Density Model Research Articles

Refined Identification of Urban Functional Zones Integrating Multisource Data Features: A Case Study of Lanzhou, China

Identifying urban functional zones is one of the important foundational activities for urban renewal and the development of high-quality urban areas. Efficient and accurate identification methods for urban functional zones are significant for smart city planning and industrial layout optimization. However, existing studies have not adequately considered the impact of the interactions between human activities and geographical space provision on the delineation of urban functional zones. Therefore, from the perspective of integrating the spatiotemporal characteristics of human activities with the distribution of urban functional facilities, by incorporating mobile signaling, POI (point of interest), and building outline data, we propose a multifactorial weighted kernel density model that integrates ‘human activity–land feature area–public awareness’ to delineate urban functional zones quantitatively. The results show that the urban functional zones in the central city area of Lanzhou are primarily characterized by dominant single functional zones nested within mixed functional zones, forming a spatial pattern of ‘single–mixed’ synergistic development. Mixed function zones are widely distributed in the center of Lanzhou City. However, the area accounted for a relatively small proportion, the overall degree of functional mixing is not high, and the inter-district differences are obvious. The confusion matrix showed 85% accuracy and a Kappa coefficient of 0.83.

Comparison of terrestrial exospheric hydrogen 3D distributions at solar minimum and maximum using TWINS Lyman-α observations

Remote sensing observations of far-ultraviolet (FUV) emissions have been used to estimate 3D neutral hydrogen (H) density models of the terrestrial exosphere under solar minimum (2008) and solar maximum (2013 and 2015) conditions. Specifically, we used Lyman-alpha (Lyman-α, FUV at 121.6 nm) radiance data acquired by the Lyman-alpha detectors (LADs) onboard NASA’s TWINS satellites, collected over several days for each of the 3 years to provide sufficient coverage of the exospheric region. The datasets included Lyman-α measurements taken only above Earth radii (Re) of 3.75, assumed to be the optically thin region of the exosphere, where the measured Lyman-α intensity along a line of sight (LOS) is linearly proportional to the atomic hydrogen column density. Based on the calibration using multiple UV-bright stars, a significant decrease in TWINS1 LAD1/2 sensitivities was found for 2013 (LAD2 ∼1/2, LAD ∼1/3) and 2015 (LAD2 ∼1/3, LAD ∼1/7) compared to 2008. The calibration uncertainty was derived to be, on average, 5%. We estimated the 3D global hydrogen density distributions from these radiance data using two different tomographic inversion methods: first, a parametric fitting method based on a spherical harmonic function of order 3 and second, a high degree-of-freedom retrieval approach to validate our retrievals of H density. Both inversion methods consistently incorporate the effects of Lyman-α absorption within the exosphere and Lyman-α re-emission from Earth’s albedo. Our results reveal that H densities during solar maximum conditions are, on average, 30%–40% higher than those during solar minimum. All models showed a high concentration of atomic H on the dayside and nightside near the Sun–Earth line, which determines a nose/geotail structure consistent with theoretical effects from the solar radiation pressure. Furthermore, we identified that H-density enhancements during solar maximum with respect to solar minimum conditions occur at mid-to-high latitudes, particularly on the dusk side, while no significant enhancement seems to occur near the dayside nose.

Integration of Geological Model and Numerical Simulation Technique to Characterize the Remaining Oil of Fractured Biogenic Limestone Reservoirs

