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The notion of squeezing in spin systems is clarified, and the principle for spin squeezing is shown. Two twisting schemes are proposed as building blocks for spin squeezing and are shown to reduce the standard quantum noise, s/2, of the coherent S-spin state down to the order of S(sup 1/3) and 1/2. Applications to partition noise suppression are briefly discussed.
Exposure of plants to sodium (Na) and salinity may increase glycine betaine accumulation in tissues. To study this, red-beet cvs. Scarlet Supreme and Ruby Queen, were grown for 42 days in a growth chamber using a re-circulating nutrient film technique with 0.25 mmol/L K and either 4.75 mmol/L (control) or 54.75 mmol/L (saline) Na (as NaCl). Plants were harvested at weekly intervals and measurements were taken on leaf water relations, leaf photosynthetic rates, chlorophyll fluorescence, chlorophyll levels, glycine betaine levels, and tissue elemental composition. Glycine betaine accumulation increased under salinity and this accumulation correlated with higher tissue levels of Na in both cultivars. Na accounted for 80 to 90% of the total cation uptake under the saline treatment. At final harvest (42 days), K concentrations in laminae ranged from approximately 65-95 micromoles g-1 dry matter (DM), whereas Na in shoot tissue ranged from approximately 3000-4000 micromoles g-1. Leaf sap osmotic potential at full turgor [psi(s100)] increased as lamina Na content increased. Glycine betaine levels of leaf laminae showed a linear relationship with leaf sap [psi(s100)]. Chlorophyll levels, leaf photosynthetic rates, and chlorophyll fluorescence were not affected by Na levels. These results suggest that the metabolic tolerance to high levels of tissue Na in red-beet could be due to its ability to synthesize and regulate glycine betaine production, and to control partitioning of Na and glycine betaine between the vacuole and the cytoplasm.
Living cells segregate molecules and reactions in various subcellular compartments known as organelles. Spatial organization is likely essential for expanding the biochemical functions of synthetic reaction systems, including artificial cells. Many studies have attempted to mimic organelle functions using lamellar membrane-bound vesicles. However, vesicles typically suffer from highly limited transport across the membranes and an inability to mimic the dense membrane networks typically found in organelles such as the endoplasmic reticulum. Here, we describe programmable synthetic organelles based on highly stable nonlamellar sponge phase droplets that spontaneously assemble from a single-chain galactolipid and nonionic detergents. Due to their nanoporous structure, lipid sponge droplets readily exchange materials with the surrounding environment. In addition, the sponge phase contains a dense network of lipid bilayers and nanometric aqueous channels, which allows different classes of molecules to partition based on their size, polarity, and specific binding motifs. The sequestration of biologically relevant macromolecules can be programmed by the addition of suitably functionalized amphiphiles to the droplets. We demonstrate that droplets can harbor functional soluble and transmembrane proteins, allowing for the colocalization and concentration of enzymes and substrates to enhance reaction rates. Droplets protect bound proteins from proteases, and these interactions can be engineered to be reversible and optically controlled. Our results show that lipid sponge droplets permit the facile integration of membrane-rich environments and self-assembling spatial organization with biochemical reaction systems.
A recursive algorithm was designed to invert large, dense, symmetric, positive definite matrices using small amounts of computer core, i.e., a small fraction of the core needed to store the complete matrix. The described algorithm is a generalized Gaussian elimination technique. Other algorithms are also discussed for the Cholesky decomposition and step inversion techniques. The purpose of the inversion algorithm is to solve large linear systems of normal equations generated by working geodetic problems. The algorithm was incorporated into a computer program called SOLVE. In the past the SOLVE program has been used in obtaining solutions published as the Goddard earth models.
In this paper, we analyze and compare the performance on a hypercube multiprocessor of some of the major multigrid techniques used in practice. The model problem considered here is that of solving the 2-D incompressible Navier-Stokes equations representing the flow between two parallel plates. Results obtained by implementing the different multigrid schemes on an iPSC are presented. Effects on the overall performance of various parameters of the algorithms, of the partitioning strategies employed, and of some of the characteristics of the underlying architecture are discussed.
