First-order Coefficient Research Articles

Deep Learning-Based Gender Recognition in Cherry Valley Ducks Through Sound Analysis.

Gender recognition is an important part of the duck industry. Currently, the gender identification of ducks mainly relies on manual labor, which is highly labor-intensive. This study aims to propose a novel method for distinguishing between males and females based on the characteristic sound parameters for day-old ducks. The effective data from the sounds of day-old ducks were recorded and extracted using the endpoint detection method. The 12-dimensional Mel-frequency cepstral coefficients (MFCCs) with first-order and second-order difference coefficients in the effective sound signals of the ducks were calculated, and a total of 36-dimensional feature vectors were obtained. These data were used as input information to train three classification models, include a backpropagation neural network (BPNN), a deep neural network (DNN), and a convolutional neural network (CNN). The training results show that the accuracies of the BPNN, DNN, and CNN were 83.87%, 83.94%, and 84.15%, respectively, and that the three classification models could identify the sounds of male and female ducks. The prediction results showed that the prediction accuracies of the BPNN, DNN, and CNN were 93.33%, 91.67%, and 95.0%, respectively, which shows that the scheme for distinguishing between male and female ducks via sound had high accuracy. Moreover, the CNN demonstrated the best recognition effect. The method proposed in this study can provide some support for developing an efficient technique for gender identification in duck production.

Unraveling the complex dynamics of temporal moments for multispecies contaminant transport in saturated porous media: A global sensitivity analysis approach

In this study, we focus on the application of global sensitivity analysis (GSA) to gain insight into the influence of model parameters on the outputs of multispecies contaminant transport model. In this context, employing GSA methods (Morris and FAST) allows us to comprehend the relative significance of each input parameter in the model. We specifically analyzed the effects of model parameters on the concentration breakthrough curves and associated temporal moments of concentration of contaminant species. The spatial variability of sensitivity indexes from Morris and FAST methods for parent and daughter contaminant species is also investigated. We represent uncertainties of longitudinal dispersivity, porosity, first-order degradation constants of parent and daughter contaminant species, and sorption distribution coefficient of parent species into the coupled multispecies contaminant transport model and GSA framework. Our results show a complex interplay between different model parameters and their varying influences on different output metrics. The ranking of parameters based on GSA shows that (i) the contaminant mass recovery of final daughter species of three species chain reaction is governed by the first-order degradation coefficient of parent and first daughter species; (ii) dispersivity and porosity are critical parameters that govern the mean residence time and variance of breakthrough curve of final daughter species; (iii) the coefficient of skewness is more sensitive to dispersivity, sorption distribution coefficient, and first-order degradation coefficient of parent species as compared to other model parameters. The variation in the sensitivity indices among contaminant species and with travel distance is observed. This study highlights the significance of global sensitivity analysis when simulating the multiple species contaminants in saturated porous media.

Effect of biochar application on physiochemical properties and nitrate degradation rate in a Siliciclastic Riverine Sandy soil

This study investigated the efficacy of biochar as a soil amendment for enhancing soil physicochemical properties and solute transport dynamics, with implications for agricultural sustainability and environmental stewardship. Batch laboratory experiments and column studies were conducted to assess the effects of biochar application on soil parameters and solute transport under saturated conditions. The saturation soil extraction approach was employed in batch leaching tests, while column experiments replicated subsurface conditions. Transport modeling using CXTFIT 2.1 elucidated solute dispersion dynamics in biochar-amended soils. Batch experiments revealed significant alterations in soil pH, electrical conductivity, and nutrient release following biochar addition. Biochar exhibited adsorption capacity for fluoride ions and released dissolved organic carbon, highlighting its potential for soil carbon sequestration and microbial activity. Column studies demonstrated enhanced solute dispersion and increased microbial activity in biochar-amended soils, as evidenced by changes in breakthrough curves and degradation rates of nitrate. Indeed, nitrate first-order degradation coefficients were 9.08E-06 for the column with only sandy soil, 3.09E-05 and 1.47E-04 for the columns with minimum and maximum doses of biochar respectively. Biochar application significantly influenced soil physicochemical properties and solute transport dynamics, with potential implications for nutrient management and contaminant attenuation in agricultural systems. Despite limitations in laboratory-scale experiments, this research provides valuable insights into biochar-soil interactions. It underscores the need for further investigation under field conditions to validate findings and optimize biochar management practices for sustainable soil and environmental management.

