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Results for “specific correlation”
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On the suppression and distortion of non-equilibrium fluctuations by transpiration
A fluid in a nonequilibrium state exhibits long-ranged correlations of its hydrodynamic fluctuations. In this article, we examine the effect of a transpiration interface on these correlations - specifically, we consider a dilute gas in a domain bisected by the interface. The system is held in a nonequilibrium steady state by using isothermal walls to impose a temperature gradient. The gas is simulated using both direct simulation Monte Carlo (DSMC) and fluctuating hydrodynamics (FHD). For the FHD simulations, two models are developed for the interface based on master equation and Langevin approaches. For appropriate simulation parameters, good agreement is observed between DSMC and FHD results with the latter showing a significant advantage in computational speed. For each approach, we quantify the effects of transpiration on long-ranged correlations in the hydrodynamic variables. The principal effect of transpiration is a suppression of the correlations, an outcome largely explained by a reduction in the temperature gradient due to the interface. We also observe a distortion of the temperature correlations, specifically the appearance of a new peak located near the interface.
Enhanced superconductivity by near-neighbor attraction in the doped extended Hubbard model
A recent experiment has unveiled an anomalously strong electron-electron attraction in the one-dimensional copper-oxide chain Ba 2–x Sr x CuO 3+δ . While the effect of the near-neighbor electron attraction V in the one-dimensional extended Hubbard chain has been examined recently, its effect in the Hubbard model beyond the one-dimensional chain remains unclear. Here, in this work, we report a density matrix renormalization group study of the extended Hubbard model on long four-leg cylinders on the square lattice. We find that the near-neighbor electron attraction V can notably enhance the long-distance superconducting correlations while simultaneously suppressing the charge-density-wave (CDW) correlations. Specifically, for a modestly strong electron attraction, the superconducting correlations become dominant over the CDW correlations with a Luttinger exponent K sc ~1 and strong divergent superconducting susceptibility. Our results provide a promising way to realize long-range superconductivity in the doped Hubbard model. The relevance of our numerical results to cuprate materials is also discussed.
BEYONDPLANCK IV. On end-to-end simulations in CMB analysis — Bayesian versus frequentist statistics
End-to-end simulations play a key role in the analysis of any high-sensitivity cosmic microwave background (CMB) experiment, providing high-fidelity systematic error propagation capabilities that are unmatched by any other means. In this paper, we address an important issue regarding such simulations, namely, how to define the inputs in terms of sky model and instrument parameters. These may either be taken as a constrained realization derived from the data or as a random realization independent from the data. We refer to these as posterior and prior simulations, respectively. We show that the two options lead to significantly different correlation structures, as prior simulations (contrary to posterior simulations) effectively include cosmic variance, but they exclude realization-specific correlations from non-linear degeneracies. Consequently, they quantify fundamentally different types of uncertainties. We argue that as a result, they also have different and complementary scientific uses, even if this dichotomy is not absolute. In particular, posterior simulations are in general more convenient for parameter estimation studies, while prior simulations are generally more convenient for model testing. Before BEYONDPLANCK, most pipelines used a mix of constrained and random inputs and applied the same hybrid simulations for all applications, even though the statistical justification for this is not always evident. BEYONDPLANCK represents the first end-to-end CMB simulation framework that is able to generate both types of simulations and these new capabilities have brought this topic to the forefront. The BEYONDPLANCK posterior simulations and their uses are described extensively in a suite of companion papers. In this work, we consider one important applications of the corresponding prior simulations, namely, code validation. Specifically, we generated a set of one-year LFI 30 GHz prior simulations with known inputs and we used these to validate the core low-level BEYONDPLANCK algorithms dealing with gain estimation, correlated noise estimation, and mapmaking.
