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At least 613 records · Page 34

NEW Fe I LEVEL ENERGIES AND LINE IDENTIFICATIONS FROM STELLAR SPECTRA

The spectrum of the Fe I atom is critical to many areas of astrophysics and beyond. Measurements of the energies of its high-lying levels remain woefully incomplete, however, despite extensive laboratory and solar analysis. In this work, we use high-resolution archival absorption-line ultraviolet and optical spectra of stars whose warm temperatures favor moderate Fe I excitation. We derive the energy for a particular upper level in Kurucz's semiempirical calculations by adopting a trial value that yields the same wavelength for a given line predicted to be about as strong as that of a strong unidentified spectral line observed in the stellar spectra, then checking the new wavelengths of other strong predicted transitions that share the same upper level for coincidence with other strong observed unidentified lines. To date, this analysis has provided the upper energies of 66 Fe I levels. Many new energy levels are higher than those accessible to laboratory experiments; several exceed the Fe I ionization energy. These levels provide new identifications for over 2000 potentially detectable lines. Almost all of the new levels of odd parity include UV lines that were detected but unclassified in laboratory Fe I absorption spectra, providing an external check on the energy values. We motivate and present the procedure, provide the resulting new energy levels and their uncertainties, list all the potentially detectable UV and optical new Fe I line identifications and their gf values, point out new lines of astrophysical interest, and discuss the prospects for additional Fe I energy level determinations.

79 ASTRONOMY AND ASTROPHYSICS↗

Non-disruptive error field identification based on magnetic island healing

Here a technique to identify intrinsic error fields (EFs) in tokamaks with minimized risk of disruption is demonstrated on the DIII-D tokamak. The method extends the conventional driven magnetic island ‘compass scan’ approach by modifying asynchronous control waveforms to enable prompt healing of the island instability. Healing of the island is achieved by reducing the imposed non-axisymmetric coil current and raising the density (here via gas fueling). The method is also shown to support multiple island threshold measurements per pulse, thus reducing the number of dedicated pulses necessary to conduct an EF identification. Non-linear modeling with the TM1 code reproduces the experimental results and approximately recovers the critical density required for island healing. Island healing is explained in the non-linear modeling by an increase in the viscous coupling between the static island and the nearby flowing plasma, thus healing the island as it accelerates into the plasma frame. Due to both simplicity and risk minimization, this technique is suitable for plasma-based EF identification in the early commissioning stages of future disruption-averse tokamaks such as ITER and SPARC.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Performance of photon reconstruction and identification with the CMS detector in proton-proton collisions at √s = 8 TeV

A description is provided of the performance of the CMS detector for photon reconstruction and identification in proton-proton collisions at a centre-of-mass energy of 8 TeV at the CERN LHC. Details are given on the reconstruction of photons from energy deposits in the electromagnetic calorimeter (ECAL) and the extraction of photon energy estimates. Furthermore, the reconstruction of electron tracks from photons that convert to electrons in the CMS tracker is also described, as is the optimization of the photon energy reconstruction and its accurate modelling in simulation, in the analysis of the Higgs boson decay into two photons. In the barrel section of the ECAL, an energy resolution of about 1% is achieved for unconverted or late-converting photons from H → γγ decays. Furthermore, different photon identification methods are discussed and their corresponding selection efficiencies in data are compared with those found in simulated events.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A new calibration method for charm jet identification validated with proton-proton collision events at $\sqrt{s}$ =13 TeV

