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Provide information and experimental support for the Si-content Lithium-Ion battery anodes fabrication.
The main purpose of this project was to provide ground-truth and satellite-based soil water content data in the Houston, Texas, area to support the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s 2022 field campaign, the Tracking Aerosol Convection Interactions ExpeRiment (TRACER). This involved installing four soil monitoring stations at different locations in the Houston area, two of which were part of the ARM facility and two were ancillary. The two stations associated directly with ARM were installed alongside other facilities managed and maintained by the TRACER research team during the intensive operational period (IOP), one located at the La Porte, Texas airport and the other located near Guy, Texas. Data from these stations were assimilated with similar data collected by the Harris County Flood Control District (HCFCD) to improve the spatial coverage of the real-time monitoring network. The ground-truth data were compared to the satellite-based (National Aeronautics and Space Administration [NASA]’s Soil Moisture Active Passive [SMAP] mission) data in the TRACER area of interest, and analyzed further to nowcast gridded data over the Houston area. The nowcasted, gridded data product was made available to TRACER researchers for use in climate and land-atmosphere interaction modeling that can help understand formation and persistence of convective storms in dense urban areas, and predict possible environmental events such as floods.
This repository contains code for the experiments in the paper "Understanding Generative AI Content with Embedding Models". Constructing high-quality features is critical to any quantitative data analysis. While feature engineering was historically addressed by carefully hand-crafting data representations based on domain expertise, deep neural networks (DNNs) now offer a radically different approach. DNNs implicitly engineer features by transforming their input data into hidden feature vectors called embeddings. For embedding vectors produced by foundation models -- which are trained to be useful across many contexts -- we demonstrate that simple and well-studied dimensionality-reduction techniques such as Principal Component Analysis uncover inherent heterogeneity in input data concordant with human-understandable explanations. Of the many applications for this framework, we find empirical evidence that there is intrinsic separability between real samples and those generated by artificial intelligence (AI).
BSC TO5 Task 7.2 Analysis of Joist Masonry Moisture Content Monitoring House - Lawrence, MA 01840 This work involved the field monitoring of embedded wood joist ends in a solid brick building in zone 5A that was retrofitted with interior insulation. Eleven joists throughout the building (which have a variety of orientations, exposures, and masonry wall types) were monitored for wood MCs at the embedded joist ends and for temperatures and RHs within the joist pocket. Indoor and outdoor conditions were also recorded. Results were collected for 28 months (December 2012-April 2015). One limitation was that the renovation was still ongoing; limited wintertime construction heating and no permanent occupancy were factors. Much of the building experienced cold interior temperatures (e.g., construction heating) during the winters. These were not typical interior heating set points. Because the building was essentially unoccupied, no significant interior moisture was generated. These boundary conditions are not normal service conditions. Overall, the RHs and MCs measured in joist pockets were higher than recommended for longterm durability. Many of the joist pockets had sustained conditions of 100% RH, and many wood MCs were in the 25%-35% range for extended periods. Typical guidance includes: (1) MCs lower than 20% are safe, and (2) decay fungi become active at MCs higher than 28%. ASHRAE xi 160 analysis showed that high RH levels coincided with temperatures that were high enough to support mold growth for most of the monitoring period (60%-70% of the hours) in most joists. However, no damage was seen at the joist ends when the instrumentation was installed or when a joist end sample was removed. This suggests that dense, old-growth framing might be able to survive these MCs without damage. Orientation has a significant effect on RH and MC levels: solar heating and drying kept all southfacing joist MCs well within the safe range. The east and west orientations had mixed results: some were in the safe range, but others exceeded the 20% MC level. The north side joists consistently had the highest MCs. Almost all the joists showed seasonal rises and falls; MC and RH conditions were higher during the summer and lower during the winter. This indicates the temperature gradient caused moisture to be driven inward during the summer. MC plots with driving rain showed no discernable correlations. In the parts of the building that had significant wintertime heating, many joists showed a drop in MC that coincided with the addition of heat, even after insulation and air sealing were installed. The joist ends showed a repeated pattern of MC measurements at their upper and lower ends. The lower joist end was consistently wetter than the upper joist end, which can be attributed to contact with the masonry pocket, gravity drainage of bulk water to the bottom of the pocket, greater drying at the top of the beam or deeper embedment at the bottom of the beam, and a larger air pocket at the top of the beam. The north-facing insulated and uninsulated joist ends were compared; a significant or consistent MC or RH difference was not seen between these cases. All three joist pockets essentially remained at a constant 100% RH.