This dataset provides partitioned evapotranspiration (ET, the combined loss of water from soil and plant surfaces) anomalies during heatwave events—soil evaporation (E) and transpiration (T)—for 268 heatwave events across 32 National Ecological Observatory Network (NEON) flux sites in the contiguous United States from 2019–2021. Using an ensemble of four high-frequency turbulence methods (Flux-variance Similarity, Conditional Eddy Covariance [CEC], CEC with Water-Use Efficiency, and Conditional Eddy Accumulation; see Zahn and Bou-Zeid 2024), half-hourly transpiration-to-evapotranspiration (T/ET) ratios were derived from 20 hertz (Hz, cycles per second) eddy covariance measurements of carbon dioxide (CO₂) and water vapor (H₂O) concentrations. The dataset spans six vegetation types including evergreen and deciduous forests, grasslands, cultivated crops, shrublands, and emergent herbaceous wetlands. Data Package Contents: The dataset includes a single CSV (comma-separated values) file containing daily anomalies (deviations from baseline conditions) for transpiration (Delta_T), evaporation (Delta_E), total evapotranspiration (Delta_ET), and T/ET ratio (Delta_T_ET) during each day of identified heatwave events. The file also includes site codes, dates, heatwave event identifiers, and day-of-heatwave indicators. The CSV file can be opened with spreadsheet software (Microsoft Excel, Google Sheets) or programming environments (Python, R, MATLAB). This resource enables researchers to investigate ecosystem-specific responses to thermal extremes, validate land surface model partitioning of ET fluxes, and examine feedbacks between water cycling and surface energy balance during heatwaves. The dataset is particularly valuable for studies linking vegetation hydraulic strategies to climate resilience, as it captures the divergent responses of shallow-rooted versus deep-rooted ecosystems. Potential applications include improving drought early warning systems, informing irrigation management strategies, and advancing our mechanistic understanding of land-atmosphere interactions under extreme heat conditions.
Abstract. Aerosols are a source of great uncertainty in radiative forcing predictions and have poorly understood health impacts. Most aerosol mass is formed in the atmosphere from reactive gas-phase organic precursors, forming secondary organic aerosol (SOA). Semivolatile organic compounds (SVOCs) (effective saturation concentration, C*, of 10−1–103 µg m−3) comprise a large fraction of organic aerosol, while intermediate-volatility organic compounds (IVOCs) (C* of 103–106 µg m−3) and volatile organic compounds (VOCs) (C* ≥ 106 µg m−3) are gas-phase precursors to SOA and ozone. The Comprehensive Thermal Desorption Aerosol Gas Chromatograph (cTAG) is the first single instrument simultaneously quantitative for a broad range of compound-specific VOCs, IVOCs and SVOCs. cTAG is a two-channel instrument which measures concentrations of C5–C16 alkane-equivalent-volatility VOCs and IVOCs on one channel and C14–C32 SVOCs on the other coupled to a single high-resolution time-of-flight mass spectrometer, achieving consistent quantification across 15 orders of magnitude of vapor pressure. cTAG obtains concentrations hourly and gas–particle partitioning for SVOCs every other hour, enabling observation of the evolution of these species through oxidation and partitioning into the particle phase. Online derivatization for the SVOC channel enables detection of more polar and oxidized species. In this work we present design details and data evaluating key parameters of instrument performance such as I/VOC collector design optimization, linearity and reproducibility of calibration curves obtained using a custom liquid evaporation system for I/VOCs and the effect of an ozone removal filter on instrument performance. Example timelines of precursors with secondary products are shown, and analysis of a subset of compounds detectable by cTAG demonstrates some of the analytical possibilities with this instrument.
