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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A Parameterization of the Cloud Scattering Polarization Signal Derived From GPM Observations for Microwave Fast Radative Transfer Models

Microwave cloud polarized observations have shown the potential to improve precipitation retrievals since they are linked to the orientation and shape of ice habits. Stratiform clouds show larger brightness temperature (TB) polarization differences (PDs), defined as the vertically polarized TB (TBV) minus the horizontally polarized TB (TBH), with ~10 K PD values at 89 GHz due to the presence of horizontally aligned snowflakes, while convective regions show smaller PD signals, as graupel and/or hail in the updraft tend to become randomly oriented. The launch of the global precipitation measurement (GPM) microwave imager (GMI) has extended the availability of microwave polarized observations to higher frequencies (166 GHz) in the tropics and midlatitudes, previously only available up to 89 GHz. This study analyzes one year of GMI observations to explore further the previously reported stable relationship between the PD and the observed TBs at 89 and 166 GHz, respectively. The latitudinal and seasonal variability is analyzed to propose a cloud scattering polarization parameterization of the PD-TB relationship, capable of reconstructing the PD signal from simulated TBs. Given that operational radiative transfer (RT) models do not currently simulate the cloud polarized signals, this is an alternative and simple solution to exploit the large number of cloud polarized observations available. Finally, the atmospheric radiative transfer simulator (ARTS) is coupled with the weather research and forecasting (WRF) model, in order to apply the proposed parameterization to the RT simulated TBs and hence infer the corresponding PD values, which show to reproduce the observed GMI PDs well.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Unbundling Smart Meter Services Through Spatio-Temporal Decomposition Agents in DER-rich Environment

Smart meters and the advanced metering infrastructure (AMI) facilitate distribution system operators (DSOs) to gather information on energy consumption at the customer level. With the increasing penetration of building-level intermittent distributed energy resources (DERs) behind the meter, DER information is not available to DSOs. At the same time, smart meter enables users to participate in grid, with real-time information. Information for behind the meter is needed by user to coordinate building level assets for maximum benefits. The concept of unbundled smart meter (USM) needs agents to decompose smart meter measurements to provide service to DSO as well as customers. In this paper, we propose a Spatio-Temporal Decomposition Agent (STDA) for USM based on Artificial Intelligence (AI). STDA can help users optimize their energy usage, help DSO to utilize building assets for the grid operation. The energy usage strategy developed by STDA is suitable for different users, and can be customized by deep learning (DL) models according to the different energy consumption habits of each user. The power prediction performance results of various DL models and evaluation using a set of data from a Hawaii utility is presented. Furthermore, STDA integration with Home Energy management Systems (HEMS) to manage resources is presented and validated. STDA pre-processes the measurements before model training, and provides the spatio-temporal decomposed forecasting.

42 ENGINEERING↗
DOE OSTI2023

Imprint of tree species mycorrhizal association on microbial‐mediated enzyme activity and stoichiometry