This data set provides the peat water content and peat temperature at time of sampling for peat cores collected before and during the SPRUCE Whole Ecosystem Warming (WEW) study. Cores for the current data set were collected during the following bulk peat sampling events: 13 June 2016 and 23 August 2016. Over time, this dataset will be updated with each new major bulk peat sampling event, and dates/methods will be updated accordingly.
Observations (from thermistor sensors and a hurricane glider) and model-based temperature were used to answer questions including the following: 1) What physical and environmental conditions explain the rapid intensification of Hurricane Laura? 2) How did the pre-existing warm mixed layer at Stone mooring (StM) influence the degree of cooling in the mixed layer? 3) How did vertical mixing, surface heat fluxes, and advective processes collectively shape the mixed layer heat evolution at StM? Observations measured by thermistor sensors showed that Hurricane Laura induced a cooling of -1.2oC in the mixed layer when Hurricane Laura’s wind speed increased to 47 m/s on 26 August. This contrasts with the -1.04oC mixed layer temperature change estimated from model-based temperature. At StM, the presence of a 31oC warm mixed layer and elevated heat content (60-80kJ/cm2) effectively preconditioned the upper ocean ahead of Hurricane Laura’s passage. After Hurricane Laura passed, turbulent mixing associated with the storm transported the heat anomalies downward into subsurface layers. In addition, this study shows that a surface heat flux of 5.04 kJ/cm2 supported the intensity of Hurricane Laura as it traversed over the StM. Using a mixed layer heat balance model, this study shows that entrainment flux and surface flux mostly contributed to the observed change in the mixed layer temperature.
Pomegranate has a unique evolutionary history given that different cultivars have eight or nine bivalent chromosomes with possible crossability between the two classes. Therefore, it is important to study chromosome evolution in pomegranate to understand the dynamics of its population. Here, we de novo assembled the Azerbaijani cultivar “Azerbaijan guloyshasi” (AG2017; 2n = 16) and re-sequenced six cultivars to track the evolution of pomegranate and to compare it with previously published de novo assembled and re-sequenced cultivars. High synteny was observed between AG2017, Bhagawa (2n = 16), Tunisia (2n = 16), and Dabenzi (2n = 18), but these four cultivars diverged from the cultivar Taishanhong (2n = 18) with several rearrangements indicating the presence of two major chromosome evolution events. Major presence/absence variations were not observed as >99% of the five genomes aligned across the cultivars, while >99% of the pan-genic content was represented by Tunisia and Taishanhong only. We also revisited the divergence between soft- and hard-seeded cultivars with less structured population genomic data, compared to previous studies, to refine the selected genomic regions and detect global migration routes for pomegranate. We reported a unique admixture between soft- and hard-seeded cultivars that can be exploited to improve the diversity, quality, and adaptability of local pomegranate varieties around the world. Our study adds body knowledge to understanding the evolution of the pomegranate genome and its implications for the population structure of global pomegranate diversity, as well as planning breeding programs aiming to develop improved cultivars.
