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At least 1,621 records · Page 90

A Fully Integrated and Self-Powered Smartwatch for Continuous Sweat Glucose Monitoring

Wearable devices for health monitoring and fitness management have foreseen a rapidly expanding market, especially those for noninvasive and continuous measurements with real-time display that provide practical convenience and eliminated safety/infection risks. In this research, a self-powered and fully integrated smartwatch that consists of flexible photovoltaic cells and rechargeable batteries in the forms of a “watch strap”, electrochemical glucose sensors, customized circuits, and display units integrated into a “dial” platform is successfully fabricated for real-time and continuous monitoring of sweat glucose levels. The functionality of the smartwatch, including sweat glucose sensing, signal processing, and display, can be supported with the harvested/converted solar energy without external charging devices. The Zn-MnO 2 batteries serve as intermediate energy storage units and the utilization of aqueous electrolytes eliminated safety concerns for batteries, which is critical for wearable devices. Such a wearable system in a smartwatch fashion realizes integration of energy modules with self-powered capability, electrochemical sensors for noninvasive glucose monitoring, and in situ and real-time signal processing/display in a single platform for the first time. The as-fabricated fully integrated and self-powered smartwatch also provides a promising protocol for statistical study and clinical investigation to reveal correlations between sweat compositions and human body dynamics.

47 OTHER INSTRUMENTATION↗

Single-shot femtosecond laser-induced breakdown spectroscopy in low-density gases

Single-shot fs laser-induced breakdown spectroscopy (LIBS) has been used to interrogate low-density gases of H 2 ⁠, CH 4 ⁠, CO 2 ⁠, and H 2 O ranging from 0.5 × 10 15 to 9.1 × 10 15 cm −3 (15–275 mTorr). Strong spectral signatures were observed above the noise baseline for each test gas at all densities considered. Unique molecular signatures were observed for both CH 4 and CO 2 along with atomic features for each gas. The LIBS intensity response with respect to density was determined for each species using Voigt lineshape fitting or numerical integration. Finally, the collection and analysis of LIBS spectra of composite mixtures of CH 4 –CO 2 and CH 4 –H 2 demonstrates that the extraction of individual densities from gas mixtures is feasible at low densities.

Artificial neural networks↗

GEANT4 parameter tuning using Professor

The GEANT4 toolkit is used extensively in high energy physics to simulate the passage of particles through matter and to predict effects such as detector efficiencies and smearing. GEANT4 uses many underlying models to predict particle interaction kinematics, and uncertainty in these models leads to uncertainty in high energy physics measurements. The GEANT4 collaboration recently made free parameters in some models accessible through partnership with GEANT4 developers. We present a study of the impact of varying parameters in three GEANT4 hadronic physics models on agreement with thin target datasets and describe fits to these datasets using the Professor model tuning framework [1]. We find that varying parameters produces substantially better agreement with some datasets, but that more degrees of freedom are required for full agreement. This work is a first step towards a common framework for propagating uncertainties in GEANT4 models to high energy physics measurements, and we outline future work required to complete that goal.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

The ATLAS Fast TracKer system

The ATLAS Fast TracKer (FTK) was designed to provide full tracking for the ATLAS high-level trigger by using pattern recognition based on Associative Memory (AM) chips and fitting in high-speed field programmable gate arrays. The tracks found by the FTK are based on inputs from all modules of the pixel and silicon microstrip trackers. The as-built FTK system and components are described, as is the online software used to control them while running in the ATLAS data acquisition system. Also described is the simulation of the FTK hardware and the optimization of the AM pattern banks. An optimization for long-lived particles with large impact parameter values is included. A test of the FTK system with the data playback facility that allowed the FTK to be commissioned during the shutdown between Run 2 and Run 3 of the LHC is reported. The resulting tracks from part of the FTK system covering a limited $\eta$-$\phi$ region of the detector are compared with the output from the FTK simulation. It is shown that FTK performance is in good agreement with the simulation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Developing an Evolutionary Baseline Model for Humans: Jointly Inferring Purifying Selection with Population History

