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At least 451 records · Page 25
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DOE OSTI2024

Development of learning objectives to support undergraduate virology curriculum guidelines

It has become increasingly important for microbiology educators to help students learn critical concepts of the discipline. This is particularly true in virology, where current challenges include increasing rates of vaccine hesitancy, misinformation about the COVID-19 pandemic, and controversy surrounding research on pathogens with pandemic potential. Having students learn virology can attract more people to the field and increase the number of people who can engage in meaningful discourse about issues relating to the discipline. However, the limited number of virologists who teach undergraduates, combined with the fact that many institutions lack stand-alone virology courses, results in virology often being taught as a limited number of lectures within an undergraduate microbiology course (if it is covered at all), which may or may not be taught by an individual trained as a virologist. To provide a framework to teach virology to undergraduate students, a team of virology educators, with support from the American Society for Virology (ASV), developed curriculum guidelines for use in a stand-alone undergraduate virology course or a virology section within another course. These guidelines are available at the ASV website (https://asv.org/curriculum-guidelines/). To assist educators in implementing these guidelines, we created examples of measurable learning objectives. This perspective provides details about the virology curriculum guidelines and learning objectives and accompanies the perspective by Boury et al. in this issue of the Journal of Microbiology & Biology Education about the recent revision of the microbiology curriculum guidelines overseen by the American Society for Microbiology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Improving radiograph analysis throughput through transfer learning and object detection

SIGN Fracture Care International partners with surgeons in low-resource hospitals worldwide to provide access to effective orthopedic care by donating educational materials and innovatively designed surgical implants. Over two decades, SIGN’s Online Surgical Database (SOSD) has grown to contain over 500,000 medical images, with radiographs holding the majority share. One challenge in working with hospitals worldwide is that both the radiographs uploaded to the SOSD and the data entry accompanying the uploads vary in quality. To improve the accuracy of data in the SOSD, we trained a model to detect surgical implants in radiographs. We first developed a tool to automatically detect radiographs, then trained an object detection model to determine the number and placement of surgical implants visible in the radiograph. Active learning was used to generate a training set containing 2,510 radiographs with screws, nails, and plates labeled by bounding boxes. Training a model to simultaneously recognize all three classes of implants gave a low average precision (AP) for the plate class, likely due to the low number of plate instances in our training set and the large variety of surgical plates used by SIGN-partnered surgeons. Applying standard image augmentation techniques to increase the plate count in our training set did not appreciably increase the AP of plate detection. To improve plate detection, we redrew the bounding boxes to account for correlations between the screw and plate classes. Training one model to detect nails and screws and a separate model to detect plates increased the AP of plate detection by 78.8 percentage points. The AP of each class was 80.7% for screws, 93.6% for nails, and 92.6% for plates; meanwhile, the sensitivity was 92% for screws, 86% for nails, and 81% for plates. We show that object detection methods can be used to detect surgical implants in radiographs of varying quality; however, the detection ability is dependent on the type of implant, and some implants, in our case plates, must be treated differently than others. Such tools can improve the throughput of radiograph analysis, assisting physicians and surgeons with the treatment of bone fractures.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2012

Data Quality Objectives Supporting Radiological Air Emissions Monitoring for the Marine Sciences Laboratory, Sequim Site

This document of Data Quality Objectives (DQOs) was prepared based on the U.S. Environmental Protection Agency (EPA) Guidance on Systematic Planning Using the Data Quality Objectives Process, EPA, QA/G4, 2/2006 (EPA 2006), as well as several other published DQOs. The intent of this report is to determine the necessary steps required to ensure that radioactive emissions to the air from the Marine Sciences Laboratory (MSL) headquartered at the Pacific Northwest National Laboratory’s Sequim Marine Research Operations (Sequim Site) on Washington State’s Olympic Peninsula are managed in accordance with regulatory requirements and best practices. The Sequim Site was transitioned in October 2012 from private operation under Battelle Memorial Institute to an exclusive use contract with the U.S. Department of Energy, Office of Science, Pacific Northwest Site Office.

airborne emissions↗
DOE OSTI2015

Boosted Object, Phenomenology, Reconstruction and Searches (BOOST 2013) Workshop (Final Technical Report)

