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At least 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Evaluation of a commercial automatic treatment planning system for prostate cancers

Recent developments in Radiation Oncology treatment planning have led to the development of software packages that facilitate automated intensity-modulated radiation therapy (IMRT) and volumetric-modulated arc therapy (VMAT) planning. Such solutions include site-specific modules, plan library methods, and algorithm-based methods. In this study, the plan quality for prostate cancer generated by the Auto-Planning module of the Pinnacle{sup 3} radiation therapy treatment planning system (v9.10, Fitchburg, WI) is retrospectively evaluated. The Auto-Planning module of Pinnacle{sup 3} uses a progressive optimization algorithm. Twenty-three prostate cancer cases, which had previously been planned and treated without lymph node irradiation, were replanned using the Auto-Planning module. Dose distributions were statistically compared with those of manual planning by the paired t-test at 5% significance level. Auto-Planning was performed without any manual intervention. Planning target volume (PTV) dose and dose to rectum were comparable between Auto-Planning and manual planning. The former, however, significantly reduced the dose to the bladder and femurs. Regression analysis was performed to examine the correlation between volume overlap between bladder and PTV divided by the total bladder volume and resultant V70. The findings showed that manual planning typically exhibits a logistic way for dose constraint, whereas Auto-Planning shows a more linear tendency. By calculating the Akaike information criterion (AIC) to validate the statistical model, a reduction of interoperator variation in Auto-Planning was shown. We showed that, for prostate cancer, the Auto-Planning module provided plans that are better than or comparable with those of manual planning. By comparing our results with those previously reported for head and neck cancer treatment, we recommend the homogeneous plan quality generated by the Auto-Planning module, which exhibits less dependence on anatomic complexity.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2014

GlyQ-IQ: Glycomics Quintavariate-Informed Quantification with High-Performance Computing and GlycoGrid 4D Visualization

Dense LC-MS datasets have convoluted extracted ion chromatograms with multiple chromatographic peaks that cloud the differentiation between intact compounds with their overlapping isotopic distributions, peaks due to insource ion fragmentation, and noise. Making this differentiation is critical in glycomics datasets because chromatographic peaks correspond to different intact glycan structural isomers. The GlyQ-IQ software is targeted chromatography centric software designed for chromatogram and mass spectra data processing and subsequent glycan composition annotation. The targeted analysis approach offers several key advantages to LC-MS data processing and annotation over traditional algorithms. A priori information about the individual target’s elemental composition allows for exact isotope profile modeling for improved feature detection and increased sensitivity by focusing chromatogram generation and peak fitting on the isotopic species in the distribution having the highest intensity and data quality. Glycan target annotation is corroborated by glycan family relationships and in source fragmentation detection. The GlyQ-IQ software is developed in this work (Part 1) and was used to profile N-glycan compositions from human serum LC-MS Datasets. The companion manuscript GlyQ-IQ Part 2 discusses developments in human serum N-glycan sample preparation, glycan isomer separation, and glycan electrospray ionization. A case study is presented to demonstrate how GlyQ-IQ identifies and removes confounding chromatographic peaks from high mannose glycan isomers from human blood serum. In addition, GlyQ-IQ was used to generate a broad N-glycan profile from a high resolution (100K/60K) nESI-LS-MS/MS dataset including CID and HCD fragmentation acquired on a Velos Pro Mass spectrometer. 101 glycan compositions and 353 isomer peaks were detected from a single sample. 99% of the GlyQ-IQ glycan-feature assignments passed manual validation and are backed with high resolution mass spectra and mass accuracies less than 7 ppm.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2020

Exploiting Colorimetry for Fidelity in Data Visualization

Advances in multimodal characterization methods fuel the generation of increasing immense hyper-dimensional data sets. Color mapping is employed for conveying higher dimensional data in two-dimensional (2D) representations for human consumption without relying on multiple projections. How one constructs these color maps, however, critically affects how accurately one perceives data. For simple scalar fields, perceptually uniform color maps and color selection have been shown to improve data readability and interpretation across research fields. In this work, we review core concepts underlying the design of perceptually uniform color maps and extend the concepts from scalar fields to two-dimensional vector fields and three-component composition fields frequently found in materials-chemistry research to enable high-fidelity visualization. Additionally, we develop the software tools PAPUC and CMPUC to enable researchers to utilize these colorimetry principles and employ perceptually uniform color spaces for rigorously meaningful color mapping of higher dimensional data representations. Last, we demonstrate how these approaches deliver immediate improvements in data readability and interpretation in microscopies and spectroscopies routinely used in discerning materials structure, chemistry, and properties.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Reaction Mechanism Generator v3.0: Advances in Automatic Mechanism Generation

