Defense Priming in Nicotiana tabacum Accelerates and Amplifies 'New' C/N Fluxes in Key Amino Acid Biosynthetic Pathways
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Reconfigurable detectors with dynamically selectable sensing and readout modes are highly desirable for implementing edge computing as well as enabling advanced imaging techniques such as foveation. The concept of a camera system capable of simultaneous passive imaging and dynamic ranging in different regions of the detector is presented. Such an adaptive-autonomous detector with both spatial and temporal control requires programmable window of exposure (time frames), ability to switch between readout modes such as full-frame imaging and zero-suppressed data, modification of the number of pixel data bits and independent programmability for distinct detector regions. In this work, a method is presented for seamlessly changing time frames and readout modes without data corruption while still ensuring that the data acquisition system (DAQ) does not need to stop and resynchronize at each change of setting, thus avoiding significant dead time. Data throughput is maximized by using a minimum unique data format, rather than lengthy frame headers, to differentiate between consecutive frames. A data control and transmitter (DCT) synchronizes data transfer from the pixel to the periphery, reconfigures the data to transmit it serially off-chip, while providing optimized decision support based on a DAQ definable mode. Measurements on a test structure demonstrate that the DCT can operate at 1 GHz in a 65 nm LP CMOS process.
Reflection fiber temperature sensors functionalized with plasmonic nanocomposite material using intensity-based modulation are demonstrated for the first time. Characteristic temperature optical response of the reflective fiber sensor is experimentally tested using Au-incorporated nanocomposite thin films deposited on the fiber tip, and theoretically validated using a thin-film-optic-based optical waveguide model. By optimizing the Au concentration in a dielectric matrix, Au nanoparticles (NP) exhibit a localized surface plasmon resonance (LSPR) absorption band in a visible wavelength that shows a temperature sensitivity ~0.025%/°C as a result of electron–electron and electron–phonon scattering of Au NP and the surrounding matrix. Detailed optical material properties of the on-fiber sensor film are characterized using scanning electron microscopy (SEM) and focused-ion beam (FIB)-assisted transmission electron microscopy (TEM). Airy’s expression of transmission and reflection using complex optical constants of layered media is used to model the reflective optical waveguide. A low-cost wireless interrogator based on a photodiode transimpedance-amplifier (TIA) circuit with a low-pass filter is designed to integrate with the sensor. The converted analog voltage is wirelessly transmitted via 2.4 GHz Serial Peripheral Interface (SPI) protocols. Feasibility is demonstrated for portable, remotely interrogated next-generation fiber optic temperature sensors with future capability for monitoring additional parameters of interest.
The nanoscale optoelectronic properties of materials can be especially important for polycrystalline photovoltaics including many sensor and solar cell designs. For thin film solar cells such as CdTe, the open-circuit voltage and short-circuit current are especially critical performance indicators, often varying between and even within individual grains. A new method for directly mapping the open-circuit voltage leverages photo-conducting AFM, along with an additional proportional-integral-derivative feedback loop configured to maintain open-circuit conditions while scanning. Alternating with short-circuit current mapping efficiently provides complementary insight into the highly microstructurally sensitive local and ensemble photovoltaic performance. Furthermore, direct open-circuit voltage mapping is compatible with tomographic AFM, which additionally leverages gradual nanoscale milling by the AFM probe essentially for serial sectioning. The two-dimensional and three-dimensional results for CdTe solar cells during in situ illumination reveal local to mesoscale contributions to PV performance based on the order of magnitude variations in photovoltaic properties with distinct grains, at grain boundaries, and for sub-granular planar defects.
Here, we describe direct measurements of ozone concentration achievable in small enclosed containers (plastic storage boxes) for use as improvised decontamination systems for small articles such as disposable PPE (N95 masks, nitrile gloves, etc.), clothing, mail and small packages, food, and other miscellaneous articles. The emphasis is on the reliable and sustained generation of ozone gas concentrations of sufficient concentration and duration to create an effective virucidal environment to achieve more than 95% to 99% viral inactivation, based upon the data already published in the peer-review literature on this topic. The suggestion that ozone be used to inactivate virus is certainly not a new idea. Our objective in this report is to make clear that the necessary levels of ozone can be improvised using simple, easy-to-use, inexpensive, and widely available supplies, and that there is every theoretical and experimental reason to believe that this approach is as highly effective in viral inactivation by ozone as are the far more expensive, complex, cumbersome, and less available equivalent ozone (and other) disinfectant systems that have themselves become unavailable during times of pandemic crisis. Using multiple types of readily available commercial ozone generators, concentration in the tested improvised enclosure is tracked over time to assess ozone charging and decay rates, and the ozone quenching effects of items placed in the box. Generator performance is compared against published ozone dosage values for virucidal and antimicrobial activity. Bubbler and box-fan-type ozone generators were found to be effective at achieving and maintaining target concentrations of 10ppm ozone or higher, whereas automotive cigarette lighter and universal serial bus type plug in “air freshener” ozone generators could not achieve the target concentrations in these experiments. Calculations and practical guidelines for assembly and effective use of an ozone box for improvised decontamination are offered. The majority of this report is directed toward the scientific justification and rationale for this approach. The end of the document summarizes the findings and offers simplified designs for the construction and use of ozone boxes as an improvised method of disinfection.