BOOST 2013 was the 5th International Joint Theory/Experiment Workshop on Phenomenology, Reconstruction and Searches for Boosted Objects in High Energy Hadron Collisions. It was locally organized and hosted by the Experimental High Energy Physics Group at the University of Arizona and held at Flagstaff, Arizona on August 12-16, 2013. The workshop provided a forum for theorists and experimentalists to present and discuss the latest findings related to the reconstruction of boosted objects in high energy hadron collisions and their use in searches for new physics. This report gives the outcomes of the BOOST 2013 Workshop.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

From Stars to Compact Objects: The Initial-Final Mass Relation

One of the key phases of stellar evolution that remains poorly understood is stellar death. We lack a predictive model for how a star of a given mass explodes and what kind of remnant it leaves behind (i.e. the initial-final mass relation, IFMR). Progress has been limited due to the difficulty in finding and weighing black holes and neutron stars in large numbers. Technological advances that allow for sub-milliarcsecond astrometry in crowded fields have opened a new window for finding black holes and neutron stars: astrometric gravitational lensing. Finding and weighing a sample of compact objects with astrometric microlensing will allow us to place some of the first constraints on the present-day mass function of isolated black holes and neutron stars, their multiplicity, and their kick velocities. All of these are fundamental inputs into understanding the death phase of stellar evolution, improving supernovae models, and interpreting LIGO detections in an astrophysical context. To achieve these goals, we require large area surveys, such as the WFIRST exoplanet microlensing survey, to photometrically identify long-duration (>120 day), un-blended microlensing events as candidate compact objects. We also require high-precision astrometric follow-up monitoring using extremely large telescopes, equipped with adaptive optics, such as TMT and GMT.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

RADIO-WEAK BL LAC OBJECTS IN THE FERMI ERA

The existence of “radio-weak BL Lac objects” (RWBLs) has been an open question, and has remained unsolved since the discovery that quasars could be radio-quiet or radio-loud. Recently, several groups identified RWBL candidates, mostly found while searching for low-energy counterparts of the unidentified or unassociated gamma-ray sources listed in the Fermi catalogs. Confirming RWBLs is a challenging task since they could be confused with white dwarfs (WDs) or weak emission line quasars (WELQs) when there are not sufficient data to precisely draw their broadband spectral energy distribution, and their classification is mainly based on a featureless optical spectra. Motivated by the recent discovery that Fermi BL Lacs appear to have very peculiar mid-IR emission, we show that it is possible to distinguish between WDs, WELQs, and BL Lacs using the [3.4]–[4.6]–[12] μ m color–color plot built using the WISE magnitudes when the optical spectrum is available. On the basis of this analysis, we identify WISE J064459.38+603131 and WISE J141046.00+740511.2 as the first two genuine RWBLs, both potentially associated with Fermi sources. Finally, to strengthen our identification of these objects as true RWBLs, we present multifrequency observations for these two candidates to show that their spectral behavior is indeed consistent with that of the BL Lac population.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Spectroscopy of 10 γ -Ray BL Lac Objects at High Redshift

We present optical spectra with high signal-to-noise ratio of 10 BL Lac objects detected at GeV energies by the Fermi satellite (3FGL catalog), which previous observations suggested are at relatively high redshift. The new observations, obtained at the 10 m Gran Telescopio Canarias, allowed us to find the redshift for J0814.5+2943 ( z = 0.703), and we can set a spectroscopic lower limit for J0008.0+4713 ( z > 1.659) and J1107.7+0222 ( z > 1.0735) on the basis of Mg ii intervening absorption features. In addition we confirm the redshifts for J0505.5+0416 ( z = 0.423) and J1450+5200 ( z > 2.470). Finally we contradict the previous z estimates for five objects (J0049.7+0237, J0243.5+7119, J0802.0+1005, J1109.4+2411, and J2116.1+3339).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Young Stellar Objects, Accretion Disks, and Their Variability with Rubin Observatory LSST

Vera C. Rubin Observatory, through the Legacy Survey of Space and Time (LSST), will allow us to derive a panchromatic view of variability in young stellar objects (YSOs) across all relevant timescales. Indeed, both short-term variability (on timescales of hours to days) and long-term variability (months to years), predominantly driven by the dynamics of accretion processes in disk-hosting YSOs, can be explored by taking advantage of the multiband filters option available in Rubin LSST, in particular the u, g, r, i filters that enable us to discriminate between photospheric stellar properties and accretion signatures. The homogeneity and depth of sky coverage that will be achieved with LSST will provide us with a unique opportunity to characterize the time evolution of disk accretion as a function of age and varying environmental conditions (e.g., field crowdedness, massive neighbors, metallicity) by targeting different star-forming regions. In this contribution to the Rubin LSST Survey Strategy Optimization Focus Issue, we discuss how implementing a dense observing cadence to explore short-term variability in YSOs represents a key complementary effort to the Wide–Fast–Deep observing mode that will be used to survey the sky over the full duration of the main survey (≈10 yr). The combination of these two modes will be vital to investigate the connection between the inner-disk dynamics and longer-term eruptive variability behaviors, such as those observed on EX Lupi–type objects.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