Nanotechnology has created a demand for new fabrication methods with an emphasis on simple, low-cost techniques. Directional solidification of eutectics (DSE) is an unconventional approach in comparison to low-temperature biomimetic approaches. A technical challenge for DSE is producing microstructural architectures on the nanometer scale. In both processes, the driving force is the minimization of Gibb's free energy. Selfassembly by biomimetic approaches depends on weak interaction forces between organic molecules to define the architectural structure. The architectural structure for solidification depends on strong chemical bonding between atoms. Constituents partition into atomic-level arrangements at the liquid-solid interface to form polyphase structures, and this atomic-level arrangement at the liquid-solid interface is controlled by atomic diffusion and total undercooling due to composition (diffusion), kinetics, and curvature of the boundary phases. Judicious selection of the materials system and control of the total undercooling are the keys to producing structures on the nanometer scale. The silicon-titanium silicide (Si-TiSi2) eutectic forms a rod structure under isothermal cooling conditions. At the NASA Glenn Research Center, directional solidification was employed along with a thermal gradient to promote uniform rods oriented with the thermal gradient. The preceding photomicrograph shows the typical transverse microstructure of a solidified Si-TiSi2 eutectic composition. The dark and light gray regions are Si and TiSi2, respectively. Preferred rod orientation along the thermal gradient was poor. The ordered TiSi2 rods have a narrow distribution in diameter of 2 to 3 m, as shown. The rod diameter showed a weak dependence on process conditions. Anisotropic etch behavior between different phases provides the opportunity to fabricate structures with high aspect ratios. The photomicrographs show the resulting microstructure after a wet chemical etch and a dry plasma etch. The wet chemical etches the silicon away, exposing the TiSi2 rods, whereas plasma etching preferentially etches the Si-TiSi2 interface to form a crater. The porous architectures are applicable to fabricating microdevices or creating templates for part fabrication. The porous rod structure can serve as a platform for fabricating microplasma devices for propulsion or microheat exchangers and for fabricating microfilters for miniatured chemical reactors. Although more work is required, self-assembly from DSE can have a role in microdevice fabrication.
Two approximations to convective transport have been implemented in an offline chemistry transport model (CTM) to explore the impact on calculated atmospheric CO2 distributions. GlobalCO2 in the year 2000 is simulated using theCTM driven by assimilated meteorological fields from the NASA s Goddard Earth Observation System Data Assimilation System, Version 4 (GEOS-4). The model simulates atmospheric CO2 by adopting the same CO2 emission inventory and dynamical modules as described in Kawa et al. (convective transport scheme denoted as Conv1). Conv1 approximates the convective transport by using the bulk convective mass fluxes to redistribute trace gases. The alternate approximation, Conv2, partitions fluxes into updraft and downdraft, as well as into entrainment and detrainment, and has potential to yield a more realistic simulation of vertical redistribution through deep convection. Replacing Conv1 by Conv2 results in an overestimate of CO2 over biospheric sink regions. The largest discrepancies result in a CO2 difference of about 7.8 ppm in the July NH boreal forest, which is about 30% of the CO2 seasonality for that area. These differences are compared to those produced by emission scenario variations constrained by the framework of Intergovernmental Panel on Climate Change (IPCC) to account for possible land use change and residual terrestrial CO2 sink. It is shown that the overestimated CO2 driven by Conv2 can be offset by introducing these supplemental emissions.
A domain-decomposed A-ϕ formulation based on Lagrange multipliers is proposed to simulate low-frequency elec- tromagnetic problems. This method partitions the computational domain into smaller subdomains, allowing each subdomain to be independently formulated using Lagrange multipliers as Dirichlet boundary conditions, while ensuring continuity of the fields across the interfaces. A mixed finite element method, utilizing both vector and scalar basis functions, is employed to discretize the formulation, resulting in a global system to be solved. The proposed method is validated using TEAM Problem 7 at 50 Hz, demonstrating its effectiveness in handling complex geometries and addressing the low-frequency breakdown issues commonly encountered in traditional finite element methods.
Elongation of main stem internodes and petioles of soybeans, Glycine max 'Ransom,' was examined in response to various photoperiod/temperature combinations and to end-of-day (EOD) light quality. Photoperiod treatments consisted of 10, 14, and 16 h in combination with day/night temperatures of 18/14, 22/18, 26/22, 30/26, and 34/30 C. The EOD treatments consisted of exposing plants to illumination from either incandescent (high far-red component, FR) or fluorescent (high red component, R) lamps during the final 0.5 h of a 10-h photoperiod. Internode elongation was not significantly promoted by the photoperiod treatments, and, in fact, under the two highest temperature regimes, internode elongation was suppressed under the longer photoperiods. Petiole elongation, however, was enhanced under the longer photoperiods at all temperatures. In the EOD light study, internode and petiole elongation was significantly greater on plants exposed to 0.5 h EOD from incandescent lamps than from fluorescent. Under the incandescent EOD treatment, plants increased dry matter production by 41% and exhibited greater partitioning of assimilates in stem and root portions than under fluorescent EOD.