Scalable Implementation of Mean-Field and Correlation Methods Based on Lie-Algebraic Similarity Transformation of Spin Hamiltonians in the Jordan–Wigner Representation
Recent work has highlighted that the strong correlation inherent in spin Hamiltonians can be effectively reduced by mapping spins to Fermions via the Jordan−Wigner transformation (JW). The Hartree−Fock method is straightforward in the Fermionic domain and may provide a reasonable approximation to the ground state. Correlation with respect to the Fermionic mean field can be recovered based on Lie-algebraic similarity transformation (LAST) with two-body correlators. Specifically, a unitary LAST variant eliminates the dependence on site ordering, while a nonunitary LAST yields size-extensive correlation energies. Whereas the first recent demonstration of such methods was restricted to small spin systems, we present efficient implementations using analytical gradients for the optimization with respect to the mean-field reference and the LAST parameters, thereby enabling the treatment of larger clusters, including systems with local spins s > $\frac{1}{2}$.
Empirical prediction of saline water atomization pressure loss and spray phase change using local flow pressure analysis
A pressure analysis technique was developed to obtain spray spatial evaporation profile in a thermal desalination process. The technique can replace temperature-based evaporation measurement methods that are challenged by liquid-phase interference. It also provides an alternative to optical methods with high cost and complexity. Fundamental analysis was developed to determine local humidity ratios from changes in local static and dynamic pressures. The analysis was applied to data obtained from an external mixing air-assist atomizer. An empirical model was developed for the pressure loss in atomization process and was used in the analysis of humidity ratio. The results were used to develop empirical correlations for local humidity ratio in spray mediums using inlet conditions. Utilizing inlet conditions to predict evaporation profiles is an important contribution as it eliminates the need to take local spray measurements. Obtaining local data is often difficult and expensive; Our method and correlation circumvent the need for that. Finally, the correlations presented in this paper apply to saline water sprays with total dissolved salt of 0-10 wt%. The salinity-specific correlations are accurate to within ±10% of experimental data. The individual models were aggregated into a unified correlation for salinities within 0-10 wt%. The unified correlation is accurate to within ±18% of experimental data.
Hospice Landscape Report
In July 2018, CMS requested assistance from Oak Ridge National Laboratory (ORNL) to provide expert data science support aimed at developing algorithms for data mining of medical data for operational and payment purposes. The project is intended to be exploratory: work is aimed at alleviating challenges associated with improper payments, specifically audit methodologies and targeting and changes to risk scores. Project goals include developing new, sophisticated methods for audit targeting and improved profile– payment error correlations, specifically focused on Medicare Part C, the program under which MAOs provide health care services to beneficiaries. ORNL conducted RADV analyses against RAPS and EDS data as well as a hospice landscape analysis per a January 2015 dataset that included Medicare beneficiaries who were in hospice in 2017 and 2018. Ongoing work under this project also involves development of predictive models for RADV investigations and hospice landscape.
Pronghorn Porous Media Model Validation with Pressure Drop Measurements
The verification and validation (V&V) of Pronghorn is imperative to assert its accuracy when predicting the fluid velocity, temperature, and pressure in high temperature gas-cooled reactors. Pronghorn is a coarse-mesh, intermediate-fidelity, and multidimensional thermal-hydraulics (TH) code developed by the Idaho National Laboratory (INL). New pebble bed experiments are used to observe the details of the fluid motion and pressure drop in the porous bed under the reactor normal operation. This paper focuses on the validation of the Pronghorn compressible and incompressible Navier-Stokes equations using the pressure drop measurements performed at the engineering-scale pebble bed facility at the Texas A&M university (TAMU). Various pressure drop correlations and porosity functions are implemented in both Pronghorn and STAR-CCM+ to compare the pressure drop due to the combined viscous and inertial resistances in the porous bed. The correlations accounting for the near-wall effect are also utilized to observe if the pressure drop estimates can be improved. Pronghorn porous media models predict the pressure drop well relative to the STAR-CCM+ simulation results and 1D correlations, and both the finite element method (FEM) and finite volume method (FVM) perform accurately. Pronghorn models are also validated with the experimental measurements given the different Reynolds number ranges and specific aspect ratios. The likelihood of the statistical significance between the pressure drop measurements and specific correlations or simulations is low provided that the overlap of their confidence intervals is more than the half of a single arm. Several validation metrics are reasonable in regard to the similar studies from other literature. The precise average pebble bed porosity estimation has much impact on the pressure drop, and the Foumeny and Montillet (dense packing) models carry out the accurate pressure drop prediction by considering the near-wall effect.