AbstractFine geological modeling leads to accurate reservoirs numerical simulations. Fractured biogenic limestone has abundant storage spaces and flow paths to accumulate oil and gas. The complexity and diversity of fractured biogenic limestone also lead to challenges in accurately characterizing its pore volume and remaining oil. This investigation aimed to enhance the understanding of fractured biotite reservoir properties via geological modeling. Numerical simulations were used to characterize the remaining oil during the late stage of field development. Considering the differences in porosity and permeability between fractures and matrix, a facies-controlled stochastic modeling technique was used to establish a dual-porosity and dual-permeability (DPDP) model for numerical simulation. Core information, logging data, and multiple seismic attributes were combined to guide low-level sequence fault interpretation for tectonic refinement. Based on classified seismic inversion, sedimentary phases were reconstructed. A discrete fracture network (DFN) model was obtained based on fracture occurrences and density models. The optimized discrete adjoint (ODA) algorithm was utilized to calibrate model parameters. The findings revealed that dense tectonic fractures develop in thick biogenic limestone areas. Combined with advanced reservoir simulation technology, these findings suggest that areas of thicker biogenic limestone were consistent with areas of higher fracture matrix conductivity multipliers. The remaining oil distribution patterns were investigated, and to deploy new wells was guided. Therefore, it is essential to better understand the tectonic characteristics of fractured biogenic limestone reservoirs and their remaining oil distribution patterns by integrating multiple sources of information and mastering advanced reservoir simulation technology for oilfield development.

Soil density specification ranges to optimise plant water use and root growth for phytocapping and urban greening projects

Soil density or compaction is one of the key variables that need to be specified for designed soil profiles as part of urban greening. Examples include land rehabilitation (mining), waste containment (phytocapping), stormwater infrastructure (bioretention basins) and green infrastructure (green roofs and street trees). This study investigates the impact of a range of specified soil densities on plant water use and root development. Native Australian plant species selected for the study include: the C4 and C3 grasses, Themeda triandra and Microlaena stipoides respectively; the Eucalyptus trees, E. camaldulensis and E. cladocalyx; and the nitrogen-fixing pioneer trees, Acacia mearnsii and Allocasuarina verticillata. The plants were established at four soil density (compaction) levels: 72, 77, 82, and 87 % MDD (maximum dry density) in tall cylinders with weekly plant water use measurement over 8 months. Root growth was analysed using WinRhizo image analysis. The experimental results were used to create generalisable models for root length density (RLD), root diameter and plant water use. The models for RLD and plant water use were parabolic in nature, revealing clear optimum ranges that could be used to guide soil density specification. Root diameter provided additional insight into the allocation of resources to root thickening above a threshold soil density of 87 % MDD, indicating plant allocation of resources towards penetrating highly compacted soils. There were correlations between plant water use and RLD that were moderate and significant, particularly for grasses. Notably, T. triandra had the greatest mean RLD, thickest roots and plant water use at 16.8cm/cm3, 0.18 mm and 10mm/week, respectively. Findings demonstrate that RLD and plant water use can be optimised together within practically achievable soil density specification ranges that are sensitive to the pitfalls of both excessively low and excessively high soil densities. Recommended soil density specification ranges include: 75–82 % MDD with plant performance within 5 % of optimum (considered excellent), 74–84 % MDD with plant performance within 10 % of optimum (considered good) and 73–85 % MDD with plant performance within 15 % of optimum (considered fair). Within these ranges, plant water use and root growth performance is well balanced with practical achievement of the soil density ranges. Due to the use of %MDD, the modelled results can be usefully generalised for any soil type. Implementation of these specifications for urban greening and phytocap projects will optimise plant growth, transpiration and hydrological function while maintaining root networks essential for establishing and maintaining resilient living infrastructure.

CT Radiomics Features Predict Change in Lung Density and Rate of Emphysema Progression.

Rationale Emphysema progression is heterogeneous. Predicting temporal changes in lung density and detecting rapid progressors may facilitate selection of individuals for targeted therapies. Objective To test whether computed tomography (CT) radiomics can be used to predict changes in lung density and detect rapid progressors. Methods We extracted radiomics features from inspiratory chest CT in 4,575 subjects with and without airflow obstruction at enrollment, who completed a follow-up visit at approximately 5 years. We quantified emphysema using adjusted lung density (ALD) and estimated emphysema progression as the annualized change in ALD (∆ALD/year) between visits. We categorized participants into rapid progressors (>1% ∆ALD/year) and stable disease (≤1% ∆ALD/year). A gradient boosting model was used (1) to predict ALD at 5-years and (2) to identify rapid progressors. Four models using demographics (base clinical model); CT density; radiomics; and combined features (clinical, radiomics, and CT density) were evaluated and tested. Results There were 1,773 (38.8%) rapid progressors. For predicting ALD at 5-years in the 20% held-out data, the base model explained 31% of the variance (adjusted R2 = 0.31) whereas R2 was 0.74 for the CT density model, 0.66 for the radiomics-only model, and 0.77 for the combined features model. For detecting rapid progressors, the base model (AUC = 0.57, 95%CI 0.53-0.61) was outperformed by the radiomics-only model (AUC = 0.73, 95%CI 0.69-0.76, ∆ =0.0003, p < 0.001) and the combined model (AUC = 0.74, 95%CI 0.71-0.77, ∆ = 0.0003, p < 0.001). Conclusions Parenchymal and airway radiomics features derived from inspiratory scans can be used to predict temporal changes in lung density and help identify rapid progressors.