Building evolutionarily appropriate baseline models for natural populations is not only important for answering fundamental questions in population genetics—including quantifying the relative contributions of adaptive versus nonadaptive processes—but also essential for identifying candidate loci experiencing relatively rare and episodic forms of selection (e.g., positive or balancing selection). Here, a baseline model was developed for a human population of West African ancestry, the Yoruba, comprising processes constantly operating on the genome (i.e., purifying and background selection, population size changes, recombination rate heterogeneity, and gene conversion). Specifically, to perform joint inference of selective effects with demography, an approximate Bayesian approach was employed that utilizes the decay of background selection effects around functional elements, taking into account genomic architecture. This approach inferred a recent 6-fold population growth together with a distribution of fitness effects that is skewed towards effectively neutral mutations. Importantly, these results further suggest that, although strong and/or frequent recurrent positive selection is inconsistent with observed data, weak to moderate positive selection is consistent but unidentifiable if rare.

59 BASIC BIOLOGICAL SCIENCES↗

Quantitative Trade-Off in Distributed Secondary Control for Autonomous AC Microgrids

In this paper, we propose to quantify the trade-off between voltage regulation and reactive power sharing in autonomous AC microgrids with distributed secondary control. It is known that voltage regulation and reactive power sharing in droop-controlled autonomous AC microgrids are two conflicting control objectives that present a natural trade-off between voltage regulation towards the voltage magnitude reference and reactive power sharing accuracy. This trade-off is commonly shown qualitatively without sufficient quantification. In this work, to quantify the trade-off between the two objectives, we focus on distributed secondary control and utilize regression and polynomial surface fitting to identify the requisite parameter area to satisfy the predefined error bands for voltage magnitude regulation and reactive power sharing. Extensive case studies are presented to validate the proposed method.

autonomous AC microgrids↗

A Multi-Function AAA Algorithm Applied to Frequency Dependent Line Modeling

Modeling of power distribution system components that are valid for a wide range of frequencies are crucial for highly accurate modeling of electromagnetic transient (EMT) events. This has recently become of interest due to the improvements needed for the resilient operation of distribution systems. Vector fitting (VF) is a very popular and commonly used algorithm for wide band representations of power system components in EMT simulations. In this research, we present a new multi-input rational approximation algorithm (MIAAA) and illustrate its advantages with respect to VF using examples of approximations of admittance matrices discussed in the literature. We show that MIAAA not only outperforms VF in terms of achieving better accuracy using lesser number of poles, but also has no numerical issues achieving convergence. In contrast to VF, MIAAA is not sensitive to the location of input sample points and it does not require good estimates for the location of the desired approximation poles. The novelty of this research work is the use of recent mathematical results to solve existing challenges in distribution system modeling and to develop rational approximations for power system models that intend to be optimal in terms of accuracy and performance.

41 EE - Solar Energy Technologies Office (EE-4S)↗

Adaptation and Plasticity of Nannochloropsis sp. in Response to Seasonal and Geographic Climate Variation

Phytoplankton respond to their environment through genetic adaptation and plasticity to maintain fitness. This poses challenges when growing microalgae for industrial applications because, inherently, outdoor mass cultivation may lead to adaptations that alter desirable phenotypic traits and environmental niches. Here, we used common garden experiments to quantify the plasticity and adaptive responses to seasonal and geographic climate variation of Nannochloropsis, a microalga commonly used in biotechnology. An initially monoclonal strain was grown outdoors across four locations in Hawaii, Texas, California, and New Mexico. Following 17 and 22 months of cultivation outdoors, we collected samples during winter and summer, respectively, and we compared strains' growth from the four sites across temperature and light gradients in the laboratory. Despite hundreds of generations of exposure to divergent climates, with ~20°C and three-fold differences in daily light intensity, strains showed only minor differences in performance. Thermal performance varied more among seasons than sites, whereas light performance varied with both season and site. Our study indicates that Nannochloropsis exhibits broad plasticity in response to light and temperature, which may inhibit genetic adaptation in space or time. Highly variable field conditions, with daily and seasonal climate fluctuations, may favor plasticity and prevent the rapid adaptation often seen in laboratory studies of microorganisms in constant environments.

