Computer-aided analysis of LANDSAT-1 MSS data: A comparison of three approaches, including a modified clustering approach
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Hoffer, R. M.↗
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Computer-aided analysis of Landsat-1 MSS data - A comparison of three approaches, including a 'modified clustering' approach
Three approaches for analyzing Landsat-1 data from Ludwig Mountain in the San Juan Mountain range in Colorado are considered. In the 'supervised' approach the analyst selects areas of known spectral cover types and specifies these to the computer as training fields. Statistics are obtained for each cover type category and the data are classified. Such classifications are called 'supervised' because the analyst has defined specific areas of known cover types. The second approach uses a clustering algorithm which divides the entire training area into a number of spectrally distinct classes. Because the analyst need not define particular portions of the data for use but has only to specify the number of spectral classes into which the data is to be divided, this classification is called 'nonsupervised'. A hybrid method which selects training areas of known cover type but then uses the clustering algorithm to refine the data into a number of unimodal spectral classes is called the 'modified-supervised' approach.
Fleming, M. D.↗
Cluster-based Characterization of Multi-dimensional Tropospheric Ozone Variability in Coastal Regions: An Analysis of Lidar Measurements and Model Results
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Claudia Bernier↗
Cooling Flow Spectra in Ginga Galaxy Clusters
The primary focus of this research project has been a joint analysis of Ginga LAC and Einstein SSS X-ray spectra of the hot gas in galaxy clusters with cooling flows is reported. We studied four clusters (A496, A1795, A2142 & A2199) and found their central temperatures to be cooler than in the exterior, which is expected from their having cooling flows. More interestingly, we found central metal abundance enhancements in two of the clusters, A496 and A2142. We have been assessing whether the abundance gradients (or lack thereof) in intracluster gas is correlated with galaxy morphological gradients in the host clusters. In rich, dense galaxy clusters, elliptical and SO galaxies are generally found in the cluster cores, while spiral galaxies are found in the outskirts. If the metals observed in clusters came from proto-ellipticals and proto-S0s blowing winds, then the metal distribution in intracluster gas may still reflect the distribution of their former host galaxies. In a research project which was inspired by the success of the Ginga LAC/Einstein SSS work, we analyzed X-ray spectra from the HEAO-A2 MED and the Einstein SSS to look for temperature gradients in cluster gas. The HEAO-A2 MED was also a non-imaging detector with a large field of view compared to the SSS, so we used the differing fields of view of the two instruments to extract spatial information. We found some evidence of cool gas in the outskirts of clusters, which may indicate that the nominally isothermal mass density distributions in these clusters are steepening in the outer parts of these clusters.
White, Raymond E., III↗
Direct Observation of Elusive (DTBM‐SEGPHOS)CuH Monomer Enables Mechanistic Insights Into Hydrocupration, Aggregation, and Dynamics of Alkene Functionalization Catalysis
The bulky diphosphine DTBM-SEGPHOS is widely employed in CuH-catalyzed transformations as it provides remarkably active catalyst systems. The transient (DTBM-SEGPHOS)CuH monomer (LCuH) is the often-invoked active species. However, its instability has prevented spectroscopic characterization and mechanistic elucidation, hindering mechanistic understanding. We report low-temperature NMR spectroscopic characterization of LCuH, enabling quantitative kinetic analysis of the stoichiometric hydrocupration and catalytic hydroboration of cyclopentene, as well as the structural identification of two CuH clusters. LCuH inserts cyclopentene at −43°C, reaffirming its high reactivity toward olefins. LCuH deactivates to form L 2 Cu 3 H 3 and L 2 Cu 4 H 4 clusters, in which LCuH dimerization initiates aggregation. Kinetic analysis of reactions of unactivated alkenes indicates that competing on-cycle alkene hydrocupration and LCuH dimerization impact performance, as catalyst deactivation and turnover occur on comparable timescales. Structure–activity analysis using atomistic simulations shows that the steric profile of DTBM-SEGPHOS increases the CuH dimerization barrier by ∼7.7 kcal mol−1 compared to that of SEGPHOS, rationalizing the unique ability of DTBM-SEGPHOS to stabilize a reactive monomer for hydrocupration of broader alkene substrates. These findings illustrate the fundamental design principle that steric control of aggregation governs CuH catalyst performance, explaining both the exceptional activity of (DTBM-SEGPHOS)CuH and the limitations imposed by competing deactivation.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
STM/S Grid LDOS Data and Analysis Code for Deciphering Majorana Zero Modes in Topological Superconductor
This dataset provides raw millikelvin scanning tunneling microscopy/spectroscopy (STM/S) grid spectroscopy data and Python analysis scripts supporting the manuscript “Deciphering Majorana Zero Modes in Topological Superconductor FeTe0.55Se0.45 with Machine-Learning-Assisted Spectral Deconvolution.” The dataset includes a raw grid spectroscopy file acquired on FeTe0.55Se0.45 at 40 mK under magnetic field, together with Python/Jupytext analysis scripts used for STM/S data processing, visualization, spectral deconvolution, Lorentzian peak fitting, feature extraction, machine-learning-assisted clustering, and figure generation. These files support the analysis of vortex-core local density of states and the identification of zero-bias-peak-related spectral components from complex in-gap states. The dataset is intended to provide a citable archival record of the data and analysis code associated with the published manuscript and to support transparency and reproducibility of the reported STM/S and machine-learning workflow.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Data and scripts associated with “Moisture content modulates DOM thermodynamic regulation of oxygen consumption in drying streambed sediments”
