Density Model Research Articles

An open source code for modeling radio wave propagation in earth’s ionosphere

We present FARR (Finite-difference time-domain ARRay), an open source, high-performance, finite-difference time-domain (FDTD) code. FARR is specifically designed for modeling radio wave propagation in collisional, magnetized plasmas like those found in the Earth’s ionosphere. The FDTD method directly solves Maxwell’s equations and captures all features of electromagnetic propagation, including the effects of polarization and finite-bandwidth wave packets. By solving for all vector field quantities, the code can work in regimes where geometric optics is not applicable. FARR is able to model the complex interaction of electromagnetic waves with multi-scale ionospheric irregularities, capturing the effects of scintillation caused by both refractive and diffractive processes. In this paper, we provide a thorough description of the design and features of FARR. We also highlight specific use cases for future work, including coupling to external models for ionospheric densities, quantifying HF/VHF scintillation, and simulating radar backscatter. The code is validated by comparing the simulated wave amplitudes in a slowly changing, magnetized plasma to the predicted amplitudes using the WKB approximation. This test shows good agreement between FARR and the cold plasma dispersion relations for O, X, R, and L modes, while also highlighting key differences from working in the time-domain. Finally, we conclude by comparing the propagation path of an HF pulse reflecting from the bottomside ionosphere. This path compares well to ray tracing simulations, and demonstrates the code’s ability to address realistic ionospheric propagation problems.

Compressed liquid density and thermodynamic modeling for the promising liquid organic hydrogen carrier Benzyltoluene/Dibenzyltoluene

Compressed liquid density and thermodynamic modeling for the promising liquid organic hydrogen carrier Benzyltoluene/Dibenzyltoluene

Probing the rest-frame wavelength dependence of quasar variability. Insights from the Zwicky Transient Facility Survey

Quasar variability can potentially unlock crucial insights into the accretion process. Understanding how this variability is influenced by wavelength is crucial for validating and refining quasar variability models. This paper aims to enhance the understanding of the dependence of variability on the rest-frame wavelength (λ_RF) by isolating the variance in different timescales in well-defined wavelength bins and examining the corona-heated accretion disk (CHAR) model. We investigated the relation between variance and rest-frame wavelength (λ_RF) using optical g- and r-band light curves from the Zwicky Transient Facility (ZTF) Data Release 15 (DR15) for ∼ 5000 quasars within narrow ranges of the black hole mass (M_BH) and Eddington ratio (R_Edd). A spectral model taking into account disk continuum emission, Balmer transitions, Fe II pseudo-continuum emission, and other emission lines is necessary to best interpret the variance spectrum. Our analysis indicates a strong anticorrelation between median variance and λ_RF for quasars with M_ BH M_ ⊙ and R_ Edd at different timescales. This anticorrelation is more pronounced at shorter timescales. The results align well with a bending power-law power spectral density (PSD) model with both the damping timescale and the high-frequency slope of the PSD depending on the wavelength. The predictions provided by the CHAR model on the variance spectrum across most timescales studied showcase its potential in constraining temperature variations within the accretion disk.

A statistical shape and density model can accurately predict bone morphology and regional femoral bone mineral density variation in children.

Finite element analysis (FEA) is a widely used tool to predict bone biomechanics in orthopaedics for prevention, treatment, and implant design. Subject-specific FEA models are more accurate than generic adult-scaled models, especially for a paediatric population, due to significant differences in bone geometry and bone mineral density. However, creating these models can be time-consuming, costly and requires medical imaging. To address these limitations, population-based models have been successful in characterizing bone shape and density variation in adults. However, children are not small adults and need their own population-based model to generate accurate and accessible musculoskeletal geometry and bone mineral density in a paediatric population. Therefore, this study aimed to create a biomechanical research tool to predict the personalized shape and density of the paediatric femur using a statistical shape and density model for a population of children aged from 4 to 18 years old. Femur morphology and bone mineral density were extracted from 330 CT scans of children. Variations in shape and density were captured using Principal Component Analysis (PCA). Principal components were correlated to demographic and linear bone measurements to create a predictive statistical shape-density model, which was used to predict femoral shape and density. A leave-one-out analysis showed that the shape-density model can predict the femur geometry with a root mean square error (RMSE) of 1.78 ± 0.46 mm and the bone mineral density with a normalized RMSE ranging from 8.9 % to 13.5 % across various femoral regions. These results underscore the model's potential to reflect real-world physiological variations in the paediatric femur. This statistical shape and density model has the potential for clinical application in rapidly generating personalized computational models using partial or no medical imaging data.

