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At least 595 records · Page 33

Profile-Drag Coefficients of Conventional and Low-Drag Airfoils as Obtained in Flight

Results of flight tests indicate that profile-drag coefficients which were obtained with the low-drag airfoils were lower than with the conventional types over the range of light coefficients tested. For comparable conditions of the lift coefficient and Reynolds Number, the low-drag airfoils have profile-drag coefficients which may be 27 percent lower than the profile drag of the conventional airfoils tested. Detailed results are presented graphically.

AIRFOILS - NAVY N-22 - CHARACTERISTICS↗

Transcriptional profiling reveals regulated genes in the hippocampus during memory formation

Transcriptional profiling (TP) offers a powerful approach to identify genes activated during memory formation and, by inference, the molecular pathways involved. Trace eyeblink conditioning is well suited for the study of regional gene expression because it requires the hippocampus, whereas the highly parallel task, delay conditioning, does not. First, we determined when gene expression was most regulated during trace conditioning. Rats were exposed to 200 trials per day of paired and unpaired stimuli each day for 4 days. Changes in gene expression were most apparent 24 h after exposure to 200 trials. Therefore, we profiled gene expression in the hippocampus 24 h after 200 trials of trace eyeblink conditioning, on multiple arrays using additional animals. Of 1,186 genes on the filter array, seven genes met the statistical criteria and were also validated by real-time polymerase chain reaction. These genes were growth hormone (GH), c-kit receptor tyrosine kinase (c-kit), glutamate receptor, metabotropic 5 (mGluR5), nerve growth factor-beta (NGF-beta), Jun oncogene (c-Jun), transmembrane receptor Unc5H1 (UNC5H1), and transmembrane receptor Unc5H2 (UNC5H2). All these genes, except for GH, were downregulated in response to trace conditioning. GH was upregulated; therefore, we also validated the downregulation of the GH inhibitor, somatostatin (SST), even though it just failed to meet criteria on the arrays. By during situ hybridization, GH was expressed throughout the cell layers of the hippocampus in response to trace conditioning. None of the genes regulated in trace eyeblink conditioning were similarly affected by delay conditioning, a task that does not require the hippocampus. These findings demonstrate that transcriptional profiling can exhibit a repertoire of genes sensitive to the formation of hippocampal-dependent associative memories.

Non-NASA Center↗

KSC 50-MHz Doppler Radar Wind Profiler (DRWP) Operational Acceptance Test (OAT) Report

This report documents analysis results of the Kennedy Space Center updated 50-MHz Doppler Radar Wind Profiler (DRWP) Operational Acceptance Test (OAT). This test was designed to demonstrate that the new DRWP operates in a similar manner to the previous DRWP for use as a situational awareness asset for mission operations at the Eastern Range to identify rapid changes in the wind environment that weather balloons cannot depict. Data examination and two analyses showed that the updated DRWP meets the specifications in the OAT test plan and performs at least as well as the previous DRWP. Data examination verified that the DRWP provides complete profiles every five minutes from 1.8-19.5 km in vertical increments of 150 m. Analysis of 5,426 wind component reports from 49 concurrent DRWP and balloon profiles presented root mean square (RMS) wind component differences around 2.0 m/s. The DRWP's effective vertical resolution (EVR) was found to be 300 m for both the westerly and southerly wind component, which the best EVR possible given the DRWP's vertical sampling interval. A third analysis quantified the sensitivity to rejecting data that do not have adequate signal by assessing the number of first-guess propagations at each altitude. This report documents the data, quality control procedures, methodology, and results of each analysis. It also shows that analysis of the updated DRWP produced results that were at least as good as the previous DRWP with proper rationale. The report recommends acceptance of the updated DRWP for situational awareness usage as per the OAT's intent.