A multimodal chemical imaging approach has been developed and applied to detail the dynamic, atomic-scale changes associated with oxidation of a zirconium alloy (Zircaloy-4). Scanning transmission electron microscopy, a gas-phase reactor chamber attached to an atom probe tomography instrument, and synchrotron-based X-ray absorption near-edge spectroscopy were employed to reveal morphology, composition, crystal, and electronic structure changes that occur during initial stages of oxidation at 300 °C. Oxidation was carried out in 10 mbar O 2 gas for short exposure times of 1 and 5 min. A multilayered oxide film with a cubic ZrO adjacent to the oxide/metal interface, a nanoscopic transition region with a graded composition of ZrO 2-x (where 0 < x < 1), and tetragonal ZrO 2 in the outermost oxide were formed. Partitioning of the major alloying element (tin) to the oxide/metal interface and heterogeneously within the oxide accompanied the development of the layered oxide. Our work provides a rapid, high-throughput approach for detailed characterisation of initial stages of zirconium alloy oxidation at an accelerated time scale, with implications for several other alloy systems.
The bubble sliding after departing from nucleation site is frequently observed in flow boiling systems and, the crucial impact on wall heat transfer has been evidenced through many experiments. As a result, the heat transfer modeling associated with sliding bubble has become one of the subjects of great attention in CFD boiling heat transfer community. The modeling efforts are primarily aimed at improving the existing Heat Flux Partitioning (HFP) model via the implementation of sliding bubble-induced heat transfer. The performance of HFP model depends inherently on the fidelity of sub-models used to predict the fundamental bubble parameters (e.g., bubble departure/lift-off diameter). In the same context, the accurate prediction of sliding bubble parameters (e.g., sliding bubble growth, sliding bubble velocity) is essential to achieving the successful heat transfer modeling associated with sliding bubble. Of many sliding bubble parameters, this paper deals with the sliding bubble velocity. Specifically, the force balance model was assessed in view of the sliding bubble velocity prediction. The parametric effect of key sub-models (e.g., drag force, bubble growth models) used in the force balance equation was investigated. The experimental data from Maity (2000) and Yoo et al. (2016) were used for demonstrating the model predictive performance. It was found that the force balance model proposed in this study was able to predict well the bubble sliding velocity based on the accurate prediction of bubble growth during sliding. The predictive performance was proven with the experimental data measured under various subcooled boiling conditions of both water and refrigerant (NOVEC-7000) flowing upward in vertical channels.
Lateral groundwater flow (LGF) is an important hydrologic process in controlling water table dynamics. Due to the relatively coarse spatial resolutions of land surface models, the representation of this process is often overlooked or overly simplified. In this study, we developed a hillslope-based lateral groundwater flow model. Specifically, we first developed a hillslope definition model based on an existing watershed delineation model to represent the subgrid spatial variability in topography. Building upon this hillslope definition, we then developed a physical-based lateral groundwater flow using Darcy’s equation. This model explicitly considers the relationships between the groundwater table along the hillslope and the river water table levels. We coupled this intra-grid model to the land component (E3SM Land Model: ELM) and river component (MOdel for Scale Adaptive River Transport: MOSART) of the Energy Exascale Earth System Model (E3SM). We tested both the hillslope definition model and the lateral groundwater flow model and performed sensitivity experiments using different configurations. Simulations for a single grid cell at 0.5°×0.5° within the Amazon basin show that the definition of hillslope is the key to modeling lateral flow processes and the runoff partition between surface and subsurface can be dramatically changed using the hillslope approach. Although our method provides a pathway to improve the lateral flow process, future improvements are needed to better capture the subgrid structure to account for the spatial variability in hillslopes within the simulated grid of land surface models.
