Optimal Reference Research Articles

Preliminary design and hydrodynamic study of power-driven float pole system in Pacific saury fishery

Pacific saury (Cololabis saira), an essential commercial fish species in the North Pacific Ocean, is captured primarily using the stick-held dip net (SHDN) method. During the netting process, the separation of the gear from the vessel is dependent on the wind and currents, which represents a passive operational approach. In this study, we designed a prototype power-driven device for SHDN gear. The device consists of two thrusters, a remote-control system, and an energy device. It was installed on a 1/10 length segment of a float pole, hereafter referred to as the power-driven float pole (PFP) prototype. Experiments were conducted on both the single-thruster and PFP prototype to investigate the relationship between their rotational speed and thrust. SolidWorks was used to model the single-thruster and PFP prototype, and Ansys Fluent was used to solve the Reynolds-averaged Navier–Stokes equations to obtain the hydrodynamic characteristics of both the thruster and PFP prototype. A comparative analysis of the experimental and simulated hydrodynamic results showed the following: (1) the flow velocity between the blade suction surface and pressure surface tended to decrease, and the pressure tended to increase; (2) the thrust of both the single-thruster and PFP prototype increased with the thruster rotational speed according to a quadratic polynomial relationship; (3) the thrust ratio between the PFP prototype and the combined thrust of the two thrusters under the no-load condition exhibited a logarithmic relationship with the increasing rotational speed; and (4) to meet the operational requirements of the PFP prototype with a working duration exceeding 350 min and a minimum thrust of 20 N, the recommended rotational speed range for the thrusters on the PFP prototype was 1569–1970 rpm. The results of this study provide a fundamental reference for the further optimization of the PFP configurations.

Fast and accurate prediction of interference spectra of non-adiabatic tapered microfiber Mach-Zehnder interferometer in liquid

Microfiber Mach-Zehnder interferometer (MMZI) is a widely used optical device. To solve the problems of large difference between the theoretical and experimental spectrum, low calculation efficiency, poor universality in spectrum calculation of MMZI, a fast and accurate calculation method for predicting the interference spectrum of MMZI used in liquid is proposed. In calculations, phase accumulated in transition region of the taper is considered to reach a good agreement between theoretical and experimental spectrum. To further improve the computational efficiency, dependence of the phase accumulation on wavelength is developed by linear fitting, and a non-linear fitting of difference of effective refractive index (∆neff) on fiber diameter, wavelength, temperature and salinity of the surrounding is obtained by the data from commercial software. In addition, a visual interface for displaying the predicted spectrum is established, by which one accurate spectral calculation can be realized within only two or three seconds. Finally, effects of LP03 mode and shape of transition region on transmission spectrum are discussed and the accuracy of this method is also verified by sensitivity. The calculation method demonstrated here provides an accurate and fast spectral prediction method for MMZI, and will afford important reference for sensor design and optimization.

Performance Optimization and Experimental Study of Small-Scale Potato-Grading Device

Traditional potato grading in China relies mostly on manual sorting, which is labor-intensive, time-consuming, costly, and inefficient. To enhance the operational performance of potato-grading devices, this paper focuses on optimizing the slide rail structure, which is the key component of a self-developed first-generation potato-grading device. A five-factor, three-level orthogonal experiment was designed, with the experimental factors being the height of the horizontal slide rail, angle of the first-stage inclined slide, angle of the second-stage inclined rail, chain horizontal movement speed, and conveyor belt speed. The indoor experiments were conducted using grading accuracy and grading efficiency as the experimental indicators. On the basis of the analysis of the orthogonal experiment results, two relatively optimal solutions were obtained, and validation experiments were conducted. The validation results show that when the height of the horizontal slide rail was 185 mm, the angle of the first-stage inclined rail was 4°, the angle of the second-stage inclined rail was 2.5°, the horizontal movement speed of the chain was 700 mm/s, and the movement speed of the conveyor belt was 275.60 mm/s, the performance of the movable rotating plate (MRP)-type grading device for potatoes reached its optimum. At this point, the grading accuracy was 94.88%, and the grading efficiency was 13.9477 t/h. Compared with the first-generation grading device, the optimized grading device achieved an improvement of 3.84% in grading accuracy and 12.94% in grading efficiency. The research methodology provided in this paper serves as a reference for the performance optimization of potato-grading devices.

Research on influencing factors of college teachers' second child fertility intentions--Taking Jinan as an example.

Fertility intentions, as a direct driver of fertility behavior, play an important role in the implementation of national fertility policy and population development. This study explored the influencing factors of college teachers' second child fertility intentions in Jinan, China on the basis of TPB. Based on the theory of planned behavior, this paper employs basic characteristics analysis, difference analysis, and factor analysis related to the fertility intentions of the participants. Analysis found participants between 31 and 40 years old had the highest second child fertility intentions, and participants with a college-age first child had the lowest second child fertility intentions. Attitude and subjective norms had a positive impact on second child fertility intentions, and policy awareness had a positive impact on attitude, which indirectly affected second child fertility intentions. Subjective norms had the greatest influence on second child fertility intentions, followed by attitude, and policy awareness had the least influence on second child fertility intentions. The findings of this paper can enrich the theoretical research on fertility intentions, and also provide more optimal practical references for the formulation and propagation of China's fertility policy as well as the improvement of the division of family roles in China. Future research can further explore the impact of fertility policy on the fertility intentions of other groups.