Calcium is important for the growth and development of plants. It serves crucial functions in cell wall and cell membrane structure and serves as a secondary messenger in signaling pathways relevant to nutrient and immunity responses. Thus, measuring calcium levels in plants is important for studies of plant biology and for technology development in food, agriculture, energy, and forest industries. Often, calcium in plants has been measured through techniques such as atomic absorption spectrophotometry (AAS), inductively coupled plasma–mass spectrometry (ICP-MS), and electrophysiology. These techniques, however, require large sample sizes, chemical extraction of samples or have limited spatial resolution. Here, we used near-edge X-ray absorption fine structure (NEXAFS) spectroscopy at the calcium L- and K-edges to measure the calcium to carbon mass ratio with spatial resolution in plant samples without requiring chemical extraction or large sample sizes. We demonstrate that the integrated absorbance at the calcium L-edge and the edge jump in the fluorescence yield at the calcium K-edge can be used to quantify the calcium content as the calcium mass fraction, and validate this approach with onion epidermal peels and ICP-MS. We also used NEXAFS to estimate the calcium mass ratio in hypocotyls of a model plant, Arabidopsis thaliana , which has a cell wall composition that is similar to that of onion epidermal peels. These results show that NEXAFS spectroscopy performed at the calcium edge provides an approach to quantify calcium levels within plants, which is crucial for understanding plant physiology and advancing plant-based materials.
Introduction: Pennycress (Thlaspi arvense L.) is an emerging intermediate oilseed crop grown in the offseason between primary summer crops to produce three cash crops in two years. Previous efforts to improve seed oil quality produced Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) genome-edited lines with decreased polyunsaturated fatty acids (PUFAs) levels, through loss of function of the FATTY ACID DESATURASE 2 (FAD2), REDUCED OLEATE DESATURATION1 (ROD1), and FATTY ACID ELONGASE1 (FAE1) genes. While seed oil compositions were previously characterized, it remains unknown how vegetative and reproductive tissue compositions might differ and affect tolerance to high temperature (HT) conditions.Methods: In four growth chamber experiments, we explored HT tolerance during flowering and silicle development. Plants were subjected to a 34 °C day/28 °C night regime and compared to control plants maintained at 20 °C. Pollen grain viability at a range of temperatures, lipid peroxidation and proline content in leaves and silicles following HT, and seed yield were measured.Results: Both fad2 and rod1 mutant lines had relatively higher pollen viability (71% and 54% respectively) under moderately elevated temperature (28 °C) compared to wild-type controls (37%). They also showed smaller decreases in seed yield (0% and 40% for fad2 and rod1 respectively, compared to 61% for wild type), following HT exposure during late flowering and early silicle development. Silicles of fad2 plants experienced 65% less lipid peroxidation under HT and 55% less buildup of proline, signifying less stress.Discussion: The differential results of fad2 and rod1 are likely due to the role of FAD2 in membranes in all tissues, whereas ROD1 predominantly affects triacylglycerol (TAG) composition in oil-accumulating tissues including pollen. Our results indicate that decreasing PUFAs, through gene editing, can increase heat tolerance in reproductive tissues as an auxiliary benefit accompanying improved seed oil quality.
A content-addressable memory (CAM) stores key-value associations such that the key is recalled by providing its associated value. While CAM recall is traditionally performed using recurrent neural network models, we show how to solve this problem using adiabatic quantum optimization. Our approach maps the recurrent neural network to a commercially available quantum processing unit by taking advantage of the common underlying Ising spin model. We then assess the accuracy of the quantum processor to store key-value associations by quantifying recall performance against an ensemble of problem sets. We observe that different learning rules from the neural network community influence recall accuracy but performance appears to be limited by potential noise in the processor. The strong connection established between quantum processors and neural network problems supports the growing intersection of these two ideas.
Fuel and water contents are inevitable in automotive engine oils. This study intends to investigate the impact of the addition of gasoline (3–20%) and water (1%) on the lubricating performance of synthetic base oil (PAO), with or without an anti-wear additive (ZDDP), for a steel-cast iron contact. Fuel-added PAO showed an increase in the load carrying capacity. Oil electrical conductivity and total acid number (TAN) measurements showed slightly increased conductivity and marginally increased acidity at a higher fuel concentration. In contrast, an increased wear rate, proportional to the fuel concentration, was observed in a prolonged test with constant-loading. Results suggested that the fuel addition is a double-edged sword: reducing the scuffing risk by providing stronger surface adsorption and increasing the sliding wear rate by bringing down the oil viscosity. The PAO-water blend formed an emulsion and resulted in a significantly increased load-carrying capacity, again likely due to the higher polarity and possibly acidity. For the ZDDP-containing PAO, the addition of 1% water and 3% fuel generated 24% and 52% higher wear. The phosphate polymerization level was reduced on the worn surfaces by the introduction of water but the thickness of ZDDP tribofilm was not significantly affected.