This data package is associated with the publication “Moisture content modulates DOM thermodynamic regulation of oxygen consumption in drying streambed sediments” published in Scientific Reports (Garayburu-Caruso et al., 2026). The package contains processed data products and scripts used to quantify how drying and re-inundation of riverbed sediments influence dissolved organic matter (DOM) thermodynamic properties and their relationship with sediment oxygen (O₂) consumption across 33 stream sites in the contiguous United States. The data package contains DOM thermodynamic metrics (e.g., Gibbs free energy of carbon oxidation and thermodynamic efficiency), and O₂ consumption along with watershed-scale climate and land-cover metrics used as explanatory variables in the analyses. Underlying unprocessed and processed ultrahigh-resolution mass spectrometry data, oxygen consumption rates from laboratory moisture-manipulation experiments, within-sample environmental properties, sediment moisture content and contextual field measurements are archived separately at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/2428003 (Laan et al., 2024) and https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1923689 (Forbes et al.,2023). A preliminary version of this data package was published in February 2026 at the time of manuscript submission. It was updated in June 2026, at the time of manuscript acceptance, to include the finalized data and additional metadata (readme, data dictionary, and file level metadata). For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. At the top level, the data package is organized into five main folders: (1) Data, (2)Figures, (3) Map, (4) GAM_Reulsts, and (5) src. The Data folder contains analysis-ready tabular files with oxygen consumption rates, DOM thermodynamic properties by site and treatment, site-level environmental variables, watershed-scale metrics, and other derived variables referenced in the manuscript. The Figures folder contains static image files associated with the main text and supplemental figures, while the Map folder includes spatial data and map-layer files used to create the sampling-location map. The GAM results folder contains the results for each of the general additive model (GAM).The src folder contains R scripts used to perform data processing, statistical analyses (including clustering, generalized additive models, and threshold analysis), and figure generation. This data package is associated with a GitHub repository found at https://github.com/WHONDRS-Hub/ECA_DOM_Thermodynamics.
Dissolved organic matter↗
Clustering, randomness and regularity in cloud fields. I - Theoretical considerations. II - Cumulus cloud fields
The current controversy existing in reference to the regularity vs. clustering in cloud fields is examined by means of analysis and simulation studies based upon nearest-neighbor cumulative distribution statistics. It is shown that the Poisson representation of random point processes is superior to pseudorandom-number-generated models and that pseudorandom-number-generated models bias the observed nearest-neighbor statistics towards regularity. Interpretation of this nearest-neighbor statistics is discussed for many cases of superpositions of clustering, randomness, and regularity. A detailed analysis is carried out of cumulus cloud field spatial distributions based upon Landsat, AVHRR, and Skylab data, showing that, when both large and small clouds are included in the cloud field distributions, the cloud field always has a strong clustering signal.
Weger, R. C.↗
BGC Atlas: a web resource for exploring the global chemical diversity encoded in bacterial genomes
Secondary metabolites are compounds not essential for an organism’s development, but provide significant ecological and physiological benefits. These compounds have applications in medicine, biotechnology and agriculture. Their production is encoded in biosynthetic gene clusters (BGCs), groups of genes collectively directing their biosynthesis. The advent of metagenomics has allowed researchers to study BGCs directly from environmental samples, identifying numerous previously unknown BGCs encoding unprecedented chemistry. Here, we present the BGC Atlas (https://bgc-atlas.cs.uni-tuebingen.de), a web resource that facilitates the exploration and analysis of BGC diversity in metagenomes. The BGC Atlas identifies and clusters BGCs from publicly available datasets, offering a centralized database and a web interface for metadata-aware exploration of BGCs and gene cluster families (GCFs). We analyzed over 35 000 datasets from MGnify, identifying nearly 1.8 million BGCs, which were clustered into GCFs. The analysis showed that ribosomally synthesized and post-translationally modified peptides are the most abundant compound class, with most GCFs exhibiting high environmental specificity. We believe that our tool will enable researchers to easily explore and analyze the BGC diversity in environmental samples, significantly enhancing our understanding of bacterial secondary metabolites, and promote the identification of ecological and evolutionary factors shaping the biosynthetic potential of microbial communities.
