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At least 577 records · Page 32

A comparison of LANDSAT TM to MSS imagery for detecting submerged aquatic vegetation in lower Chesapeake Bay

LANDSAT Thematic Mapper (TM) and Multispectral Scanner (MSS) imagery generated simultaneously over Guinea Marsh, Virginia, are assessed in the ability to detect submerged aquatic, bottom-adhering plant canopies (SAV). An unsupervised clustering algorithm is applied to both image types and the resulting classifications compared to SAV distributions derived from color aerial photography. Class confidence and accuracy are first computed for all water areas and then only shallow areas where water depth is less than 6 feet. In both the TM and MSS imagery, masking water areas deeper than 6 ft. resulted in greater classification accuracy at confidence levels greater than 50%. Both systems perform poorly in detecting SAV with crown cover densities less than 70%. On the basis of the spectral resolution, radiometric sensitivity, and location of visible bands, TM imagery does not offer a significant advantage over MSS data for detecting SAV in Lower Chesapeake Bay. However, because the TM imagery represents a higher spatial resolution, smaller SAV canopies may be detected than is possible with MSS data.

Ackleson, S. G.↗

Hierarchical Image Segmentation of Remotely Sensed Data using Massively Parallel GNU-LINUX Software

A hierarchical set of image segmentations is a set of several image segmentations of the same image at different levels of detail in which the segmentations at coarser levels of detail can be produced from simple merges of regions at finer levels of detail. In [1], Tilton, et a1 describes an approach for producing hierarchical segmentations (called HSEG) and gave a progress report on exploiting these hierarchical segmentations for image information mining. The HSEG algorithm is a hybrid of region growing and constrained spectral clustering that produces a hierarchical set of image segmentations based on detected convergence points. In the main, HSEG employs the hierarchical stepwise optimization (HSWO) approach to region growing, which was described as early as 1989 by Beaulieu and Goldberg. The HSWO approach seeks to produce segmentations that are more optimized than those produced by more classic approaches to region growing (e.g. Horowitz and T. Pavlidis, [3]). In addition, HSEG optionally interjects between HSWO region growing iterations, merges between spatially non-adjacent regions (i.e., spectrally based merging or clustering) constrained by a threshold derived from the previous HSWO region growing iteration. While the addition of constrained spectral clustering improves the utility of the segmentation results, especially for larger images, it also significantly increases HSEG s computational requirements. To counteract this, a computationally efficient recursive, divide-and-conquer, implementation of HSEG (RHSEG) was devised, which includes special code to avoid processing artifacts caused by RHSEG s recursive subdivision of the image data. The recursive nature of RHSEG makes for a straightforward parallel implementation. This paper describes the HSEG algorithm, its recursive formulation (referred to as RHSEG), and the implementation of RHSEG using massively parallel GNU-LINUX software. Results with Landsat TM data are included comparing RHSEG with classic region growing.

Tilton, James C.↗

Searching for the 3.5 keV Line in the Stacked Suzaku Observations of Galaxy Clusters

We perform a detailed study of the stacked Suzaku observations of 47 galaxy clusters, spanning a redshift range of 0.01-0.45, to search for the unidentified 3.5 keV line. This sample provides an independent test for the previously detected line. We detect a 2sigma-significant spectral feature at 3.5 keV in the spectrum of the full sample. When the sample is divided into two subsamples (cool-core and non-cool core clusters), the cool-core subsample shows no statistically significant positive residuals at the line energy. A very weak (approx. 2sigma confidence) spectral feature at 3.5 keV is permitted by the data from the non-cool-core clusters sample. The upper limit on a neutrino decay mixing angle of sin(sup 2)(2theta) = 6.1 x 10(exp -11) from the full Suzaku sample is consistent with the previous detections in the stacked XMM-Newton sample of galaxy clusters (which had a higher statistical sensitivity to faint lines), M31, and Galactic center, at a 90% confidence level. However, the constraint from the present sample, which does not include the Perseus cluster, is in tension with previously reported line flux observed in the core of the Perseus cluster with XMM-Newton and Suzaku.