Profiler↗

Estimating Uncertainties in the SBUV Version 8.6 Merged Profile Ozone Data Set

The combined record of total and profile ozone measurements from the solar backscatter ultraviolet (SBUV) and SBUV/2 series of instruments, known as the SBUV Merged Ozone Data (MOD) product, constitutes the longest satellite-based ozone time series from a single instrument type and as such plays a key role in ozone trend analyses. Following the approach documented in Frith et al. (2014) to analyze the merging uncertainties in the MOD total ozone record, we use Monte Carlo simulations to estimate the potential for uncertainties in the calibration and drift of individual instruments in the profile ozone merged data set. We focus our discussion on the trends and associated merging uncertainty since 2001 in an effort to verify the start of ozone recovery as predicted by chemistry climate models. We find that merging uncertainty dominates the overall estimated uncertainty when considering only the 15 years of data since 2001. We derive trends versus pressure level for the MOD data set that are positive in the upper stratosphere as expected for ozone recovery. These trends appear to be significant when only statistical uncertainties are included but become not significant at the 2o level when instrument uncertainties are accounted for. However, when we use the entire data set from 1979 through 2015 and fit to the EESC (equivalent effective stratospheric chlorine) we find statistically significant fits throughout the upper stratosphere at all latitudes. This implies that the ozone profile data remain consistent with our expectation that chlorine is the dominant ozone forcing term.

Ozone profile↗

(abstract) Steady State Temperature Profile in a Cylinder Heated by Microwaves

We have developed a new theory to calculate the steady state temperature profile in a cylindrical sample positioned along the entire axis of a cylindrical microwave cavity. Temperature profiles were computed for alumina rods of various radii excited by one of the TM0n0 modes with n = 1, 2, or 3. Sample surface and center temperatures will be presented as a function of total sample absorbed power or electric field strength at the sample surface. An approach for attaining more uniform heating within the sample by reducing the magnitude of the inverted temperature profile using a concentric outer cylindrical tube will be discussed.

microwave↗

Accuracies of Atmospheric Profiles Obtained from GPS Occultations

Radio occultation studies of the terrestrial atmosphere are possible through use of signals transmitted by satellites of the Global Positioning System (GPS) and received by one or more other satellites in low earth orbit (LEO). The perturbed phase of the occulted signal gives direct information on the refractivity profile in the region of occultation, from which vertical profiles of density, pressure, and temperature can be retrieved. Based on model simulations the capability of GPS to provide atmospheric profiles is assessed.

atmospheric↗

A Two-Step Time-Series Data Clustering Method for Building-Level Load Profile

Residential and commercial buildings have huge potential to contribute value to improve grid resilience by participating grid services. To reveal the significant value, it is critical to estimate the grid service capability from these buildings. Unlike the large-scale distributed energy resources such as wind and solar farms, those buildings need to participate grid services in aggregation, not by individual. Therefore, it is important to appropriately group buildings for aggregation. The load profiles in the same group will have similar characteristics at the same time step, so grid operators can send the grid service signal to the customer group with a higher chance to respond at that time step. In this paper, we develop a load profile clustering method to classify the building-level load profiles for grid service capability estimation and the results have proved the effectiveness of this method.

AMI↗

Early Battery Performance Prediction for Mixed Use Charging Profiles Using Hierarchal Machine Learning

A key step limiting how fast batteries can be deployed is the time necessary to provide evaluation and validation of performance. Using data analysis approaches, such as machine learning, the validation process can be accelerated. However, questions on the validity of projecting models trained on limited data or simple cycling profiles, such as constant current cycling, to real-world scenarios with complex loads remains. Here, we present the ability to predict performance with less than 1.2% mean absolute percent error when trained on cells aged using complex electric vehicle discharge profiles, and either AC Level 2 charge or DC Fast charge profiles, using only the first 45 cycles, namely 5% of the total testing time. While error is low across the projections, this study also highlights that battery lifetime analysis using only cycling data may not extrapolate safely to certain real-world conditions due to the impact of calendar degradation.

25 ENERGY STORAGE↗

Qualitative and quantitative profiles of jejunal oligosaccharides and cecal short–chain fatty acids in broiler chickens receiving different dietary levels of fiber, protein and exogenous enzymes

Dietary supplemental carbohydrases are able to degrade non-starch polysaccharides and generate oligosaccharides in the gastrointestinal tract. This study was conducted to investigate the influence of dietary fiber and protein levels on growth performance, nutrient utilization, digesta oligosaccharides profile and cecal short-chain fatty acid (SCFA) profile in broilers receiving diets supplemented with xylanase or protease individually or in combination. Enzyme supplementation had no effect on growth performance. There was significant (P < 0.05) fiber × protein × xylanase interaction for ileal nitrogen digestibility and significant (P < 0.01) protein × xylanase × protease interaction for nitrogen-corrected apparent metabolizable energy. Birds fed high-fiber diets had higher (P < 0.05) jejunal oligosaccharides and cecal SCFA concentrations. Xylanase and protease combination produced the greatest pentose (Pent) levels in low fiber–adequate protein diets but lowest levels in highfiber–low protein diets. There was significant (P < 0.05) fiber × xylanase × protease interaction explained by the digesta concentrations of (Pent) 3 , (Pent) 4 and (Pent) 5 being greatest (P < 0.5) in protease-only supplemented high-fiber diets but lowest in protease-only supplemented low-fiber diets. Furthermore, these results suggest that, of all the factors investigated, dietary fiber level had the greatest effect on modulating digesta concentration of oligosaccharides and cecal SCFA. Evidence points to the fact that there is considerable capacity for generating pentose oligosaccharides in the digestive tract of broilers receiving diets rich in fibrous feedstuffs, and that this may have a beneficial effect on microbial profile in the digestive tract.