common garden experiment↗

Knock Intensity Distribution and a Stochastic Control Framework for Knock Control

One of the main factors limiting the efficiency of spark-ignited (SI) engines is the occurrence of engine knock. In high temperature and high pressure in-cylinder conditions, the fuel–air mixture auto-ignites creating pressure shock waves in the cylinder. Knock can significantly damage the engine and hinder its performance; as such, conservative knock control strategies are generally implemented which avoid such operating conditions at the cost of lower thermal efficiencies. Significant improvements in the performance of conventional knock controllers are possible if the properties of the knock process are better characterized and exploited in knock controller designs. One of the methods undertaken to better characterize knocking instances is to employ a probabilistic approach, in which the likelihood of knock is derived from the statistical distribution of knock intensity (KI). In this paper, it is shown that KI values at a fixed operating point for single fuel and dual fuel engines are accurately described using a mixed lognormal distribution. The fitting accuracy is compared against those for a randomly generated mixed-lognormally distributed dataset, and shown to exceed a 95% accuracy threshold for almost all of the operating points tested. Additionally, this paper discusses a stochastic knock control approach that leverages the mixed lognormal distribution to adjust spark timing based on KI measurements. Overall, this more informed knock control strategy would allow for improvements in engine performance and fuel efficiency by minimizing knock occurrences.

42 ENGINEERING↗

Assessment of Long Term Creep Using Strain Rate Matching From the Stepped Isostress Method

Creep testing is an ongoing need, particularly with the development of new candidate alloy systems for advanced energy systems. The conventional creep test (CT) is regarded as a proven method to gather creep data however, the test is impractical due to being real-time: lasting up to 105 hours to characterize the service of long-lived turbomachinery components. Accelerated methods to gather the long-term creep properties of materials are needed to reduce the time to qualification of new materials. The time-temperature-stress-superposition principle (TTSSP) and the derivative time-temperature superposition principle (TTSP), time-stress superposition principle (TSSP), stepped isothermal method (SIM), and stepped isostress method (SSM) are accelerated creep tests (ACT) commonly used to predict the long-term creep behaviors of polymers and composites. The TTSP and TSSP tests require multiple specimen tested at various temperatures/stresses whereas the SIM and SSM tests employ a single specimen where temperature/stress are periodically step increased until rupture. The stepped creep deformation curve can then be time and strain shifted to produce a master creep curve. While these ACTs are useful tools to predict long-term creep, the drawback is the lack of mathematical laws to determine the virtual start time and time shift factors, especially for different materials. In this paper, a new self-calibration approach is developed and compared to existing SSM data for Kevlar 49. This new approach focuses on matching the creep strain rates between stress steps and fitting the data to a master curve using a modified theta projection model. This is performed using a MATLAB code consisting of five subroutines. The first subroutine takes the stress, time, and creep strain from SSM/SIM tests, and segregates the data intro arrays corresponding to each stress level. The second subroutine finds the constants for the modified theta projection model for each stress level. The third subroutine performs a time shift adjustment using creep strain rate matching. The fourth subroutine calculates the accelerated time of rupture. The last subroutine generates accelerated creep versus time plots. Kevlar 49 SSM data is gathered from literature and run through the MATLAB code. The master curves generated from the MATLAB are compared to the conventional creep curve of Kevlar 49 as well as the master curve gathered from literature in order to validate the feasibility of this new approach. The goal of this project is to vet if the self-calibration approach can produce results similar to the reference calibration approach.

36 MATERIALS SCIENCE↗

Introductory guide to backgrounds in XPS spectra and their impact on determining peak intensities