Many measurements at the LHC require efficient identification of heavy-flavour jets, i.e. jets originating from bottom (b) or charm (c) quarks. An overview of the algorithms used to identify c jets is described and a novel method to calibrate them is presented. This new method adjusts the entire distributions of the outputs obtained when the algorithms are applied to jets of different flavours. It is based on an iterative approach exploiting three distinct control regions that are enriched with either b jets, c jets, or light-flavour and gluon jets. Results are presented in the form of correction factors evaluated using proton-proton collision data with an integrated luminosity of 41.5 fb$^{-1}$ at √s = 13 TeV, collected by the CMS experiment in 2017. The closure of the method is tested by applying the measured correction factors on simulated data sets and checking the agreement between the adjusted simulation and collision data. Furthermore, a validation is performed by testing the method on pseudodata, which emulate various mismodelling conditions. The calibrated results enable the use of the full distributions of heavy-flavour identification algorithm outputs, e.g. as inputs to machine-learning models. Thus, they are expected to increase the sensitivity of future physics analyses.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Investigations on a fuzzy process: effect of diffusion on calibration and particle identification in Liquid Argon Time Projection Chambers

Ionization electron diffusion in Liquid Argon Time Projection Chambers (LArTPCs) has typically been considered at the detector design stage, but little attention has been given to its effects on calibration and particle identification. We use a GEANT4-based simulation to study how diffusion impacts these techniques, and give consideration to how this effect is simulated. We find that diffusion can cause a drift-dependent bias to both the median and Most Probable Value (MPV) of dQ/dx distributions. The bias is estimated to be ~2.5% (median) and ~5.0% (MPV) for typical maximum drift times in currently running LArTPCs before adding detector specific considerations such as electric field non-uniformities. This information indicates that these metrics should not be used for calibration without care, contrary to the conventional wisdom. The impact of diffusion on the ability of LArTPCs to separate muons and protons is small, and not expected to pose any problems in future detectors. Diffusion may however be a significant source of systematic uncertainty when separating particles of more similar masses (muons and pions, kaons and protons). Separation of such populations may be improved by implementation of a drift-time dependent particle identification.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

PROBING THE MSP PRENATAL STAGE: THE OPTICAL IDENTIFICATION OF THE X-RAY BURSTER EXO 1745-248 IN TERZAN 5

We report on the optical identification of the neutron star burster EXO 1745-248 in Terzan 5. The identification was performed by exploiting Hubble Space Telescope/Advanced Camera for Surveys images acquired in Director's Discretionary Time shortly after (approximately one month) the Swift detection of the X-ray burst. The comparison between these images and previous archival data revealed the presence of a star that is currently brightened by ∼3 mag, consistent with expectations during an X-ray outburst. The centroid of this object well agrees with the position, in the archival images, of a star located in the turn-off/sub-giant-branch region of Terzan 5. This supports the scenario that the companion should have recently filled its Roche Lobe. Such a system represents the prenatal stage of a millisecond pulsar, an evolutionary phase during which heavy mass accretion on the compact object occurs, thus producing X-ray outbursts and re-accelerating the neutron star.

79 ASTRONOMY AND ASTROPHYSICS↗

CDvist: A webserver for identification and visualization of conserved domains in protein sequences

Identification of domains in protein sequences allows their assigning to biological functions. Several webservers exist for identification of protein domains using similarity searches against various databases of protein domain models. However, none of them provides comprehensive domain coverage while allowing bulk querying and their visualization schemes can be improved. To address these issues, we developed CDvist (a comprehensive domain visualization tool), which combines the best available search algorithms and databases into a user-friendly framework. First, a given protein sequence is matched to domain models using high-specificity tools and only then unmatched segments are subjected to more sensitive algorithms resulting in a best possible comprehensive coverage. In conclusion, bulk querying and rich visualization and download options provide improved functionality to domain architecture analysis.