Planets undergo differentiation that includes segregation of metal from silicate at high temperatures and pressures ranging from deep planetary core pressures (>300 GPa for Earth)to very shallow conditions of asteroids (<100 MPa).The multi-anvil solid media apparatus accesses the middle part of this range from 3 to 30 GPa –pressure relevant to the interior of Mercury, Venus, Earth, Earth’s Moon, and Mars. Early planets are thought to have experienced high temperatures from a combination of heat sources including radioactive decay, gravitational and accretional heating, and impact processes. These heating events led to melting of mantles and cores, thus requiring an understanding of solid-liquid equilibria in metal-silicate systems. In 2006 we established a multi-anvil facility at NASA-JSC combining an 880 ton press and a Kawai/Walker type module from Rockland Research. Our high PT work has been greatly facilitated by use of the COMPRES multi-anvil assemblies (1). Our recent work has included studies of element partitioning between liquid metal and liquid silicate(e.g., 2), as well as between minerals and melts(e.g., 3), both of which have led to better constraints on the timing and conditions of planetary differentiation(e.g. 4). Several examples involving sustained efforts will be summarized below and for the presentation. The distribution of siderophile (iron-loving) elements between core and mantle is controlled by metal-silicate equilibrium across a wide range of pressures. Therefore, experimentation across this pressure range helps to calibrate elemental partitioning models that can be applied to planets, and used to predict mantle chemistry and composition during planetary differentiation. Our studies have focused on a wide range of siderophile elements (refractory Ni, Co, W, Mo; volatile P, Ga, Cu, Sn, Sb; highly siderophile Au, Pd) that have constrained partitioning, valence, and isotopic fractionation, and applied to Earth, Moon, and Mars. When molten mantles (magma oceans) cool enough to initiate crystallization, the solids precipitate at depth and in large planets this involves high pressure phases like garnet, majorite, akimotoite, and ringwoodite. As these solids precipitate they can segregate from liquid by density contrasts, thus causing elemental fractionation which can be used to decipher timing of differentiation. Mineral/melt and metal/silicate equilibria in our lab have helped to better understand high pressure fractionation of isotopic parent/daughter pairs Hf/W, Mn/Cr, Pd/Ag, Pt/Os, Re/Os, and U/Pb, and their application to Earth, Moon and Mars. There remains great potential for multi-anvil experimentation to shed light on many pressure–dependent aspects of planetary evolution such as core formation, high pressure phase equilibria, redox equilibria, and volatile evolution and storage. References1. Leinenweber, K., et al.(2012) American Mineralogist,97, 353–368. 2.Righter, K., et al.(2020) Geochem. Persp. Lett.15, 1-6.3. Righter, K., et al.(2020) Met. Planet. Sci 55, 2741-2757.4. Righter, K., et al.(2020)Earth and Planetary Science Letters,552, 116590.
Abstract Many Earth system models (ESMs) approximate surface emissivity as a broadband constant. This approximation reduces the computational burden, yet omits the spectral structure of emissivity and atmospheric absorption. Neglecting spectral variation in surface emission introduces biases in longwave (LW) atmospheric fluxes and heating. Biases are strongest over surfaces with strongly varying emissivity and minimal atmospheric opacity. We examine these biases over water, ice, and snow surfaces. We partition spectral emissivity into the 16 spectral bands utilized by a single‐column atmospheric radiative transfer model (RRTMG_LW) commonly used in ESMs. We quantify flux and heating biases introduced by broadband assumptions relative to the spectrally resolved case for standard atmospheric profiles over each surface type. Current assumptions tend to overestimate upwelling surface fluxes; for example, the greybody assumption overestimates flux by 1.6 W/m 2 (0.52%) at the bottom of a mid‐latitude winter atmosphere over ice, and by 2.33 (1.0%) at the top of atmosphere. The blackbody assumption tends to artificially cool Earth's surface, stabilizing the lower troposphere. Interestingly, the optimal broadband emissivity can deviate from the Planck‐weighted mean by up to 3% depending on surface type and atmospheric profile. We investigate bias sensitivity to surface temperature, cloud water path, and atmospheric water vapor. Bias is most sensitive to water vapor content, and least sensitive to cloud water path. Lastly, we show that a modified greybody method with updated broadband values can reduce total surface flux bias up to 1.69 , comparable to a five‐band approach and at a fraction of the computational cost.