59 BASIC BIOLOGICAL SCIENCES↗

Depth profiling and standardization from the back side of a sample for accurate analyses: Emphasis on quantifying low‐fluence, shallow implants in diamond‐like carbon

Rationale Back‐side thinning of wafers is used to eliminate issues with transient sputtering when analyzing near‐surface element distributions. Precise and accurate calibrated implants are created by including a standard reference material during the implantation. Combining these methods allows accurate analysis of low‐fluence, shallow features even if matrix effects are a concern. Methods Implanted Na (<2.0 × 10 11 ions/cm 2 , peaking <50 nm) in diamond‐like carbon (DLC) film on silicon (solar wind returned by NASA's Genesis mission) was prepared for measurement as follows. Implanted surfaces of samples were epoxied to wafers and back‐side‐thinned using physical or chemical methods. Thinned samples were then implanted with reference ions for accurate quantification of the solar wind implant. Analyses used a CAMECA IMS 7f‐GEO SIMS in depth‐profiling mode. Results Back‐side‐implanted reference ions reduced the need to change sample mounts or stage position and could be spatially separated from the solar wind implant even when measuring monoisotopic ions. Matrix effects in DLC were mitigated and the need to find an identical piece of DLC for a reference implant was eliminated. Accuracy was only limited by the back‐side technique itself. Conclusions Combining back‐side depth profiling with back‐side‐implanted internal standards aides quantification of shallow mono‐ and polyisotopic implants. This technique helps mitigate matrix effects and keeps measurement conditions consistent. Depth profile acquisition times are longer, but if sample matrices are homogeneous, procedural changes can decrease measurement times.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Solving the duck curve in a smart grid environment using a non-cooperative game theory and dynamic pricing profiles

With the intermittency that comes with electricity generation from renewables, utilizing dynamic pricing will encourage the demand-side to respond in a smart way that would minimize the electricity costs and flatten the net electricity demand curve. Determining the optimal dynamic pricing profile that would leverage distributed storage to flatten the curve is a novel idea that needs to be studied. Moreover, the economic feasibility of utilizing distributed electrical energy storage is still not given in the literature. Therefore, in this paper, a novel way of solving a citywide dynamic model using a bilevel programming algorithm is introduced. The problem is developed as a novel non-cooperative Stackelberg game that utilizes air-conditioning systems and electrical storage through the end-users to determine the optimal dynamic pricing profile. The results show that the combined effect of utilizing demand-side air-conditioning systems and distributed storage together can flatten the curve while employing the optimal dynamic pricing profile. An economic study is performed to determine the economic feasibility of 20 different cases with different battery designs and the level of solar penetration. Three metrics were used to evaluate the economic performance of each case: the levelized cost of storage, the levelized cost of energy, and the simple payback period. Most cases had levelized cost of storage values lower than 0.457 $/kWh, which is the lower bound available in the literature. Seven out of 16 cases have a simple payback period shorter than the lifetime of the system (25 years). The case with a 100 MW PV power plant and a battery storage of size 597 MWh, was found to be the most promising case with a simple payback period of 12.71 years for the photovoltaic plant and 19.86 years for the demand-side investments.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A deep redox proteome profiling workflow and its application to skeletal muscle of a Duchenne Muscular Dystrophy model

