Bond ordering and molecular spin-orbital fluctuations in the cluster Mott insulator GaTa 4 Se 8
Not Available
36 MATERIALS SCIENCE↗
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Results for “distribution function”
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Cumulants and correlation functions of net-proton, proton, and antiproton multiplicity distributions in Au+Au collisions at energies available at the BNL Relativistic Heavy Ion Collider
Here, we report a systematic measurement of cumulants, C n , for net-proton, proton, and antiproton multiplicity distributions, and correlation functions, κ n , for proton and antiproton multiplicity distributions up to the fourth order in Au+Au collisions at $\sqrt{s_{NN}}$ = 7.7, 11.5, 14.5, 19.6, 27, 39, 54.4, 62.4, and 200 GeV. The C n and κ n are presented as a function of collision energy, centrality and kinematic acceptance in rapidity, y, and transverse momentum, p T . The data were taken during the first phase of the Beam Energy Scan (BES) program (2010–2017) at the BNL Relativistic Heavy Ion Collider (RHIC) facility. The measurements are carried out at midrapidity (|y| < 0.5) and transverse momentum 0.4 < p T < 2.0 GeV/c, using the STAR detector at RHIC. We observe a nonmonotonic energy dependence ($\sqrt{s_{NN}}$ = 7.7–62.4 GeV) of the net-proton C 4 /C 2 with the significance of 3.1σ for the 0–5% central Au+Au collisions. This is consistent with the expectations of critical fluctuations in a QCD-inspired model. Thermal and transport model calculations show a monotonic variation with $\sqrt{s_{NN}}$. For the multiparticle correlation functions, we observe significant negative values for a two-particle correlation function, κ 2 , of protons and antiprotons, which are mainly due to the effects of baryon number conservation. Furthermore, it is found that the four-particle correlation function, κ 4 , of protons plays a role in determining the energy dependence of proton C 4 /C 1 below 19.6 GeV, which cannot be understood by the effect of baryon number conservation.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Macroecological distributions of gene variants highlight the functional organization of soil microbial systems
Abstract The recent application of macroecological tools and concepts has made it possible to identify consistent patterns in the distribution of microbial biodiversity, which greatly improved our understanding of the microbial world at large scales. However, the distribution of microbial functions remains largely uncharted from the macroecological point of view. Here, we used macroecological models to examine how the genes encoding the functional capabilities of microorganisms are distributed within and across soil systems. Models built using functional gene array data from 818 soil microbial communities showed that the occupancy-frequency distributions of genes were bimodal in every studied site, and that their rank-abundance distributions were best described by a lognormal model. In addition, the relationships between gene occupancy and abundance were positive in all sites. This allowed us to identify genes with high abundance and ubiquitous distribution (core) and genes with low abundance and limited spatial distribution (satellites), and to show that they encode different sets of microbial traits. Common genes encode microbial traits related to the main biogeochemical cycles (C, N, P and S) while rare genes encode traits related to adaptation to environmental stresses, such as nutrient limitation, resistance to heavy metals and degradation of xenobiotics. Overall, this study characterized for the first time the distribution of microbial functional genes within soil systems, and highlight the interest of macroecological models for understanding the functional organization of microbial systems across spatial scales.
59 BASIC BIOLOGICAL SCIENCES↗
Simulation-Based Analysis of Feeder Operation with Different PV Smart Inverter Functions on an Actual Distribution System: Preprint
High penetration of photovoltaics (PV) in distribution feeders can cause problems, such as overvoltage, reverse power flow, and large net load changes. Traditional voltage regulation devices, such as capacitors and voltage regulators, can solve some of these problems but might have some delays. Today, smart inverters are gradually being used to provide voltage regulation and frequency support in distribution systems. Different smart inverter settings have been recommended in various rules and standards; however, the potential benefits and their impacts on distribution system operation are not well compared and studied. This paper presents a comparison of different smart inverter settings as applied to a distribution system. An actual feeder model from San Diego Gas & Electric Company is used to conduct the simulation. Additionally, a load disaggregation method is proposed to disaggregate the load and PV profile for each load location using advanced metering infrastructure net load measurements. Then, different smart inverter settings are applied to the PV systems in the feeder, and the simulation results are compared. The results show that the implementation of specific functions of smart inverters can reduce voltage exceedances, and the utility can determine the specific inverter setting based on its operational requirements.