A Robust Translational Motion Compensation Method for Moving Target ISAR Imaging Based on Phase Difference-Lv’s Distribution and Auto-Cross-Correlation Algorithm

Translational motion compensation constitutes a pivotal and essential procedure in inverse synthetic aperture radar (ISAR) imaging. Many researchers have previously proposed their methods to address this requirement. However, conventional methods may struggle to produce satisfactory results when dealing with non-stationary moving targets or operating under conditions of low signal-to-noise ratios (SNR). Aiming at this challenge, this article proposes a parametric non-search method that contains two main stages. The radar echoes can be modeled as polynomial phase signals (PPS). In the initial stage, the energy of the received two-dimensional signal is coherently integrated into a peak point by leveraging phase difference (PD) and Lv’s distribution (LVD), from which the high-order polynomial coefficients can be obtained accurately. The estimation of the first-order coefficients is conducted during the second stage. The auto-cross-correlation function for range profiles is introduced to enhance the accuracy and robustness of estimation. Subsequently, a novel mathematical model for velocity estimation is proposed, and its least squares solution is derived. Through this model, a sub-resolution solution can be obtained without requiring interpolation. By employing all the estimated polynomial coefficients, the non-stationary motion of the target can be fully compensated, yielding the acquisition of a finely focused image. Finally, the experimental findings validate the superiority and robustness of the proposed method in comparison to state-of-the-art approaches.

Intra and Inter-Rater Variability in the Interpretation of White Blood Cell Scintigraphy of Hip and Knee Prostheses.

Background: White blood cell (WBC) scintigraphy plays a major role in the diagnostic approach to periprosthetic infections. Although the procedure has been standardized by the publication of several guidelines, the interpretation of this technique may be susceptible to intra and inter-variability. We aimed to assess the reproducibility of interpretation between nuclear medicine physicians and by the same physician and to demonstrate that Cohen's coefficient is more unstable than Gwet's coefficient, as the latter is influenced by the prevalence rates. Methods: We enrolled 59 patients who performed a Technetium-99m WBC (99mTc-WBC) scintigraphy for suspected hip or knee prosthesis infection. Three physicians, blinded to all patient clinical data, performed two image readings. Each WBC study was assessed both visually and semi-quantitatively according to the guidelines of the European Association of Nuclear Medicine (EANM). For semi-quantitative analysis, readers drew an irregular Region of Interest (ROI) over the suspected infectious lesion and copied it to the normal contralateral bone. The mean counts per ROI were used to calculate lesion-to-reference tissue (LR) ratios for both late and delayed images. An increase in LR over time (LRlate> LRdelayed) of more than 20% was considered indicative of infection. Agreement between readers and between readings was assessed by the first-order agreement coefficient (Gwet's AC1). Reading time for each scan was compared between the three readers in both the first and the second reading, using the Generalized Linear Mixed Model. Results: An excellent agreement was found among all three readers: 0.90 for the first reading and 0.94 for the second reading. Both inter- and intra-variability showed values ≥0.86. Gwet's method demonstrated greater robustness than the Cohen coefficient when assessing the intra and inter-rater variability, since it is not influenced by the prevalence rate. Conclusions: These studies can contribute to improving the reliability of nuclear medicine imaging techniques and to evaluating the effectiveness of trainee preparation.

Chemical kinetic study of methane blended with ammonia cracked gas at elevated temperature and pressure

Ammonia (NH3) on-line cracking to produce hydrogen (H2) can avoid direct ammonia combustion and is an important method to enhance combustion performance and control nitrogen oxide (NOx) emissions. This work aims to study the effects of various ammonia energy ratios (ENH3) and cracking ratios (CNH3) on the combustion and NO emission characteristics of methane (CH4) blended with ammonia cracked gas under lean-burn condition. The results showed that methane co-combustion and ammonia cracking significantly enhance the laminar burning velocity (LBV). The chemical effect plays a dominant role in the enhancement of LBV, but its relative contribution gradually decreases with increasing ENH3 and CNH3. A linear relationship between LBV and (O+H+OH+NH2 + CH3)max was observed, with both the slope and intercept being functions of CNH3. At an ENH3 of 20 %, NO emission decrease with increasing CNH3. At an ENH3 of 80 %, NO emission first increase and then decrease. The percentage of thermal NO is less than 1 % under ambient condition and could increase to as much as 22 % under elevated condition (500 K, 10 atm). Additionally, there was a quadratic polynomial relationship between (O+H+OH+NH2)max and the final NO mole fraction within an equivalence ratio range from 0.4 to 0.8. The second-order coefficient exhibits a linear correlation with CNH3, while the first-order and constant coefficient show a quadratic polynomial correlation with CNH3.