Photoelectron and Auger peaks are central to most of the important uses of x-ray photoelectron spectroscopy (XPS), and thus, they receive the most attention in many types of analysis. Quantitative chemical analysis using XPS requires the assessment of the intensities of the photoemission peaks of the elements detected. Determination of peak intensities requires separation of the photoelectron peak signals from the background on which the peaks rest. For the determination of peak area intensities, the background is subtracted from overall signal intensity. The spectral background is also critical when peak fitting is used to determine intensities of overlapping peaks, and the model of background used in this process can impact the results. In addition to the impact on quantitative analysis, information about the depth distribution of elements in the near surface region can often be obtained by visual inspection of the background and quantified using appropriate modeling. Here, this introductory guide provides some basic information about backgrounds in the XPS analysis, describes the types of background models that are commonly used, suggests some of their strengths and weaknesses, and provides examples of their use and misuse. Although the fundamental nature of some components of the background signals in XPS is not understood, indicating that none of the models in use are fully correct and the area is subject to active research, appropriate good practices have been established for most routine analysis. The guide describes good practices, identifies errors that frequently appear in the literature, and uses examples to demonstrate the impacts of background selections on determinations of peak intensities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Developing a Continuous Nuclear Data Evaluation Method for the Resolved and Unresolved Resonance Regions With FITAPI and SAMMY [Poster]

SAMMY is an R-matrix Bayesian fitting program used in the analysis of nuclear cross section data. SAMMY produces separate cross section models in the resolved and unresolved resonance regions. This project develops a new method of continuous evaluation joining both energy regions with FITAPI. Full energy spectrum model introduces cross covariance between physics models allowing more accurate description of uncertainty. Consistency developed between physics models by the use of a unique set of prior parameters. An unresolved region cross section developed with sensitivity to resolved cross section. Incorporation into ORNL FITAPI provides access to greater number of parameter estimation algorithms.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Biofilm Interaction Mapping and Analysis (BIMA) of Interspecific Interactions in Pseudomonas Co-culture Biofilms

Pseudomonas species are ubiquitous in nature and include numerous medically, agriculturally and technologically beneficial strains of which the interspecific interactions are of great interest for biotechnologies. Specifically, co-cultures containing Pseudomonas stutzeri have been used for bioremediation, biocontrol, aquaculture management and wastewater denitrification. Furthermore, the use of P. stutzeri biofilms, in combination with consortia-based approaches, may offer advantages for these processes. Understanding the interspecific interaction within biofilm co-cultures or consortia provides a means for improvement of current technologies. However, the investigation of biofilm-based consortia has been limited. We present an adaptable and scalable method for the analysis of macroscopic interactions (colony morphology, inhibition, and invasion) between colony-forming bacterial strains using an automated printing method followed by analysis of the genes and metabolites involved in the interactions. Using Biofilm Interaction Mapping and Analysis (BIMA), these interactions were investigated between P. stutzeri strain RCH2, a denitrifier isolated from chromium (VI) contaminated soil, and 13 other species of pseudomonas isolated from non-contaminated soil. One interaction partner, Pseudomonas fluorescens N1B4 was selected for mutant fitness profiling of a DNA-barcoded mutant library; with this approach four genes of importance were identified and the effects on interactions were evaluated with deletion mutants and mass spectrometry based metabolomics.

59 BASIC BIOLOGICAL SCIENCES↗

Design of Novel Flash Ironmaking Reactors for Greatly Reduced Energy Consumption and CO2 Emissions

The development of a novel ironmaking technology based on fine iron ore concentrate in a flash reactor is summarized. The design of potential industrial reactors for flash ironmaking based on the computational fluid dynamics technique is described. Overall, this simulation work has shown that the size of the reactor used in the novel flash ironmaking technology (FIT) can be quite reasonable vis-à-vis the blast furnaces. A flash reactor of 12 m diameter and 35 m height with a single burner operating at atmospheric pressure would produce 1.0 million tons of iron per year. The height can be further reduced by either using multiple burners, preheating the feed gas, or both. The computational fluid dynamics (CFD)-based design of potential industrial reactors for flash ironmaking pointed to a number of features that should be incorporated. The flow field should be designed in such a way that a larger portion of the reactor is used for the reduction reaction but at the same time excessive collision of particles with the wall must be avoided. Further, a large diameter-to-height ratio that still allows a high reduction degree should be used from the viewpoint of decreased heat loss. This may require the incorporation of multiple burners and solid feeding ports.