Research on the additive manufacturing of metals often neglects any characterization of the composition of final parts, erroneously assuming a compositional homogeneity that matches the feedstock material. Here, the composition of electron-beam-melted Ti-6Al-4V produced through three distinct scanning strategies (linear raster and two point melting strategies, random fill and Dehoff fill) is characterized both locally and globally through energy-dispersive spectroscopy and quantitative chemical analysis. As a result of the different scanning strategies used, differing levels of preferential vaporization occur across the various parts, leading to distinct final compositions, with extremes of ~5.8 wt.% Al and ~4.8 wt.% Al. In addition, energy-dispersive spectroscopy composition maps reveal specific features in both the XY and XZ planes (with Z being the build direction) as a result of local inhomogeneous preferential vaporization. The subsequent change in composition significantly modifies the materials’ state of parts, wherein parts and local regions with higher aluminum contents lead to higher hardness levels (with a ~50 HV difference) and elastic property values and vice versa. While varying scan strategies and scan parameters are known to modify the microstructure and properties of a part, the effect on composition cannot, and should not, be neglected.
The aim of this study was to evaluate the production of dried fruits and juices from chokeberry as potential sources of bioactive compounds with beneficial effects on human health. Dry powders and juices from chokeberry were analyzed for the contents of sugars with high-performance liquid chromatography coupled with an evaporative light scattering detector (HPLC-ELSD method), and the antioxidant capacity was analyzed by the FRAP (ferric-reducing ability of plasma) and ABTS (2,2'-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid)) tests. Polyphenols were then identified by high performance liquid chromatography (HPLC) coupled with a tandem mass spectrometer and a photodiode-array detector (LC-PDA-ESI-MS/MS), and their quantitative analysis was carried out by UPLC-MS/MS (using a Q/TOF detector and a PDA detector). A total of 27 polyphenolic compounds was identified in chokeberry products, including 7 anthocyanins, 11 flavonols, 5 phenolic acids, 3 flavan-3-ols and 1 flavanone. Three anthocyanin derivatives were reported for the first time from chokeberry fruit. A higher activity of the bioactive compounds was determined in dried fruit pomace and in juice obtained from crushed fruits than in those from the whole fruits. In addition, the pomace was found to be a better material for the production of dry powders, compared to chokeberry fruits.
By identifying the relationship between calcium location in the plant cell and nutrient bioavailability, the plant characteristics leading to maximal calcium absorption by humans can be identified. Knowledge of plant cellular and molecular targets controlling calcium location in plants is emerging. These insights should allow for better strategies for increasing the nutritional content of foods. In particular, the use of preparation-free elemental imaging technologies such as synchrotron X-ray fluorescence (SXRF) microscopy in plant biology may allow researchers to understand the relationship between subcellular location and nutrient bioavailability. These approaches may lead to better strategies for altering the location of calcium within the plant to maximize its absorption from fruits and vegetables. These modified foods could be part of a diet for children and adults identified as at-risk for low calcium intake or absorption with the ultimate goal of decreasing the incidence and severity of inadequate bone mineralization.