Perturbation to the redox state accompanies many diseases and its effects are viewed through oxidation of biomolecules, including proteins, lipids, and nucleic acids. The thiol groups of protein cysteine residues undergo an array of redox post-translational modifications (PTMs) that are important for regulation of protein and pathway function. To better understand what proteins are redox regulated following a perturbation, it is important to be able to comprehensively profile protein thiol oxidation at the proteome level. Herein, we report a deep redox proteome profiling workflow and demonstrate its application in measuring the changes in thiol oxidation along with global protein expression in skeletal muscle from mdx mice, a model of Duchenne Muscular Dystrophy (DMD). In depth coverage of the thiol proteome was achieved with >18,000 Cys sites from 5608 proteins in muscle being quantified. Compared to the control group, mdx mice exhibit markedly increased thiol oxidation, where ~2% shift in the median oxidation occupancy was observed. Further, pathway analysis for the redox data revealed that coagulation system and immune-related pathways were among the most susceptible to increased thiol oxidation in mdx mice, whereas protein abundance changes were more enriched in pathways associated with bioenergetics. This study illustrates the importance of deep redox profiling in gaining greater insight into oxidative stress regulation and pathways/processes that are perturbed in an oxidizing environment.

60 APPLIED LIFE SCIENCES↗

A temperature profile diagnostic for radiation waves on OMEGA-60

Predicting and matching radiation wave propagation with computational models has proven difficult. Information provided by experiments studying radiation flow has been limited when only radiation breakout is measured. We have developed the COAX (co-axial) diagnostic platform to provide spatial temperature profiles of a radiation wave through low density foams as a more detailed constraint for simulations. COAX uses a standard, laser-driven OMEGA-60 halfraum to drive radiation down a titanium-laden silicon oxide foam. Point-projection X-ray absorption spectroscopy perpendicular to the radiation flow measures the spatial profile of titanium ionization. The spectroscopic measurement utilizes a broadband capsule backlighter. Imaging and streak spectroscopy are used to characterize the size and spectrum of this source. Radiography provides an additional constraint by capturing the developing shock as the radiation flow becomes subsonic. The DANTE diagnostic is used to measure the halfraum temperature. Here, we provide a spectroscopic analysis of COAX data to determine temperature, and we describe experimental sources of uncertainty. The temperature is obtained by comparison to multi-temperature synthetic spectra post-processed from radiation-hydrodynamics simulations. Quantitative comparison between data and synthetic spectra generated from temperature profiles at relevant simulation times enable determination of a peak temperature of 114 ± 8 eV at 265 ± 22.4 μm from the halfraum. This represents an improvement over the temperature uncertainties of previous radiation flow experiments. Further refinements to the spectroscopic analysis could achieve ±4 eV. The combination between space-resolved spectroscopy and radiography enables us to determine the distance from the halfraum of both the radiation front and the shock front at the time of measurement. For the example shown in this paper the radiation front position is 600–630 μm at 3.43 ± 0.16 ns and the shock front position is 633 μm at 3.3 ± 0.24 ns.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

D retention and depth profile behavior for single crystal tungsten with high temperature neutron irradiation

Single crystalline W (tungsten) samples irradiated at 633, 963 and 1073 K by neutrons to a damage level of 0.1 dpa were exposed to a high-flux D (deuterium) plasma at 673, 873 and 973 K, respectively, in TPE (Tritium Plasma Experiment) at INL (Idaho National Laboratory). Deuterium desorption was analyzed by TDS (Thermal Desorption Spectroscopy), and D depth profiles were determined by NRA (Nuclear Reaction Analysis) at SNL (Sandia National Laboratories). HIDT (Hydrogen Isotope Diffusion and Trapping) simulation code was applied to evaluate D behavior for neutron-damaged W at higher temperature. The D retention at depths up to 3 f.tm for the neutron-damaged sample at 673 K was two orders of magnitude larger than that for undamaged tungsten, and its D desorption spectrum had a single broad stage at around 900 K. As the neutron irradiation/plasma exposure temperature increased, D retention was largely reduced, and the desorption temperature was increased to higher temperatures above 1100 K. The D depth profiles by NRA also showed D migration toward bulk by higher temperature irradiation, compared to undamaged W. The HIDT simulation indicated that the major binding energy of D was changed from 1.43 eV to 2.07 eV at higher neutron irradiation and plasma exposure temperatures, suggesting that some vacancies and small vacancy clusters would aggregate to form larger voids, or depopulation of weak traps at high D plasma exposure temperatures. It can be said that more stable trapping sites played dominant roles in the D retention at higher neutron irradiation and plasma exposure temperature. The binding energy by HIDT simulation was almost consistent with the reported value by TMAP, but the consideration of not only total D retention measured by TDS but also D depth profile by NRA led to the more accurate D behavior in neutron-damaged W.

