Density Inversion Research Articles

RESEARCH ON DEMONSTRATE TRANSPORTATION DEVELOPMENT WITH HEAT MAP

Abstract. Heat map is an intuitive and accurate visualization tool for spatial data, which is wildly used in many fields. Based on analysis and setting the various layer weights and technical levels of traffic lines, we can use heat map to demonstrate the distribution state and development level of transportation in certain region, with using the comprehensively methods of inverse distance weight, histogram equalization, density compensation and repetitive parameter iteration. The heat map rule describes the rules of traffic line weighting, line-to-poly modification, dot density adjustment and liner fitting, et al, which can extract and demonstrate transportation development index accurately. Based on traffic layer of global geographic data in some Asian and African countries, heat map of transportation development index test has been done to verify the feasibility and reliability.

Partially accreted crusts of neutron stars

Context. Neutron stars in low-mass binary systems are subject to accretion when material originating from the companion star accumulates on the surface. In most cases, the justified and common assumption in studying the properties of the neutron star crust is the fully accreted crust approximation. However, observations of some X-ray transient sources indicate that the original crust has not been completely replaced by accreted material, but is partly composed of the compressed original crust. Aims. The crust of an accreting neutron star beyond the fully accreted crust approximation was studied; a two-part (or hybrid) crust made of the original crust that is compressed and of the accreted material crashing onto it was reconstructed as a function of the accretion stage. The differences in the composition and energy sources for the fully accreted and hybrid crusts influence the cooling and transport properties. Methods. A simple semi-empirical formula of a compressible liquid drop was used to compute the equation of state and composition of the hybrid crust. Calculations were based on the single-nucleus model, with a more accurate treatment of the neutron drip point. We compared the nuclear reactions triggered by compression in the original crust and in the accreted matter part of the hybrid crust. We discuss another crust compression astrophysical phenomenon related to spinning neutron stars. Results. The compression of the originally catalyzed outer crust triggers exothermic reactions (electron captures and pycnonuclear fusions) that deposit heat in the crust. The heat sources are cataloged as a function of the compression until the fully accreted crust approximation is reached. The pressure at which neutron drip occurs is a nonmonotonic function of the depth, leading to a temporary neutron drip anomaly. The additional potential source of energy for partially accreted crusts is the occurrence of a density inversion phenomenon between some compressed layers. Conclusions. The original crust of a neutron star cannot be neglected for the initial period of accretion, when the original crust is not fully replaced by the accreted matter. The amount of heat associated with the compression of the original crust is on the same order of magnitude as that from the sources acting in the accreted part of the hybrid crust.

Evaluation of long-term antibody kinetics in healthcare workers vaccinated with inactivated COVID-19 Vero cell vaccine (CoronaVac), a propensity score-matched observational study

ObjectivesThis study aimed to evaluate the long-term antibody kinetics after vaccinating with an inactivated COVID-19 Vero cell vaccine (CoronaVac) in healthcare workers (HCWs) at a single center in Turkey. MethodsFor this prospective observational study, Chemiluminescence immunoassay (CLIA) and enzyme-linked immunosorbent assay (ELISA) were used for the determination of binding antibodies (bAb) and neutralizing antibodies (nAb), respectively. Antibody kinetics were compared for the potential influencing factors, and propensity score analysis was performed to match the subcohort for age. ResultsEarly bAb and nAb response was achieved in all 343 participants. Titers of bAbs against SARS-CoV-2 on 42 days post-vaccination (dpv) were higher in HCWs who were aged <40 years and who had a history of COVID-19. SARS-CoV-2 bAb levels in HCWs on days 42 (n = 97), 90 (n = 97), and 180 (n = 97) were 175 IU/ml (3.9-250), 107 IU/ml (2.4-250), and 66.1 IU/ml (2.57-250), respectively (p<0.001). SARS-CoV-2 bAb (p<0.001) and nAb (p<0.001) titers decreased significantly over time. There was a high negative correlation between SARS-CoV-2 antibody titers and inverse optic density of nAb responses (Pearson correlation coefficient: -0.738, p<0.001). ConclusionsWhen the antibody responses were compared, it was seen that the vaccine immunogenicity was better in those who had prior COVID-19 history and were aged <40 years. In the course of time, it was determined that there was a significant decrease in bAb and nAb responses after the 90th day. These results may guide approval decisions for booster COVID-19 vaccines.