Abstract Understanding the effects of tree species and their mycorrhizal association on soil processes is critical for predicting the ecosystem consequences of species shifts owing to global change and forest management decisions. While it is well established that forests dominated by different mycorrhizal types can vary in how they cycle carbon (C), nitrogen (N) and phosphorus (P), the degree to which these patterns are driven by microbial‐mediated enzyme activity (EA) and ecoenzymatic stoichiometry (ES) remains elusive. Here, we synthesized the effects of mycorrhizal association on seven soil enzymes involved in microbial C, N and P acquisition and ES using data from 56 peer‐reviewed papers. We found that relative to soil in ectomycorrhizal (EcM) trees, soil in arbuscular mycorrhizal (AM) trees exhibited greater activity of some C acquisition enzymes (e.g. beta‐glucosidase; BG) and higher ecoenzymatic ratios of BG/NAG (N‐acetyl‐glucosaminidase) and BG/AP (acid phosphatase). These results supported that AM trees had rapid C and nutrient turnover rates, inorganic nutrient economics and high soil microbial C limitation. We also found evidence for an organic nutrient economy and greater soil microbial demand for nutrients in EcM trees compared to AM trees. In addition, the effect of mycorrhizal association on the activity of certain soil enzymes and enzymatic stoichiometry (i.e. BG and BG/NAG ratio) appeared to be associated with the differences in soil pH, phylogenetic group (i.e. conifers and broadleaves) and leaf habit (i.e. evergreen and deciduous) between AM and EcM trees. The results from the global meta‐analysis suggested that soil EA and ES appear to play critical roles in shaping the differences in the nutrient economy between AM and EcM tree species, but leaf morphology and soil conditions should be considered in evaluations of soil processes in forests of different mycorrhizal associations. Given that most of the studies in the database were from the temperate and subtropical regions, further research in other biomes is needed to elucidate the underlying mechanisms driving the mycorrhizal effect at the global scale. Read the free Plain Language Summary for this article on the Journal blog.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Conditional filamentation as an adaptive trait of bacteria and its ecological significance in soils

Bacteria can regulate cell morphology in response to environmental conditions, altering their physiological and metabolic characteristics to improve survival. Conditional filamentation, in which cells suspend division while continuing lateral growth, is a strategy with a range of adaptive benefits. Here, we review the causes and consequences of conditional filamentation with respect to bacterial physiology, ecology and evolution. We describe four major benefits from conditional filamentation: stress tolerance, surface colonization, gradient spanning and the facilitation of biotic interactions. Adopting a filamentous growth habit involves fitness trade-offs which are also examined. We focus on the role of conditional filamentation in soil habitats, where filamentous morphotypes are highly prevalent and where environmental heterogeneity can benefit a conditional response. Here, to illustrate the use of information presented in our review, we tested the conditions regulating filamentation by the forest soil isolate Paraburkholderia elongata 5N T . Filamentation by P. elongata was induced at elevated phosphate concentrations, and was associated with the accumulation of intracellular polyphosphate, highlighting the role of filamentation in a phosphate-solubilizing bacterium. Conditional filamentation enables bacteria to optimize their growth and metabolism in environments that are highly variable, a trait that can impact succession, symbioses, and biogeochemistry in soil environments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

On the use of air temperature and precipitation as surrogate predictors in soil respiration modelling

Soil respiration (R S ), the soil-to-atmosphere CO 2 flux that is a major component of the global carbon cycle, is strongly influenced by local soil temperature (T soil ) and water content (SWC). Regional to global-scale R S modelling thus requires this information at local scales, but few high-quality, wall-to-wall (global) T soil and SWC data exist. As a result, such modelling efforts commonly use air temperature (T air ) and monthly precipitation (P m ) as surrogate predictors, but their site-scale accuracy and potential bias are unknown. In this report we used monthly data from 880 sites across a wide variety of different environmental conditions (i.e., climate, ecosystem type, elevation, vegetation leaf habit and drainage conditions) to determine the suitability of T air as a surrogate for T soil , and data from 507 sites to examine the suitability of P m as a surrogate for SWC. Site-specific linear and second-order exponential non-linear models were compared using model evaluation metrics (i.e., slope, p-value of slope, root mean square error [RMSE], index of agreement and model efficiency). We found that T soil and T air are highly correlated and explain similar R S variability. In contrast, P m is not a good surrogate for SWC, even though P m explains a similar amount of R S variability to SWC. The wide variability in the site-specific relationships between R S and SWC means that no single relationship can be used for large-scale modelling. The results from this study support the use of T air in continental-to-global scale R S models, and highlight the urgent need for continental-to-global scale SWC datasets for the modelling and evaluation of future soil carbon dynamics under global climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Pith–specific lignification in Nicotiana attenuata as a defense against a stem–boring herbivore