Time-Optimal Trajectory Planning and Tracking for Autonomous Vehicles.

This article presents a hierarchical control framework for autonomous vehicle trajectory planning and tracking, addressing the challenge of accurately following high-speed, at-limit maneuvers. The proposed time-optimal trajectory planning and tracking (TOTPT) framework utilizes a hierarchical control structure, with an offline trajectory optimization (TRO) module and an online nonlinear model predictive control (NMPC) module. The TRO layer generates minimum-lap-time trajectories using a direct collocation method, which optimizes the vehicle's path, velocity, and control inputs to achieve the fastest possible lap time, while respecting the vehicle dynamics and track constraints. The NMPC layer is responsible for precisely tracking the reference trajectories generated by the TRO in real time. The NMPC also incorporates a preview algorithm that utilizes the predicted future travel distance to estimate the optimal reference speed and curvature for the next time step, thereby improving the overall tracking performance. Simulation results on the Catalunya circuit demonstrated the framework's capability to accurately follow the time-optimal raceline at an average speed of 116 km/h, with a maximum lateral error of 0.32 m. The NMPC module uses an acados solver with a real-time iteration (RTI) scheme, to achieve a millisecond-level computation time, making it possible to implement it in real time in autonomous vehicles.

A novel method of fuel consumption prediction for wing-diesel hybrid ships based on high-dimensional feature selection and improved blending ensemble learning method

Establishing an accurate fuel consumption prediction model is essential to optimize energy efficiency in wing-diesel hybrid ships. This study proposes an improved Blending ensemble learning method for predicting fuel consumption. Initially, the original data is cleaned using artificial experience and Interquartile Range (IQR) method. A high-dimensional feature selection method, variance analysis- Pearson correlation-mutual information-permutation importance (VA-PC-MI-PI), is then proposed to identify 16 key features from the initial 111 features. Furthermore, 9 algorithms are employed for prediction analysis under different temporal resolution data conditions. Based on the results, optimal time step and algorithm models are determined to construct the Blending ensemble model (BEM). Subsequently, the feature data of “sailing speed” and “bow draft”, which account for the highest permutation importance, are imported into the metadata set to alleviate insufficient BEM data utilization. Additionally, Extra Trees (ET) model is chosen as the meta-learner for adaptation and Bayesian method is employed for global optimization. The resulting improved Blending ensemble model (IBEM) exhibits optimal prediction accuracy and generalization ability with an RMSE of 66.04 kg/h, representing a reduction of 16.99% and 13.86% compared to the Support Vector Machine (SVM) model and BEM, respectively. Additionally, the IBEM exhibits significantly smaller residuals and absolute residuals, demonstrating superior predictive stability and consistency. This study provides an important reference and basis for energy efficiency prediction, control, and optimization of wing-diesel hybrid ships.

Reference Genes for Expression Analyses by qRT-PCR in Enterobacter cancerogenus.

The Enterobacter cancerogenus strain EcHa1 was isolated from the dead larvae of Helicoverpa armigera, and has the potential for biocontrol of some Lepidoptera insects. In order to screen insecticidal-related genes by qRT-PCR, stable endogenous reference genes used for normalizing qRT-PCR data were selected and evaluated from 13 housekeeping genes (HKGs). The expression levels of the HKGs were determined using qRT-PCR under different experimental conditions, including two culture temperatures and three bacterial OD values. Five stability analysis methods (Ct, BestKeeper, NormFinder, geNorm, and RefFinder) were used to comprehensively rank the candidate genes. The results showed that the optimal reference genes varied under different experimental conditions. The combination of gyrA and gyrB was recommended as the best reference gene combination at 28 °C, while gyrA and rpoB was the best combination at 37 °C. When the OD values were 0.5, 1.0 and 2.0, the recommended reference gene combinations were ftsZ and gyrA, rpoB and gyrB, and gyrA and pyk, respectively. The most suitable reference genes were gyrA and gyrB under all experimental conditions. Using gyrA and gyrB as the reference genes for qRT-PCR, EcHa1 was found to invade all tissues of the H. armigera larvae, and expressed a candidate pathogenic factor Hcp at high levels in gut, Malpighian tubules, and epidermis tissues. This study not only establishes an accurate and reliable normalization for qRT-PCR in entomopathogenic bacteria but also lays a solid foundation for further study of functional genes in E. cancerogenus.

