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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records

EnCache: A Dynamic Profiling Based Reconfiguration Technique for Improving Cache Energy Efficiency

With each CMOS technology generation, leakage energy consumption has been dramatically increasing and hence, managing leakage power consumption of large last-level caches (LLCs) has become a critical issue in modern processor design. In this paper, we present EnCache, a novel software-based technique which uses dynamic profiling-based cache reconfiguration for saving cache leakage energy. EnCache uses a simple hardware component called profiling cache, which dynamically predicts energy efficiency of an application for 32 possible cache configurations. Using these estimates, system software reconfigures the cache to the most energy efficient configuration. EnCache uses dynamic cache reconfiguration and hence, it does not require offline profiling or tuning the parameter for each application. Furthermore, EnCache optimizes directly for the overall memory subsystem (LLC and main memory) energy efficiency instead of the LLC energy efficiency alone. The experiments performed with an x86-64 simulator and workloads from SPEC2006 suite confirm that EnCache provides larger energy saving than a conventional energy saving scheme. For single core and dual-core system configurations, the average savings in memory subsystem energy over a shared baseline configuration are 30.0% and 27.3%, respectively.

Cache Energy Saving↗

Dynamic Profiling of β-Coronavirus 3CL Mpro Protease Ligand-Binding Sites

β-coronavirus (CoVs) alone has been responsible for three major global outbreaks in the 21st century. The current crisis has led to an urgent requirement to develop therapeutics. Even though a number of vaccines are available, alternative strategies targeting essential viral components are required as a backup against the emergence of lethal viral variants. One such target is the main protease (Mpro) that plays an indispensable role in viral replication. The availability of over 270 Mpro X-ray structures in complex with inhibitors provides unique insights into ligand–protein interactions. Herein, we provide a comprehensive comparison of all nonredundant ligand-binding sites available for SARS-CoV2, SARS-CoV, and MERS-CoV Mpro. Extensive adaptive sampling has been used to investigate structural conservation of ligand-binding sites using Markov state models (MSMs) and compare conformational dynamics employing convolutional variational auto-encoder-based deep learning. Our results indicate that not all ligand-binding sites are dynamically conserved despite high sequence and structural conservation across β-CoV homologs. This highlights the complexity in targeting all three Mpro enzymes with a single pan inhibitor.

59 BASIC BIOLOGICAL SCIENCES↗

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↗

Experimental Study of TCP Throughput Profiles and Dynamics Over Dedicated Connections

A throughput profile expressed as a function of the round-trip times of a data transport infrastructure is a critical indicator of its level of optimization, particularly, over dedicated connections. We study the throughput profiles of eleven TCP versions using measurements collected over dedicated hardware-emulated connections with distances spanning round the earth. Among them, BBR has overall higher temporal variations and lower throughput profiles compared to five loss-based TCP versions, and the comparison with other TCP versions is mixed. Using the Poincare map regions of throughput time traces, we show that the richer dynamics of BBR are correlated with its lower throughput profiles. We present basic analytical results that indicate that higher temporal variations of TCP methods lead to lower throughput profiles, thereby establishing the underlying causality. Under external losses, BBR achieves sustained high throughput compared to others as the loss rate is increased. Overall, our results provide insights into the relationship between time dynamics and throughput profiles of TCP versions, in particular, show that limited time traces can be indicative of global properties of throughput profiles.

Rao, Nageswara↗

Dynamic proteomic profiling of a unicellular cyanobacterium Cyanothece ATCC51142 across light-dark diurnal cycles

Unicellular cyanobacteria of the genus Cyanothece are recognized for their ability to execute nitrogen (N2)-fixation in the dark and photosynthesis in the light. Systems-wide dynamic proteomic profiling with mass spectrometry (MS) analysis reveals fundamental insights into the control and regulation of these functions. To expand upon the current knowledge of protein expression patterns in Cyanothece ATCC51142, we performed quantitative proteomic analysis using partial ("unsaturated") metabolic labeling and high mass accuracy LC-MS analysis. This dynamic proteomic profiling identified 721 actively synthesized proteins with significant temporal changes in expression throughout the light-dark cycles, of which 425 proteins matched with previously characterized cycling transcripts. The remaining 296 proteins contained a cluster of proteins uniquely involved in DNA replication and repair, protein degradation, tRNA synthesis and modification, transport and binding, and regulatory functions. Analysis of protein functions revealed that the expression of nitrogenase in the dark is mediated by higher respiration and glycogen metabolism. We have also shown that Cyanothece ATCC51142 utilizes alternative pathways for carbon (C) and nitrogen (N) acquisition, particularly, aspartic acid and glutamate as substrates of C and N, respectively. Utilization of phosphoketolase (PHK) pathway for the conversion of xylulose-5P to pyruvate and acetyl-P likely constitutes an alternative strategy to compensate higher ATP and NADPH demand. In conclusion, this study provides a deeper insight into how Cyanothece ATCC51142 modulates cellular functions to accommodate photosynthesis and N2-fixation within the single cell.