dark matter↗

Anomaly Detection in Large Sets of High-Dimensional Symbol Sequences

This paper addresses the problem of detecting and describing anomalies in large sets of high-dimensional symbol sequences. The approach taken uses unsupervised clustering of sequences using the normalized longest common subsequence (LCS) as a similarity measure, followed by detailed analysis of outliers to detect anomalies. As the LCS measure is expensive to compute, the first part of the paper discusses existing algorithms, such as the Hunt-Szymanski algorithm, that have low time-complexity. We then discuss why these algorithms often do not work well in practice and present a new hybrid algorithm for computing the LCS that, in our tests, outperforms the Hunt-Szymanski algorithm by a factor of five. The second part of the paper presents new algorithms for outlier analysis that provide comprehensible indicators as to why a particular sequence was deemed to be an outlier. The algorithms provide a coherent description to an analyst of the anomalies in the sequence, compared to more normal sequences. The algorithms we present are general and domain-independent, so we discuss applications in related areas such as anomaly detection.

Budalakoti, Suratna↗

Unsupervised anomaly clustering via offset alignment in multivariate grid sensing data

Modern industries increasingly rely on multi-sensor technologies to acquire complex, high-dimensional data streams, enabling advanced monitoring and control systems. One critical application is online anomaly detection in electrical smart grids, where multivariate and multimodal sensing technologies play a vital role. However, detecting anomalies in such time-series data is challenging due to their inherent temporal dependencies and stochastic behavior. Traditional approaches based on supervised and semi-supervised learning methods depend on labeled datasets, which are often unavailable in real-world scenarios. While unsupervised methods have emerged as promising alternatives, these methods are highly susceptible to noise and outliers commonly present in sensing applications. Furthermore, deep learning-based anomaly detection methods, despite their performance, are often criticized for their black-box nature, limiting their applicability in safety-critical and online environments where interpretability and explainability are paramount. In this work, we propose an unsupervised anomaly clustering method leveraging a cyclic alignment-based offset detection algorithm for multivariate time-series signals. The proposed method is applied to multivariate data collected from vibrational, voltage, and magnetic field sensors deployed in a local grid substation. Our results demonstrate the robustness of the algorithm in accurately clustering various anomalies/events across different sensing modalities. Additionally, we compare the effectiveness of the proposed approach against a simple pattern-based anomaly detection method, which performs well for univariate data but fails to generalize to multivariate and multimodal time-series data.

Mukherjee, Subrata [ORNL] (ORCID:0000000309930338)↗

HI observations of dwarf galaxies out to a distance of 50 Mpc

Here we report our preliminary findings from an HI search for dwarf galaxies in three environmentally distinct regions of the sky: a galactic void, a galactic cluster, and an interaction field. This study is sensitive at the 5(sigma) level to hydrogen masses as low as 5 x 10(exp 5) solar mass. We have made three possible detections of previously uncatalogued objects: one in the void field, and two in the cluster field. Reduction of the interaction field is in progress.

Simpson, Caroline↗

The EMSS catalog of X-ray-selected clusters of galaxies. 1: An atlas of CCD images of 41 distant clusters

An atlas of deep, wide-field R-band charge coupled device (CCD) images of a complete sample of distant, X-ray-selected clusters of galaxies is presented. These clusters are the 41 most distant (z is greater than or equal to 0.15) and most X-ray-luminous (L(sub x) is greater than or equal to 2 x 10(exp 44) ergs/s) clusters in the Einstein Observatory Extended Medium Sensitivity Survey (EMSS) catalog that are observable from Mauna Kea (delta is greater than -40 deg). The sample spans a redshift range of 0.15 is less than or equal to z is less than or equal to 0.81 and includes at least two and possibly as many as six rich clusters with z is greater than 0.5. For the most part, the data are of superior quality, with a median seeing of 0.8 sec full width half-maximum (FWHM) and coverage of at least 1 Mpc x 1 Mpc in the cluster frame (H(sub 0) = 50; q(sub 0) = 1/2). In addition, we update the available optical, X-ray, and radio data on the entire EMSS sample of 104 clusters. We outline the cluster selection criteria in detail and emphasize that X-ray-selected cluster samples may prove to be more useful for cosmological studies than optically selected samples. The EMSS cluster sample in particular can be exploited for diverse cosmological investigations, as demonstrated by the detection of evolution in the X-ray luminosity function previously reported, and more recently by the discovery of a large number of gravitationally lensed images in these clusters.