59 BASIC BIOLOGICAL SCIENCES↗

DeepSZ: identification of Sunyaev–Zel’dovich galaxy clusters using deep learning

Galaxy clusters identified via the Sunyaev–Zel’dovich (SZ) effect are a key ingredient in multiwavelength cluster cosmology. In this paper, we present and compare three methods of cluster identification: the standard matched filter (MF) method in SZ cluster finding, a convolutional neural networks (CNN), and a ‘combined’ identifier. We apply the methods to simulated millimeter maps for several observing frequencies for a survey similar to SPT-3G, the third-generation camera for the South Pole Telescope. The MF requires image pre-processing to remove point sources and a model for the noise, while the CNN requires very little pre-processing of images. Additionally, the CNN requires tuning of hyperparameters in the model and takes cut-out images of the sky as input, identifying the cut-out as cluster-containing or not. We compare differences in purity and completeness. The MF signal-to-noise ratio depends on both mass and redshift. Our CNN, trained for a given mass threshold, captures a different set of clusters than the MF, some with signal-to-noise-ratio below the MF detection threshold. However, the CNN tends to mis-classify cut-out whose clusters are located near the edge of the cut-out, which can be mitigated with staggered cut-out. We leverage the complementarity of the two methods, combining the scores from each method for identification. The purity and completeness are both 0.61 for MF, and 0.59 and 0.61 for CNN. The combined method yields 0.60 and 0.77, a significant increase for completeness with a modest decrease in purity. We advocate for combined methods that increase the confidence of many low signal-to-noise clusters.

79 ASTRONOMY AND ASTROPHYSICS↗

The PhyloFacts FAT-CAT web server: ortholog identification and function prediction using fast approximate tree classification

The PhyloFacts ‘Fast Approximate Tree Classification’ (FAT-CAT) web server provides a novel approach to ortholog identification using subtree hidden Markov model-based placement of protein sequences to phylogenomic orthology groups in the PhyloFacts database. Results on a data set of microbial, plant and animal proteins demonstrate FAT-CAT’s high precision at separating orthologs and paralogs and robustness to promiscuous domains. We also present results documenting the precision of ortholog identification based on subtree hidden Markov model scoring. The FAT-CAT phylogenetic placement is used to derive a functional annotation for the query, including confidence scores and drill-down capabilities. PhyloFacts’ broad taxonomic and functional coverage, with >7.3 M proteins from across the Tree of Life, enables FAT-CAT to predict orthologs and assign function for most sequence inputs. Four pipeline parameter presets are provided to handle different sequence types, including partial sequences and proteins containing promiscuous domains; users can also modify individual parameters. PhyloFacts trees matching the query can be viewed interactively online using the PhyloScope Javascript tree viewer and are hyperlinked to various external databases.

59 BASIC BIOLOGICAL SCIENCES↗

Strain/species identification in metagenomes using genome-specific markers

Shotgun metagenome sequencing has become a fast, cheap and high-throughput technology for characterizing microbial communities in complex environments and human body sites. However, accurate identification of microorganisms at the strain/species level remains extremely challenging. We present a novel k-mer-based approach, termed GSMer, that identifies genome-specific markers (GSMs) from currently sequenced microbial genomes, which were then used for strain/species-level identification in metagenomes. Using 5390 sequenced microbial genomes, 8 770 321 50-mer strain-specific and 11 736 360 species-specific GSMs were identified for 4088 strains and 2005 species (4933 strains), respectively. The GSMs were first evaluated against mock community metagenomes, recently sequenced genomes and real metagenomes from different body sites, suggesting that the identified GSMs were specific to their targeting genomes. Sensitivity evaluation against synthetic metagenomes with different coverage suggested that 50 GSMs per strain were sufficient to identify most microbial strains with ≥0.25× coverage, and 10% of selected GSMs in a database should be detected for confident positive callings. Application of GSMs identified 45 and 74 microbial strains/species significantly associated with type 2 diabetes patients and obese/lean individuals from corresponding gastrointestinal tract metagenomes, respectively. Our result agreed with previous studies but provided strain-level information. The approach can be directly applied to identify microbial strains/species from raw metagenomes, without the effort of complex data pre-processing.