59 BASIC BIOLOGICAL SCIENCES↗

Density profile of dynamical halos

Among the most fundamental properties of a dark matter halo is its density profile. Motivated by the recent proposal by García et al . [Mon. Not. R. Astron. Soc. 521 , 2464 (2023)] to define a dynamical halo as the collection of orbiting particles in a gravitationally bound structure, we characterize the mean and scatter of the orbiting profile of dynamical halos as a function of their orbiting mass. Here, we demonstrate that the orbiting profile of individual halos at fixed mass depends on a single dynamical variable, the halo radius 𝑟 h , which characterizes the spatial extent of the profile. The scatter in halo radius at fixed orbiting mass is ≈16%. Only a small fraction of this scatter arises due to differences in halo formation time, with late-forming halos being more compact (smaller halo radii). Accounting for this additional correlation results in an ≈11% scatter in halo radius at fixed mass and halo formation time.

79 ASTRONOMY AND ASTROPHYSICS↗

Talbot-Lau X-Ray Deflectometry for Dynamic Density Profile Measurements

X-ray phase contrast imaging with transmission gratings for density profile measurements is being developed for dynamic experimental applications. Talbot-Lau deflectometry is a new method of measuring x-ray refraction in addition to attenuation and ultra-small angle scattering that has recently been developed for static imaging, primarily for medical and industrial applications. A flash x-ray source, with a spot size much larger than the continuous microfocus sources of static imaging systems, must be used to obtain density profiles from fast-evolving systems, and only a single exposure can be obtained. These new challenges are addressed by introducing an asymmetric setup and developing a forward modeling technique to infer an electron density profile from a single-image, low spatial–resolution system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Real-time observation of toroidal current redistributions induced by three-dimensional MHD phenomena triggering vertical displacement events in tokamak plasmas

Three-dimensional MHD instabilities, including edge-localized modes (ELMs) and internal reconnection events (IREs), have been observed to precipitate loss of vertical stability in tokamak plasmas, resulting in vertical displacement events (VDEs). This vertical destabilization can occur due to toroidal current redistributions and/or shape changes resulting from these phenomena. Using a recently introduced method for rapidly reconstructing the two-dimensional toroidal plasma current density profile in real-time, results are presented that demonstrate the specific current distribution changes that occur during ELMs (on KSTAR) and IREs (on MAST-U) that lead to loss of vertical control. The method most efficiently reconstructs the toroidal current density profile by doing so on a basis of principal components of historical profiles. These principal components isolate dominant current profile dynamics, improving interpretability, increasing speed, and reducing dimensionality of the profile computation. On KSTAR, this computation is executed in the real-time plasma control system at a rate of 10 kHz (limited by available CPU cycle times), allowing the current profile evolution to be assessed at several times over the course of each ELM event. Further, by incorporating the reconstructions into a novel vertical stability metric, the contribution of specific current profile dynamics to the loss of vertical stability can be assessed in real-time for VDE avoidance and improved understanding of the causal relationship between three-dimensional MHD phenomena and VDEs. The success of this method in approximating toroidal current density profiles from kinetic equilibrium reconstructions is also presented ($R^2=0.990$), along with its capability to produce other equilibrium quantities of interest in real-time at high time resolution.

edge-localized modes↗

Measurement-based performance profiles and dynamics of UDT over dedicated connections

Wide-area data transfers in high-performance computing and big data scenarios are increasingly being carried over dedicated network connections that provide high capacities at low loss rates. UDP-based transport protocols are expected to be particularly well-suited for such transfers but their performance is relatively unexplored over a wide range of connection lengths, compared to TCP over shared connections. We present extensive throughput measurements of UDP-based Data Transfer (UDT) over a suite of physical and emulated 10 Gbps connections. In sharp contrast to current UDT analytical models, these measurements indicate much more complex throughput dynamics that are sensitive to the connection modality, protocol parameters, and round-trip times. Lyapunov exponents estimated from the Poincare maps of UDT traces clearly indicate regions of instability and complex dynamics. We propose a simple model based on the ramp-up and sustainment regimes of a generic transport protocol, which qualitatively illustrates the dominant monotonicity and concavity properties of throughput profiles and relates them to Lyapunov exponents. These measurements and analytical results together enable us to comprehensively evaluate UDT performance and select parameters to achieve high throughput, and they also provide guidelines for designing effective transport protocols for dedicated connections.

Foster, Ian↗

Characterizing Ion Profiles in Dynamic Junction Light-Emitting Electrochemical Cells

Organic semiconductors have the unique ability to conduct both ionic and electronic charge carriers in thin films, an emerging advantage in applications such as light-emitting devices, transistors, and electrochromic devices, among others. Evidence suggests that the profiles of ions and electrochemical doping in the polymer film during operation significantly impact the performance and stability of the device. However, few studies have directly characterized ion profiles within LECs. Here, we present profiles of ion distributions in LECs following application of voltage, via time-of-flight secondary ion mass spectrometry. Ion distributions were characterized with regard to film thickness, salt concentration, applied voltage, and relaxation over time. Results provide insight into the correlation between ion profiles and device performance, as well as potential approaches to tuning electrochemical doping processes in LECs.