Mathematical models for traffic-source PM2.5 dispersion in an urban street canyon considering the capture capability of roadside trees

Rapid urbanization increases the densely built-up blocks, the population and vehicles. Large amounts of particulate matter (PM), especially PM2.5 (PM with an aerodynamic diameter of 2.5μm or less), from vehicle exhaust are critical to human health. In typical street canyons in hot and humid regions, traffic-source PM usually diffuses to the densely built-up blocks through roadside trees. Roadside trees are a double-edged sword, serving as “guards” to absorb PM2.5 while may lead to PM2.5 gathering in street levels, thereby influencing the PM2.5 dispersion in the densely built-up blocks. To quantify the dispersion process, this study proposed traffic-source PM2.5 dynamic dispersion models considering the capture capability of roadside trees and built-up blocks based on the OSPM model. Due to the difficulty in obtaining the adsorption and deposition rate of the proposed models, the numerical simulations by ENVI-met software were used to solve and obtain the relationship between capture capability and characteristic index of roadside trees. Subsequently, The accuracy and effectiveness of the proposed traffic-source PM2.5 dynamic dispersion models were verified through field experimental data. Results show that the calculated PM2.5 concentration significantly linearly increased with the measured values with the determined coefficient (R2) of 0.98, and the first-order coefficient close to 1. It indicates that the proposed traffic-source PM2.5 dispersion model accurately quantified the impact of roadside trees on PM2.5 and its concentration dispersion process to the built-up blocks. This study provides suggestions for designing characteristic indexes of roadside trees and built-up blocks to improve the air quality of urban street canyons.

Intergrader Agreement in Grading Optical Coherence Tomography Morphologic Features in Eyes With Intermediate Nonexudative Age-Related Macular Degeneration.

To determine the reliability of a nine-point summary scale for grading intermediate age-related macular degeneration (AMD) image morphologic features based on the Early Treatment Diabetic Retinopathy Study (ETDRS) grid. Two trained graders independently divided spectral domain-optical coherence tomography (SD-OCT) scans into nine subfields and then graded each subfield for the presence of intraretinal hyperreflective foci (HRF), reticular pseudodrusen (RPD), and incomplete or complete retinal pigment epithelium and outer retinal atrophy (iRORA or cRORA). Grading results were assessed by summing the subfield grades into a nine-point summary score and also by using an eye-level binary grade for presence of the finding in any subfield. Gwet's first-order agreement coefficient (AC1) was calculated to assess intergrader agreement. Images of 79 eyes from 52 patients were evaluated. Intergrader agreement was higher when the OCT grades were summarized with a nine-point summary score (Gwet's AC1 0.92, 0.89, 0.99, and 0.99 for HRF, RPD, iRORA, and cRORA, respectively) compared with the eye-level binary grade (Gwet's AC1 0.75, 0.76, 0.97, and 0.96 for HRF, RPD, iRORA, and cRORA, respectively), with significant differences detected for HRF and RPD. The use of a nine-point summary score showed higher reliability in grading when compared to the binary subfield- and eye-level data, and thus may offer more precise estimation of AMD disease staging. These findings suggest that a nine-point summary score could be a useful means of disease staging by using findings on OCT in clinical studies of AMD.

Towards High-Performance Pockels Effect-Based Modulators: Review and Projections.

The ever-increasing demand for high-speed data transmission in telecommunications and data centers has driven the development of advanced on-chip integrated electro-optic modulators. Silicon modulators, constrained by the relatively weak carrier dispersion effect, face challenges in meeting the stringent requirements of next-generation photonic integrated circuits. Consequently, there has been a growing interest in Pockels effect-based electro-optic modulators, leveraging ferroelectric materials like LiNbO3, BaTiO3, PZT, and LaTiO3. Attributed to the large first-order electro-optic coefficient, researchers have delved into developing modulators with expansive bandwidth, low power consumption, compact size, and linear response. This paper reviews the working principles, fabrication techniques, integration schemes, and recent highlights in Pockels effect-based modulators.