Ongoing invasions by American bullfrogs and red-eared sliders in the Republic of Korea

ABSTRACT Invasive species can be unpredictable in their ability to adapt and spread across novel landscapes. American bullfrogs (Lithobates catesbeianus) and red-eared sliders (Trachemys scripta elegans) have become invasive in South Korea since their introduction in the 1970s through the food and pet trades. One of the first steps to their population regulations is to determine each species’ distribution in the country, which will allow for the identification of at-risk areas. In this study, we used a combination of kernel density and habitat suitability modeling to identify regions of current invasion and future spread for both species. We additionally modeled habitat suitability under a variety of climate scenarios, spanning 2021–2100 in order to determine possible climate change-based spread. For L. catesbeianus we found the total possible invasible area to be 46.2% of the country under current climate conditions, with 26.5% of the country currently invaded. For T. scripta, we found the total possible invasible area to be 38.5% of the country under current climate conditions, with 2.1% currently invaded. Finally, based on climate change predictions, both species are expected to have a decreased range of suitable area in the coming decades. The variations between the two invasive species pertain to their different breeding ecology.

3D Compact Geometry Inversion for Gravity Data

Abstract Gravity inversion quantitatively provides a 3D model of density contrasts, significantly enhancing the information extracted from acquired data. However, the inherent non-uniqueness of inversion poses challenges in precisely determining the boundaries of anomalous bodies. We have developed an iterative algorithm of gravity inversion that reconstructs the geometric features of the anomalous bodies by discretizing the 3D interpretation model with vertical and juxtaposed prism cells. These prisms incorporate sheet-like initial models which are typically derived from prior information or imaging results. This study proposed a new parameter, the Thickness Factor (TF), which is determined by the thickness of the prism cells under the assumption of homogeneous anomalous bodies. The TF establishes an approximate linear relationship between the source geometry and gravity anomalies, enabling the reconstruction of the source geometry to be formulated as a linear optimization problem. The approach demonstrates the potential for target inversion in the presence of multiple causative sources in synthetic cases and shows insensitivity to noise signals and reliability in reconstructing the geometry of complex sources. The proposed method is then applied to real data from the Galinge iron ore deposit in Northwest China and the drilling data is used as prior information. The inversion results are consistent with previous drilling interpretations and allow a rough estimation of the volume of the ore bodies.

Constraining the Milky Way’s Dispersion Measure Using FRB and X-Ray Data

The dispersion measures (DMs) of the fast radio bursts (FRBs) are a valuable tool to probe the baryonic content of the intergalactic medium and the circumgalactic medium of the intervening galaxies along the sightlines. However, interpreting the DMs is complicated by the contribution of the hot gas in and around our Milky Way. This study examines the relationship between DMMW, derived from localized FRBs, and the Galaxy’s hot gas, using X-ray absorption and emission data from O vii and O viii. We find evidence for a positive correlation between DMMW and O vii absorption, reflecting contributions from both the disk and halo components. This conclusion is supported by two lines of evidence: (1) no correlation between DMMW and O vii/O viii emission, which primarily traces dense disk regions; and (2) the comparison with electron density models, where DMMW aligns with models that incorporate both disk and halo components but significantly exceeds predictions from pure disk-only models, emphasizing the halo’s role. Furthermore, the lack of correlation with O viii absorption suggests that the primary temperature of the Galaxy’s hot gas is likely around 2×106 K or less, as traced by O vii absorption, while gas at higher temperatures (∼3–5 × 106 K) is present but less abundant. Our findings provide insights into the Milky Way’s gas distribution and improve DMMW estimates for future cosmological studies.

Factors controlling high elevations in the Canadian Cordillera: Isostatic analysis and thermal contributions

The Canadian Cordillera is characterized by higher mean elevation and thinner crust compared to the adjacent craton to the east, in apparent contradiction with the Airy isostatic model. Roy Hyndman hypothesized that the high Cordillera elevations may be supported by an overall hot, low-density Cordilleran backarc mantle, but this idea hasn't been tested at the regional scale. We use a new high-resolution crustal thickness model for western Canada derived from teleseismic receiver functions and active source data, to conduct a detailed analysis of elevation-crustal thickness trends in four distinct regions: forearc, backarc, foreland, and craton. The backarc and foreland regions have higher elevations relative to the forearc and craton, requiring additional buoyancy beneath these areas. Using a grid search, we find that unrealistically low crustal densities are required to explain the high elevations and, therefore, the support must come from below the crust. To isolate the mantle component, we use a global crustal density model to correct for the effects of crustal density variations. After correction, the elevation-crustal thickness trends in each area align with the Airy hypothesis. For a given crustal thickness, the elevation of the backarc region is ~700 m higher than that of the craton. This is consistent with uplift caused by a hot backarc mantle. However, the difference is lower than that determined for the entire North American Cordillera (~1600 m). This may suggest the mantle under the Canadian Cordillera is slightly cooler than regions to the adjacent US Cordillera, perhaps due to the absence of ongoing subduction.