Chlorophyll has long been used as a natural indicator of plant health and photosynthetic efficiency. Laser-induced fluorescence (LIF) is an emerging technique for understanding broad spectrum organic processes and has more recently been used to monitor chlorophyll response in plants. Previous work has focused on developing a LIF technique for imaging moss mats to identify metal contamination with the current focus shifting toward application to moss fronds and aiding sample collection for chemical analysis. Two laser systems (CoCoBi a Nd:YGa pulsed laser system and Chl-SL with two blue continuous semiconductor diodes) were used to collect images of moss fronds exposed to increasing levels of Cu (1, 10, and 100 nmol/cm 2 ) using a CMOS camera. The best methods for the preprocessing of images were conducted before the analysis of fluorescence signatures were compared to a control. The Chl-SL system performed better than the CoCoBi, with dynamic time warping (DTW) proving the most effective for image analysis. Manual thresholding to remove lower decimal code values improved the data distributions and proved whether using one or two fronds in an image was more advantageous. A higher DTW difference from the control correlated to lower chlorophyll a/b ratios and a higher metal content, indicating that LIF, with the aid of image processing, can be an effective technique for identifying Cu contamination shortly after an event.
Triaxial neutron stars can be sources of continuous gravitational radiation detectable by ground-based interferometers. The amplitude of the emitted gravitational wave can be greatly affected by the state of the hydrodynamical fluid flow inside the neutron star. In this work, we examine the most triaxial models along two sequences of constant rest mass, confirming their dynamical stability. We also study the response of a triaxial figure of quasiequilibrium under a variety of perturbations that lead to different fluid flows. Starting from the general relativistic compressible analog of the Newtonian Jacobi ellipsoid, we perform simulations of Dedekind-type flows. We find that in some cases the triaxial neutron star resembles a Riemann-S-type ellipsoid with minor rotation and gravitational wave emission as it evolves towards axisymmetry. The present results highlight the importance of understanding the fluid flow in the interior of a neutron star in terms of its gravitational wave content.
Estimates of galaxy distances based on indicators that are independent of cosmological redshift are fundamental to astrophysics. Researchers use them to establish the extragalactic distance scale, to underpin estimates of the Hubble constant, and to study peculiar velocities induced by gravitational attractions that perturb the motions of galaxies with respect to the “Hubble flow” of universal expansion. In 2006 the NASA/IPAC Extragalactic Database (NED) began making available a comprehensive compilation of redshift-independent extragalactic distance estimates. A decade later, this compendium of distances (NED-D) now contains more than 100,000 individual estimates based on primary and secondary indicators, available for more than 28,000 galaxies, and compiled from over 2000 references in the refereed astronomical literature. This paper describes the methodology, content, and use of NED-D, and addresses challenges to be overcome in compiling such distances. Currently, 75 different distance indicators are in use. We include a figure that facilitates comparison of the indicators with significant numbers of estimates in terms of the minimum, 25th percentile, median, 75th percentile, and maximum distances spanned. Brief descriptions of the indicators, including examples of their use in the database, are given in an appendix.
The James Webb Space Telescope ( JWST ) is nearing its launch date of 2018, and is expected to revolutionize our knowledge of exoplanet atmospheres. In order to specifically identify which observing modes will be most useful for characterizing a diverse range of exoplanetary atmospheres, we use an information content (IC) based approach commonly used in the studies of solar system atmospheres. We develop a system based upon these IC methods to trace the instrumental and atmospheric model phase space in order to identify which observing modes are best suited for particular classes of planets, focusing on transmission spectra. Specifically, the atmospheric parameter space we cover is T = 600–1800 K, C/O = 0.55–1, [M/H] = 1–100 × Solar for an R = 1.39 R{sub J}, M = 0.59 M{sub J} planet orbiting a WASP-62-like star. We also explore the influence of a simplified opaque gray cloud on the IC. We find that obtaining broader wavelength coverage over multiple modes is preferred over higher precision in a single mode given the same amount of observing time. Regardless of the planet temperature and composition, the best modes for constraining terminator temperatures, C/O ratios, and metallicity are NIRISS SOSS+NIRSpec G395. If the target’s host star is dim enough such that the NIRSpec prism is applicable, then it can be used instead of NIRISS SOSS+NIRSpec G395. Lastly, observations that use more than two modes should be carefully analyzed because sometimes the addition of a third mode results in no gain of information. In these cases, higher precision in the original two modes is favorable.