distribution system↗
Novel corrections to the momentum sum rule for nuclear structure functions
Not Available
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Lipid droplets in plants and algae: Distribution, formation, turnover and function
We report plant oils represent an energy-rich and carbon-dense group of hydrophobic compounds. These oils are not only of economic interest, but also play important, fundamental roles in plant and algal growth and development. The subcellular storage compartments of plant lipids, referred to as lipid droplets (LDs), have long been considered relatively inert oil vessels. However, research in the last decade has revealed that LDs play far more dynamic roles in plant biology than previously appreciated, including transient neutral lipid storage, membrane remodeling, lipid signaling, and stress responses. Here we discuss recent developments in the understanding of LD formation, turnover and function in land plants and algae.
59 BASIC BIOLOGICAL SCIENCES↗
Iterative Linearization for Phasor-Defined Optimal Power Dispatch
Optimal power flow (OPF) problems, which dispatch power targets to controllable generating units across a network, must generally account for non-convex constraints on power flow. Furthermore, adapting those problems so as to make them solvable with convex optimization techniques is an area of much academic and operational interest. In this paper, we present a method for solving OPF as a quadratic program by iteratively refining and re-initializing a linearized model of power flow based on the outputs of an associated nonlinear solver. The linear model on which we demonstrate this method is an adapted version of an approximation designed for use with unbalanced distribution networks. As an important benefit, the model allows for the explicit inclusion of nodal voltage phasor values in both the OPF problem's objective and its constraints, which opens the door to the idea of phasor-based control (PBC) design. We show in simulations on the IEEE 13-node test feeder that our method quickly converges to a set of phasor targets that are sufficiently precise for use in operations at the distribution level.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Investigating the vertical distribution of the disk as a function of radial action
As heating processes can broaden the distributions of radial actions and the vertical distributions of the Galactic disks, we investigate the vertical distribution of the Galactic disks as a function of radial action based on Apache Point Observatory Galactic Evolution Experiment (APOGEE) and Gaia data in order to deepen our understanding of the formation and heating history of the Galactic disks. The vertical distributions of the thin and thick Galactic disks defined in the chemical plane were fitted with a simple exponential function with a free parameter of scale height in different radial action ranges. Therefore, we were able to analyze the scale height as a function of radial action for different disk populations. We find that the distributions of radial action for both the thin and thick disks can be approximately described by pseudo-isothermal distributions, which give a statistical measurement for the temperature of the disk as indicated by the mean radial action of the star sample. Estimations of the scale heights in different radial action ranges for these pseudo-isothermal distributions of the disks seem to show fixed relationships between radial action J R and scale height h. We describe these relationships with a two-parameter function of h = √(J R /a)+b, where a and b are free parameters. When testing with a three-parameter function of h = α √(J R /a)+b, we find that this two-parameter function describes the thin disk well, but we note the function should be used with care for the thick disk. When comparing the best-fit relationships between the inner and outer disk for both of the thin and thick disks, we find that the relationships are nearly the same for the thin disks but are different for the thick disks. The inner thick disk shows a nearly flattened relationship, while the outer thick disk presents a gradually increasing relationship. This work highlights an alternative way to unveil the heating history of the disks by investigating the relationship between scale height and radial action, as these relationships encode the formation and heating history of the Galactic disks.
79 ASTRONOMY AND ASTROPHYSICS↗
Multiclass Classification Using Bayesian Multivariate Adaptive Regression Splines
We present a new Bayesian model for the problem of multiclass classification. In this model, the probabilities of class membership of a given observation are determined by the mean of a latent Gaussian distribution. The mean functions of this latent distribution consist of combinations of highly flexible basis functions of the inputs: multivariate adaptive regression splines (MARS), first developed for multiple regression. We use reversible jump Markov chain Monte Carlo to make inference on the classification model, including the number of basis functions. We compare the probabilistic classification performance of our proposed approach to existing methods on simulated and benchmark data, and compare uncertainty estimates on simulated data. Our proposed method compares favorably with existing Bayesian and frequentist multiclass classification methods in out-of-sample probabilistic classification, and uncertainty estimation of these probabilistic classifications. We examine the fit of the proposed method to a data set of hurricane storm surge levels near Delaware Bay, US, and conclude that sea level rise is a key contributor to damage delivered by storm surge.