Gioia, I. M.↗

Temperature and elemental abundances in the Abell cluster A576 derived from X-ray observations

Results of the Einstein Solid State Spectrometer (SSS) observations of the central region of Abell 576 combined with HEAO 1 spectra of the total cluster are reported. Line emission due to Fe, Si, and S from a hot plasma in the central region of the object are detected. Abundances roughly one-half of the solar value are derived for these elements. The total cluster spectrum is well fitted by a thermal bremsstrahlung model with a temperature of 4 +3.5 or -1.4 x 10 to the 7th K. This temperature is in conflict with the SSS temperature determination for the center of the cluster. This difference can be explained if cooling takes place in the central part of the cluster, or if the X-ray emission in the center is dominated by the emission of a single galaxy.

Rothenflug, R.↗

Anomalous dust in the open cluster Trumpler 37

New IUE data were obtained towards stars in the open cluster Trumpler 37. Extinction curves derived from these data show that the anomalous dust detected towards HD 204827 and HD 210072 is not unique to those lines of sight but occurs generally in that region of the sky. The dust is apparently associated with the Trumpler 37 cluster, which forms the center of Cepheus OB2. This is a complex region of star formation where the evolution of dust grains through shock waves could be considered likely. A supernova in a slightly older star-forming region of Cep OB2 located next to Trumpler 37 is a possible source of such a shock wave.

Clayton, Geoffrey C.↗

A Search for CMB Decrements Towards Distant Cluster Candidates PC 1643+4631 and VLA 1312+4237 at 28.5 GHz

Recently, Jones et al. used the Ryle telescope, operating at a frequency of 15 GHz, to detect a flux decrement in the direction of the quasar pair PC 1643+461A,B. They interpreted this signal as the Sunyaev-Zel'dovich effect (SZE) produced by a distant cluster of galaxies. In the course of an effort to measure CMB anisotropies using the VLA at 8.4 GHz, Richards et al. (1997) detected a similar, but smaller, decrement which we refer to as VLA 1312+4237. They also proposed that this signal might be explained as the SZE signal of a distant galaxy cluster. We report observations in the direction of these claimed sources with the Berkeley Illinois Maryland Association (BIMA) interferometer operating at 28.5 GHz. We find no evidence for SZE emission in the direction of either of the claimed sources. In the case of PC 1643+4631, the BIMA data are inconsistent with the cluster emission model proposed by Jones et al. at greater than 99.99% confidence. Together with published x-ray and optical searches, these results make a compelling case against the existence of a massive cluster in the direction of PC 1643+4631. Because of the different scales to which the VLA and BIMA instruments are sensitive, the BIMA observations are not as constraining for the VLA 1312+4237 source. The BIMA data are inconsistent with the cluster model proposed by Richards et al. (1997) at approximately 80% confidence.

Holzapfel, W. L.↗

The detection of distant cooling flows and the formation of dark matter

Cooling flows involving substantial mass inflow rates appear to be common in many nearby rich and poor clusters and in isolated galaxies. The extensive optical and ultraviolet filaments produced by the thermal instability of large flows are detectable out to redshifts greater than 1. It is proposed that this may explain the extended optical line emission reported in, and around, many distant radio galaxies, narrow-line quasars, and even nearby normal and active galaxies. An important diagnostic to distinguish cooling flows from other possible origins of emission line filaments is the presence of extensive regions at high thermal pressure. Other evidence for distant cooling flows and the resultant star formation is further discussed, together with the implications of cooling flow initial-mass functions for galaxy formation and the nature of 'dark' matter.