Alcove formation in dissolving cliffs driven by density inversion instability

We demonstrate conditions that give rise to cave-like features commonly found in dissolving cliffsides with a minimal two-phase physical model. Alcoves that are wider at the top and tapered at the bottom, with sharp-edged ceilings and sloping floors, are shown to develop on vertical solid surfaces dissolving in aqueous solvents. As evident from descending plumes, sufficiently large indentations evolve into alcoves as a result of the faster dissolution of the ceiling due to a solutal Rayleigh–Bénard density inversion instability. In contrast, defects of size below the boundary layer thickness set by the critical Rayleigh number smooth out, leading to stable planar interfaces. The ceiling recession rate and the alcove opening area evolution are shown to be given to first-order by the critical Rayleigh number. By tracking passive tracers in the fluid phase, we show that the alcoves are shaped by the detachment of the boundary layer flow and the appearance of a pinned vortex at the leading edge of the indentations. The attached boundary layer past the developing alcove is then found to lead to rounding of the other sides and the gradual sloping of the floor.

Role of the edge stochastic layer in density pump-out by resonant magnetic perturbations

The role of the edge stochastic layer on particle transport is addressed in DIII-D plasmas with applied resonant magnetic perturbations (RMPs) causing density pump-out (a term used to denote the density reduction at the top of the pedestal due to the applied RMPs). Using an analytical model that adds the stochastic parallel transport of electrons (Harvey et al 1981 Phys. Rev. Lett. 47 102) to the fluid equations, the ambipolar radial electric field and particle flux are calculated simultaneously. In this model the nonambipolar electron particle flux, driven by the stochastic magnetic field, is predominantly balanced by the nonambipolar perpendicular ion flux, driven by toroidal viscosity, across a narrow stochastic layer of order two percent of the plasma radius (0.98 < ψ n < 1). The model reproduces the level of density pump-out and its dependence on RMP amplitude near the separatrix for three plasma discharges for which the pedestal foot is at medium to high collisionality . The experimentally observed and numerically tested inverse density dependence of density pump-out (Hu et al 2020 Nucl. Fusion 60 076001) is accurately captured by the model: an increase in collisionality with density in the pedestal foot results in a decrease in stochastic diffusivity, and hence a decrease in the level of pump-out.

Generalized maximum entropy based identification of graphical ARMA models

This paper focuses on the joint estimation of parameters and topologies of multivariate graphical autoregressive moving-average (ARMA) processes. Since the graphical structure of a model can be characterized by the sparsity pattern of its inverse spectral density matrix, a generalized maximum entropy optimization model is derived by imposing a sparse regularization on the inverse spectrum from which the parameters of the AR part and the graph topology can be simultaneously estimated. Then, the whole graphical ARMA model is identified by alternatingly estimating the graphical AR part by solving the regularized maximum entropy problem and the MA part by applying the moment estimation method. The weight to the sparsity regularization term is chosen according to the information theoretic model selection criterion, and simulation examples are provided to illustrate the effectiveness of the proposed identification approach.