59 BASIC BIOLOGICAL SCIENCES↗
State-level suicide mortality insights: a comparative study of VHA veterans and the whole US population
Background: Suicide is a leading cause of death in the US Comparative State-level spatial analysis between Veterans Health Administration (VHA veterans) and the whole US population can reveal differences in conditions for targeted interventions and intricate geographical patterns. Methods: The study population contains 2018 and 2019 suicide deaths of VHA veterans and the whole US population. They were used to calculate state-level rates. States were classified by whether their VHA veteran and whole US population rates were above or below respective mean rates. Local Moran’s I was leveraged to examine spatial autocorrelation. Results: State-level suicide mortality rates and disparities among states were generally higher for VHA veterans (2018: 37.3 ± 7.2; 2019: 46.8 ± 8.3) than for the whole US population (2018: 16.6 ± 4.3; 2019: 16.4 ± 4.4). For both populations, there were statistically significant clusters with high suicide rates. Over one-fourth of states demonstrated inverse relationships, with rates above mean for one group but below for other. VHA veterans are at higher risk with over one-third of states had greater than average veteran suicide risk ratio. Conclusions: VHA veterans are at higher risk than the whole population across all states. Mortality disparities among states and clusters of states with high and low rates suggest targeted interventions and cooperative health strategies may help address these differences.
60 APPLIED LIFE SCIENCES↗
A minimal SufB 2 C 2 complex functions as a [4Fe-4S] cluster scaffold in methanogenic archaea
Iron-sulfur clusters are essential cofactors in all domains of life, yet their biogenesis in obligately anaerobic archaea remains poorly understood. Here, we characterized the minimal two-protein SUF system in methanogenic archaea, composed solely of SufB and SufC. Using Methanococcus maripaludis as a model, we demonstrate that the SUF proteins from its native host form a stable SufB 2 C 2 heterotetramer that binds a [4Fe-4S] cluster via three conserved cysteines in SufC. Mutations of conserved cysteine and histidine residues of SufB do not impair cluster binding. The complex interacts with the SAM-containing methanogenesis marker protein 10 (MmpX), suggesting direct Fe-S cluster transfer from SufB 2 C 2 to target proteins. Mutational analysis of Methanothermococcus thermolithotrophicus proteins confirmed that SufC is the primary cluster-binding component, while SufB enhances ATPase and cluster transfer activities. Evolutionary comparisons suggest that this two-protein SUF system represents an ancestral form of Fe-S cluster biogenesis.
59 BASIC BIOLOGICAL SCIENCES↗
SEAFORML (Smart Exploration and Analysis For Optimal and Robust Machine Learning)
The poster discusses data analysis of the WAVgraph database and applied machine learning methods for it. The database is a long-term project that seeks to be a comprehensive repository of information on cyber threats and is updated regularly. It was previously unanalyzed and unexplored. The goal was to learn more about it and its contents in order to have a better understanding and enable better use. The data analysis and discovery enabled further exploration through natural language processing, similarity, and clustering methods. The poster shows some of the insights from the analysis and explains the methods used for the machine learning applications.
24 - POWER TRANSMISSION AND DISTRIBUTION↗
A Search for Ram-pressure Stripping in the Hydra I Cluster
Ram-pressure stripping is a method by which hot interstellar gas can be removed from a galaxy moving through a group or cluster of galaxies. Indirect evidence of ram-pressure stripping includes lowered X-ray brightness in a galaxy due to less X-ray emitting gas remaining in the galaxy. Here we present the initial results of our program to determine whether cluster elliptical galaxies have lower hot gas masses than their counterparts in less rich environments. This test requires the use of the high-resolution imaging of the Chandra Observatory and we present our analysis of the galaxies in the nearby cluster Hydra I.
Brown, B.↗
NASA Space Science and a Search for Ram-Pressure Stripping in the Hydra I Cluster
The NASA Goddard Space Flight Center's Sciences and Exploration Directorate seeks to expand scientific knowledge through observational and theoretical research in the study of the Earth-Sun system, the solar system and the origins of life, and the birth and evolution of the universe. This talk will discuss some of the cutting-edge space science research being conducted at Goddard. In addition, I will discuss my research on ram-pressure stripping in cluster elliptical galaxies. Ram-pressure stripping is a method by which hot interstellar gas can be removed from a galaxy moving through a group or cluster of galaxies. Indirect evidence of ram-pressure stripping includes lowered X-ray brightness in a galaxy due to less X-ray emitting gas remaining in the galaxy. Here we present the initial results of our program to determine whether cluster elliptical galaxies have lower hot gas masses than their counterparts in less rich environments. This test requires the use of the high-resolution imaging of the Chandra Observatory and we present our analysis of the galaxies in the nearby cluster Hydra I.