Enhancing the Performance of Unmanned Aerial Vehicle-Based Estimation of Rape Chlorophyll Content by Reducing the Impact of Crop Coverage

Estimating leaf chlorophyll content (LCC) in a timely manner and accurately is of great significance for the precision management of rape. The spectral index derived from UAV images has been adopted as a non-destructive and efficient way to map LCC. However, soil background impairs the performance of UAV-based LCC estimation, limiting the accuracy and applicability of the LCC estimation model, and this issue remains to be addressed. Thus, this research was conducted to study the influence of soil pixels in UAV RGB images on LCC estimation. UAV campaigns were conducted from overwintering to flowering stages to cover the process of soil background being gradually covered by rapeseed plants. Three planting densities of 11.25, 18.75, and 26.26 g/m2 were chosen to further enrich the different soil background percentage levels, namely, the rape fractional vegetation coverage (FVC) levels. The results showed that, compared to the insignificant difference observed for the ground measured LCC at a certain growth stage, a significant difference was found for most of the spectral indices extracted without soil background removal, indicating the influence of soil background. Removing soil background during the extraction of the spectral index enhanced the LCC estimation accuracy, with the coefficient of determination (R2) increasing from 0.58 to 0.68 and the root mean square error (RMSE) decreasing from 5.19 to 4.49. At the same time, the applicability of the LCC estimation model for different plant densities (FVC levels) was also enhanced. The lower the planting density, the greater the enhancement. R2 increased from 0.53 to 0.70, and the RMSE decreased from 5.30 to 4.81 under a low planting density of 11.25 g/m2. These findings indicate that soil background removal significantly enhances the performance of UAV-based rape LCC estimation, particularly under various FVC conditions.

Assessment of solitary pulmonary nodules using dual-layer spectral detector computed tomography.

We aim to quantitatively investigate the difference between benign and malignant solid pulmonary nodules that appeared on dual-energy spectral computed tomography, and assess the diagnostic accuracy of several parameters derived from computed tomography in differentiating malignant from benign pulmonary nodules. Between September 2021 and December 2022, spectral images of 71 patients (male:female = 44:27, mean age = 71.0 years) confirmed by pathology were retrospectively analyzed in the venous phase. Patients were classified into the malignant group and the benign group. The iodine concentration values of the nodules, normalized iodine concentration of the nodules to the neighboring vessels, virtual monochromatic images of 40 and 80 keV, and slope of the spectral curve were calculated and compared between the benign and malignant groups. Receiver operating characteristic curves and the area under the curve were performed to assess the diagnostic performance of the above parameters. Both virtual monochromatic images and iodine concentration maps prove to be highly useful in differentiating benign and malignant pulmonary nodules. The malignant pulmonary nodules have higher iodine density and slope of the spectral curve than the benign lesions. The combined model of iodine density and curve slope with an optimal cutoff of 0.39 (area under the curve = 0.82) yielded a sensitivity of 95% and a specificity of 63%. Contrast-enhanced dual-energy spectral computed tomography allows promising capability of distinguishing malignant from benign lesions, potential for avoiding unnecessary invasive procedure or surgery.