Modern 3D electron microscopy approaches have recently allowed unprecedented insight into the 3D ultrastructural organization of cells and tissues, enabling the visualization of large macromolecular machines, such as adhesion complexes, as well as higher-order structures, such as the cytoskeleton and cellular organelles in their respective cell and tissue context. Given the inherent complexity of cellular volumes, it is essential to first extract the features of interest in order to allow visualization, quantification, and therefore comprehension of their 3D organization. Each data set is defined by distinct characteristics, e.g., signal-to-noise ratio, crispness (sharpness) of the data, heterogeneity of its features, crowdedness of features, presence or absence of characteristic shapes that allow for easy identification, and the percentage of the entire volume that a specific region of interest occupies. All these characteristics need to be considered when deciding on which approach to take for segmentation. The six different 3D ultrastructural data sets presented were obtained by three different imaging approaches: resin embedded stained electron tomography, focused ion beam- and serial block face- scanning electron microscopy (FIB-SEM, SBF-SEM) of mildly stained and heavily stained samples, respectively. For these data sets, four different segmentation approaches have been applied: (1) fully manual model building followed solely by visualization of the model, (2) manual tracing segmentation of the data followed by surface rendering, (3) semi-automated approaches followed by surface rendering, or (4) automated custom-designed segmentation algorithms followed by surface rendering and quantitative analysis. Depending on the combination of data set characteristics, it was found that typically one of these four categorical approaches outperforms the others, but depending on the exact sequence of criteria, more than one approach may be successful. Based on these data, we propose a triage scheme that categorizes both objective data set characteristics and subjective personal criteria for the analysis of the different data sets.
Optimizing metamaterials with complex geometries is a big challenge. Although an active learning algorithm, combining machine learning (ML), quantum computing, and optical simulation, has emerged as an efficient optimization tool, it still faces difficulties in optimizing complex structures that have potentially high performance. In this work, we comprehensively analyze the performance of an optimization algorithm for metamaterial design on the integrated HPC and quantum systems. We demonstrate significant time advantages through message-passing interface (MPI) parallelization on the high-performance computing (HPC) system showing approximately 54% faster ML tasks and 67 times faster optical simulation against serial workloads. Furthermore, we analyze the performance of a quantum algorithm designed for optimization, which runs with various quantum simulators on a local computer or HPC-quantum system. Results showcase ~24 times speedup when executing the optimization algorithm on the HPC-quantum hybrid system. This study paves a way to optimize complex metamaterials using the integrated HPC-quantum system.
Abstract. The Niwot Ridge Subalpine Forest AmeriFlux site (US-NR1) has been measuring eddy-covariance ecosystem fluxes of carbon dioxide, heat, and water vapor since 1 November 1998. Throughout this 17-year period there have been changes to the instrumentation and improvements to the data acquisition system. Here, in Part 1 of this three-part series of papers, we describe the hardware and software used for data-collection and metadata documentation. We made changes to the data acquisition system that aimed to reduce the system complexity, increase redundancy, and be as independent as possible from any network outages. Changes to facilitate these improvements were (1) switching to a PC/104-based computer running the National Center for Atmospheric Research (NCAR) In-Situ Data Acquisition Software (NIDAS) that saves the high-frequency data locally and over the network, and (2) time-tagging individual 10 Hz serial data samples using network time protocol (NTP) coupled to a GPS-based clock, providing a network-independent, accurate time base. Since making these improvements almost 2 years ago, the successful capture of high-rate data has been better than 99.98 %. We also provide philosophical concepts that shaped our design of the data system and are applicable to many different types of environmental data collection.