97 MATHEMATICS AND COMPUTING↗
Fast calculation of diffraction patterns from an ensemble of aligned molecules
We report an algorithm to calculate electron diffraction patterns for molecules with anisotropic angular distribution, which is significantly faster than existing methods. The algorithm uses a transform to convert the molecular orientation distribution, which is a function of three Euler angles, to the atom-pair distribution functions which depend on the polar and azimuthal angles. The diffraction signal can then be calculated from the atom-pair distributions. We demonstrate the computation method numerically by calculating electron diffraction patterns for a symmetric top molecule (trifluoroiodomethane) and an asymmetric top molecule (formaldehyde) and show that it reduces the calculation time by approximately two orders of magnitude compared to the standard brute-force method. Here, the method can also be applied to the calculation of x-ray diffraction patterns.
74 ATOMIC AND MOLECULAR PHYSICS↗
Crystal Structure of Colloidally Prepared Metastable Ag 2 Se Nanocrystals
Structural polymorphism is known for many bulk materials; however, on the nanoscale metastable polymorphs tend to form more readily than in the bulk, and with more structural variety. One such metastable polymorph observed for colloidal Ag 2 Se nanocrystals has traditionally been referred to as the “tetragonal” phase. While there are reports on the chemistry and properties of this metastable polymorph, its crystal structure, and therefore electronic structure, has yet to be determined. We report that an anti-PbCl 2 -like structure type (space group P2 1 /n) more accurately describes the powder X-ray diffraction and X-ray total scattering patterns of colloidal Ag 2 Se nanocrystals prepared by several different methods. Density functional theory (DFT) calculations indicate that this anti-PbCl 2 -like Ag 2 Se polymorph is a dynamically stable, narrow-band-gap semiconductor. Here, the anti-PbCl 2 -like structure of Ag 2 Se is a low-lying metastable polymorph at 5–25 meV/atom above the ground state, depending on the exchange-correlation functional used.
77 NANOSCIENCE AND NANOTECHNOLOGY↗
Discrete spherical harmonic functions for texture representation and analysis
A basis of discrete harmonic functions for efficient representation and analysis of crystallographic texture is presented. Discrete harmonics are a numerical representation of the harmonics on the sphere. A finite element formulation is utilized to calculate these orthonormal basis functions, which provides several advantageous features for quantitative texture analysis. These include high-precision numerical integration, a simple implementation of the non-negativity constraint and computational efficiency. Simple examples of pole figure and texture interpolation and of Fourier filtering using these basis sets are presented.
36 MATERIALS SCIENCE↗
Factorized approach to radiative corrections for inelastic lepton-hadron collisions [Slides]
We propose a new factorized approach to QED radiative corrections (RCs) in inclusive and semi-inclusive lepton-hadron deep-inelastic scattering. The method allows the systematic resummation of the logarithmically enhanced into factorized lepton distribution and fragmentation (or jet) functions that are universal for all final states. The new approach provides a uniform treatment of RCs for the extraction of parton distribution functions, transverse momentum dependent distributions, and other partonic correlation functions from lepton-hadron collision data.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Multidimensional Distributional Neural Network Output Demonstrated in Super‐Resolution of Surface Wind Speed
Accurate quantification of uncertainty in neural network predictions remains a central challenge for scientific applications involving high-dimensional, correlated data. While existing methods capture either aleatoric or epistemic uncertainty, few offer closed-form, multidimensional distributions that preserve spatial correlation while remaining computationally tractable. In this work, we present a framework for training neural networks with a multidimensional Gaussian loss, generating a closed-form predictive distribution over outputs informed by non-identically distributed training data. Our approach captures aleatoric uncertainty by iteratively estimating the means and covariance matrices, and is demonstrated on a super-resolution example out-of-training-sample. We leverage a Fourier representation of the covariance matrix to stabilize network training and preserve spatial correlation. We introduce a novel regularization strategy—referred to as information sharing—that interpolates between image-specific and global covariance estimates, enabling convergence of the super-resolution downscaling network trained on image-specific distributional loss functions. This framework allows for efficient sampling, explicit correlation modeling, and extensions to more complex distribution families all without disrupting prediction performance. We demonstrate the method on a surface wind speed downscaling task and discuss its broader applicability to uncertainty-aware prediction in scientific models.