Multi-scale analysis of urban forests and socioeconomic patterns in a desert city, Phoenix, Arizona

Understanding the relationship between various socioeconomic factors and urban forest structure is essential for directing resources to ensure equitable distribution of green space. Through a case study of a desert city, i.e., Phoenix, AZ, this study provides a novel application of Multiscale Geographically Weighted Regression (MGWR) in which we explore the spatially variable relationships between a wide array of socioeconomic indicators and urban forest attributes. Through the computation of various scales of influence for different explanatory variables, MGWR enhances our analysis’s precision and stresses the association between socioeconomic status and urban forest structure at local and regional scales. Our results indicate that although there has been a pattern of green inequality where minority and low-income communities have less access to urban forests, education levels were mostly insignificant based on the MGWR results. In some instances, higher incomes are negatively correlated with tree canopy coverage. Additionally, the stem density model outperformed the canopy coverage model in terms of prediction accuracy. This research adds a new dimension to urban forestry literature and emphasizes the value of customized urban planning strategies and the environmental justice implications of urban forestry, particularly in arid environments.

Transient temperature and pressure coupling model of cementing injection stage in ultra deep wells considering segmental rheological model, casing eccentricity and U-tube effect

The geological environments of ultra deep wells such as high temperature and high pressure (HTHP), narrow safety density window pose significant challenges to cementing operation. Considering segmental rheological model and density model, casing eccentricity, U-tube effect and viscous dissipation, this paper established a transient temperature and pressure coupling model during cementing injection stage of ultra deep wells. The segmental rheological model can describe the rheological properties of cementing fluids under HTHP much better. Considering casing eccentricity and viscous dissipation can accurately model the variation of temperature and pressure profiles. Taking U-tube effect into the model, the formation process of vacuum section at top of the casing can be simulated. The fully implicit finite-difference approach was used to solve the coupling model, and the calculation results were compared with field measurement data and simulation data to verify its accuracy. The calculation errors of the developed model are respectively 10% and 5% compared to field measurement data and Wellplan’s simulation data. Numerical simulations were conducted to reveal the cementing fluid distribution, transient temperature distribution and pressure distribution during the cementing injection stage. The simulation results show that the variety of cementing fluids with different density, rheological properties and thermophysical parameters complicates the change mechanism of temperature and pressure. The temperature and pressure distributions both present unsteady characteristics during cementing injection stage, which puts forward higher requirements of pressure control for narrow safety density window formation. The influence of temperature and pressure on rheology of cementing fluids cannot be ignored, and segmental rheological model should be considered for accurate pressure prediction. Also the casing eccentricity cannot be ignored for cementing pressure calculation in deviated or horizontal wells. Managed pressure cementing (MPC) has a greater advantage in dealing with narrow density window formation. The synergistic control of cementing fluid density and back pressure can keep the equivalent circulating density (ECD) within the safe density window. Through the application of the transient temperature and pressure coupling model, we can simulate the variations of key dynamic parameters during cementing injection stage and optimize the cementing parameters.

Experimental Measurements and Modeling of Density and Viscosity for Methyl Caprate + 1-Alkanol at Atmospheric Pressure and Different Temperatures

Experimental Measurements and Modeling of Density and Viscosity for Methyl Caprate + 1-Alkanol at Atmospheric Pressure and Different Temperatures

Coherent Radio Emission from “Main-sequence Radio Pulse Emitters”: A New Stellar Diagnostic to Probe 3D Magnetospheric Structures