One of the fundamental factors contributing to the spatiotemporal inaccuracy in climate modeling is the mapping of solution field data between different discretizations and numerical grids used in the coupled component models. The typical climate computational workflow involves evaluation and serialization of the remapping weights during the preprocessing step, which is then consumed by the coupled driver infrastructure during simulation to compute field projections. Tools like Earth System Modeling Framework (ESMF) and TempestRemap offer capability to generate conservative remapping weights, while the Model Coupling Toolkit (MCT) that is utilized in many production climate models exposes functionality to make use of the operators to solve the coupled problem. However, such multistep processes present several hurdles in terms of the scientific workflow and impede research productivity. In order to overcome these limitations, we present a fully integrated infrastructure based on the Mesh Oriented datABase (MOAB) library, which allows for a complete description of the numerical grids and solution data used in each submodel. Through a scalable advancing-front intersection algorithm, the supermesh of the source and target grids are computed, which is then used to assemble the high-order, conservative, and monotonicity-preserving remapping weights between discretization specifications. The Fortran-compatible interfaces in MOAB are utilized to directly link the submodels in the Energy Exascale Earth System Model (E3SM) to enable online remapping strategies in order to simplify the coupled workflow process. We demonstrate the superior computational efficiency of the remapping algorithms in comparison with other state-of-the-science tools and present strong scaling results on large-scale machines for computing remapping weights between the spectral element atmosphere and finite volume discretizations on the polygonal ocean grids.
Lagrangian particle tracking schemes allow a wide range of flow and transport processes to be simulated accurately, but a major challenge is numerically implementing the inter-particle interactions in an efficient manner. This article develops a multi-dimensional, parallelized domain decomposition (DDC) strategy for mass-transfer particle tracking (MTPT) methods in which particles exchange mass dynamically. We show that this can be efficiently parallelized by employing large numbers of CPU cores to accelerate run times. In order to validate the approach and our theoretical predictions we focus our efforts on a well-known benchmark problem with pure diffusion, where analytical solutions in any number of dimensions are well established. In this work, we investigate different procedures for “tiling” the domain in two and three dimensions (2-D and 3-D), as this type of formal DDC construction is currently limited to 1-D. An optimal tiling is prescribed based on physical problem parameters and the number of available CPU cores, as each tiling provides distinct results in both accuracy and run time. We further extend the most efficient technique to 3-D for comparison, leading to an analytical discussion of the effect of dimensionality on strategies for implementing DDC schemes. Increasing computational resources (cores) within the DDC method produces a trade-off between inter-node communication and on-node work. For an optimally subdivided diffusion problem, the 2-D parallelized algorithm achieves nearly perfect linear speedup in comparison with the serial run-up to around 2700 cores, reducing a 5 h simulation to 8 s, while the 3-D algorithm maintains appreciable speedup up to 1700 cores.
This paper explores the feasibility of an experimentation strategy for investigating sensitivities in fast components of atmospheric general circulation models. The basic idea is to replace the traditional serial-in-time long-term climate integrations by representative ensembles of shorter simulations. The key advantage of the proposed method lies in its efficiency: since fewer days of simulation are needed, the computational cost is less, and because individual realizations are independent and can be integrated simultaneously, the new dimension of parallelism can dramatically reduce the turnaround time in benchmark tests, sensitivities studies, and model tuning exercises. The strategy is not appropriate for exploring sensitivity of all model features, but it is very effective in many situations. Two examples are presented using the Community Atmosphere Model version 5. The first example demonstrates that the method is capable of characterizing the model cloud and precipitation sensitivity to time step length. A nudging technique is also applied to an additional set of simulations to help understand the contribution of physics-dynamics interaction to the detected time step sensitivity. In the second example, multiple empirical parameters related to cloud microphysics and aerosol lifecycle are perturbed simultaneously in order to explore which parameters have the largest impact on the simulated global mean top-of-atmosphere radiation balance. Results show that in both examples, short ensembles are able to correctly reproduce the main signals of model sensitivities revealed by traditional long-term climate simulations for fast processes in the climate system. The efficiency of the ensemble method makes it particularly useful for the development of high-resolution, costly and complex climate models.
This repository contains all of the methods for the NSRDB data processing pipeline. The NSRDB is a serially complete collection of hourly and half-hourly values of meteorological data and the three most common measurements of solar radiation: global horizontal, direct normal and diffuse horizontal irradiance.