Plants have developed tissue-specific defense strategies in response to various herbivores with different feeding habits. Although defense responses to leaf-chewing insects have been well studied, little is known about stem-specific responses, particularly in the pith, to stem-boring herbivores. To understand the stem-specific defense, we first conducted a comparative transcriptomic analysis of the wild tobacco Nicotiana attenuata before and after attack by the leaf-chewing herbivore Manduca sexta and the stem borer Trichobaris mucorea. When the stem-boring herbivore attacked, lignin-associated genes were upregulated specifically in the inner parenchymal cells of the stem, the pith; lignin also accumulated highly in the attacked pith. Silencing the lignin biosynthetic gene cinnamyl alcohol dehydrogenase enhanced the performance of the stem-boring herbivore but had no effect on the growth of the leaf-chewing herbivore. Two-dimensional nuclear magnetic resonance results revealed that lignified pith contains feruloyltyramine as an unusual lignin component in the cell wall, as a response against stem-boring herbivore attack. Pith-specific lignification induced by the stem-boring herbivore was modulated by both jasmonate and ethylene signaling. Furthermore, these results suggest that lignin provides a stem-specific inducible barrier, protecting plants against stem-boring insects.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Evolutionary constraints and climate variability jointly shape starch–sugar balance in woody plants

Nonstructural carbohydrates (NSC) buffer plants against carbon imbalances, yet their partitioning between storage and soluble pools remains elusive at global scales. Here, we compiled a dataset of starch to soluble sugar ratio (St : Su) for 308 woody species across 220 sites world-wide and introduce a dimensionless index that integrates storage and demand while minimizing methodological artifacts. St : Su was strongly associated with growth, identifying it as a key axis of carbon allocation. Foliage consistently exhibited lower St : Su than lignified organs, reflecting a division between transient and conservative pools. Conifers accumulated more starch in foliage but less in stems relative to angiosperms, while leaf habits and mycorrhizal associations further modulated organ-specific strategies. Contrary to expectation, foliar and root St : Su varied little among biomes, but stems exhibited higher ratios in tropical rainforests than in boreal or arid regions, reflecting differences in species composition and adaptive storage under disturbance. Phylogeny constrained stem storage, whereas climatic variability, rather than mean conditions, dominated allocation in leaves and roots. These findings establish St : Su as a robust functional trait linking allocation strategies, growth, and resilience, which can be used to improve vegetation model prediction of forest productivity and mortality under climate variability.

Li, Weibin [Lanzhou Univ. (China)] (ORCID:00000001↗
DOE OSTI2024

Sixteen multiple-amplifier sensing charge-coupled devices and characterization techniques targeting the next generation of astronomical instruments

We present a candidate sensor for future spectroscopic applications, such as a Stage-5 Spectroscopic Survey Experiment or the Habitable Worlds Observatory. This type of charge-coupled device (CCD) sensor features multiple in-line amplifiers at its output stage allowing multiple measurements of the same charge packet, either in each amplifier or in the different amplifiers. Recently, the operation of an eight-amplifier sensor has been experimentally demonstrated, and we present the operation of a 16-amplifier sensor. This new sensor enables a noise level of ∼1 erms− with a single sample per amplifier. In addition, it is shown that sub-electron noise can be achieved using multiple samples per amplifier. In addition to demonstrating the performance of the 16-amplifier sensor, we aim to create a framework for future analysis and performance optimization of this type of detectors. New models and techniques are presented to characterize specific parameters, which are absent in conventional CCDs and Skipper CCDs: charge transfer between amplifiers and independent and common noise in the amplifiers and their processing.