59 BASIC BIOLOGICAL SCIENCES↗

DMINDA: an integrated web server for DNA motif identification and analyses

DMINDA (DNA motif identification and analyses) is an integrated web server for DNA motif identification and analyses, which is accessible at http: //csbl.bmb.uga.edu/DMINDA/. This web site is freely available to all users and there is no login requirement. This server provides a suite of cis-regulatory motif analysis functions on DNA sequences, which are important to elucidation of the mechanisms of transcriptional regulation: (i) de novo motif finding for a given set of promoter sequences along with statistical scores for the predicted motifs derived based on information extracted from a control set, (ii) scanning motif instances of a query motif in provided genomic sequences, (iii) motif comparison and clustering of identified motifs, and (iv) co-occurrence analyses of query motifs in given promoter sequences. The server is powered by a backend computer cluster with over 150 computing nodes, and is particularly useful for motif prediction and analyses in prokaryotic genomes. We believe that DMINDA, as a new and comprehensive web server for cis-regulatory motif finding and analyses, will benefit the genomic research community in general and prokaryotic genome researchers in particular.

59 BASIC BIOLOGICAL SCIENCES↗

FUSARIUM-ID v.3.0: An Updated, Downloadable Resource for Fusarium Species Identification

Species within Fusarium are of global agricultural, medical, and food/feed safety concern and have been extensively characterized. However, accurate identification of species is challenging and usually requires DNA sequence data. FUSARIUM-ID ( http://isolate.fusariumdb.org/blast.php ) is a publicly available database designed to support the identification of Fusarium species using sequences of multiple phylogenetically informative loci, especially the highly informative ~680-bp 5' portion of the translation elongation factor 1-alpha (TEF1) gene that has been adopted as the primary barcoding locus in the genus. However, FUSARIUM-ID v.1.0 and 2.0 had several limitations, including inconsistent metadata annotation for the archived sequences and poor representation of some species complexes and marker loci. Here, we present FUSARIUM-ID v.3.0, which provides the following improvements: (i) additional and updated annotation of metadata for isolates associated with each sequence, (ii) expanded taxon representation in the TEF1 sequence database, (iii) availability of the sequence database as a downloadable file to enable local BLAST queries, and (iv) a tutorial file for users to perform local BLAST searches using either freely available software, such as SequenceServer, BLAST+ executable in the command line, and Galaxy, or the proprietary Geneious software. FUSARIUM-ID will be updated on a regular basis by archiving sequences of TEF1 and other loci from newly identified species and greater in-depth sampling of currently recognized species.

Plant Sciences↗

Preliminary Thermoluminescent Dosimeter Glow Curve Analysis with Automated Glow Peak Identification for LiF Mg,Ti

When appropriately analyzed, thermoluminescent dosimeter glow curve analysis allows for improved quantification of thermoluminescent material behavior while flagging abnormalities. The mathematical separation of a glow curve into contributions from energetically unique trap states, or glow curve analysis, may be used to remove undesired effects of signal fading for complex materials. A generalized glow curve analysis software for the separation of glow curves is presented in this paper. Written in C ++ , the software uses the first-order kinetics model with automatic peak identification. The automatic identification of peaks is achieved through a unique peak-finding algorithm. Here, the program was performance tested using experimental glow curve data from LiF:Mg,Ti, and comparative results are presented.

47 OTHER INSTRUMENTATION↗

FCC feasibility studies: Impact of tracker- and calorimeter-detector performance on jet flavor identification and Higgs physics analyses

The ambitious physics program planned for the Future Circular Collider electron-positron phase imposes stringent constraints on detector performance. This study systematically investigates how different detector configurations impact jet flavor identification and their effects on high-profile physics analyses. Using Higgs boson coupling measurements and searches for invisible Higgs decays as benchmarks, we evaluate the sensitivity of these analyses to variations in tracker and calorimeter detector properties. We examine modifications to single-point resolution, material budget, silicon layer placement, and particle identification capabilities, quantifying their effects on flavor-tagging performance. Additionally, we present the first comprehensive study of Higgs-to-invisible decay detection using full detector simulation, providing insights for optimizing detector designs at lepton colliders.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Identification of the first small-molecule ligand of the neuronal receptor sortilin and structure determination of the receptor–ligand complex