Explaining the differences in massive star models from various simulations

ABSTRACT The evolution of massive stars is the basis of several astrophysical investigations, from predicting gravitational-wave event rates to studying star formation and stellar populations in clusters. However, uncertainties in massive star evolution present a significant challenge when accounting for these models’ behaviour in stellar population studies. In this work, we present a comparison between five published sets of stellar models from the BPASS (Binary Population and Spectral Synthesis), BoOST (Bonn Optimized Stellar Tracks), Geneva, MIST (MESA Isochrones and Stellar Tracks), and PARSEC (PAdova and TRieste Stellar Evolution Code) simulations at near-solar metallicity. The different sets of stellar models have been computed using slightly different physical inputs in terms of mass-loss rates and internal mixing properties. Moreover, these models also employ various pragmatic methods to overcome the numerical difficulties that arise due to the presence of density inversions in the outer layers of stars more massive than 40 M⊙. These density inversions result from the combination of inefficient convection in the low-density envelopes of massive stars and the excess of radiative luminosity to the Eddington luminosity. We find that the ionizing radiation released by the stellar populations can change by up to 18 per cent, the maximum radial expansion of a star can differ between 100 and 1600 R⊙, and the mass of the stellar remnant can vary up to 20 M⊙ between the five sets of simulations. We conclude that any attempts to explain observations that rely on the use of models of stars more massive than 40 M⊙ should be made with caution.

Biomarkers for Components of Dietary Protein and Carbohydrate with Application to Chronic Disease Risk in Postmenopausal Women

We recently developed protein and carbohydrate intake biomarkers using metabolomics profiles in serum and urine, and used them to correct self-reported dietary data for measurement error. Biomarker-calibrated carbohydrate density was inversely associated with chronic disease risk, whereas protein density associations were mixed. To elucidate and extend this earlier work through biomarker development for protein and carbohydrate components, including animal protein and fiber. Prospective disease association analyses were undertaken in Women's Health Initiative (WHI) cohorts of postmenopausal US women, aged 50-79 y when enrolled at 40 US clinical centers. Biomarkers were developed using an embedded human feeding study (n=153). Calibration equations for protein and carbohydrate components were developed using a WHI nutritional biomarker study (n=436). Calibrated intakes were associated with chronic disease incidence in WHI cohorts (n=81,954) over a 20-y (median) follow-up period, using HR regression methods. Previously reported elevations in cardiovascular disease (CVD) with higher-protein diets tended to be explained by animal protein density. For example, for coronary heart disease a 20% increment in animal protein density had an HR of 1.20 (95% CI: 1.02, 1.42) relative to the HR for total protein density. In comparison, cancer and diabetes risk showed little association with animal protein density beyond that attributable to total protein density. Inverse carbohydrate density associations with total CVD were mostly attributable to fiber density, with a 20% increment HR factor of 0.89 (95% CI: 0.83, 0.94). Cancer risk showed little association with fiber density, whereas diabetes risk had a 20% increment HR of 0.93 (95% CI: 0.88, 0.98) relative to the HRs for total carbohydrate density. In a population of postmenopausal US women, CVD risk was associated with high-animal-protein and low-fiber diets, cancer risk was associated with low-carbohydrate diets, and diabetes risk was associated with low-fiber/low-carbohydrate diets.

One-Dimensional Fokker–Planck Equations and Functional Inequalities for Heavy Tailed Densities

We present and discuss connections between the problem of trend to equilibrium for one-dimensional Fokker–Planck equations modeling socio-economic problems, and one-dimensional functional inequalities of the type of Poincaré, Wirtinger and logarithmic Sobolev, with weight, for probability densities with polynomial tails. As main examples, we consider inequalities satisfied by inverse Gamma densities, taking values on mathbb R_+, and Cauchy-type densities, taking values on mathbb R.

Probing collective enhancement in nuclear level density with evaporation α particle spectra