PowerSystems.jl is a package to organize and manipulate data for the study of energy systems with diverse modeling requirements. This software serves two main purposes: to reduce the burden of large power system data set development, and to promote reproducible research and simulation. PowerSystems.jl implements an abstract hierarchy to represent and customize power systems data and includes data containers for quasi-static and dynamic simulation applications. Key features include efficient management of large quantities of time series data, optimized serialization, and comprehensive validation capabilities. For further information regarding the Sienna modeling framework at NREL, see: https://www.nrel.gov/analysis/sienna.html
The dataset comprises measures, using Colorado State University's Ice Spectrometer (IS, an immersion freezing device with a range from 0°C down to -26 to -29°C) of atmosperic ice nucleating particle (INP) concentrations taken on ARM's Mobile Facility (AMF-1) Aerosol Observing System, near Villa Yacanto in central Argentina, during the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) Experiment. A filter sampler was mounted on the AOS trailer (2 m below the AOS inlet). Single-use filter units open to the atmosphere fitted with pre-cleaned and pre-sterilized, 47-mm dia. Nuclepore polycarbonate filters were used. Filters were typically drawn for an 8-hour period, totaling 6000 liters sampled on average. After collection, filters were stored at -20°C until processed. Initial processing to obtain spectra of INP number concentration active via the immersion freezing mechanism versus temperature was conducted using CSU's IS instrument (McCluskey et al., 2018). For measurment of INPs, collected aerosol particles were re-suspended in 7-8 mL of 0.1 µm-filtered deionized (DI) water. Aliquots of each suspension, and serial dilutions, were dispensed into trays which were fit into aluminum blocks in the IS. Samples are cooled at 0.33°C min-1 and the freezing temperatures of wells recorded automatically. Cumulative INP concentrations were determined by first calculating the INPs per mL of suspension based on Vali (1971) and then converting to concentration per standard liter of air using the proportion of the total liquid sample dispensed and the air sample volumes. An aliquot of suspension fro selected samples were also heat treated (95°C for 20 min) to denature and deactivate biological INPs, and another aliquot digested in 10% H2O2 at 95°C under UV-B to remove all organic carbon INPs. McCluskey, C. S., J. Ovadnevaite, M. Rinaldi, J. Atkinson, F. Belosi, D. Ceburnis, S. Marullo, T. C. J. Hill, U. Lohmann, Z. A. Kanji, C. O’Dowd, S. M. Kreidenweis, P. J. DeMott, 2018: Marine and Terrestrial Organic Ice Nucleating Particles in Pristine Marine to Continentally-Influenced Northeast Atlantic Air Masses, Journal of Geophysical Research: Atmospheres, 123, 6196–6212, https://doi.org/10.1029/2017JD028033. Vali, G., 1971: Quantitative evaluation of experimental results on the heterogeneous freezing nucleation of supercooled liquids. J. Atmos. Sci., 28, 402–409.
The dataset comprises measures, using Colorado State University's Ice Spectrometer (IS, an immersion freezing device with a range from 0°C down to -26 to -29°C) of atmospheric ice nucleating particle (INP) concentrations taken on the Atmospheric Radiation Measurement (ARM) program Aerial Facilty (AAF) G-1 aircraft. INP measurements on the G-1 were collected from varied altitudes on different flights over the region of the Sierras de Córdoba mountain range of north-central Argentina, centred over ARM's Mobile Facility (AMF-1) near Villa Yacanto, where ground-based INP measures were being taken concurrently. Both studies took place as part of the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) Experiment. A filter sampling system was deployed on the G-1 to collect aerosol particles for post-processing of INPs collected on filters (measuring their immersion freezing ability) once returned to Colorado State University (CSU). Filter holders used were pre-cleaned aluminum in-line units loaded with pre-cleaned and pre-sterilized 47 mm dia. Nuclepore polycarbonate filters (0.2 mm pore size). Filters were drawn for varied times, resulting in varied volumes collected (51 to 1667 SL). Mass flow rate was recorded in real-time so that total sampled volume (at standard temperature and pressure) could be determined. A total of 34 sample filters were collected over the IOP, including 5 blanks. Filters were stored at -20°C freezer prior to frozen return to Colorado State University (CSU). . Processing to obtain spectra of INP number concentration active via the immersion freezing mechanism versus temperature was conducted using CSU's IS instrument (McCluskey et al., 2018). For measurment of INPs, collected aerosol particles were re-suspended in 7 mL of 0.02 µm-filtered deionized water. Aliquots of each suspension, and serial dilutions, were dispensed into trays which were fit into aluminum blocks in the IS. Samples are cooled at 0.33°C min-1 and the freezing temperatures of wells recorded automatically. Cumulative INP concentrations were determined by first calculating the INPs per mL of suspension based on Vali (1971) and then converting to concentration per standard liter of air using the proportion of the total liquid sample dispensed and the air sample volumes. Aliquots of suspensions from selected samples were also heat treated (95°C for 20 min) to denature and deactivate biological INPs, and digested in 10% H2O2 at 95°C under UV-B to remove all organic carbon INPs. McCluskey, C. S., J. Ovadnevaite, M. Rinaldi, J. Atkinson, F. Belosi, D. Ceburnis, S. Marullo, T. C. J. Hill, U. Lohmann, Z. A. Kanji, C. O’Dowd, S. M. Kreidenweis, P. J. DeMott, 2018: Marine and Terrestrial Organic Ice Nucleating Particles in Pristine Marine to Continentally-Influenced Northeast Atlantic Air Masses, Journal of Geophysical Research: Atmospheres, 123, 6196–6212, https://doi.org/10.1029/2017JD028033. Vali, G., 1971: Quantitative evaluation of experimental results on the heterogeneous freezing nucleation of supercooled liquids. J. Atmos. Sci., 28, 402–409.
