed at ungrazed sites nearby (9.95-10.65), suggesting the important role of livestock grazing on microbial diversities. Closer examination showed that the dissimilarity of microbial community at our study sites increased with elevations, revealing an elevation-decay relationship of microbial functional genes. Both microbial functional diversity and the number of unique genes increased with elevations. Furthermore, we detected a tight linkage of greenhouse gas (CO 2 ) and relative abundances of carbon cycling genes. Our biogeographic study provides insights on microbial functional diversity and soil biogeochemical cycling in Tibetan pastures.

altitudinal gradient↗
DOE OSTI2024

Spatial patterns in occupancy and density of larval lampreys in freshwater habitats restored to a Stage 0 condition

Abstract We examined occupancy and density of larval lampreys ( Entosphenus tridentatus and Lampetra spp.) in two rivers in Oregon (USA) restored to a Stage 0 condition 1–5 years prior, using a multiscale occupancy model and a zero‐inflated Poisson mixture model. We sampled lampreys using backpack electrofishing in randomly distributed, paired, 1‐m 2 quadrats and recorded environmental data. Probabilities of occupancy and density were higher when water velocity was low, the substrate was noncompacted, and sediment was dominated by fines (<4 mm). At mean water depth (0.34 m) and velocity (0.09 m/s), estimated densities in occupied quadrats were 4.8 lampreys/m 2 (95%: 3.4–6.9) when the substrate was compacted, and fines were not dominant, and 21.1 lampreys/m 2 (95%: 17.7–25.3) when the substrate was noncompacted and fines were dominant. Probabilities of detecting occupancy in a 1‐m 2 quadrat sampled by backpack electrofishing were 0.76 (95%: 0.64–0.87) when captured after visual observation and 0.80 (95%: 0.71–0.88) with blind sweeps (i.e., constantly moving the net regardless of observation). The probability of capturing a single lamprey in a quadrat sampled by blind sweeps was 0.32 (95%: 0.27–0.37). Sampling in paired 1‐m 2 quadrats facilitated concurrent examination of patterns in occupancy and density while accounting for capture probability, which could aid temporal monitoring of restored habitats. To the best of our knowledge, this is the first study to document occupancy and estimate densities of larval lampreys in habitats that underwent valley floor restoration to Stage 0. We observed both lamprey genera within 5 years of restoration. Aquatic restoration that increases low‐velocity, noncompacted, fine sediment habitats could benefit lampreys.

Harris, Julianne E.↗