Brown, Beth↗
A Search for Ram-pressure Stripping in the Hydra I Cluster
Ram-pressure stripping is a method by which hot interstellar gas can be removed from a galaxy moving through a group or cluster of galaxies. Indirect evidence of ram-pressure stripping includes lowered X- ray brightness in a galaxy due to less X-ray emitting gas remaining in the galaxy. Here we present the initial results of our program to determine whether cluster elliptical galaxies have lower hot gas masses than their counterparts in less rich environments. This test requires the use of the high-resolution imaging of the Chundru Observatory and we present our analysis of the galaxies in the nearby cluster Hydra I.
Brown, B. A.↗
The peculiar velocities of rich clusters in the hot and cold dark matter scenarios
We present the results of a study of the peculiar velocities of rich clusters of galaxies. The peculiar motion of rich clusters in various cosmological scenarios is of interest for a number of reasons. Observationally, one can measure the peculiar motion of clusters to greater distances than galaxies because cluster peculiar motions can be determined to greater accuracy. One can also test the slope of distance indicator relations using clusters to see if galaxy properties vary with environment. We have used N-body simulations to measure the amplitude and rms cluster peculiar velocity as a function of bias parameter in the hot and cold dark matter scenarios. In addition to measuring the mean and rms peculiar velocity of clusters in the two models, we determined whether the peculiar velocity vector of a given cluster is well aligned with the gravity vector due to all the particles in the simulation and the gravity vector due to the particles present only in the clusters. We have investigated the peculiar velocities of rich clusters of galaxies in the cold dark matter and hot dark matter galaxy formation scenarios. We have derived peculiar velocities and associated errors for the scenarios using four values of the bias parameter ranging from b = 1 to b = 2.5. The growth of the mean peculiar velocity with scale factor has been determined and compared to that predicted by linear theory. In addition, we have compared the orientation of force and velocity in these simulations to see if a program such as that proposed by Bertschinger and Dekel (1989) for elliptical galaxy peculiar motions can be applied to clusters. The method they describe enables one to recover the density field from large scale redshift distance samples. The method makes it possible to do this when only radial velocities are known by assuming that the velocity field is curl free. Our analysis suggests that this program if applied to clusters is only realizable for models with a low value of the bias parameter, i.e., models in which the peculiar velocities of clusters are large enough that the errors do not render the analysis impracticable.
Rhee, George F.↗
The spatial distribution, kinematics, and dynamics of the galaxies in the region of Abell 2634 and 2666
A total of 663 galaxies with known redshifts in a 12 deg x 12 deg field centered on A2634, including 211 new measurements, are used to study in detail the structure of the region. In it we find six main galaxy concentrations: the nearby clusters A2634 and A2666, two groups in the vicinity of A2634, and two distant clusters at approximately 18,000 (A2622) and approximately 37,000 km/s seen in projection near the core of A2634. For A2634, the most richly sampled of those concentrations, we are able to apply strict cluster membership criteria. Two samples - one containing 200 galaxies within 2 deg from the cluster center and a second, magnitude-limited, of 118 galaxies within the central half degree - are used to examine the structure, kinematics, dynamics, and morphological segregation of the cluster. We show that early type galaxies appear to be a relaxed system, while the spiral population eschews the center of the cluster and exhibits both a multimodal velocity distribution and a much larger velocity dispersion that the ellipticals. We propose that the spiral galaxies of A2634 represent a dynamically young cluster population. For the galaxy component of A2634, we find no evidence of significant substructure in the central regions. We also conclude that the adoption of lenient membership criteria that ignore the dynamical complexity of A2634 are unlikely to be responsible for the conflicting results reported on the motion of this cluster with respect ot the CMB. The kinematical and dynamical analysis is extended to A2634's close companion, A2666, and the two distant background clusters.
Scodeggio, Marco↗
Distant Massive Clusters and Cosmology
We present a status report of our X-ray study and analysis of a complete sample of distant (z=0.5-0.8), X-ray luminous clusters of galaxies. We have obtained ASCA and ROSAT observations of the five brightest Extended Medium Sensitivity (EMSS) clusters with z > 0.5. We have constructed an observed temperature function for these clusters, and measured iron abundances for all of these clusters. We have developed an analytic expression for the behavior of the mass-temperature relation in a low-density universe. We use this mass-temperature relation together with a Press-Schechter-based model to derive the expected temperature function for different values of Omega-M. We combine this analysis with the observed temperature functions at redshifts from 0 - 0.8 to derive maximum likelihood estimates for the value of Omega-M. We report preliminary results of this analysis.
Donahue, Megan↗