Bivariate first-order random coefficient integer-valued autoregressive processes based on modified negative binomial operator

In this paper, a new bivariate random coefficient integer-valued autoregressive process based on modified negative binomial operator with dependent innovations is proposed. Basic probabilistic and statistical properties of this model are derived. To estimate unknown parameters, Yule-Walker, conditional least squares and conditional maximum likelihood methods are considered and evaluated by Monte Carlo simulations. Asymptotic properties of the estimators are derived. Moreover, coherent forecasting and possible extension of the proposed model is provided. Finally, the proposed model is applied to the monthly crime datasets and compared with other models.

Assessing the risk of E. coli contamination from manure application in Chinese farmland by integrating machine learning and Phydrus

This study aims to present a comprehensive study on the risks associated with the residual presence and transport of Escherichia coli (E. coli) in soil following the application of livestock manure in Chinese farmlands by integrating machine learning algorithms with mechanism-based models (Phydrus). We initially review 28 published papers to gather data on E. coli's die-off and attachment characteristics in soil. Machine learning models, including deep learning and gradient boosting machine, are employed to predict key parameters such as the die-off rate of E. coli and first-order attachment coefficient in soil. Then, Phydrus was used to simulate E. coli transport and survival in 23692 subregions in China. The model considered regional differences in E. coli residual risk and transport, influenced by soil properties, soil depths, precipitation, seasonal variations, and regional disparities. The findings indicate higher residual risks in regions such as the Northeast China, Eastern Qinghai-Tibet Plateau, and pronounced transport risks in the fringe of the Sichuan Basin fringe, the Loess Plateau, the North China Plain, the Northeast Plain, the Shigatse Basin, and the Shangri-La region. The study also demonstrates a significant reduction in both residual and transport risks one month after manure application, highlighting the importance of timing manure application and implementing region-specific standards. This research contributes to the broader understanding of pathogen behavior in agricultural soils and offers practical guidelines for managing the risks associated with manure use. This study's comprehensive method offers a potentially valuable tool for evaluating microbial contaminants in agricultural soils across the globe.

Atmospheric extinction coefficients and night sky brightness at ITB-Undana remote telescope site

Abstract A remote telescope system has been established at Universitas Nusa Cendana, Kupang. Bosscha Observatory, Institut Teknologi Bandung (ITB), and the Physics Study Program at Universitas Nusa Cendana (Undana) collaborated to develop the system. The ITB-Undana Telescope system has a QSI 616 CCD camera and BV RI Bessel filter attached to a 20-cm (f/10) Schmidt-Cassegrain reflector. Several research and public outreach activities have been conducted using the ITB-Undana remote telescope throughout 2023. When establishing a new astronomical observation site, it is imperative to conduct sky characterization and quality assessment. This process involves measuring night sky brightness and atmospheric extinction coefficients. In May 2023, we observed photometric standard stars using the absolute photometry technique with BV RI Bessel filters. We also utilized the Sky Quality Meter (SQM) to measure night sky brightness over three nights from May 24th to May 26th, 2023, to compare the sky brightness values obtained through the absolute photometry method. Our initial measurement shows a first-order extinction coefficient value ranging from k b ′ = 0.269 to 0.520, k v ′ = 0.216 to 0.297, k r ′ = 0.019 to 0.206, and k i ′ = 0.127 to 0.163, for B, V, R, and I filter, respectively. Application of extinction coefficient value in the sky field gives a mean sky brightness value in V bandpass, V sky = 19.431 ± 0.022, with color index (B − V )sky = 0.492 ± 0.039. These night sky brightness values are suitable for measurements using the SQM.

Dynamic changes in dissolved organic matter during transport of landfill leachate in porous medium.

The dynamic changes in dissolved organic matter (DOM) during the transport of landfill leachate (LL) in porous medium should be explored, considering the high levels of DOM in the LL of municipal solid waste. Column experiments were carried out at 25°C at a Darcy's flux of 0.29cm/h for 2722h to compare the transport of Cl-, ultraviolet absorbance at 254nm (UV254), chemical oxygen demand (COD), and dissolved organic carbon (DOC) in the simulated porous medium by using the CXTFIT2.1 code. Results showed that the convection-dispersion equation (CDE) could describe Cl- transport well. The high levels of λ and D could be highly correlated with the physicochemical properties of the porous medium. The transport of the studied DOM with evident aromatic character could be described appropriately by the CDE model with the first-order reaction assumption, considering the similar variation trends of UV254, COD, and DOC in the effluent during experiments. Specifically, the values of retardation factor (R) were in the following order: DOC > UV254 > COD, whereas the low values of the first-order decay coefficient (k1) for DOC and COD were still higher than that for UV254. High contents of humic-like substances in the DOM with complex toxic components resulted in the natural low removal efficiencies of COD, DOC, and UV254 (≤ 23%), which could be confirmed by the variations of fluorescence index (FI) and humification index (HIX) in the effluent. The results should be helpful in evaluating the environmental risk induced by the LL leakage in a landfill site.