In chemical kinetics research, kinetic models containing hundreds of species and tens of thousands of elementary reactions are commonly used to understand and predict the behavior of reactive chemical systems. Reaction Mechanism Generator (RMG) is a software suite developed to automatically generate such models by incorporating and extrapolating from a database of known thermochemical and kinetic parameters. Here, we present the recent version 3 release of RMG and highlight improvements since the previously published description of RMG v1.0. Most notably, RMG can now generate heterogeneous catalysis models in addition to the previously available gas- and liquid-phase capabilities. For model analysis, new methods for local and global uncertainty analysis have been implemented to supplement first-order sensitivity analysis. The RMG database of thermochemical and kinetic parameters has been significantly expanded to cover more types of chemistry. The present release includes parallelization for faster model generation and a new molecule isomorphism approach to improve computational performance. RMG has also been updated to use Python 3, ensuring compatibility with the latest cheminformatics and machine learning packages. Overall, RMG v3.0 includes many changes which improve the accuracy of the generated chemical mechanisms and allow for exploration of a wider range of chemical systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

IsoMatchMS : Open-Source Software for Automated Annotation and Visualization of High Resolution MALDI-MS Spectra

Due to its speed, accuracy, and adaptability to various sample types, matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) has become a popular method to identify molecular isotope profiles from biological samples. Often MALDI-MS data do not include tandem MS fragmentation data, and thus the identification of compounds in samples requires external databases so that the accurate mass of detected signals can be matched to known molecular compounds. Most relevant MALDI-MS software tools developed to confirm compound identifications are focused on small molecules (e.g., metabolites, lipids) and cannot be easily adapted to protein data due to their more complex isotopic distributions. Here, we present an R package called IsoMatchMS for the automated annotation of MALDI-MS data for multiple datatypes: intact proteins, peptides, and glycans. This tool accepts already derived molecular formulas or, for proteomics applications, can derive molecular formulas from a list of input peptides or proteins including proteins with post-translational modifications. In conclusion, visualization of all matched isotopic profiles is provided in a highly accessible HTML format called a trelliscope display, which allows users to filter and sort by several parameters such as match scores and the number of peaks matched. IsoMatchMS simplifies the annotation and visualization of MALDI-MS data for downstream analyses.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

One‐at‐a‐Time Parameter Perturbation Ensemble of the Community Land Model, Version 5.1

Comprehensive land models are subject to significant parametric uncertainty, which can be hard to quantify due to the large number of parameters and high model computational costs. We constructed a large parameter perturbation ensemble (PPE) for the Community Land Model version 5.1 with biogeochemistry configuration (CLM5.1-BGC). We performed more than 2,000 simulations perturbing 211 parameters across six forcing scenarios. This provides an expansive data set, which can be used to identify the most influential parameters on a wide range of output variables globally, by biome, or by plant functional type. We found that parameter effects can exceed scenario effects and that a small number of parameters explains a large fraction of variance across our ensemble. The most important parameters can differ regionally and also based on the forcing scenario. The software infrastructure developed for this experiment has greatly reduced the human and computer time needed for CLM PPEs, which can facilitate routine investigation of parameter sensitivity and uncertainty, as well as automated calibration.

Kennedy, Daniel [NSF National Center for Atmospher↗
DOE OSTI2021

Quantitative imaging and automated fuel pin identification for passive gamma emission tomography