MarFS, a Near-POSIX Interface to Cloud Objects

The engineering forces driving development of “cloud” storage have produced resilient, cost-effective storage systems that can scale to 100s of petabytes, with good parallel access and bandwidth. These features would make a good match for the vast storage needs of High-Performance Computing datacenters, but cloud storage gains some of its capability from its use of HTTP-style Representational State Transfer (REST) semantics, whereas most large datacenters have legacy applications that rely on POSIX file-system semantics. MarFS is an open-source project at Los Alamos National Laboratory that allows us to present cloud-style object-storage as a scalable near-POSIX file system. We have also developed a new storage architecture to improve bandwidth and scalability beyond what’s available in commodity object stores, while retaining their resilience and economy. Additionally, we present a scheme for scaling the POSIX interface to allow billions of files in a single directory and trillions of files in total.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

MOFA: Multi-objective Flux Analysis for the COBRA Toolbox

Environments of biological organisms are frequently nutrient and energy limited. This necessitates that systems exert tight regulation of trade-offs among key biological processes. Quantitative knowledge of these tradeoffs is essential for successful manipulation of biosystems (e.g., metabolic engineering projects). Using genome-scale constraint-based models of metabolism (GSMs), Multi-Objective Flux Analysis (MOFA) allows analyses of trade-offs among a system’s key biological tasks. The leading software for conducting a variety of constraint-based analyses using GSMs is the COBRA Toolbox for MATLAB. Results: We have developed a new add-on tool for COBRA that performs MOFA for a number of objectives only limited by computation power.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Objective tropical cyclone extratropical transition detection in high-resolution reanalysis and climate model data

This paper describes an objective technique for detecting the extratropical transition (ET) of tropical cyclones (TCs) in high-resolution gridded climate data. The algorithm is based on previous observational studies using phase spaces to define the symmetry and vertical thermal structure of cyclones. Storm tracking is automated, allowing for direct analysis of climate data. Tracker performance in the North Atlantic is assessed using 23 years of data from the variable-resolution Community Atmosphere Model (CAM) at two different resolutions (DX 55 km and 28 km), the Climate Forecast System Reanalysis (CFSR, DX 38 km), and the ERA-Interim Reanalysis (ERA-I, DX 80 km). The mean spatiotemporal climatologies and seasonal cycles of objectively detected ET in the observationally constrained CFSR and ERA-I are well matched to previous observational studies, demonstrating the capability of the scheme to adequately find events. High resolution CAM reproduces TC and ET statistics that are in general agreement with reanalyses. One notable model bias, however, is significantly longer time between ET onset and ET completion in CAM, particularly for TCs that lose symmetry prior to developing a cold-core structure and becoming extratropical cyclones, demonstrating the capability of this method to expose model biases in simulated cyclones beyond the tropical phase.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Multi‐objective optimization for cost‐efficient and resilient machining under tool wear

Abstract With the onset and rapid growth of smart manufacturing, there is a constant increase in the demand for automation technologies to enhance productivity while providing uninterrupted, cost‐efficient, and resilient machining. Traditional manufacturing systems, however, suffer from several losses due to machine faults and degradation. Specifically, tool wear directly impacts the precision and quality of the milled parts, which causes an increase in the scrap production. Hence, more attempts are required to meet the desired quota of successful parts, which in turn results in wasted material, longer delays, further tool degradation, and higher energy, machining, and labor costs. As such, this paper develops a multi‐objective optimization framework to generate the optimal control set points (e.g., feed rate and width of cut) that minimize the total cost of machining operations resulting from multiple contradictory cost functions (e.g., material, energy, tardiness, machining, labor, and tool) in the presence of tool wear. Notably, we estimate the total expected cost in dollars, which provides automatic and intuitive weighting in this multi‐objective formulation. The optimization framework is tested on a high‐fidelity face milling model that has been validated on real data from industry. Results show significant dollar savings of up to as compared to the default control scheme.