Collective enhancement in nuclear level density (CELD) and its fadeout has been studied experimentally using neutron and high energy $\ensuremath{\gamma}$-ray spectra earlier. Attempts to probe CELD with $\ensuremath{\alpha}$-particle spectra were made for compound nucleus (CN) $^{178}\mathrm{Hf}$ in the excitation energy $54--124$ MeV, but no signature of CELD was found. The possible reason behind this nonobservance has been discussed in a few subsequent reports. In our previous study, evidence of CELD was found using neutron spectra and enhancement faded away near 25 MeV of excitation energy. This implies that the effect of CELD on $\ensuremath{\alpha}$ particles, if any, would be found at excitation lower than 25 MeV. With the aim to observe CELD and its fadeout with $\ensuremath{\alpha}$-particle spectra, two reactions $^{12}\mathrm{C}+^{116}\mathrm{Sn},^{159}\mathrm{Tb}$, forming CN in different mass region ($A\ensuremath{\approx}128$ and $A\ensuremath{\approx}171$) were studied. Evaporation $\ensuremath{\alpha}$-particle spectra were measured for these reactions in singles as well as in coincidence with neutrons. Experimental data were compared with statistical model calculations and inverse level density parameter ($k$) were obtained from $\ensuremath{\alpha}$-particle spectra. As a function of CN excitation energy, the $k$ value showed peak like structure for the reaction $^{12}\mathrm{C}+^{159}\mathrm{Tb}$ which indicates fadeout of CELD. No such evidence was found for the reaction $^{12}\mathrm{C}+^{116}\mathrm{Sn}$. Collective enhancement factor for daughter nuclei populated in $^{12}\mathrm{C}+^{159}\mathrm{Tb}$ reaction was extracted. Critical energy of the fadeout was found to be similar to that of mass $A\ensuremath{\approx}188$ region.

Spectro-temporal behavior of dye-based solid-state random lasers under picosecond pumping regime.

In this work, the spectral and temporal properties of the random laser emission from dye-doped solid state powders are investigated in picosecond pumping regime. Ultrafast time-resolved spectroscopy achieved with a streak-camera has been used to perform a detailed study of the temporal evolution of the spectrum of their single pulses. Under conditions of low population inversion density, it is observed that the detected radiation occurs as isolated peaks with a very narrow spectro-temporally spread (ΔωΔt≅1). This behavior remains under conditions of high population inversion density, suggesting that the underlying physical mechanism that produces the emission is the same whatever the pumping conditions. Measurements carried out by varying the numerical aperture of the detection system show that each detected peak within a single pulse is associated with a photon pack emitted in a random direction and wavelength. The relationship between the distribution of paths lengths done by photons inside the active medium, and the gain explains the observed behavior.

AVA inversion of pre-stack seismic data with cross-gradient constraints

The ill-posed feature is one basic attribute of geophysical inversion methods. As an example of geophysical inverse problem, AVA (Amplitude variation with incident angle) inversion of pre-stack seismic data is susceptible to noise and uncertainty in the acquisition. To get stable and accurate inversion results, the regularization constraints on model parameter need to be added into the objective function of AVA inversion. In AVA inversion, the most commonly used regularization includes sparsity constraint (e.g. L1-norm regularization, Cauchy regularization) and a priori model parameters constraint, and so forth. However, the existing AVA inversion methods do not consider the structural similarity of different model parameters. All of the different model parameters represent the same underground geological structure, so they should have similar structure. This paper adopts the cross gradient to measure the structural similarity of different model parameters. Next, the cross gradients of different model parameters are added into the objective function of AVA inversion as a regularization term to implement structural similarity constraint. Results of the model numerical tests and real seismic data indicate that the AVA inversion with cross-gradient constraint has higher stability compared to the AVA inversion without structural similarity constraint, especially for the density inversion results.

A functional-data approach to the Argo data

The Argo data is a modern oceanography dataset that provides unprecedented global coverage of temperature and salinity measurements in the upper 2000 meters of depth of the ocean. We study the Argo data from the perspective of functional data analysis (FDA). We develop spatiotemporal functional kriging methodology for mean and covariance estimation to predict temperature and salinity at a fixed location as a smooth function of depth. By combining tools from FDA and spatial statistics, including smoothing splines, local regression, and multivariate spatial modeling and prediction, our approach provides advantages over current methodology that consider pointwise estimation at fixed depths. Our approach naturally leverages the irregularly-sampled data in space, time, and depth to fit a space-time functional model for temperature and salinity. The developed framework provides new tools to address fundamental scientific problems involving the entire upper water column of the oceans, such as the estimation of ocean heat content, stratification, and thermohaline oscillation. For example, we show that our functional approach yields more accurate ocean heat content estimates than ones based on discrete integral approximations in pressure. Further, using the derivative function estimates, we obtain a new product of a global map of the mixed layer depth, a key component in the study of heat absorption and nutrient circulation in the oceans. The derivative estimates also reveal evidence for density inversions in areas distinguished by mixing of particularly different water masses.