The identification of the first small-molecule ligand of the neuronal receptor sortilin and structure determination of the receptor–ligand complex are reported. Sortilin is a type I membrane glycoprotein belonging to the vacuolar protein sorting 10 protein (Vps10p) family of sorting receptors and is most abundantly expressed in the central nervous system. Sortilin has emerged as a key player in the regulation of neuronal viability and has been implicated as a possible therapeutic target in a range of disorders. Here, the identification of AF40431, the first reported small-molecule ligand of sortilin, is reported. Crystals of the sortilin–AF40431 complex were obtained by co-crystallization and the structure of the complex was solved to 2.7 Å resolution. AF40431 is bound in the neurotensin-binding site of sortilin, with the leucine moiety of AF40431 mimicking the binding mode of the C-terminal leucine of neurotensin and the 4-methylumbelliferone moiety of AF40431 forming π-stacking with a phenylalanine.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Automated identification of crystallographic ligands using sparse-density representations

A novel procedure for identifying ligands in macromolecular crystallographic electron-density maps is introduced. Density clusters in such maps can be rapidly attributed to one of 82 different ligands in an automated manner. A novel procedure for the automatic identification of ligands in macromolecular crystallographic electron-density maps is introduced. It is based on the sparse parameterization of density clusters and the matching of the pseudo-atomic grids thus created to conformationally variant ligands using mathematical descriptors of molecular shape, size and topology. In large-scale tests on experimental data derived from the Protein Data Bank, the procedure could quickly identify the deposited ligand within the top-ranked compounds from a database of candidates. This indicates the suitability of the method for the identification of binding entities in fragment-based drug screening and in model completion in macromolecular structure determination.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Rapid experimental SAD phasing and hot-spot identification with halogenated fragments

Through X-ray crystallographic fragment screening, 4-bromopyrazole was discovered to be a `magic bullet' that is capable of binding at many of the ligand `hot spots' found in HIV-1 reverse transcriptase (RT). The binding locations can be in pockets that are `hidden' in the unliganded crystal form, allowing rapid identification of these sites for in silico screening. In addition to hot-spot identification, this ubiquitous yet specific binding provides an avenue for X-ray crystallographic phase determination, which can be a significant bottleneck in the determination of the structures of novel proteins. The anomalous signal from 4-bromopyrazole or 4-iodopyrazole was sufficient to determine the structures of three proteins (HIV-1 RT, influenza A endonuclease and proteinase K) by single-wavelength anomalous dispersion (SAD) from single crystals. Both compounds are inexpensive, readily available, safe and very soluble in DMSO or water, allowing efficient soaking into crystals.

Bauman, Joseph D.↗

Identification of inversion domains in KTiOPO{sub 4}via resonant X-ray diffraction

The identification and high-resolution mapping of the absolute crystallographic structure in multi-domain ferroelectric KTiOPO{sub 4} is achieved through a novel synchrotron X-ray diffraction method. On a single Bragg reflection, the intensity ratio in resonant diffraction below and above the Ti absorption K edge demonstrates a domain contrast up to a factor of ∼270, thus implementing a non-contact, non-destructive imaging technique with micrometre spatial resolution, applicable to samples of arbitrarily large dimensions. A novel method is presented for the identification of the absolute crystallographic structure in multi-domain polar materials such as ferroelectric KTiOPO{sub 4}. Resonant (or ‘anomalous’) X-ray diffraction spectra collected across the absorption K edge of Ti (4.966 keV) on a single Bragg reflection demonstrate a huge intensity ratio above and below the edge, providing a polar domain contrast of ∼270. This allows one to map the spatial domain distribution in a periodically inverted sample, with a resolution of ∼1 µm achieved with a microfocused beam. This non-contact, non-destructive technique is well suited for samples of large dimensions (in contrast with traditional resonant X-ray methods based on diffraction from Friedel pairs), and its potential is particularly relevant in the context of physical phenomena connected with an absence of inversion symmetry, which require characterization of the underlying absolute atomic structure (such as in the case of magnetoelectric coupling and multiferroics)

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