Trap density estimation for TDDB testing in SiC power MOSFETs

Abstract The trap density estimation of SiC power MOSFET in time-dependent dielectric breakdown (TDDB) was investigated by using experiment and TCAD simulation. The gate leakage current (IGSS) under negative voltage was measured and a current spike was found which was linearly shifted with TDDB stress. Based on four-state nonradiative multi phonon (NMP) defect capture model, the mechanism and modeling of IGSS current spike was studied. Based on TCAD simulation, the characteristics of gate oxygen donor traps including trap energy level, trap density, and position distribution were estimated, and the trap density model in TDDB experiment was proposed and verified. This study may contribute to the estimation of trap density in SiC MOSFET.

Approaches for estimating the unsaturated hydraulic conductivity of compacted quartz sand via particle packing theory

The unsaturated hydraulic conductivity (K) is one of the most important properties for evaluating moisture and gas migration in soil. However, the precise measurement of K in the laboratory often requires considerable time and economic costs. Currently, the most commonly used method to calculate K is to obtain it from the soil–water characteristic curve (SWCC) and saturated hydraulic conductivity. The void ratio e has a crucial influence on the variation in K. In this study, by combining two extended SWCC models (the Kwan model and the modified linear packing density model (MLPDM)) proposed by Liu et al. and two models (Model KS1 and Model KS2) for predicting the saturated hydraulic conductivity (KS) of compacted quartz sand, two approaches (Approach I and Approach II) for estimating the K of compacted quartz sand were proposed. A series of laboratory experiments (constant head permeability tests and alternative simplified evaporation tests) were conducted to verify and evaluate the accuracy and applicability of the two approaches for predicting the K values of compacted quartz sand. For Approach I, the average RMSE was 6.31 × 10− 6. For Approach II, the average RMSE was 5.82 × 10−6. Both Approach I and Approach II provided accurate and reasonable K values for 20 compacted quartz sand samples. Therefore, Approach I and Approach II can be used to predict moisture and gas migration in compacted quartz sand.

Adaptive energy reference for machine-learning models of the electronic density of states

Adaptive energy reference for machine-learning models of the electronic density of states

The Spatiotemporal Coupling and Synergistic Evolution of Economic Resilience and Ecological Resilience in Africa

Investigating the spatiotemporal coupling and coordinated evolution of economic and ecological resilience in Africa provides theoretical support and scientific foundation for the continent’s green and high-quality development. From the perspective of evolutionary resilience, this study constructs an evaluation model for Africa’s economic resilience and ecological resilience. Using kernel density models, namely the “economic-ecological” resilience zoning method, the coupling coordination degree model, and the Haken model, this study explores the spatiotemporal alignment, coupling, and synergistic evolution of economic and ecological resilience in Africa in a step-by-step manner. The results show that (1) the overall level of economic resilience in Africa is relatively low, with increasing regional disparities. Spatially, economic resilience exhibits a distribution pattern of “low values widely spread, high values concentrated”; the level of ecological resilience, in contrast, shows a more pronounced dispersion, with a spatial distribution of “low values concentrated, high values dispersed”; (2) based on the “economic-ecological” resilience zoning method, most African countries and regions fall into the low economic resilience category, with weak economic resilience and prominent issues related to economic instability. The seven major high economic resilience zones largely overlap with the high economic resilience-high ecological resilience areas, demonstrating good spatiotemporal alignment between economic and ecological resilience; (3) in terms of the spatiotemporal coupling relationship between economic resilience and ecological resilience, most of Africa falls into the disordered category, with an increasingly obvious polarization trend in the coupling coordination degree; (4) from the perspective of the synergistic relationship between economic resilience and ecological resilience, ecological resilience dominates the symbiotic system formed by economic resilience and ecological resilience. The development of ecological resilience and economic resilience is mutually inhibitive, with prominent contradictions between the economy and the environment. Ecological and economic resilience have formed an internal mechanism of positive feedback in the synergistic system. The regional differences in the synergistic value have expanded, while the differences within regions have narrowed, indicating an emerging trend of spatial differentiation.