16 multiple-amplifer sensing CCD (MAS-CCD)↗
DOE OSTI2024

FiberFlex: Real-time FPGA-based Intelligent and Distributed Fiber Sensor System for Pedestrian Recognition

In recent years, security monitoring of public places and critical infrastructure has heavily relied on the widespread use of cameras, raising concerns about personal privacy violations. To balance the need for effective security monitoring with the protection of personal privacy, we explore the potential of optical fiber sensors for this application. This article proposes FiberFlex, an intelligent and distributed fiber sensor system. Ultizing Field Programmable Gate Arrays (FPGA) high-level synthesis (HLS) acceleration, FiberFlex offers real-time pedestrian detection by co-designing the entire pipeline of optical signal acquisition, processing, and recognition networks based on the principles of optical fiber sensing. As a promising alternative to traditional camera-based monitoring systems, FiberFlex achieves pedestrian detection by analyzing the vibration patterns caused by pedestrian footsteps, enabling security monitoring while preserving individual privacy. FiberFlex comprises three modules: First , fiber-optic sensing system: A fiber-optic distributed acoustic sensing (DAS) system is built and used to measure the ground vibration waves generated by people walking. Second , algorithms: We first collect the training data by measuring the ground vibration waves, label the data, and use the data to train the neural network models to perform pedestrian recognition. Third , hardware accelerators: We use HLS tools to design hardware modules on FPGA for data collection and pre-processing and integrate them with the downstream neural network accelerators to perform in-line real-time pedestrian detection. The final detection results are sent back from FPGA to the host CPU. We implement our system FiberFlex with the in-house built DAS system and AMD/Xilinx Kintex7 FPGA KC705 board and verify the whole system using the real-world collected data. We conduct recognition tests on five test subjects of varying ages, heights, and weights in a fixed sensing area. Each subject experienced 20 real-time recognition tests using their daily walking habits, and the subjects were given adequate rest between tests. After 100 tests on five test subjects, the overall real-time recognition accuracy exceeded \(88.0\%\) . The whole system uses 55 W of power, 33 W in the optical DAS system and 22 W in the FPGA. Relying on its end-to-end interdisciplinary design, FiberFlex seamlessly combines fiber-optic sensors with FPGA accelerators to enable low-power real-time security monitoring without compromising privacy, making it a valuable addition to the existing security monitoring network. According to FiberFlex, more valuable research can be conducted in the future, such as fall monitoring for the elderly, migration of identification networks between different application scenarios, and improvement of anti-interference performance in more complex environments. In future perception networks, where the “eyes” are not feasible, let’s use fiber optic touch instead.

Distributed↗
DOE OSTI2020

Hydrometeor Shape Variability in Snowfall as Retrieved from Polarimetric Radar Measurements

A polarimetric radar–based method for retrieving atmospheric ice particle shapes is applied to snowfall measurements by a scanning Ka-band radar deployed at Oliktok Point, Alaska (70.495°N, 149.883°W). The mean aspect ratio, which is defined by the hydrometeor minor-to-major dimension ratio for a spheroidal particle model, is retrieved as a particle shape parameter. The radar variables used for aspect ratio profile retrievals include reflectivity, differential reflectivity, and the copolar correlation coefficient. The retrievals indicate that hydrometeors with mean aspect ratios below 0.2–0.3 are usually present in regions with air temperatures warmer than approximately from –17° to –15°C, corresponding to a regime that has been shown to be favorable for growth of pristine ice crystals of planar habits. Radar reflectivities corresponding to the lowest mean aspect ratios are generally between –10 and 10 dBZ. For colder temperatures, mean aspect ratios are typically in a range between 0.3 and 0.8. There is a tendency for hydrometeor aspect ratios to increase as particles transition from altitudes in the temperature range from –17° to –15°C toward the ground. Furthermore, this increase is believed to result from aggregation and riming processes that cause particles to become more spherical and is associated with areas demonstrating differential reflectivity decreases with increasing reflectivity. Aspect ratio retrievals at the lowest altitudes are consistent with in situ measurements obtained using a surface-based multiangle snowflake camera. Pronounced gradients in particle aspect ratio profiles are observed at altitudes at which there is a change in the dominant hydrometeor species, as inferred by spectral measurements from a vertically pointing Doppler radar.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Radar Retrieval Evaluation and Investigation of Dendritic Growth Layer Polarimetric Signatures in a Winter Storm