Fabian, A. C.↗

Limits of Detection for EXAFS Characterization of Heterogeneous Single-Atom Catalysts

Single-atom catalysts (SACs), consisting of individual metal atoms dispersed on a support, attract attention due to their unique reactivity, efficient use of precious metals, and precise chemical tunability. Characterization of the metal species is crucial to substantiate structure–function relationships. Authors often use—and referees often require—X-ray absorption spectroscopy (XAS) data to prove the absence of clustered metal (or metal oxide) structures after pre-treatment and under in situ or operando conditions. However, there has been no critical assessment of the limitations of XAS in substantiating such conclusive statements, which is particularly important given the potential outsized influence of minority catalyst structures in dictating catalytic activity. Here, in this article, we quantitatively assess the detection limits of XAS to identify metal (or metal oxide) clusters in samples containing predominantly single atoms by modeling the extended X-ray absorption fine structure (EXAFS) of mixtures of structures. We identified that a significant fraction of clusters can coexist with SAC active sites (e.g., ~10% metallic Pt or ~40% oxidized Pt clusters in Pt/CeO 2 SACs), while eluding detection via EXAFS with any statistical significance. To generalize these conclusions, a descriptor-based screening of bulk metal oxides using a continuous Cauchy wavelet transform was proposed that suggests certain materials for which differentiating atomically dispersed metal species and metal oxide clusters would be infeasible by EXAFS (e.g., ReO x ). Based on this analysis, we suggest best practices for the study of SACs using EXAFS and provide recommendations to ensure that conclusions do not outpace the evidence used to support them. In this rapidly expanding research area, rigorous characterization will lead to greater understanding of the behavior of SACs and ultimately improved catalytic materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Optical emissivity dataset of multi-material heterogeneous designs generated with automated figure extraction

Optical device design is typically an iterative optimization process based on a good initial guess from prior reports. Optical properties databases are useful in this process but difficult to compile because their parsing requires finding relevant papers and manually converting graphical emissivity curves to data tables. Here, we present two contributions: one is a dataset of thermal emissivity records with design-related parameters, and the other is a software tool for automated colored curve data extraction from scientific plots. We manually collected 64 papers with 176 figures reporting thermal emissivity and automatically retrieved 153 colored curve data records. The automated figure analysis software pipeline uses Faster R-CNN for axes and legend object detection, EasyOCR for axes numbering recognition, and k-means clustering for colored curve retrieval. Additionally, we manually extracted geometry, materials, and method information from the text to add necessary metadata to each emissivity curve. Finally, we analyzed the dataset to determine the dominant classes of emissivity curves and determine the underlying design parameters leading to a type of emissivity profile.

47 OTHER INSTRUMENTATION↗

Sparse Bayesian mass mapping with uncertainties: hypothesis testing of structure

ABSTRACT A crucial aspect of mass mapping, via weak lensing, is quantification of the uncertainty introduced during the reconstruction process. Properly accounting for these errors has been largely ignored to date. We present a new method to reconstruct maximum a posteriori (MAP) convergence maps by formulating an unconstrained Bayesian inference problem with Laplace-type l1-norm sparsity-promoting priors, which we solve via convex optimization. Approaching mass mapping in this manner allows us to exploit recent developments in probability concentration theory to infer theoretically conservative uncertainties for our MAP reconstructions, without relying on assumptions of Gaussianity. For the first time, these methods allow us to perform hypothesis testing of structure, from which it is possible to distinguish between physical objects and artefacts of the reconstruction. Here, we present this new formalism, and demonstrate the method on simulations, before applying the developed formalism to two observational data sets of the Abell 520 cluster. Initial reconstructions of the Abell 520 catalogues reported the detection of an anomalous ‘dark core’ – an overdense region with no optical counterpart – which was taken to be evidence for self-interacting dark matter. In our Bayesian framework, it is found that neither Abell 520 data set can conclusively determine the physicality of such dark cores at $99{{\ \rm per\ cent}}$ confidence. However, in both cases the recovered MAP estimators are consistent with both sets of data.