Robot Grasping Based on Stacked Object Classification Network and Grasping Order Planning

In this paper, the robot grasping for stacked objects is studied based on object detection and grasping order planning. Firstly, a novel stacked object classification network (SOCN) is proposed to realize stacked object recognition. The network takes into account the visible volume of the objects to further adjust its inverse density parameters, which makes the training process faster and smoother. At the same time, SOCN adopts the transformer architecture and has a self-attention mechanism for feature learning. Subsequently, a grasping order planning method is investigated, which depends on the security score and extracts the geometric relations and dependencies between stacked objects, it calculates the security score based on object relation, classification, and size. The proposed method is evaluated by using a depth camera and a UR-10 robot to complete grasping tasks. The results show that our method has high accuracy for stacked object classification, and the grasping order effectively and successfully executes safely.

SH-SH wave inversion for S-wave velocity and density

SS-waves (SV-SV waves and SH-SH waves) are capable of inverting S-wave velocity ([Formula: see text]) and density ([Formula: see text]) because they are sensitive to both parameters. SH-SH waves can be separated from multicomponent data sets more effectively than the SV-SV wave because the former is decoupled from the PP-wave in isotropic media. In addition, the SH-SH wave can be better modeled than the SV-SV wave in the case of strong velocity/impedance contrast because the SV-SV wave has multicritical angles, some of which can be quite small when velocity/impedance contrast is strong. We derive an approximate equation of the SH-SH wave reflection coefficient as a function of [Formula: see text] and [Formula: see text] in natural logarithm variables. The approximation has high accuracy, and it enables the inversion of [Formula: see text] and [Formula: see text] in a direct manner. Both coefficients corresponding to [Formula: see text] and [Formula: see text] are “model-parameter independent” and thus there is no need for prior estimate of any model parameter in inversion. Then, we develop an SH-SH wave inversion method and demonstrate it by using synthetic data sets and a real SH-SH wave prestack data set from the west of China. We find that [Formula: see text] and [Formula: see text] can be reliably estimated from the SH-SH wave of small angles.

Level density within a micro-macroscopic approach

Statistical level density ρ(E,A) is derived for nucleonic system with a given energy E, particle number A and other integrals of motion in the micro-macroscopic approximation beyond the standard saddle-point method of the Fermi gas model. This level density reaches the two limits; the well-known Fermi gas grand-canonical ensemble limit for a large entropy S related to large excitation energies, and the finite micro-canonical limit for a small combinatorical entropy S at low excitation energies. The inverse level density parameter K as function of the particle number A in the semiclassical periodic orbit theory, taking into account the extended Thomas-Fermi and Strutinsky shell corrections, is calculated and compared with experimental data.

Robust Poisson multi-Bernoulli mixture filter using adaptive birth distributions for extended targets

This paper presents a robust Poisson multi-Bernoulli mixture (PMBM) filter using adaptive birth distributions for the tracking of multiple extended targets. Firstly, in order to be immune to the uncertainty of target birth, we present a novel measurement-driven adaptive birth distribution that is robust to the arbitrariness of locations where new targets appear. Then, to enhance practicability of algorithm, the Beta distribution is employed to describe unknown detection probability augmented into the extended target state. On these bases, the detailed recursion and closed-form solutions to the proposed filter are derived by means of approximating the intensity of target birth and potential targets to Beta gamma Gaussian inverse Wishart (BGGIW) mixture form and density of existing Bernoulli component to a single BGGIW form. Moreover, the computational bottleneck caused by data associations is settled by truncating the PMBM filtering density using the Gibbs sampler of the Metropolis Hasting Markov Chain Monte Carlo (MCMC). Simulation results show the robustness and effectiveness of the proposed method.