Wilson, James P.↗
DOE OSTI2019

Polarization Amplitude-Based Method of Determining the Bearing and Roll Angles of an Object in Motion from Orthogonal Circularly Polarized Signals of a Radio Beacon

The possibility of determining the bearing and roll angles of an object in motion is investigated based on orthogonal left- and right-hand circularly polarized signals simultaneously radiated by a radio beacon from two points with the known coordinates spatially spaced in the horizontal plane. The bearing and roll angles are determined onboard the object in motion using a two-channel receiving system based on polarization amplitude-based processing of resultant vector signals received in a linear polarization basis.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Constructing the Pareto front for multi-objective Markov chains handling a strong Pareto policy approach

In this paper, we present a multi-objective solution of the Pareto front for a certain class of discrete-time ergodic controllable Markov chains. For solving the problem, we transform the original multi-objective problem into an equivalent nonlinear programming problem implementing the Lagrange principle. We then propose to adopt the Tikhonov’s regularization method to ensure the convergence of the cost functions to a unique point into the Pareto front. We show that Pareto policies are characterized as optimal policies. One of the fundamental problems related to the construction of the Pareto front is the existence and characterization of both, Pareto and strong Pareto policies. By introducing the Tikhonov’s regularizator, we ensure the existence of strong Pareto policies. This paper proposes a real solution to this problem. We formulate the original problem considering several constraints: (a) we employ the c-variable method for the introduction of linear constraints over the nonlinear problem and (b) restrict the cost functions, allowing points in the Pareto front to have a small distance from one another. The constraints imposed by the c-variable method make the problem computationally tractable and the restriction imposed by the small distance change ensures the continuation of the Pareto front. The resulting equation in this nonlinear system is an optimization problem for which the necessary and efficient condition of a minimum is solved using the projected gradient method. Moreover, we also prove the convergence conditions and compute the estimate rate of convergence of variables corresponding to the Lagrange principle and the Tikhonov’s regularization, respectively. We provide all the details needed to implement the proposed method in an efficient way. The usefulness of the method is successfully demonstrated by a numerical example.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

A new bi-objective periodic vehicle routing problem with maximization market share in an uncertain competitive environment

This paper presents a new variant of periodic vehicle routing problem in which the reaching time to the customers affects market share. Thus, there is a competition between distributors to achieve more market share by reaching the customers earlier than others; moreover, travel time between each two pairs of customers is uncertain. This situation is called an uncertain competitive environment. For the given problem, a new bi-objective mathematical model including minimization of total traveled time and maximization of the market share is presented. In order to solve this model, a multi-objective particle swarm (MOPSO) and local MOPSO algorithms are applied; and to evaluate the algorithm performance, some samples are generated; and the results of algorithms are compared based on some comparison metrics. The results demonstrate that the proposed LMOPSO algorithm leads to a better performance compared to the MOPSO in most comparison metrics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Bi-objective approaches for home healthcare medical team planning and scheduling problem

In this paper, we study the medical team planning and scheduling in home healthcare within a weekly horizon, including the planning of nursing visits and the daily traveling route scheduling. Two objectives are considered: the first one is to minimize the total operation cost of the healthcare agency and the second one is to maximize the patient satisfaction. The problem is formulated as a mixed integer program, to seek for a trade-off between two objectives, with the characteristics of the patient requirements including nursing types, nursing frequency and service length considered. Medical team types, available service days and overwork penalty are also respected in the model. Then an ϵ-constraint method is adopted to obtain exact non-dominated solutions. To address large-scale problem instances, three heuristic approaches are developed to generate approximate Pareto fronts in a reasonable time. The set of non-dominated solutions are valuable for decision-making. Computational experiments are conducted and the results demonstrate the efficiency of the approaches.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Rational RBF-based partition of unity method for efficiently and accurately approximating 3D objects

We consider the problem of reconstructing 3D objects via meshfree interpolation methods. In this framework, we usually deal with large data sets and thus develop an efficient local scheme via the well-known partition of unity method. The main contribution in this paper consists in constructing the local interpolants for the implicit interpolation by means of rational radial basis functions. Numerical experiments, devoted to test the accuracy of the scheme, confirm that the proposed method is particularly performing when 3D objects, or more in general implicit functions defined by scattered points, need to be approximated.

97 MATHEMATICS AND COMPUTING↗