Weak cosmic censorship conjecture and black hole shadow for black hole with generalized uncertainty principle

Based on string theory, loop quantum gravity, black hole physics, and other theories of quantum gravity, physicists have proposed generalized uncertainty principle (GUP) modifications. In this work, within the framework of GUP gravity theory, we successfully derive an exact solution to Einstein’s field equation, and discuss the possibility of using EHT to test GUP and how GUP changes the weak cosmic censorship conjecture for black holes. We analyze two different ways of constructing GUP rotating black holes (model I and model II). Model I takes into account the modification of mass by GUP, i.e., the change in mass by quantization of space, and the resulting GUP rotating black hole metric (18) is similar in form to the Kerr black hole metric. Model II takes into account the modification of the rotating black hole when GUP is an external field, where GUP acts like an electric charge, and the resulting GUP rotating black hole metric (19) is similar in form to the Kerr–Newman black hole metric. The difference between (18) and (19) in the spacetime linear structure provides a basis for us to examine the physical nature of GUP rotating black holes from observation. By analyzing the shadow shape of the GUP rotating black hole, we discover intriguing characteristics regarding the impact of first-order and second-order momentum correction coefficients on the black hole’s shadow shape. These findings will be instrumental in future GUP testing using EHT. Additionally, by incident test particle and scalar field with a rotating GUP black hole, the weak cosmic censorship conjecture is not violated in either extreme black holes or near-extreme black holes.

A comprehensive heat transfer prediction model for tubular moving bed heat exchangers using CFD-DEM: Validation and sensitivity analysis

This study established a complete heat transfer prediction model that integrates four heat transfer sub-models, including contact heat conduction, gas film heat conduction, heat radiation, and heat convection, along with an artificial softening correction based on combined approach of computational fluid dynamics and discrete element method (CFD-DEM). The model’s precision was confirmed by experimental results with relative errors below 5 %. The discussion on the heat flux contributions of the above four heat transfer mechanisms shows that with an initial particle temperature of 200℃, tube wall temperature of 30℃, and particle descent velocity of 1.3 mm/s, gas film conduction heat flux is the primary contributor to the total tube wall heat flux at 60.5 %, followed by radiation heat flux (19.5 %), contact conduction heat flux (12.1 %), and convection heat flux (7.9 %). Besides, the presentation of physical fields related to particles and the fluid showcases the model’s capability in elucidating the heat and mass transfer characteristics of the particle–fluid-wall system within tubular MBHEs. Furthermore, a local nominal range sensitivity analysis, along with a study of factors’ influence rules, was performed to quantify the effects of the 8 key model parameters on heat transfer results. The analysis indicates that fluid thermal conductivity is the predominant factor with its nondimensionalized first-order sensitivity coefficient of 54.9 %, succeeded by particle-to-wall angle factor (15.4 %), wall emissivity (14.4 %), gas film thickness (9.6 %), wall thermal conductivity (2.3 %), wall roughness (-1.6 %), particle Young’s modulus (-1.4 %), and particle specific heat capacity (0.4 %). Finally, their impacts on the heat prediction results were presented in detail.

Introducing a transition domain for describing the solute exchange between macropores/fractures and matrix in dual-permeability system

The dual-permeability model (DPM) is highly efficient for describing the solute transport with multiple flow paths in macroporous/fractured media. However, an accurate and efficient description of the solute exchange process between the macropores/fractures and matrix in the dual-permeability system still remains a challenge. Therefore, a new approach, the dual-permeability model with transition domain (DPMTD), is proposed under saturated conditions. DPMTD characterizes the boundary layer by dividing the part of the matrix blocks in contact with the macropores (or fractures) into the transition domain. This new method takes into account the effect of concentration distribution in the matrix on the solute exchange process without upgrading the dimension of equations. The expressions of the first-order mass transfer coefficient, which is used to describe the interdomain solute exchange in the DPMTD, for four defined aggregate geometries are obtained. A sand column experiment containing an artificial macropore is used to evaluate the performance of the DPMTD and DPM. The simulation results of the DPMTD and DPM reveal that the DPMTD captures the bimodal transport (especially the first peak) more effectively because it calculates the rapid solute exchange in the early time and the slow solute exchange in the later stage more accurately. Subsequently, we studied the effect of η, which indicates the volume proportion of the boundary layer to the dual-permeability media in the DPMTD, on results. In short, this study emphasizes the importance of the boundary layer, and provides a new efficient approach to describe solute exchange process between macropores (or fractures) and matrix in dual-permeability system.