The dataset comprises measures, using Colorado State University's Ice Spectrometer (IS, an immersion freezing device with a range from 0 °C down to -26 to -29 °C) of atmospheric ice nucleating particle (INP) concentrations taken at ARM's Southern Great Plains (SGP) Site Guest Instrument Facility (GIF), in Lamont, Oklahoma, during the Aerosol-Ice Formation Closure Pilot Study (AEROICESTUDY). A filter sampler was mounted approximately 6 m above ground level atop the GIF rooftop platform. Single-use filter units open to the atmosphere fitted with pre-cleaned and pre-sterilized, 47-mm diameter Nuclepore polycarbonate filters were used. Filters were typically drawn for either a full day period (9AM-5PM CDT) or broken up into morning (9AM-12PM CDT) and afternoon (1PM-5PM CDT) periods. Additionally, 4 overnight filters were taken (6PM-8AM CDT). The volume of air filtered was typically between 3000 and 8000 standard liters for daily samples. After collection, filters were stored at -20 °C until processed. Initial processing to obtain spectra of INP number concentration active via the immersion freezing mechanism versus temperature was conducted using CSU's IS instrument (McCluskey et al., 2018). For measurement of INPs, collected aerosol particles were re-suspended in 8 mL of 0.1 µm-filtered deionized (DI) water. Aliquots of each suspension, and serial dilutions, were dispensed into trays which were fit into aluminum blocks in the IS. Samples were cooled at 0.33 °C per min and the freezing temperatures of wells recorded automatically. Cumulative INP concentrations were determined by first calculating the INPs per mL of suspension based on Vali (1971) and then converting to concentration per standard liter of air using the proportion of the total liquid sample dispensed and the air sample volumes. Two-tailed, 95% confidence intervals for binomial sampling were based on Equation 2 from Agresti and Coull (1998). Aliquots of suspensions from selected samples were also heat treated (95 °C for 20 min) to denature and deactiv
Detailed transects of snow depths and related measurements were made with a magnaprobe along fixed lines in Utqiagvik, AK. The operator measures snow depth by plunging a rod with a sliding basket into the snow and pressing a trigger. At this point, the data logger records the distance between the tip of the rod and the height of the basket, the measurement number, the time, and the geographic location of the measurement. To measure snow depth, the rod tip must be placed at the snow-ground or snow-sea ice interface. The interface can be hard or soft; in the latter case, it is possible to “over-probe”, producing a snow depth that is too high. At times, the probe was also used to measure the depths of other interfaces within the snowpack (for example, the depth to persistent ice lenses) or the water depths of ponds atop the tundra or sea ice. When these alternative depth measurements were made, the operator recorded the location, measurement number, and composition of the alternative depth measurement in a field notebook. The data logger on the probe stores several thousand points. Data is downloaded to a computer at the end of a day or several days. Probes: We used 2 magnaprobes identified as GEO1 and GEODEL with the following serial numbers: S/N 20240416 (GEO1) and S/N P48066 (GEODEL). Note : There are three data levels available with this dataset: b3, b4, and a6. New users of these data are strongly encouraged to use the level a6 or b4 data.