Models for plasmasphere and plasmatrough density and average ion mass including dependence on L, MLT, geomagnetic activity, and phase of the solar cycle

Using observations of mass density inferred from standing Alfvén wave frequencies and electron density inferred from plasma wave frequencies, predominantly for the Combined Release and Radiation Effects Satellite (CRRES) and Van Allen Probes spacecraft, we used symbolic nonlinear regression to find analytical formulas for the equatorial electron density, ne, mass density, ρm, and average ion mass, M≡ρm/ne. We separate the data into plasmasphere and plasmatrough populations based on the observed values of ne in order to find formulas for plasmasphere, plasmatrough, and both plasmasphere and plasmatrough. Our models depend on position, the solar extreme ultraviolet (EUV) F10.7 flux, geomagnetic activity parameters such as Kp, AE, Dst, and the solar wind dynamic pressure. Formulas for M are presented with or without ne as an input parameter. By examining formulas of varying complexity, we are able to determine the relative importance of the various dependencies. The most important dependencies for ne and ρm are that they decrease with respect to L shell and geomagnetic activity as specified by parameters such as Kp. The most important dependence of M is that M increases with respect to increasing F10.7. The value of M is close to unity within the plasmasphere, but can be significantly above 1 in the plasmatrough. Although ne and ρm have maximum value at dusk local time, M has maximum value at dawn local time. The O+ concentration is larger at dawn local time, but the O+ density can be comparable at dawn and dusk because of larger ne at dusk.

Discovery of 26 new Galactic radio transients by MeerTRAP

Abstract Radio searches for single pulses provide the opportunity to discover one-off events, fast transients and some pulsars that might otherwise be missed by conventional periodicity searches. The MeerTRAP real-time search pipeline operates commensally to observations with the MeerKAT telescope. Here, we report on 26 new Galactic radio transients, mostly rotating radio transients (RRATs) and also the detection of one RRAT and two pulsars that were independently discovered by other surveys. The dispersion measures of two of the new sources marginally exceed the Galactic contribution depending on the electron density model used. Using a simple method of fitting a Gaussian function to individual pulses, and obtaining positions of arcsecond accuracy from image-based localisations using channelised voltage data from our transient buffer, we have derived timing solutions spanning multiple years for five sources. The timing parameters imply ages of several Myr and low surface magnetic field strengths which is characteristic of RRATs. We were able to measure spin periods for eight more transients, including one source which appears to rotate every 17.5 seconds. A majority of the sources have only been seen in one observation, sometimes despite multiple return visits to the field. Some sources exhibit complex emission features like component switching and periodic microstructure.

Determination of Cenozoic Sedimentary Structures Using Integrated Geophysical Surveys: A Case Study in the Hebei Plain, China.

The strong multi-stage tectonic movement caused the northwest of the North China Plain to rise and the southeast to fall. The covering layer in the plain area was several kilometers thick. In addition to expensive drilling, it is difficult to obtain deep geological information through traditional geological exploration. In this study, gravity, magnetotelluric (MT) sounding and shallow seismic methods are used to explore the basement relief and stratigraphic structure of the alluvial proluvial area in front of Taihang Mount in the North China Plain so as to understand the geological structure and sedimentary evolution of the area. The gravity anomaly map reveals the basement uplift, depression shape and faults distribution on the horizontal plane in the whole area. The MT profile reflects the geoelectric characteristics of the three-layer distribution in the Cenozoic. The seismic profile deployed on the Daxing Uplift depicts the structural style of the uplift area. The well-to-seismic calibration establishes the relationship between the lithostratigraphic and the wave impedance interface so that we can accurately obtain the shape and depth of the bedrock surface and further subdivide Cenozoic strata. Finally, we have improved the accuracy of interface inversion by using a variable density model based on density logging parameter statistics to constrain the depth of geological interfaces determined through drilling and multi-geophysical methods. Through the combination of geology and comprehensive geophysics, we have obtained the undulating patterns of Paleogene and Quaternary bottom interfaces, the structural styles of the basement and the distribution of faults in the survey area, which provide strong support for the study of neotectonic movement and sedimentary environment evolution since the Cenozoic. The successful application of this pattern proves that geophysical surveys based on prior geological information are an important supplementary tool for geological research in thick coverage areas.

Density model checks via the lack-of-fitness

Density model checks via the lack-of-fitness

Relation between Electrostatic Charge Density and Spin Hamiltonian Models of Ligand Field in Lanthanide Complexes.