36 MATERIALS SCIENCE↗

Orbits and Masses of Binaries from Speckle Interferometry at SOAR

We present results from Speckle inteferometric observations of 15 visual binaries and one double-line spectroscopic binary, carried out with the HRCam Speckle camera of the SOAR 4.1 m telescope. These systems were observed as a part of an on-going survey to characterize the binary population in the solar vicinity, out to a distance of 250 pc. We obtained orbital elements and mass sums for our sample of visual binaries. The orbits were computed using a Markov Chain Monte Carlo algorithm that delivers maximum likelihood estimates of the parameters, as well as posterior probability density functions that allow us to evaluate their uncertainty. Their periods cover a range from 5 yr to more than 500 yr; and their spectral types go from early A to mid M, implying total system masses from slightly more than 4M{sub ⊙} down to 0.2M {sub ⊙}. They are located at distances between approximately 12 and 200 pc, mostly at low Galactic latitude. For the double-line spectroscopic binary YSC8, we present the first combined astrometric/radial-velocity orbit resulting from a self-consistent fit, leading to individual component masses of 0.897 ± 0.027 M {sub ⊙} and 0.857 ± 0.026 M {sub ⊙}; and an orbital parallax of 26.61 ± 0.29 mas, which compares very well with the Gaia DR2 trigonometric parallax (26.55 ± 0.27 mas). In combination with published photometry and trigonometric parallaxes, we place our objects on an H-R diagram and discuss their evolutionary status. We also present a thorough analysis of the precision and consistency of the photometry available for them.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Functional Principal Component Analysis of Radio–Optical Reference Frame Tie

The Gaia optical reference frame is intrinsically undefined with respect to global orientation and spin, so it needs to be anchored in the radio-based International Celestial Reference Frame (ICRF) to provide a referenced and quasi-inertial celestial coordinate system. The link between the two fundamental frames is realized through two samples of distant extragalactic sources, mostly active galactic nuclei and quasars, but only the smaller sample of radio-loud ICRF sources with optical counterparts is available to determine the mutual orientation. The robustness of this link can be mathematically formulated in the framework of functional principal component analysis using a set of vector spherical harmonics to represent the differences in celestial positions of the common objects. The weakest eigenvectors are computed, which describe the greatest deficiency of the link. The deficient or poorly determined terms are specific vector fields on the sphere that carry the largest errors of absolute astrometry using Gaia in reference to the ICRF. This analysis provides guidelines for the future development of the ICRF maximizing the accuracy of the link over the entire celestial sphere. A measure of the robustness of a least-squares solution, which can be applied to any linear model fitting problem, is introduced to help discriminate between reference frame tie models of different degrees.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A Multi-Function AAA Algorithm Applied to Frequency-Dependent Line Modeling: Preprint

We present a new multi-input rational approximation algorithm (MIAAA) and illustrate its advantages respect to the popular Vector Fitting (VF) algorithm using examples of approximations of admittance matrices discussed in a very recent paper and by the creators of VF. We show that not only MIAAA outperforms VF in terms of achieving better accuracy using a smaller number of poles, but also has no numerical issues to achieve convergence. In contrast to VF, MIAA is not sensitive to the location of input sample points and it does not require good estimates for the location of the desired approximation poles.

97 MATHEMATICS AND COMPUTING↗

A MIMO AAA Agorithm for Frequency Dependent Line Modeling

Modeling of power distribution system components that are valid for a wide range of frequencies are crucial for highly accurate modeling of electromagnetic transient (EMT) events. This has recently become of interest due to the improvements needed for the resilient operation of distribution systems. Vector fitting (VF) is a very popular and commonly used algorithm for wide band representations of power system components in EMT simulations. In this research, we present a new multi-input rational approximation algorithm (MIAAA) and illustrate its advantages with respect to VF using examples of approximations of admittance matrices discussed in the literature. We show that MIAAA not only outperforms VF in terms of achieving better accuracy using lesser number of poles, but also has no numerical issues achieving convergence. In contrast to VF, MIAAA is not sensitive to the location of input sample points and it does not require good estimates for the location of the desired approximation poles. The novelty of this research work is the use of recent mathematical results to solve existing challenges in distribution system modeling and to develop rational approximations for power system models that intend to be optimal in terms of accuracy and performance.

AAA algorithm↗