Massively parallel reporter assays and mouse transgenic assays provide correlated and complementary information about neuronal enhancer activity
High-throughput massively parallel reporter assays (MPRAs) and phenotype-rich in vivo transgenic mouse assays are two potentially complementary ways to study the impact of noncoding variants associated with psychiatric diseases. Here, we investigate the utility of combining these assays. Specifically, we carry out an MPRA in induced human neurons on over 50,000 sequences derived from fetal neuronal ATAC-seq datasets and enhancers validated in mouse assays. We also test the impact of over 20,000 variants, including synthetic mutations and 167 common variants associated with psychiatric disorders. We find a strong and specific correlation between MPRA and mouse neuronal enhancer activity. Four out of five tested variants with significant MPRA effects affected neuronal enhancer activity in mouse embryos. Mouse assays also reveal pleiotropic variant effects that could not be observed in MPRA. Our work provides a catalog of functional neuronal enhancers and variant effects and highlights the effectiveness of combining MPRAs and mouse transgenic assays.
Direct Nanoscale Characterization of Deep Levels in AgCuInGaSe 2 Using Electron Energy–Loss Spectroscopy in the Scanning Transmission Electron Microscope
A new experimental framework for the characterization of defects in semiconductors is demonstrated. Through the direct, energy-resolved correlation of three analytical techniques spanning six orders of magnitude in spatial resolution, a critical mid-bandgap electronic trap level (E V + 0.56 eV) within Ag 0.2 Cu 0.8 In 1–x Ga x Se 2 is traced to its nanoscale physical location and chemical source. This is achieved through a stepwise, site-specific correlated characterization workflow consisting of device-scale (≈1 mm 2 ) deep level transient spectroscopy (DLTS) to survey the traps present, scanning probe–based DLTS (scanning-DLTS) for mesoscale-resolved (hundreds of nanometers) mapping of the target trap state’s spatial distribution, and scanning transmission electron microscope based electron energy-loss spectroscopy (STEM-EELS) and X-ray energy-dispersive spectroscopy for nanoscale energy-, structure, and chemical-resolved investigation of the defect source. Furthermore, this first demonstration of the direct observation of sub-bandgap defect levels via STEM-EELS, combined with the DLTS methods, provides strong evidence that the longsuspected Cu In/Ga substitutional defects are indeed the most likely source of the E V + 0.56 eV trap state and serves as a key example of this approach for the fundamental identification of defects within semiconductors, in general.
Clostridioides difficile utilizes siderophores as an iron source and FhuDBGC contributes to ferrichrome uptake
ABSTRACT Clostridioides difficileremains a public health threat commonly observed following antibiotic use. Due to the importance of iron in many cell processes, most bacteria, includingC. difficile, have multiple mechanisms of acquiring iron. Previous studies have examined ferrous iron uptake inC. difficile; here we focus on the role of siderophores. In a growth assay, we show thatC. difficilecan use a variety of siderophores as the sole iron source. InC. difficile,two ABC transporters induced under low iron conditions are predicted siderophore importers: FhuDBGC and YclNOPQ. We hypothesized that these transporters are responsible for the uptake of the siderophores we tested. To investigate the specificity of these transporters, we purified the substrate binding proteins and examined siderophore binding using thermal shift. We demonstrate increased stability between one siderophore binding protein, FhuD, and the siderophore ferrichrome, suggesting a binding interaction. This specificity correlates with the inability of anΔfhuDBGCmutant to grow efficiently under iron limiting conditions in the presence of ferrichrome. WhileC. difficileused additional siderophores in our growth experiments, we did not observe increased thermal stability between the receptor proteins and any of the other siderophores tested, suggesting these siderophores do not bind these receptors and other siderophore import mechanisms remain to be elucidated. Redundancy in iron acquisition is a microbial survival adaptation to cope with the constant battle for iron within a host. Greater knowledge about howC. difficileacquires iron will provide insight about howC. difficilecolonizes and persists in the colon. IMPORTANCE This study is the first example ofC. difficilegrowing with siderophores as the sole iron source and describes the characterization of the ferric hydroxamate uptake ABC transporter (FhuDBGC). This transporter shows specificity to the siderophore ferrichrome. While not required for pathogenesis, this transporter highlights the redundancy in iron acquisition mechanisms thatC. difficileuses to compete for iron during an infection.