Understanding the ligand field interactions in lanthanide-containing magnetic molecular complexes is of paramount importance for understanding their magnetic properties, and simple models for rationalizing their effects are much desired. In this work, the equivalence between electrostatic models, which derive their results from calculating the electrostatic interaction energy of the charge density of the 4f electrons in an electrostatic potential representing the ligands, and the common quantum mechanical effective spin Hamiltonian in the space of the ground J multiplet is formulated in detail. This enables the construction of an electrostatic potential for any given ligand field Hamiltonian and discusses the effects of the ligand field interactions in terms of an interaction of a generalized 4f charge density with the electrostatic potential. Such models often allow for an easier rationalization of the ligand field interactions, and it can be hoped that the results in this work will help us to better understand the effects of ligand field in lanthanide complexes.

Model of the structure of the Earth’s crust and Upper Mantle along the Middle Ural transect (Based on the results of Volumetric seismic Density Modeling)

A geological and geophysical model of the structure of the earth’s crust and upper mantle along the Middle Ural transect is presented (as a vertical section of a three-dimensional seismic density model). The methodology for constructing a 3D density model of the earth’s crust and upper mantle for the Middle Urals is outlined. The model was created based on the results of interpretation of gravity anomalies in the Bouguer reduction and deep seismic sounding data. Creating a volumetric one consists of several stages. At the first stage, gradient velocity sections were constructed in the format of grid functions (2D models of seismic velocity distribution) to a depth of 80 km, which were converted into density ones using refined formulas. Next, a threedimensional zero-approximation density model is constructed (using interpolation methods) and the difference between the observed gravitational field and the field of this model is calculated. For the difference field, the inverse problem is solved the density values at the nodes of the computational grid are determined, which need to be added to the zeroapproximation model in order to satisfy the observed field. A comparison is made of the gradient density section obtained by a vertical section of the author’s volumetric density model of the earth’s crust and upper mantle of the Middle Urals along the line of the Middle Ural transect, with a density model created on the basis of a two-dimensional interpretation along this transect (according to the EUROPROBE program). The cross-section of the volumetric density model reflects the main features of the deep structure of the study area, presented in the two-dimensional model, and supplements them with new data on the distribution of physical parameters in the earth’s crust and mantle. This illustrates the fact that a three-dimensional density model, the construction of which takes into account geophysical data specified over the entire study area, carries more information about the structure of the earth’s crust than two-dimensional models.

Dung predicts the global distribution of herbivore grazing pressure in drylands.

Dryland grazing sustains millions of people worldwide but, when poorly managed, threatens food security. Here we combine livestock and wild herbivore dung mass data from surveys at 760 dryland sites worldwide, representing independent measurements of herbivory, to generate high-resolution maps. We show that livestock and wild herbivore grazing is globally disconnected, and identify hotspots of herbivore activity across Africa, the Eurasian grasslands, India, Australia and the United States. Wild herbivore dung mass was negatively correlated with total organic nitrogen, yet strong site-level correlations exist between our livestock dung estimates and total soil organic nitrogen. Using dung mass as a proxy of herbivore abundance enables standardized, field-based measures of grazing pressure that account for different herbivore types. This can improve herbivore density modelling and guide better management practices for populations that rely on dryland-grazing livestock for food.

Assessing the Impacts of Selective Logging on the Forest Understory in the Amazon Using Airborne LiDAR

Reduced-impact logging (RIL) has been recognized as a promising strategy for biodiversity conservation and carbon sequestration within sustainable forest management (SFM) areas. However, monitoring the forest understory—a critical area for assessing logging impacts—remains challenging due to limitations in conventional methods such as field inventories and global navigation satellite system (GNSS) surveys, which are time-consuming, costly, and often lack accuracy in complex environments. Additionally, aerial and satellite imagery frequently underestimate the full extent of disturbances as the forest canopy obscures understory impacts. This study examines the effectiveness of the relative density model (RDM), derived from airborne LiDAR data, for mapping and monitoring understory disturbances. A field-based validation of LiDAR-derived RDM was conducted across 25 sites, totaling 5504.5 hectares within the Jamari National Forest, Rondônia, Brazil. The results indicate that the RDM accurately delineates disturbances caused by logging infrastructure, with over 90% agreement with GNSS field data. However, the model showed the greatest discrepancy for skid trails, which, despite their lower accuracy in modeling, accounted for the largest proportion of the total impacted area among infrastructure. The findings include the mapping of 35.1 km of primary roads, 117.4 km of secondary roads, 595.6 km of skid trails, and 323 log landings, with skid trails comprising the largest proportion of area occupied by logging infrastructure. It is recommended that airborne LiDAR assessments be conducted up to two years post-logging, as impacts become less detectable over time. This study highlights LiDAR data as a reliable alternative to traditional monitoring approaches, with the ability to detect understory impacts more comprehensively for monitoring selective logging in SFM areas of the Amazon, providing a valuable tool for both conservation and climate mitigation efforts.