Compliance of member States to the Treaty on the Non-Proliferation of Nuclear Weapons is monitored through nuclear safeguards. The Passive Gamma Emission Tomography (PGET) system is a novel instrument developed within the framework of the International Atomic Energy Agency (IAEA) project JNT 1510, which included the European Commission, Finland, Hungary and Sweden. The PGET is used for the verification of spent nuclear fuel stored in water pools. Advanced image reconstruction techniques are crucial for obtaining high-quality cross-sectional images of the spent-fuel bundle to allow inspectors of the IAEA to monitor nuclear material and promptly identify its diversion. In this work, we have developed a software suite to accurately reconstruct the spent-fuel cross sectional image, automatically identify present fuel rods, and estimate their activity. Unique image reconstruction challenges are posed by the measurement of spent fuel, due to its high activity and the self-attenuation. While the former is mitigated by detector physical collimation, we implemented a linear forward model to model the detector responses to the fuel rods inside the PGET, to account for the latter. The image reconstruction is performed by solving a regularized linear inverse problem using the fast-iterative shrinkage-thresholding algorithm. We have also implemented the traditional filtered back projection (FBP) method based on the inverse Radon transform for comparison and applied both methods to reconstruct images of simulated mockup fuel assemblies. Higher image resolution and fewer reconstruction artifacts were obtained with the inverse-problem approach, with the mean-square-error reduced by 50%, and the structural-similarity improved by 200%. We then used a convolutional neural network (CNN) to automatically identify the bundle type and extract the pin locations from the images; the estimated activity levels finally being compared with the ground truth. The proposed computational methods accurately estimated the activity levels of the present pins, with an associated uncertainty of approximately 5%.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Performance of CUDA Unified Memory in CMS Heterogeneous Pixel Reconstruction

The management of separate memory spaces of CPUs and GPUs brings an additional burden to the development of software for GPUs. To help with this, CUDA unified memory provides a single address space that can be accessed from both CPU and GPU. The automatic data transfer mechanism is based on page faults generated by the memory accesses. This mechanism has a performance cost, that can be with explicit memory prefetch requests. Various hints on the inteded usage of the memory regions can also be given to further improve the performance. The overall effect of unified memory compared to an explicit memory management can depend heavily on the application. In this paper we evaluate the performance impact of CUDA unified memory using the heterogeneous pixel reconstruction code from the CMS experiment as a realistic use case of a GPU-targeting HEP reconstruction software. We also compare the programming model using CUDA unified memory to the explicit management of separate CPU and GPU memory spaces.

Kortelainen, Matti J.↗
DOE OSTI2025

Experience with the alpaka performance portability library in the CMS software

ion Library for Parallel Kernel Acceleration) is a header-only C++ library that provides performance portability across different back-ends, abstracting the underlying levels of parallelism. It supports serial and parallel execution on CPUs, and extremely parallel execution on NVIDIA, AMD and Intel GPUs.This contribution will show how alpaka is used in the CMS software to develop and maintain a single code base; to use different toolchains to build the code for each supported back-end, and link them into a single application; to seamlessly select the best backend at runtime, and implement portable reconstruction algorithms that run efficiently on CPUs and GPUs from different vendors. It will describe the validation and deployment of the alpaka-based implementation in the CMS High Level Trigger, and highlight how it achieves near-native performance.

Alawieh, Jaafar [CERN]↗
DOE OSTI2020

Coupled-cluster techniques for computational chemistry: The CFOUR program package

An up-to-date overview of the CFOUR program system is given. After providing a brief outline of the evolution of the program since its inception in 1989, a comprehensive presentation is given of its well-known capabilities for high-level coupled-cluster theory and its application to molecular properties. Subsequent to this generally well-known background information, much of the remaining content focuses on lesser-known capabilities of CFOUR, most of which have become available to the public only recently or will become available in the near future. Each of these new features is illustrated by a representative example, with additional discussion targeted to educating users as to classes of applications that are now enabled by these capabilities. Lastly, some speculation about future directions is given, and the mode of distribution and support for CFOUR are outlined in the appendix.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Precision measures of the primordial abundance of deuterium

We report the discovery of deuterium absorption in the very metal-poor ([Fe/H] = –2.88) damped Lyα system at z {sub abs} = 3.06726 toward the QSO SDSS J1358+6522. On the basis of 13 resolved D I absorption lines and the damping wings of the H I Lyα transition, we have obtained a new, precise measure of the primordial abundance of deuterium. Furthermore, to bolster the present statistics of precision D/H measures, we have reanalyzed all of the known deuterium absorption-line systems that satisfy a set of strict criteria. We have adopted a blind analysis strategy (to remove human bias) and developed a software package that is specifically designed for precision D/H abundance measurements. For this reanalyzed sample of systems, we obtain a weighted mean of (D/H){sub p} = (2.53 ± 0.04) × 10{sup –5}, corresponding to a universal baryon density 100 Ω{sub b,} {sub 0} h {sup 2} = 2.202 ± 0.046 for the standard model of big bang nucleosynthesis (BBN). By combining our measure of (D/H){sub p} with observations of the cosmic microwave background (CMB), we derive the effective number of light fermion species, N {sub eff} = 3.28 ± 0.28. We therefore rule out the existence of an additional (sterile) neutrino (i.e., N {sub eff} = 4.046) at 99.3% confidence (2.7σ), provided that the values of N {sub eff} and of the baryon-to-photon ratio (η{sub 10}) did not change between BBN and recombination. We also place a strong bound on the neutrino degeneracy parameter, independent of the {sup 4}He primordial mass fraction, Y {sub P}: ξ{sub D} = +0.05 ± 0.13 based only on the CMB+(D/H){sub p} observations. Combining this value of ξ{sub D} with the current best literature measure of Y {sub P}, we find a 2σ upper bound on the neutrino degeneracy parameter, |ξ| ≤ +0.062.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Big Data in HEP: A comprehensive use case study