Bacterial communities protect the alga Microchloropsis salina from grazing by the rotifer Brachionus plicatilis
Open algal ponds are likely to succumb to unpredictable, devastating crashes by one or several deleterious species. Developing methodology to mitigate or prevent pond crashes will increase algal biomass production, drive down costs for algae farmers, and reduce the risk involved with algae cultivation, making it more favorable for investment by entrepreneurs and biotechnology companies. In this work, we postulate that specific algal-bacterial co-cultures grown with the green alga Microchloropsis salina prevented grazing by the marine rotifer, Brachionus plicatilis. We obtained seven algal-bacterial co-cultures from crashed rotifer cultures, maintained them in co-culture with Microchloropsis salina , and used a microalgal survival assay to determine that algae present in each co-culture were protected from rotifer grazing and culture crash. After months of routinely diluting and maintaining these seven algal-bacterial co-cultures, we repeated the assay and found the opposite result: none of the seven bacterial communities protected the microalgae from rotifer grazing. We performed 16S rRNA gene amplicon sequencing on the protective and nonprotective co-culture samples and identified substantial differences in the makeup of the bacterial communities. Protective bacterial communities consisted primarily of Alphaproteobacteria (Rhodobacteraceae) and Gammaproteobacteria ( Marinobacter , Pseudomonas, Methylophaga ) while nonprotective bacterial communities were less diverse and missing many putatively crucial members. We compared the seven protective communities with the seven nonprotective communities and we correlated specific bacterial amplicon sequence variants with algal protection. With these data, our future research will aim to define and develop an engineered-microbiome that can stabilize industrial Microchloropsis salina cultures by protecting against grazer-induced pond crashes.
Does plasma jet sintering follow an Arrhenius-type expression?
Atmospheric pressure, ambient temperature plasma jets have become a promising candidate for material processing in parallel with developments in additive manufacturing. Recent work has shown that plasma jets can be used to sinter printed nanoparticles at temperatures much lower than typically required for conventional thermal sintering. In this report we conduct a mechanistic study on plasma jet sintering that correlates specific energy input with the electrical conductivity of printed silver films after sintering. Increasing the specific energy input accelerated the sintering process following an Arrhenius-like exponential trend across a large range of conditions, including both helium and argon plasma jets. Although an exponential relationship is also found with the plasma heated substrate temperature, independent studies indicate that heating is not the primary mechanism. These results suggest there is a general behavior that couples the plasma jet with the surface.
Towards linking lab and field lifetimes of perovskite solar cells
Metal halide perovskite solar cells (PSCs) represent a promising low-cost, thin-film photovoltaic (PV) technology, with unprecedented power conversion efficiencies (PCEs) obtained for both single-junction and tandem applications. To push PSCs toward commercialization, it is critical, albeit challenging, to understand device reliability under real-world outdoor conditions where multiple stress factors (e.g., light, heat, humidity) coexist, generating complicated degradation behaviors. It is necessary to identify accelerated indoor testing protocols - which can correlate specific stressors with observed degradation modes in fielded devices - to quickly guide PSC development. Here, we use a state-of-the-art p-i-n PSC stack (with PCE up to ~25.5%) to show that indoor accelerated stability tests can predict our 6-month outdoor aging tests. Device degradation rates under illumination and at elevated temperatures are most instructive for understanding outdoor device reliability. Further, we also find that the indium tin oxide (ITO)/self-assembled monolayer (SAM)-based hole transport layer (HTL)/perovskite interface most strongly affects our device operation stability. Improving the ion-blocking properties of the SAM HTL increases averaged device operational stability at 50 degree C-85 °C by a factor of ~2.8, reaching over 1000 h at 85 °C and to near 8200 h at 50 °C with a projected 20% degradation, which is among the best to date for high-efficiency p-i-n PSCs.