Main-sequence radio pulse emitters (MRPs) are magnetic early-type stars that produce coherent radio emission observed in the form of periodic radio pulses. The emission mechanism behind this is the electron-cyclotron maser emission (ECME). Among all kinds of magnetospheric emission, ECME is unique due to its high directivity and intrinsically narrow bandwidth. The emission is also highly circularly polarized and the sign of polarization is opposite for the two magnetic hemispheres. This combination of properties makes ECME highly sensitive to the three-dimensional structures in the stellar magnetospheres. This is especially significant for late-B and A-type magnetic stars that do not emit other types of magnetospheric emission such as Hα, the key probe used to trace magnetospheric densities. In this paper, we use an ultra-wideband observation (0.4–2 GHz) of a late B-type MRP HD 133880 to demonstrate how we can extract information on plasma distribution from ECME. We achieve this by examining the differences in pulse arrival times (“lags”) as a function of frequencies and qualitatively comparing those with lags obtained by simulating ECME ray paths in hot stars’ magnetospheres. This reveals that the stellar magnetosphere has a disk-like overdensity inclined to the magnetic equator with a centrally concentrated density that primarily affects the intermediate frequencies (400–800 MHz). This result, which is consistent with the recent density model proposed for hotter centrifugally supported magnetospheres, lends support to the idea of a unifying model for magnetospheric operations in early-type stars, and also provides further motivation to fully characterize the ECME phenomenon in large-scale stellar magnetospheres.

The 3D Density Structure of the South China Sea Based on Wavelet Multi-Scale Analysis of Gravity Data and Its Tectonic Implications

Due to its unique geographical location and complex geological evolution processes, the South China Sea has been a focus of extensive research. Previous studies on the density structure of the South China Sea mostly focused on 2D density structures, with relatively limited research on 3D density structures. A comprehensive study is still needed to refine the expansion mechanism and tectonic evolution of the South China Sea. In this study, we utilized wavelet multi-scale analysis of gravity data to obtain a 3D density model of the South China Sea and discussed its tectonic evolution from the pattern of density anomalies. The inversion results show that (1) the expansion of the South China Sea caused the typical thin oceanic crust and parts of the continent–ocean transition zone may fracture due to the expansion; (2) the low-density anomaly in the upper mantle of Luzon Island may indicate partial melting or the upwelling of asthenosphere materials; and (3) the expansion of the South China Sea is influenced by multiple plate forces and uneven forces affect the distribution of high-density anomalies in the upper mantle.

Implications for Galactic Electron Density Structure from Pulsar Sightlines Intersecting H ii Regions

Recent radio surveys have revealed pulsars with dispersion and scattering delays induced by ionized gas that are larger than the rest of the observed pulsar population, in some cases with electron column densities (or dispersion measures, DMs) larger than the maximum predictions of Galactic electron density models. By cross-matching the observed pulsar population against H ii region catalogs, we show that the majority of pulsars with DM > 600 pc cm−3 and scattering delays τ(1 GHz) > 10 ms lie behind H ii regions, and that H ii region intersections may be relevant to as much as a third of the observed pulsar population. The fraction of the full pulsar population with sightlines intersecting H ii regions is likely larger. Accounting for H ii regions resolves apparent discrepancies where Galactic electron density models place high-DM pulsars beyond the Galactic disk. By comparing emission measures inferred from recombination line observations to pulsar DMs, we show that H ii regions can contribute tens to hundreds of parsecs per cubic centimeter in electron column density along a pulsar line of sight. We find that nearly all pulsars with significant excess (and deficit) scattering from the mean τ–DM relation are spatially coincident with known discrete ionized gas structures, including H ii regions. Accounting for H ii regions is critical to the interpretation of radio dispersion and scattering measurements as electron density tracers, both in the Milky Way and in other galaxies.

Satellite observations and modeling of the plasmapause structure and dynamics

We investigated the structure and dynamics of the plasmapause using electron density data from the Arase (ERG) satellite between 2017 and 2019. By fitting the electron density profile to a hyperbolic function using the least-squares method, 1891 plasmapause events were identified. The hyperbolic function’s fitting parameters were used to estimate the plasmapause’s location and thickness. The plasmapause location and thickness were mapped onto the geomagnetic equator plane. We examined the dependence of the plasmapause location and thickness on the geomagnetic disturbance. The median plasmapause location on the geomagnetic equator plane was 32,089 km from Earth’s center. Plasmapause locations depend on geomagnetic disturbances that vary between four and six radii of the Earth.In contrast, the median plasmapause thickness obtained by fitting a hyperbolic function on the geomagnetic equator plane was 2472 km. The thickness changed from ∼1500 km at night to ∼ 3000 km during the daytime. The thickness was several times larger than the ring current H+ Larmor radius, suggesting an association with plasma instability in the plasmapause due to the penetration of magnetospheric electric fields.Additionally, we developed a three-dimensional empirical electron density model with historical effects associated with refilling the plasmasphere, plasmapause, and magnetosphere. The International Reference Ionosphere (IRI) model can be enhanced to incorporate the electron density model of the plasmasphere and estimate the total electron content (TECp) in the plasmasphere using the empirical model. Our analysis provides valuable insights into plasmapause and contributes to a better understanding of the inner magnetosphere.