Evaluation of Empirical Atmospheric Models Using Swarm-C Satellite Data

Swarm-C satellite, a new instrument for atmospheric study, has been the focus of many studies to evaluate its usage and accuracy. This paper takes the Swarm-C satellite as a research object to verify the Swarm-C accelerometer’s inversion results. This paper uses the two-row orbital elements density inversion to verify the atmospheric density accuracy results of the Swarm-C satellite accelerometer. After the accuracy of the satellite data is verified, this paper conducts comparative verification and empirical atmospheric model evaluation experiments based on the Swarm-C accelerometer’s inversion results. After comparing with the inversion results of the Swarm-C semi-major axis attenuation method, it is found that the atmospheric density obtained by inversion using the Swarm-C accelerometer is more dynamic and real-time. It shows that with more available data, the Swarm-C satellite could be a new high-quality instrument for related studies along with the well-established satellites. After evaluating the performance of the JB2008 and NRLMSISE-00 empirical atmospheric models using the Swarm-C accelerometer inversion results, it is found that the accuracy and real-time performance of the JB2008 model at the altitude where the Swarm-C satellite is located are better than the NRLMSISE-00 model.

Borehole Geophysical Joint Inversion to Fully Evaluate Shaly Sandstone Formations

Simultaneous inversion of sonic, density, and electrical resistivity borehole-derived well logs, has been addressed in literature in recent years. However, this problem is not broadly studied for dual-porosity sandstone formations. In addition, most authors presumed salinity and matrix properties as known parameters in their studies. We integrate the conservation of mass to model density, a differential effective medium theory for elastic modeling, and a laboratory-supported model for electrical resistivity of dual-porosity sandstones. Utilizing this methodology, we simulate electrical resistivity, sonic, and density well-log data. We develop a stochastic global search engine to jointly invert petrophysical properties. We build a dual-porosity formation with associated petrophysical properties and show the proposed workflow accurately replicates true well-log responses in the oil column, water leg, and transition zone. Local petrophysical properties (microporosity, intergranular porosity, total porosity, and water saturation) and global model parameters (salinity, matrix properties, critical porosity, resistivity lithology exponents, and sonic length scales for different pore networks) are all well recovered. The developed multiphysics calibrated rock models will assist petrophysicists and seismic analysts to identify and distinguish sandstone facies characteristics from well-log and prestack seismic data.

A Review of the Global Polygonal Faults: Are They Playing a Big Role in Fluid Migration?

Polygonal faults (PFs) have been widely found in over 100 sedimentary basins worldwide, mainly in marine setting on continental margins and intracratonic sedimentary basins. PFs are characterized by layer-bound minor normal faults arranged in polygonal patterns and multi-direction strikes, most of which were developed in fine-grained sediments rich in claystone. The genesis mechanisms of PFs have been recognized as non-tectonic, mainly including shear failure, syneresis, density inversion, low coefficients of friction and gravity sliding theory. Previous studies often regarded PFs as conduits playing a role in favouring fluid migration, which were also regarded as fluid source expelled during PF generation. However, some researchers proposed that the PF-bearing layer is generally impermeable and may act as a seal. To better understand the role of PFs in fluid migration and their contrition to the shallower hydrocarbon accumulation, a geophysical review of global PFs case studies is conducted in this paper. A comprehensive analysis is carried out based on abundant case studies, with key parameters analyzed including the PFs characteristics (e.g., buried depth, lithology, size, etc.), formation mechanisms of PFs, tectonic-sedimentary setting, and the spatial relationship of PFs, nearby major fluid migration pathways and high amplitude anomalies. The compilation of global PF case studies of shows that hydrocarbon fluids from the deep is more likely to migrate upward through normal big faults, gas chimneys or unconformities surface around PFs. In most cases, PFs play limited roles in fluid migration, such as in South China Sea where hydrocarbon accumulations have been observed under the PFs and the PF-bearing layer may act as a seal trapping the free gas underneath. Generally, the role of PFs in fluid migration should be determined through a comprehensive analysis of the characteristics of PFs, surrounding amplitude anomalies, hydrocarbon distribution, and even the sealing ability of PFs which needs further study. It is more likely that the PFs play a limited role in vertical fluid migration and related shallower hydrocarbon accumulation and distribution.