Abstract This study evaluates ice particle size distribution and aspect ratio φ Multi-Radar Multi-Sensor (MRMS) dual-polarization radar retrievals through a direct comparison with two legs of observational aircraft data obtained during a winter storm case from the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) campaign. In situ cloud probes, satellite, and MRMS observations illustrate that the often-observed K dp and Z DR enhancement regions in the dendritic growth layer can either indicate a local number concentration increase of dry ice particles or the presence of ice particles mixed with a significant number of supercooled liquid droplets. Relative to in situ measurements, MRMS retrievals on average underestimated mean volume diameters by 50% and overestimated number concentrations by over 100%. IWC retrievals using Z DR and K dp within the dendritic growth layer were minimally biased relative to in situ calculations where retrievals yielded −2% median relative error for the entire aircraft leg. Incorporating φ retrievals decreased both the magnitude and spread of polarimetric retrievals below the dendritic growth layer. While φ radar retrievals suggest that observed dendritic growth layer particles were nonspherical (0.1 ≤ φ ≤ 0.2), in situ projected aspect ratios, idealized numerical simulations, and habit classifications from cloud probe images suggest that the population mean φ was generally much higher. Coordinated aircraft radar reflectivity with in situ observations suggests that the MRMS systematically underestimated reflectivity and could not resolve local peaks in mean volume diameter sizes. These results highlight the need to consider particle assumptions and radar limitations when performing retrievals. significance statement Developing snow is often detectable using weather radars. Meteorologists combine these radar measurements with mathematical equations to study how snow forms in order to determine how much snow will fall. This study evaluates current methods for estimating the total number and mass, sizes, and shapes of snowflakes from radar using images of individual snowflakes taken during two aircraft legs. Radar estimates of snowflake properties were most consistent with aircraft data inside regions with prominent radar signatures. However, radar estimates of snowflake shapes were not consistent with observed shapes estimated from the snowflake images. Although additional research is needed, these results bolster understanding of snow-growth physics and uncertainties between radar measurements and snow production that can improve future snowfall forecasting.

Meteorology & Atmospheric Sciences↗
DOE OSTI2022

Extending the Heat Index

The Heat Index is a widely used measure of apparent temperature that accounts for the effects of humidity using Steadman’s model of human thermoregulation. Steadman’s model, however, gives unphysical results when the air is too hot and humid or too cold and dry, leading to an undefined Heat Index. For example, at a relative humidity of 80%, the Heat Index is only defined for temperatures in the range of 288-304 K (59-88 degrees Fahrenheit). Here, Steadman’s thermoregulation model is extended to define the Heat Index for all combinations of temperature and humidity, allowing for an assessment of Earth’s future habitability. The extended Heat Index can be mapped onto physiological responses of an idealized human, such as heat exhaustion, heat stroke, and even heat death, providing an indication of regional health outcomes for different degrees of global warming.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Semi-Analytic Functions to Calculate the Deposition Coefficients for Ice Crystal Vapor Growth in Bin and Bulk Microphysical Models

Numerical cloud models require estimates of the vapor growth rate for ice crystals. Current bulk and bin microphysical parameterizations generally assume that vapor growth is diffusion limited, though some parameterizations include the influence of surface attachment kinetics through a constant deposition coefficient. A parameterization for variable deposition coefficients is provided herein. The parameterization is an explicit function of the ambient ice supersaturation and temperature, and an implicit function of crystal dimensions and pressure. The parameterization is valid for variable surface types including growth by dislocations and growth by step nucleation. Deposition coefficients are predicted for the two primary growth directions of crystals, allowing for the evolution of the primary habits. Comparisons with benchmark calculations of instantaneous mass growth indicate that the parameterization is accurate to within a relative error of 1%. Parcel model simulations using Lagrangian microphysics as a benchmark indicate that the bulk parameterization captures the evolution of mass mixing ratio and fall speed with typical relative errors of less than 10%, whereas the average axis lengths can have errors of up to 20%. The bin model produces greater accuracy with relative errors often less that 10%. The deposition coefficient parameterization can be used in any bulk and bin scheme, with low error, if an equivalent volume spherical radius is provided.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Quantifying Uncertainty in Ice Particle Velocity–Dimension Relationships Using MC3E Observations