Gravitational lensing of spherically symmetric black holes in dark matter halos

The gravitational lensing of supermassive black holes surrounded by dark matter halo has attracted a great number of interests in recent years. However, many studies employed simplified dark matter density models, which makes it very hard to give a precise prediction on the dark matter effects in real astrophysical galaxies. In this work, to more accurately describe the distribution of dark matter in real astrophysical galaxies, we study the gravitational lensing of black holes in astrophysical dark matter halo models (Beta, Burkert, Brownstein, and Moore). The deflection angle is obtained using a generalized Gibbons-Werner approach. The visual angular positions and the Einstein rings are also calculated by adopting the gravitational lens equation. Specifically, we choose the supermassive black holes in Milky Way Galaxy, Andromeda galaxy (M31), Virgo galaxy (M87), and ESO138-G014 galaxy as examples, including the corresponding fitted value of dark matter halos. The results suggest that the dark matter halo described by the Beta model has non-negligible influences on the gravitational deflection angle and gravitational lensing observations. However, the Burkert, Brownstein, and Moore models have relatively small influences on angular position of images and the Einstein ring.

Assessing the validity and limits of linear density models for predicting dissociation–association equilibria in supercritical water

A linear relationship between the logarithms of solute dissociation constants, log(K), and the density of water, log (ρH2O), has empirically been demonstrated for decades and raised hope for an universal formalism to describe solute thermodynamic properties over wide ranges of temperature and density at supercritical conditions. Yet, neither a theoretical foundation nor an assessment of the ranges of validity have been presented. Here, we use classical molecular dynamics (MD) simulations as a complementary tool to assess the validity of this linear relationship for the example of NaCl and reveal its limits at water densities below ca. 0.3gcm−3. The derivative ∂log(K)/∂log(ρH2O) is calculated based on the volume of reaction and water compressibility derived from the simulations performed in the isothermal–isobaric ensemble at 673K. Our results corroborate the linear dependence of log(K) vs. log(ρH2O) in the experimentally studied density range and suggest that the linear dependence also extends to higher densities. However, towards lower densities, log(K) decreases and takes on values that are lower than would be expected by simply extrapolating the linear behavior. This decrease is consistent with earlier theoretical predictions for the behavior of log(K) at vapor-like densities but questions the relevance of some indirect experimental evidence obtained at low temperatures. Although the function described by log(K) vs log(ρH2O) is non-linear in the low density range, it can be considered well-behaved even at near critical conditions.

Drilling Fluid Density Optimization for Narrow Density Window Fractured Formation

Abstract Fractures are prevalent in the Leikoupo Formation in western Sichuan, with a narrow safe density window of 0.06-0.12 g/cm3, leading to frequent downhole accidents like kicks and losses. Using Pengzhou X well as a case study, this research employed numerical simulation to analyze the impact of various drilling fluid densities within this window on displacement rate and bottomhole pressure. It established an optimal drilling fluid density model for fractured formations with narrow density windows. Findings reveal that as drilling fluid density increases, annulus up-return velocity decreases, potentially trapping fracture gas in the upper annulus. Optimal drilling fluid density lies within this narrow window, maintaining a dynamic balance between preventing fast gas return and fluid accumulation in fractured formations. The model applied to Pengzhou Y well yields a drilling density correlation of 0.000001036, consistent with optimized model results. This approach optimizes drilling fluid density within narrow density windows, mitigating downhole gushing and leakage accidents.