Experimental Particle Physics has been at the forefront of analyzing the worlds largest datasets for decades. The HEP community was the first to develop suitable software and computing tools for this task. In recent times, new toolkits and systems collectively called Big Data technologies have emerged to support the analysis of Petabyte and Exabyte datasets in industry. While the principles of data analysis in HEP have not changed (filtering and transforming experiment-specific data formats), these new technologies use different approaches and promise a fresh look at analysis of very large datasets and could potentially reduce the time-to-physics with increased interactivity. In this talk, we present an active LHC Run 2 analysis, searching for dark matter with the CMS detector, as a testbed for Big Data technologies. We directly compare the traditional NTuple-based analysis with an equivalent analysis using Apache Spark on the Hadoop ecosystem and beyond. In both cases, we start the analysis with the official experiment data formats and produce publication physics plots. Lastly, we will discuss advantages and disadvantages of each approach and give an outlook on further studies needed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Data-driven precision determination of the material budget in ALICE

The knowledge of the material budget with a high precision is fundamental for measurements of direct photon production using the photon conversion method due to its direct impact on the total systematic uncertainty. Moreover, it influences many aspects of the charged-particle reconstruction performance. In this article, two procedures to determine data-driven corrections to the material-budget description in ALICE simulation software are developed. One is based on the precise knowledge of the gas composition in the Time Projection Chamber. The other is based on the robustness of the ratio between the produced number of photons and charged particles, to a large extent due to the approximate isospin symmetry in the number of produced neutral and charged pions. Both methods are applied to ALICE data allowing for a reduction of the overall material budget systematic uncertainty from 4.5% down to 2.5%. Using these methods, a locally correct material budget is also achieved. The two proposed methods are generic and can be applied to any experiment in a similar fashion.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Reactome and the Gene Ontology: digital convergence of data resources

Abstract Motivation Gene Ontology Causal Activity Models (GO-CAMs) assemble individual associations of gene products with cellular components, molecular functions and biological processes into causally linked activity flow models. Pathway databases such as the Reactome Knowledgebase create detailed molecular process descriptions of reactions and assemble them, based on sharing of entities between individual reactions into pathway descriptions. Results To convert the rich content of Reactome into GO-CAMs, we have developed a software tool, Pathways2GO, to convert the entire set of normal human Reactome pathways into GO-CAMs. This conversion yields standard GO annotations from Reactome content and supports enhanced quality control for both Reactome and GO, yielding a nearly seamless conversion between these two resources for the bioinformatics community. Supplementary information Supplementary data are available at Bioinformatics online.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

sitoolbox: A package for Bayesian estimation of the isotropy violation in the CMB sky

ABSTRACT The standard model of cosmology predicts a statistically isotropic (SI) cosmic microwave background (CMB) sky. However, the SI violation signals are always present in an observed sky-map. Different cosmological artefacts, measurement effects, and unavoidable effects during data analysis, etc. may lead to isotropy violation in an otherwise SI sky. Therefore, a proper data analysis technique should calculate all these SI violation signals, so that they can be matched with SI violation signals from the known sources, and then conclude if there is any intrinsic SI violation in the CMB sky. In one of our recent works, we presented a general Bayesian formalism for measuring the isotropy violation signals in the CMB sky in the presence of an idealized isotropic noise. In this paper, we have extended the mechanism and develop a software package, sitoolbox, for measuring SI violation in presence of anisotropic noise and masking.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Reekeekee- and roodoodooviruses, two different Microviridae clades constituted by the smallest DNA phages