Price, M. A.↗

The alignment between brightest cluster galaxies and host clusters

The alignment between the brightest cluster galaxies (BCGs) and host clusters can reveal the mystery of the formation and evolution of galaxy clusters. We measure cluster orientations in optical based on the projected distribution of member galaxies and in X-ray by fitting the morphology of intracluster medium (ICM). Cluster orientations determined in the two wavelengths are generally consistent. The orientation alignment between BCGs and host clusters is confirmed and more significant than in previous works. We find that BCGs are more aligned with cluster orientations measured in X-ray than those from optical data. Clusters with a brighter BCG generally show a stronger alignment. We argue that the detected redshift evolution of the alignment is probably caused by observational bias rather than intrinsic evolution. The alignment is not related to the ellipticity of BCGs, and the richness, ellipticity, and dynamical state of host clusters. As a result, the strong alignment between BCGs and the morphology of ICMs may be the consequence of the co-evolution between the central massive galaxy and host clusters.

79 ASTRONOMY AND ASTROPHYSICS↗

Shape evolution of neutron-rich 106,108,110 Mo isotopes in the triaxial degree of freedom

Background: Neutron-rich nuclei with mass number between 100 and 110 attract much attention, since several kinds of shapes, such as spherical, prolate, oblate, and triaxial shapes, are predicted. In particular, for neutron-rich Mo isotopes, different models predict different magnitudes and rigidity of triaxial deformation. Previous interpretations of experimental results based solely on low-lying $2^+_2$ states are insufficient to distinguish between the rigid triaxial shape, $\gamma$ vibration, or $\gamma$-soft rotor. Purpose: The shape evolution of 106 Mo, 108 Mo, and 110 Mo is investigated through their $2^+_1$-state lifetimes, decay-branching ratios of the $2^+_2$ state, and energies of the low-lying collective excited states with $K^π = 0^+, 2^+$, and $4^+$. Method: $\beta$-delayed $\gamma$-ray spectroscopy was employed for neutron-rich Nb and Zr isotopes produced at the RIKEN RI Beam Factory to populate excited states in 106 Mo, 108 Mo, and 110 Mo. The EUroball-RIKEN Cluster Array was used for high-resolution $\gamma$-ray detection and lifetimes of the $2^+_1$ states were determined using the UK fast-timing array of LaBr 3 (Ce) detectors. Results: New $\gamma$-ray transitions and levels are reported, including newly assigned $0^+_2$ states in 108,110 Mo. Quadrupole deformations were obtained for 106,108,110 Mo from their $2^+_1$ energies and lifetimes. The $\beta$-delayed neutron-emission probabilities of 108 Nb and 110 Nb were determined by examining the $\gamma$ rays of their respective daughter decays. Conclusions: In this work, the even-odd energy staggering in the $2^+_2$ band was compared with typical patterns of the $\gamma$-vibrational band, rigid triaxial rotor, and $\gamma$-soft rotor. The very small even-odd staggering of 106 Mo, 108 Mo, and 110 Mo favors a $\gamma$-vibrational band assignment. The kinematic moment of inertia for the $2^+_2$ band showed a trend similar to the ground-state band, which is as expected for the $\gamma$-vibrational band. Beyond-mean-field calculations employing the constrained Hartree-Fock-Bogoliubov and local quasiparticle-random-phase approximation method using the SLy5 + T interaction reproduced the ground and $2^+_2$ bands in 106 Mo and 108 Mo. The collective wave functions are consistent with the interpretation of the $2^+_2$ band as the $\gamma$-vibrational band of the prolate shape. However, the staggering pattern observed in 110 Mo differs from the one suggested in the calculations which predict a $\gamma$-soft rotor. There was no experimental indication of the oblate shape or the $\gamma$-soft rotor predicted in these Mo isotopes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Minnesota peat viromes reveal terrestrial and aquatic niche partitioning for local and global viral populations