Discovery of a Millisecond Pulsar Associated with Terzan 6

Observations show that globular clusters (GCs) might be among the best places to find millisecond pulsars (MSPs). However, the GC Terzan 6 seems to be an exception without any pulsar discovered, although its high stellar encounter rate suggests that it harbors dozens of them. We report the discovery of the first radio pulsar, PSR J1750–3116A, likely associated with Terzan 6 in a search of C-band (4–8 GHz) data from the Robert C. Byrd Green Bank Telescope with a spin period of 5.33 ms and dispersion measure (DM) ≃ 383 pc cm−3. The mean flux density of this pulsar is approximately 3 μJy. The DM agrees well with predictions from the Galactic free electron density model, assuming a distance of 6.7 kpc for Terzan 6. PSR J1750–3116A is likely an isolated MSP, potentially formed through dynamical interactions, considering the core-collapsed classification and the exceptionally high stellar encounter rate of Terzan 6. This is the highest radio frequency observation that has led to the discovery of a pulsar in a GC to date. While L-band (1–2 GHz) observations of this cluster are unlikely to yield significant returns due to propagation effects, we predict that further pulsar discoveries in Terzan 6 will be made by existing radio telescopes at higher frequencies.

Constraining the Initial Mass Function via Stellar Transients

The stellar initial mass function (IMF) represents a fundamental quantity in astrophysics and cosmology describing the mass distribution of stars from low mass all the way up to massive and very massive stars. It is intimately linked to a wide variety of topics, including stellar and binary evolution, galaxy evolution, chemical enrichment, and cosmological reionization. Nonetheless, the IMF still remains highly uncertain. In this work, we aim to determine the IMF with a novel approach based on the observed rates of transients of stellar origin. We parametrize the IMF with a simple but flexible Larson shape, and insert it into a parametric model for the cosmic UV luminosity density, local stellar mass density, type Ia supernova (SN Ia), core-collapse supernova (CCSN), and long gamma-ray burst (LGRB) rates as a function of redshift. We constrain our free parameters by matching the model predictions to a set of empirical determinations for the corresponding quantities via a Bayesian Markov Chain Monte Carlo method. Remarkably, we are able to provide an independent IMF determination with a characteristic mass mc=0.10−0.08+0.24M⊙ and high-mass slope ξ=−2.53−0.27+0.24 that are in accordance with the widely used IMF parameterizations (e.g., Salpeter, Kroupa, Chabrier). Moreover, the adoption of an up-to-date recipe for the cosmic metallicity evolution allows us to constrain the maximum metallicity of LGRB progenitors to Zmax=0.12−0.05+0.29Z⊙. We also find which progenitor fraction actually leads to SN Ia or LGRB emission (e.g., due to binary interaction or jet-launching conditions), put constraints on the CCSN and LGRB progenitor mass ranges, and test the IMF universality. These results show the potential of this kind of approach for studying the IMF, its putative evolution with the galactic environment and cosmic history, and the properties of SN Ia, CCSN, and LGRB progenitors, especially considering the wealth of data incoming in the future.

Approaches for predicting the soil-water characteristic curves of compacted quartz sand based on particle packing theory

The soil-water characteristic curve (SWCC) is an important basis for describing hydraulic properties, which is closely related to environmental problems such as the migration of toxic substances from groundwater and soil. The SWCC models vary considerably with respect to the void ratio or bulk density. However, the void ratio and bulk density of the same soil change at different depths or positions within a flat space. Accurate simulation or calculation requires a precise SWCC, but measuring every SWCC under each density or void ratio condition is difficult. In this study, two particle packing models, the Kwan model and the modified linear packing density model (MLPDM), were introduced into the van Genuchten (VG) model to predict the SWCC for soil at the minimum void ratio (the maximum dry density). Then, the prediction method of the SWCCs for the same soil with different densities or void ratios was given. A series of laboratory tests using quartz sand mixtures were conducted to verify the accuracy of two extended models (the K-VG model and the M-VG model). For the K-VG model, the average RMSE was 0.020. For the M-VG model, the average RMSE was 0.017. In general, the SWCCs predicted by the two extended models were consistent with the measured values.