Environmental Molecular Sciences Laboratory↗

Health impact assessment of air pollution using a dynamic exposure profile: Implications for exposure and health impact estimates

In both ambient air pollution epidemiology and health impact assessment an accurate assessment of the population exposure is crucial. Although considerable advances have been made in assessing human exposure outdoors, the assessments often do not consider the impact of individual travel behavior on such exposures. Population-based exposures to NO{sub 2} and O{sub 3} using only home addresses were compared with models that integrate all time-activity patterns-including time in commute-for Flanders and Brussels. The exposure estimates were used to estimate the air pollution impact on years of life lost due to respiratory mortality. Health impact of NO{sub 2} using an exposure that integrates time-activity information was on average 1.2% higher than when assuming that people are always at their home address. For ozone the overall estimated health impact was 0.8% lower. Local differences could be much larger, with estimates that differ up to 12% from the exposure using residential addresses only. Depending on age and gender, deviations from the population average were seen. Our results showed modest differences on a regional level. At the local level, however, time-activity patterns indicated larger differences in exposure and health impact estimates, mainly for people living in more rural areas. These results suggest that for local analyses the dynamic approach can contribute to an improved assessment of the health impact of various types of pollution and to the understanding of exposure differences between population groups. - Highlights: Black-Right-Pointing-Pointer Exposure to ambient air pollution was assessed integrating population mobility. Black-Right-Pointing-Pointer This dynamic exposure was integrated into a health impact assessment. Black-Right-Pointing-Pointer Differences between the dynamic and residential exposure were quantified. Black-Right-Pointing-Pointer Modest differences in health impact were found at a regional level. Black-Right-Pointing-Pointer At municipal level larger differences were found, influenced by gender and age.

54 ENVIRONMENTAL SCIENCES↗

Dynamic Vertical Profiles of Peat Porewater Chemistry in a Northern Peatland

We measured pH, cations, nutrients, and total organic carbon (TOC) over 3 years to examine weekly to monthly variability in porewater chemistry depth profiles (0–3.0 m) in an ombrotrophic bog in Minnesota, USA. We also compared temporal variation at one location to spatial variation in depth profiles at 16 locations across the bog. Most solutes exhibited large gradients with depth. pH increased by two units and calcium concentrations increased over 20 fold with depth, and may reflect peatland development from minerotrophic to ombrotrophic conditions. Ammonium concentrations increased almost 20 fold and TOC concentrations decreased by half with depth, and these patterns likely reflect mineralization of peat or decomposition of TOC. There was also considerable temporal variation in the porewater chemistry depth profiles. Ammonium, soluble reactive phosphorus, and potassium showed greater temporal variation in near-surface porewater, while pH, calcium, and TOC varied more at depth. This variation demonstrates that deep peat porewater chemistry is not static. Lastly, temporal variation in solute chemistry depth profiles was greater than spatial variation in several instances, especially in shallow porewaters. In conclusion, characterizing both temporal and spatial variability is necessary to ensure representative sampling in peatlands, especially when calculating solute pools and fluxes and parameterizing process-based models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dynamic transcriptome profiling of Bean Common Mosaic Virus (BCMV) infection in Common Bean ( Phaseolus vulgaris L.)

Background: Bean common mosaic virus (BCMV) is widespread, with Phaseolus species as the primary host plants. Numerous BCMV strains have been identified on the basis of a panel of bean varieties that distinguish the pathogenicity types with respect to the viral strains. The molecular responses in Phaseolus to BCMV infection have not yet been well characterized. Results: We report the transcriptional responses of a widely susceptible variety of common bean ( Phaseolus vulgaris L., cultivar ‘Stringless green refugee’) to two BCMV strains, in a time-course experiment. We also report the genome sequence of a previously unreported BCMV strain. The interaction with the known strain NL1-Iowa causes moderate symptoms and large transcriptional responses, and the newly identified strain (Strain 2 or S2) causes severe symptoms and moderate transcriptional responses. The transcriptional profiles of host plants infected with the two isolates are distinct, and involve numerous differences in splice forms in particular genes, and pathway specific expression patterns. Conclusions: We identified differential host transcriptome response after infection of two different strains of Bean common mosaic virus (BCMV) in common bean ( Phaseolus vulgaris L.). Virus infection initiated a suite of changes in gene expression level and patterns in the host plants. Pathways related to defense, gene regulation, metabolic processes, photosynthesis were specifically altered after virus infection. Results presented in this study can increase the understanding of host-pathogen interactions and provide resources for further investigations of the biological mechanisms in BCMV infection and defense.

59 BASIC BIOLOGICAL SCIENCES↗