Damage detection of road domain waveform guardrail structure based on machine learning multi-module fusion.

The current highway waveform guardrail recognition technology has encountered problems with low segmentation accuracy and strong noise interference. Therefore, an improved U-net semantic segmentation model is proposed to improve the efficiency of road maintenance detection. The model training is guided by mixed expansion convolution and mixed loss function, while the presence of guardrail shedding is investigated by using partial mean values of gray values in ROI region based on segmentation results, while the first-order detail coefficients of wavelet transform are applied to detect guardrail defects and deformation. It has been determined that the Miou and Dice of the improved model are improved by 8.63% and 17.67%, respectively, over the traditional model, and that the method of detecting defects in the data is more accurate than 85%. As a result of efficient detection of highway waveform guardrail, the detection process is shortened and the effectiveness of the detection is improved later on during road maintenance.

Sm substitution induced spin reorientation and stabilization of double perovskite structure resulting in enhanced magnetoelectricity in LaYFe2O6

We report an enhanced magnetoelectric (ME) effect in spin–phonon coupled single-phase La1−xSmxYFe2O6 (0 ≤ x ≤ 1). The structural, electric, magnetic, and ME properties have been investigated to establish their interplay leading to magnetoelectricity. X-ray diffraction study suggests the facilitation of the P21nm phase (double perovskite lattice arrangements) formation and improved structural order due to the substitution of Sm in the lattice. Antiferromagnetic (AFM) transition ∼700 K along with a spin-reorientation transition around room temperature (RT) and below is observed in the thermomagnetic curve. The indication of short range ordering in the magnetization data in the form of a non-Griffiths-like phase (nGP) is observed. The short range ordering could be minimized along with consequent improvement in AFM ordering, due to Sm substitution. An enhanced (∼31% with respect to x = 0) RT first-order ME coupling coefficient ∼0.59 mV cm−1 Oe−1 in x = 0.75 composition is observed. The findings reported here open the door to exercise spin-reorientation transition in the spin–phonon coupled double perovskites for spintronic device applications.

Integral Transforms and the Hyers–Ulam Stability of Linear Differential Equations with Constant Coefficients

Integral transform methods are a common tool employed to study the Hyers–Ulam stability of differential equations, including Laplace, Kamal, Tarig, Aboodh, Mahgoub, Sawi, Fourier, Shehu, and Elzaki integral transforms. This work provides improved techniques for integral transforms in relation to establishing the Hyers–Ulam stability of differential equations with constant coefficients, utilizing the Kamal transform, where we focus on first- and second-order linear equations. In particular, in this work, we employ the Kamal transform to determine the Hyers–Ulam stability and Hyers–Ulam stability constants for first-order complex constant coefficient differential equations and, for second-order real constant coefficient differential equations, improving previous results obtained by using the Kamal transform. In a section of examples, we compare and contrast our results favorably with those established in the literature using means other than the Kamal transform.

Vertical behavior of a suction caisson using state-dependent sand friction angles

The vertical bearing capacity of the suction caissons is vital to the safety of marine jacket foundations. The sand friction angle is a key parameter for calculating the vertical bearing capacity. The sand friction angle is state-dependent, which is affected by the compact state and stress state. However, this effect is neglected in the current study, resulting in deviations in the calculation results of the vertical bearing capacity. Therefore, a novel method is preliminarily proposed to account for this impact while evaluating the vertical bearing capacity of suction foundations. First, a new friction angle is expressed as a function of relative density and soil depth, which differs significantly from the commonly used constant friction angle. The state-dependent sand friction angle is available. Then, the general and simplified vertical bearing capacity formulas are clarified. Four key parameters in the former and a new first-order coefficient in the latter are identified. The calculation procedure based on the new friction angle is also specified. Finally, combined with model tests, a comparison study is carried out. The results show that the calculation results using the new friction angle are more accurate and practical. This study can provide a reference for the foundation design.