17 WIND ENERGY↗
Three-dimensional electronic scaffolds for monitoring and regulation of multifunctional hybrid tissues
Recently, the integration of electronic elements with cellular scaffolds has brought forth the ability to monitor and control tissue function actively by using flexible free-standing two-dimensional (2D) systems. Capabilities for electrically probing complex, physicochemical and biological three-dimensional (3D) microenvironments demand, however, 3D electronic scaffolds with well-controlled geometries and functional-component distributions. This work presents the development of flexible 3D electronic scaffolds with precisely defined dimensions and microelectrode configurations formed using a process that relies on geometric transformation of 2D precursors by compressive buckling. It demonstrates a capability to fabricate these constructs in diverse 3D architectures and/or electrode distributions aimed at achieving an enhanced level of control and regulation of tissue function relatively to that of other approaches. In addition, this work presents the integration of these 3D electronic scaffolds within engineered 3D cardiac tissues, for monitoring of tissue function, controlling tissue contraction through electrical stimulation, and initiating on-demand, local release of drugs, each through well-defined volumetric spaces. These ideas provide opportunities in fields ranging from in vitro drug development to in vivo tissue repair and many others.
3D electronic scaffolds↗
Redox and Thiols in Archaea
Low molecular weight (LMW) thiols have many functions in bacteria and eukarya, ranging from redox homeostasis to acting as cofactors in numerous reactions, including detoxification of xenobiotic compounds. The LMW thiol, glutathione (GSH), is found in eukaryotes and many species of bacteria. Analogues of GSH include the structurally different LMW thiols: bacillithiol, mycothiol, ergothioneine, and coenzyme A. Many advances have been made in understanding the diverse and multiple functions of GSH and GSH analogues in bacteria but much less is known about distribution and functions of GSH and its analogues in archaea, which constitute the third domain of life, occupying many niches, including those in extreme environments. Archaea are able to use many energy sources and have many unique metabolic reactions and as a result are major contributors to geochemical cycles. As LMW thiols are major players in cells, this review explores the distribution of thiols and their biochemistry in archaea.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Review of Power System Support Functions for Inverter-Based Distributed Energy Resources - Standards, Control Algorithms, and Trends
Penetration of renewable energy in power systems has been increasing in the past decades in response to increased global electricity demand and concerns for the environment. Distributed energy resources (DERs) based on renewables have experienced rapid growth thanks to the incentive programs and broad-based participation. With the growing prevalence of DERs, the risk of grid instability and vulnerability increases due to the intermittent nature of renewable energy. At the same time, the voltage and frequency deviation problems emerge more often when the reverse power flow occurs under supply-demand imbalance in distributed power systems. Standards and grid codes have been issued for DER inverters to interconnect with the distribution grid. The updated standard and grid codes expect DERs to provide a variety of power system support functions in order to incorporate higher DER penetration and to maximize DER value to the grid. This paper provides an overview of the power system support functions from renewable DER inverters, which are categorized as: voltage regulation by active/reactive power control, frequency regulation by active power control, voltage ride-through, and frequency ride-through. The benefits and drawbacks of each algorithm are presented and compared with its predecessor, manifesting the logic in the evolution of the algorithms.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Securing Solar for the Grid: Extreme Control Whitepaper
Emerging standards outlining desired behaviors for Distributed Energy Resources (DER), such as IEEE 1547-2018, define several device-level control functions to regulate DER power injections/consumptions in response to locally sensed grid conditions. The ability to adjust settings of aggregations of DER with standardized embedded control functionality constitutes a mechanism which can, potentially, create undesirable or deleterious effects on the power grid. The purpose of this white paper is to highlight unintended effects stemming from improperly tuned embedded control functions in Distributed Energy Resources (DER), which could be exploited by a malicious entity as a means to attack the power grid.
14 SOLAR ENERGY↗