Abstract Background Peatlands are expected to experience sustained yet fluctuating higher temperatures due to climate change, leading to increased microbial activity and greenhouse gas emissions. Despite mounting evidence for viral contributions to these processes in peatlands underlain with permafrost, little is known about viruses in other peatlands. More generally, soil viral biogeography and its potential drivers are poorly understood at both local and global scales. Here, 87 metagenomes and five viral size-fraction metagenomes (viromes) from a boreal peatland in northern Minnesota (the SPRUCE whole-ecosystem warming experiment and surrounding bog) were analyzed for dsDNA viral community ecological patterns, and the recovered viral populations (vOTUs) were compared with our curated PIGEON database of 266,125 vOTUs from diverse ecosystems. Results Within the SPRUCE experiment, viral community composition was significantly correlated with peat depth, water content, and carbon chemistry, including CH 4 and CO 2 concentrations, but not with temperature during the first 2 years of warming treatments. Peat vOTUs with aquatic-like signatures (shared predicted protein content with marine and/or freshwater vOTUs) were significantly enriched in more waterlogged surface peat depths. Predicted host ranges for SPRUCE vOTUs were relatively narrow, generally within a single bacterial genus. Of the 4326 SPRUCE vOTUs, 164 were previously detected in other soils, mostly peatlands. None of the previously identified 202,371 marine and freshwater vOTUs in our PIGEON database were detected in SPRUCE peat, but 0.4% of 80,714 viral clusters (VCs, grouped by predicted protein content) were shared between soil and aquatic environments. On a per-sample basis, vOTU recovery was 32 times higher from viromes compared with total metagenomes. Conclusions Results suggest strong viral “species” boundaries between terrestrial and aquatic ecosystems and to some extent between peat and other soils, with differences less pronounced at higher taxonomic levels. The significant enrichment of aquatic-like vOTUs in more waterlogged peat suggests that viruses may also exhibit niche partitioning on more local scales. These patterns are presumably driven in part by host ecology, consistent with the predicted narrow host ranges. Although more samples and increased sequencing depth improved vOTU recovery from total metagenomes, the substantially higher per-sample vOTU recovery after viral particle enrichment highlights the utility of soil viromics.

59 BASIC BIOLOGICAL SCIENCES↗

Chemical Compositions of Red Giant Stars from Habitable Zone Planet Finder Spectroscopy

We have used the Habitable Zone Planet Finder (HPF) to gather high-resolution, high signal-to-noise near-infrared spectra of 13 field red horizontal branch (RHB) stars, one open cluster giant, and one very metal-poor halo red giant. The HPF spectra cover the 0.81–1.28 μm wavelength range of the zyJ bands, partially filling the gap between the optical (0.4–1.0 μm) and infrared (1.5–2.4 μm) spectra already available for the program stars. We derive abundances of 17 species from LTE-based computations involving equivalent widths and spectrum syntheses, and estimate abundance corrections for the species that are most affected by departures from LTE in RHB stars. Generally good agreement is found between HPF-based metallicities and abundance ratios and those from the optical and infrared spectral regions. Light element transitions dominate the HPF spectra of these red giants, and HPF data can be used to derive abundances from species with poor or no representation in optical spectra (e.g., C i, P i, S i, K i). Attention is drawn to the HPF abundances in two field solar-metallicity RHB stars of special interest: one with an extreme carbon isotope ratio, and one with a rare, very large lithium content. The latter star is unique in our sample in exhibiting very strong He i 10830 Å absorption. The abundances of the open cluster giant concur with those derived from other wavelength regions. Detections of C i and S i in HD 122563 are reported, yielding the lowest metallicity determination of [S/Fe] from more than one multiplet.

47 OTHER INSTRUMENTATION↗