Abstract Ice particle terminal fall velocity ( V t ) is fundamental for determining microphysical processes, yet remains extremely challenging to measure. Current theoretical best estimates of V t are functions of Reynolds number. The Reynolds number is related to the Best number, which is a function of ice particle mass, area ratio ( A r ), and maximum dimension ( D max ). These estimates are not conducive for use in most models since model parameterizations often take the form , where ( α , β ) depend on habit and D max . A previously developed framework is used to determine surfaces of equally plausible ( α , β ) coefficients whereby ice particle size/shape distributions are combined with V t best estimates to determine mass- ( V M ) or reflectivity-weighted ( V Z ) velocities that closely match parameterized V M ,SD or V Z ,SD calculated using the ( α , β ) coefficients using two approaches. The first uses surfaces of equally plausible ( a , b ) coefficients describing mass ( M )–dimension relationships (i.e., ) to calculate mass- or reflectivity-weighted velocity from size/shape distributions that are then used to determine ( α , β ) coefficients. The second investigates how uncertainties in A r , D max , and size distribution N ( D ) affect V M or V Z . For seven of nine flight legs flown on 20 and 23 May 2011 during the Mesoscale Continental Convective Clouds Experiment (MC3E), uncertainty from natural parameter variability—namely, the variability in ice particle parameters in similar meteorological conditions—exceeds uncertainties arising from different A r assumptions or D max estimates. The combined uncertainty between A r , D max , and N ( D ) produced smaller variability in ( α , β ) compared to varying M ( D ), demonstrating M ( D ) must be accurately quantified for model fall velocities. Primary sources of uncertainty vary considerably depending on environmental conditions. Significance Statement Ice particle fall velocity is fundamental for numerous processes within clouds, and hence is a critical property that must be accurately represented in weather and climate models. Using aircraft observations of ice particle shapes and sizes obtained in clouds behind midlatitude thunderstorms, this work develops a new framework for estimating ice particle fall velocities and their uncertainty, including quantifying the importance of different uncertainty sources from cloud microphysics measurements. Natural parameter variability contributes the most uncertainty in ice particle fall velocity estimates, although other sources can also be important contributors to uncertainty in certain conditions. Additional work examining ice particle data is needed to further understand how dependent uncertainty in certain ice particle properties are to local environmental conditions.

Meteorology & Atmospheric Sciences↗
DOE OSTI2023

Development of a dynamical model and energy analysis for wheel loader

The objective of this paper is to develop a fully integrated model for the wheel loader, including the subsystem dynamics of the engine, drivetrain, working circuit, steering circuit, and vehicle. It leads to a high-order strongly nonlinear system, and all state variables are coupled together to form a Multi-Input and Multi-Output (MIMO) system. A control architecture is proposed to decouple the MIMO system into several Single-Input and Single-Output (SISO) systems. Here, a tracking problem has been formulated to validate this fully integrated model with the field test data. The accuracy of the model is verified by the 2.3% difference between the measured and simulated fuel consumption. Meanwhile, an energy distribution analysis is conducted to reveal the energy consumption and energy loss of each portion of the wheel loader. Such a model can be used to plan the working pattern, guide the driving habits of human operators, or refine the underlying architecture, leading to the ultimate goal of reducing total fuel consumption and improving productivity.