Small circular single-stranded DNA viruses of the Microviridae family are both prevalent and diverse in all ecosystems. They usually harbor a genome between 4.3 and 6.3 kb, with a microvirus recently isolated from a marine Alphaproteobacteria being the smallest known genome of a DNA phage (4.248 kb). A subfamily, Amoyvirinae, has been proposed to classify this virus and other related small Alphaproteobacteria-infecting phages. Here, we report the discovery, in meta-omics data sets from various aquatic ecosystems, of sixteen complete microvirus genomes significantly smaller (2.991–3.692 kb) than known ones. Phylogenetic analysis reveals that these sixteen genomes represent two related, yet distinct and diverse, novel groups of microviruses—amoyviruses being their closest known relatives. We propose that these small microviruses are members of two tentatively named subfamilies Reekeekeevirinae and Roodoodoovirinae. As known microvirus genomes encode many overlapping and overprinted genes that are not identified by gene prediction software, we developed a new methodology to identify all genes based on protein conservation, amino acid composition, and selection pressure estimations. Surprisingly, only four to five genes could be identified per genome, with the number of overprinted genes lower than that in phiX174. These small genomes thus tend to have both a lower number of genes and a shorter length for each gene, leaving no place for variable gene regions that could harbor overprinted genes. Even more surprisingly, these two Microviridae groups had specific and different gene content, and major differences in their conserved protein sequences, highlighting that these two related groups of small genome microviruses use very different strategies to fulfill their lifecycle with such a small number of genes. The discovery of these genomes and the detailed prediction and annotation of their genome content expand our understanding of ssDNA phages in nature and are further evidence that these viruses have explored a wide range of possibilities during their long evolution.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Precise mapping of new group I introns in tRNA genes

Bacterial tRNA have been found interrupted at various positions in the anticodon loop by group I introns, in four types. The primary bioinformatic tool for group I intron discovery is a covariance model that can identify conserved features in the catalytic core and can sometimes identify the typical uridine residue at the -1 position, preceding the 5-prime splice site, but cannot identify the typical guanidine residue at the omega position, preceding the 3-prime splice site, to achieve precise mapping. One approach to complete the automation of group I intron mapping is to focus instead on the exons, which is enabled by the regularity of tRNAs. We develop a software module, within a larger package (tFind) aimed at mapping bacterial tRNA and tmRNA genes precisely, that expands this list of four known classes of intron-interrupted tRNAs to 21 cases. A new covariance model for these introns is presented. The wobble base pair formed by the -1 uridine is considered a determinant of the 5-prime splice site, yet one reasonably large new type bears a cytidine nucleotide at that position.

Williams, Kelly P.↗
DOE OSTI2014

Continuous mutual improvement of macromolecular structure models in the PDB and of X-ray crystallographic software: the dual role of deposited experimental data

Macromolecular structures deposited in the PDB can and should be continually reinterpreted and improved on the basis of their accompanying experimental X-ray data, exploiting the steady progress in methods and software that the deposition of such data into the PDB on a massive scale has made possible. Accurate crystal structures of macromolecules are of high importance in the biological and biomedical fields. Models of crystal structures in the Protein Data Bank (PDB) are in general of very high quality as deposited. However, methods for obtaining the best model of a macromolecular structure from a given set of experimental X-ray data continue to progress at a rapid pace, making it possible to improve most PDB entries after their deposition by re-analyzing the original deposited data with more recent software. This possibility represents a very significant departure from the situation that prevailed when the PDB was created, when it was envisioned as a cumulative repository of static contents. A radical paradigm shift for the PDB is therefore proposed, away from the static archive model towards a much more dynamic body of continuously improving results in symbiosis with continuously improving methods and software. These simultaneous improvements in methods and final results are made possible by the current deposition of processed crystallographic data (structure-factor amplitudes) and will be supported further by the deposition of raw data (diffraction images). It is argued that it is both desirable and feasible to carry out small-scale and large-scale efforts to make this paradigm shift a reality. Small-scale efforts would focus on optimizing structures that are of interest to specific investigators. Large-scale efforts would undertake a systematic re-optimization of all of the structures in the PDB, or alternatively the redetermination of groups of structures that are either related to or focused on specific questions. All of the resulting structures should be made generally available, along with the precursor entries, with various views of the structures being made available depending on the types of questions that users are interested in answering.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