Faster network disruption from layered oscillatory dynamics
Nonlinear complex network-coupled systems typically have multiple stable equilibrium states. Following perturbations or due to ambient noise, the system is pushed away from its initial equilibrium, and, depending on the direction and the amplitude of the excursion, it might undergo a transition to another equilibrium. It was recently demonstrated [M. Tyloo, J. Phys. Complex. 3 03LT01 (2022)] that layered complex networks may exhibit amplified fluctuations. Here, I investigate how noise with system-specific correlations impacts the first escape time of nonlinearly coupled oscillators. Interestingly, I show that, not only the strong amplification of the fluctuations is a threat to the good functioning of the network but also the spatial and temporal correlations of the noise along the lowest-lying eigenmodes of the Laplacian matrix. Finally, I analyze first escape times on synthetic networks and compare noise originating from layered dynamics to uncorrelated noise.
Diagnosis of 3D magnetic field and mode composition in MHD turbulence with Y -parameter
ABSTRACT Magnetic fields are crucial in numerous astrophysical processes within the interstellar medium (ISM). However, the detailed determination of magnetic field geometry is notoriously challenging. Based on the modern magnetohydrodynamic (MHD) turbulence theory, we introduce a novel statistical technique, the ‘Y-parameter’, to decipher the magnetic field inclination in the ISM and identify dominant turbulence modes. The Y-parameter, calculated as the ratio of anisotropies of different Stokes parameter combinations, displays contrasting trends with the mean-field inclination angle in Alfvénic and compressible turbulence modes. A Y-parameter value around 1.5 ± 0.5 provide a statistical boundary to determine the dominant MHD turbulence modes. We have discovered specific correlations between the Y-parameter value and the inclination angle that unveil the dominant turbulence mode. This methodology, when applied to future radio polarization surveys such as LOFAR and SKA, promises to significantly enhance our knowledge of 3D magnetic field in the ISM and improve our understanding of interstellar turbulence.
Stochastic modeling of x-ray superfluorescence
An approach to modeling the dynamics of x-ray amplified spontaneous emission and superfluorescence, the phenomenon of collective x-ray emission initiated by intense pulses of x-ray free-electron lasers, is developed based on stochastic partial differential equations. The equations are derived from first principles, and the relevant approximations, derivation steps, and extensions specific to stimulated x-ray emission are presented. The resulting equations take the form of three-dimensional generalized Maxwell-Bloch equations augmented with noise terms for both field and atomic variables. The derived noise terms possess specific correlation properties that enable the correct reconstruction of spontaneous emission. Consequently, the developed theoretical formalism is universally suitable for describing all stages of stimulated x-ray emission: spontaneous emission, amplified spontaneous emission, and superfluorescence. Here, we present numerical examples that illustrate various properties of the emitted field, including spatiotemporal coherence and spectral-angular and polarization characteristics. We anticipate that the proposed theoretical framework will establish a robust foundation for interpreting measurements in stimulated x-ray emission spectroscopy, modeling x-ray laser oscillators, and describing other experiments leveraging x-ray superfluorescence.
Microstructural and infiltration properties of woven preforms during chemical vapor infiltration
Interface-resolved direct numerical simulations (DNSs) of chemical vapor infiltration (CVI) have been performed over a range of furnace-operating conditions (Thiele moduli) and for practical woven preform geometries. A level-set method is used to resolve the geometry of the initial preform at tow scale. The interface between the vapor and solid phase is then evolved in time through the entire CVI densification cycle, fully resolving the time-varying topology between the two phases. In contrast to previous level-set methods for CVI simulation, the physical reaction and diffusion processes govern the level-set movement in the current approach. The surface deposition kinetics is described by the usual one-step model. In this paper, the DNS data are used to study the evolving porosity, surface-to-volume ratio, and flow infiltration properties (permeability and effective diffusivities). Additionally, comparisons are made to popularly-assumed structure functions and the standard, Kozeny–Carmen porous media model commonly employed in modeled CFD simulations of CVI. The virtual DNS experiments reveal a Thiele modulus and preform geometry (fabric layup) dependence which the existing microstructural and infiltration models are not able to describe throughout the entire densification process. The DNS-based, woven geometry-specific correlations can be applied directly to mean-field, furnace-scale CFD simulations.