42 ENGINEERING↗
DOE OSTI2021

Isotope ratio-based quantification of carbon assimilation highlights the role of plastidial isoprenoid precursor availability in photosynthesis

Abstract Background We report a method to estimate carbon assimilation based on isotope ratio-mass spectrometry (IRMS) of 13 CO 2 labeled plant tissue. Photosynthetic carbon assimilation is the principal experimental observable which integrates important aspects of primary plant metabolism. It is traditionally measured through gas exchange. Despite its centrality in plant research, gas exchange performs poorly with rosette growth habits typical of Arabidopsis thaliana , mutant lines with limited biomass, and accounts poorly for leaf shading. Results IRMS-based carbon assimilation values from plants labeled at different light intensities were compared to those obtained by gas exchange, and the two methods yielded similar values. Using this method, we observed a strong correlation between 13 C content and labeling time (R 2 = 0.999) for 158 wild-type plants labeled for 6 to 42 min. Plants cultivated under different light regimes showed a linear response with respect to carbon assimilation, varying from 7.38 nmol 13 C mg −1 leaf tissue min −1 at 80 PAR to 19.27 nmol 13 C mg −1 leaf tissue min −1 at 500 PAR. We applied this method to examine the link between inhibition of the 2 C -methyl- d -erythritol-4-phosphate (MEP) pathway and suppression of photosynthesis. A significant decrease in carbon assimilation was observed when metabolic activity in the MEP pathway was compromised by mutation or herbicides targeting the MEP pathway. Mutants affected in MEP pathway genes 1-DEOXY- d -XYLULOSE 5-PHOSPHATE SYNTHASE (DXS) or 1-HYDROXY-2-METHYL-2-(E)-BUTENYL 4-DIPHOSPHATE SYNTHASE (HDS) showed assimilation rates 36% and 61% lower than wild type. Similarly, wild type plants treated with the MEP pathway inhibitors clomazone or fosmidomycin showed reductions of 52% and 43%, respectively, while inhibition of the analogous mevalonic acid pathway, which supplies the same isoprenoid intermediates in the cytosol, did not, suggesting inhibition of photosynthesis was specific to disruption of the MEP pathway. Conclusions This method provides an alternative to gas exchange that offers several advantages: resilience to differences in leaf overlap, measurements based on tissue mass rather than leaf surface area, and compatibility with mutant Arabidopsis lines which are not amenable to gas exchange measurements due to low biomass and limited leaf surface area. It is suitable for screening large numbers of replicates simultaneously as well as post-hoc analysis of previously labeled plant tissue and is complementary to downstream detection of isotopic label in targeted metabolite pools.

2C‑methyl‑d‑erythritol 4‑phosphate pathway↗
DOE OSTI2026

Municipality of Anchorage Household Travel Survey

The 2002 Household Travel Survey for the municipality of Anchorage, Alaska, collected demographic, socioeconomic, and travel information about households and persons (age five and older) on an assigned, 24-hour travel period. The main objective of the study, conducted by NuStats, was to improve the transportation system. 2,035 households were recruited to participate in the study. Of these, 1,293 completed travel logs depicting detailed data on driving habits, such as purpose of the trips, time of the data, and mode of transportation—spanning from April 1, 2002, to May 17, 2002. This dataset is part of the Metropolitan Travel Survey Archive, which includes travel surveys from numerous public agencies across the United States and is archived by the Transportation Secure Data Center to ensure their continued public availability.

1Hz data↗
DOE OSTI2026

2002 VCMPO Model Calibration and Home-Based Travel Survey

The 2001-2002 Model Calibration and Home-Based Travel Survey was a study conducted in Volusia County, Florida. One of the major purposes of the survey project was to collect information to allow for a better understanding of the travel habits and patterns of residents within Volusia County. The project was jointly funded by the Florida Department of Transportation, Volusia County, and the Volusia County MPO. Demographic and trip data were collected for 2,727 households from February 20, 2002, to February 28, 2002. Respondents were asked to record their travel and activities for a 48-hour period. Detailed information regarding their trips, including mode of transportation, trip purpose, departure and arrival times, and number of passengers, were gathered from 13,408 trips.

1Hz data↗