During the 1997 Photochemistry of Ozone Loss in the Arctic Region in Summer (POLARIS) mission, simultaneous in situ observations of NOx and HOx radicals, their precursors, and the radiation field were obtained in the lower stratosphere. We use these observations to evaluate the primary mechanisms that control NOx-HNO3 exchange and to understand their control over the partitioning between NO2 and HNO3 in regions of continuous sunlight. We calculate NOx production (PNOx) and loss (LNOx) in a manner directly constrained by the in situ measurements and current rate constant recommendations, using approaches for representing albedo, overhead O3 and [OH] that reduce model uncertainty. We find a consistent discrepancy of 18% between modeled rates of NOx production and loss (LNOx = 1.18P(sub NOx)), which is within the measurement uncertainty of +/- 27%. The partitioning between NOx production processes is [HNO3 + OH (41 +/- 2)%; HNO3 + hv (59 +/- 2)%] and between NOx loss processes is [NO2 + OH, 90% to >97%; BrONO2 + H2O, 10% to <3%]. The steady-state description of NOx-HNO3 exchange reveals the significant influence of the tight correlation between the photolysis rate of HNO3 and [OH] established by in situ measurements throughout the lower stratosphere. Parametrizing this relationship, we find: (1) the steady-state value of [NO2](sub 24h-avg)/[HNO3] in the continuously sunlit, lower stratosphere is a function only of temperature and number density; and (2) the partitioning of NOx production between HNO3 + OH and HNO3 + hv is nearly constant throughout most of the lower stratosphere. We describe a methodology (functions of latitude, day, temperature, and pressure) for accurately predicting the steady-state value of [NO2](sub 24h-avg)/[HNO3] and the partitioning of NOx production within these regions. The results establish a metric to compare observations of [NO2](sub 24h-avg)/[HNO3] within the continuously sunlit region and provide a simple diagnostic for evaluating the accuracy of models that attempt to describe the coupled NOx-HOx photochemistry in the lower stratosphere.
Abstract Background The Basic Local Alignment Search Tool (BLAST) is a suite of commonly used algorithms for identifying matches between biological sequences. The user supplies a database file and query file of sequences for BLAST to find identical sequences between the two. The typical millions of database and query sequences make BLAST computationally challenging but also well suited for parallelization on high-performance computing clusters. The efficacy of parallelization depends on the data partitioning, where the optimal data partitioning relies on an accurate performance model. In previous studies, a BLAST job was sped up by 27 times by partitioning the database and query among thousands of processor nodes. However, the optimality of the partitioning method was not studied. Unlike BLAST performance models proposed in the literature that usually have problem size and hardware configuration as the only variables, the execution time of a BLAST job is a function of database size, query size, and hardware capability. In this work, the nucleotide BLAST application BLASTN was profiled using three methods: shell-level profiling with the Unix “time” command, code-level profiling with the built-in “profiler” module, and system-level profiling with the Unix “gprof” program. The runtimes were measured for six node types, using six different database files and 15 query files, on a heterogeneous HPC cluster with 500+ nodes. The empirical measurement data were fitted with quadratic functions to develop performance models that were used to guide the data parallelization for BLASTN jobs. Results Profiling results showed that BLASTN contains more than 34,500 different functions, but a single function, RunMTBySplitDB, takes 99.12% of the total runtime. Among its 53 child functions, five core functions were identified to make up 92.12% of the overall BLASTN runtime. Based on the performance models, static load balancing algorithms can be applied to the BLASTN input data to minimize the runtime of the longest job on an HPC cluster. Four test cases being run on homogeneous and heterogeneous clusters were tested. Experiment results showed that the runtime can be reduced by 81% on a homogeneous cluster and by 20% on a heterogeneous cluster by re-distributing the workload. Discussion Optimal data partitioning can improve BLASTN’s overall runtime 5.4-fold in comparison with dividing the database and query into the same number of fragments. The proposed methodology can be used in the other applications in the BLAST+ suite or any other application as long as source code is available.