36 MATERIALS SCIENCE↗

Space-charge effects in ionization beam profile monitors

Ionization profile monitors (IPMs) are widely used in accelerators for non-destructive and fast diagnostics of high energy particle beams. At high beam intensities, the space-charge forces make the measured IPM profiles significantly different from those of the beams. We analyze dynamics of the secondaries in IPMs and develop an effective algorithm to reconstruct the beam sizes from the measured IPM profiles. Efficiency of the developed theory is illustrated in application to the Fermilab 8 GeV proton Booster IPMs.

43 PARTICLE ACCELERATORS↗

Active microbial biomass decreases, but microbial growth potential remains similar across soil depth profiles under deeply-vs. shallow-rooted plants

Climate-smart land management practices that replace shallow-rooted annual crop systems with deeply-rooted perennial plants can contribute to soil carbon sequestration. However, deep soil carbon accrual may be influenced by active microbial biomass and their capacity to assimilate fresh carbon at depth. Incorporating active microbial biomass, dormancy, and growth in microbially-explicit models can improve our ability to predict soil's capacity to store carbon. But, so far, the microbial parameters that are needed for such modeling are poorly constrained, especially in deep soil layers. Here, we used a lab incubation experiment and growth kinetics model to estimate how microbial parameters vary along 240 cm of soil depth in profiles under shallow- (soy) and deeply-rooted (switchgrass) plants 11 years after plant cover conversion. We also assessed resource origin and availability (total organic carbon, 14 C, extractable organic carbon, specific UV absorbance of K 2 SO 4 extractable organic C, total nitrogen, total dissolved nitrogen) along the soil profiles to examine associations between soil chemical and biological parameters. Even though root biomass was greater and rooting depth was deeper under switchgrass than soy, resource availability and microbial growth parameters were generally similar between vegetation types. Instead, depth significantly influenced soil chemical and biological parameters. For example, resource availability and total and relative active microbial biomass decreased with soil depth. Decreases in the relative active microbial biomass coincided with increased lag time (response time to external carbon inputs) along the soil profiles. Even at a depth of 210–240 cm, microbial communities were activated to grow by added resources within a day. Maximum specific growth rate decreased to a depth of 90 cm and then remained consistent in deeper layers. Our findings show that >10 years of vegetation and rooting depth changes may not be long enough to alter microbial growth parameters, and suggest that at least a portion of the microbial community in deep soils can grow rapidly in response to added resources. Our study determined microbial growth parameters that can be used in microbially-explicit models to simulate carbon dynamics in deep soil layers.

14C↗

nmRanalysis: An Open-Source Web Application for Semi-automated NMR Metabolite Profiling

Though data acquisition and initial signal pre-processing of nuclear magnetic resonance (NMR) spectra have achieved high degrees of automation, downstream processing - specifically the profiling of spectra - has bottlenecked the overall NMR analysis workflow. Several efforts have been made to mitigate this bottleneck, but these solutions often trade an increase in automation for limitations elsewhere. Here, in this technical note, we introduce nmRanalysis, a user-friendly web-application that integrates the strengths of existing profiling tools for a more automated profiling workflow. nmRa-nalysis additionally incorporates novel features, including a machine-learning-driven recommender system for me-tabolite identification, further increasing the utility of nmRanalysis over the individual tools that it incorporates.

Flores, Javier E. [Pacific Northwest National Labo↗

Statistically Driven Metabolite and Lipid Profiling of Patients from the Undiagnosed Diseases Network

Advancements in molecular separations coupled with mass spectrometry have enabled large-scale metabolome analyses for clinical cohorts. A population of interest for metabolome profiling are patients with rare disease for which abnormal metabolic signatures may yield clues into the genetic bases, as well as mechanistic drivers of the disease and possible treatment options. We undertook the metabolome profiling of a large cohort of patients with mysterious conditions characterized through the Un-diagnosed Diseases Network (UDN). Due to the size and enrollment procedures, collection of the metabolomes for UDN pa-tients took place over three years. We describe the study design to adjust for measurements collected over a long time-scale and how this enabled statistical analyses to summarize the metabolome of individual patients. We demonstrate the removal of time-based batch effects, overall statistical characteristics of the UDN population, and two case-studies of interest that demonstrate the utility of metabolome profiling for rare diseases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