Controllable regulation of diamond nucleation and growth on GaN substrates through pulse bias duty ratio

GaN/AlN/diamond composite structures were prepared by the pulsed-DC bias-enhance nucleation (BEN) technique. Smooth diamond interface on GaN surface obtained for the first time by BEN technique. Different bias duty ratios (30%–70 %) can regulate the nucleation of diamond. The nucleation density increases and then decreases with the increase of duty ratio. The highest nucleation density was 1011 cm−2 which enough to grow a dense diamond layer on GaN. The effect of BEN treatment on the interface was investigated and some positive and negative results were obtained. After diamond deposition, GaN layer was protected by amorphous carbon and dielectric layers from hydrogen plasma, which implies that the BEN technique has the potential to be applied to grow diamond on GaN surfaces. A smooth and complete interfacial structure was obtained after diamond deposition. After the BEN treatment, 10 nm AlN layer was carbonized into an amorphous structure. BEN duty cycle can modulate GaN/AlN/diamond interface structure, which may reduce interfacial thermal conductivity. These results demonstrate the potential of BEN technique for diamond deposition on GaN substrates and provides a reference for further optimization.

Time- and Region-Specific Selection of Reference Genes in the Rat Brain in the Lithium-Pilocarpine Model of Acquired Temporal Lobe Epilepsy.

Reverse transcription followed by quantitative polymerase chain reaction (RT-qPCR) is a commonly used tool for gene expression analysis. The selection of stably expressed reference genes is required for accurate normalization. The aim of this study was to identify the optimal reference genes for RT-qPCR normalization in various brain regions of rats at different stages of the lithium-pilocarpine model of acquired epilepsy. We tested the expression stability of nine housekeeping genes commonly used as reference genes in brain research: Actb, Gapdh, B2m, Rpl13a, Sdha, Ppia, Hprt1, Pgk1, and Ywhaz. Based on four standard algorithms (geNorm, NormFinder, BestKeeper, and comparative delta-Ct), we found that after pilocarpine-induced status epilepticus, the stability of the tested reference genes varied significantly between brain regions and depended on time after epileptogenesis induction (3 and 7 days in the latent phase, and 2 months in the chronic phase of the model). Pgk1 and Ywhaz were the most stable, while Actb, Sdha, and B2m demonstrated the lowest stability in the analyzed brain areas. We revealed time- and region-specific changes in the mRNA expression of the housekeeping genes B2m, Actb, Sdha, Rpl13a, Gapdh, Hprt1, and Sdha. These changes were more pronounced in the hippocampal region during the latent phase of the model and are thought to be related to epileptogenesis. Thus, RT-qPCR analysis of mRNA expression in acquired epilepsy models requires careful selection of reference genes depending on the brain region and time of analysis. For the time course study of epileptogenesis in the rat lithium-pilocarpine model, we recommend the use of the Pgk1 and Ywhaz genes.

Progress, limitations, and prospects for improvement in understanding the impact of urban built environment on residents’ leisure-time physical activity in China: A systematic review

Leisure-time physical activities (LTPAs) play a crucial role in improving health. Likewise, improving certain aspects of the built environment is essential for promoting residents to engage in LTPA. However, the impact of urban built environment characteristics on residents’ levels of LTPA and its underlying mechanism remain unclear. To address this gap, we conducted a systematic literature review in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. In 2022, we searched eight databases and identified 453 relevant publications. The selected literature had to meet specific inclusion criteria: (i) the sample targeted Chinese adults (≥18 years), and (ii) it quantified the effect of urban built environment characteristics on residents’ levels of LTPA. Out of the initial pool, 18 articles met our inclusion criteria. Our findings indicate that although previous studies have revealed that esthetic perception and road safety can facilitate residents’ participation in LTPA, there is a lack of methods for identifying built environment characteristics and analyzing the psychosocial mediation mechanism between the built environment and LTPA in specific populations. Improving the robustness of research conclusions is an important research direction that will yield solid evidence of the impact of the urban environment on human health. Limited evidence exists regarding the association between urban built environment characteristics in China and residents’ LTPA levels. However, advancements in remote sensing images, computer vision in artificial intelligence, and machine learning technologies offer innovative avenues for modeling built environments and land use functions. Developing an impact mechanism model of the built environment and LTPA using individual perceptions and social psychological factors as mediating mechanisms is imperative. This approach will serve as a reference for urban spatial optimization and the development of spatial planning intervention tools.

Research on the Evolution and Innovation of Guangdong Province's Business Environment from a Digital Perspective

This study, conducted against the backdrop of current digital development, systematically analyzes and discusses the status quo, problems, and countermeasures of the business environment in Guangdong Province. It reviews and critiques both domestic and international research on the definition of the business environment, the relationship between digitalization and the business environment, and the factors influencing the digitalization of the business environment. A comprehensive analysis of the internationalized business environment of Guangdong Province is presented, showcasing its advantages and characteristics in terms of digital infrastructure, digital technology innovation, and data element circulation, while also pointing out existing deficiencies and challenges. These serve as a reference for further optimization of the business environment. The article concludes by exploring and suggesting innovative pathways for Guangdong Province's internationalized business environment, proposing a series of specific measures and plans to enhance digital innovation leadership capabilities and create a digitally empowered business environment. The aim is to promote the digital transformation and upgrading of Guangdong Province's business environment, thereby improving its level of digital development and international competitiveness.

Evaluating optimal reference translations

Abstract The overall translation quality reached by current machine translation (MT) systems for high-resourced language pairs is remarkably good. Standard methods of evaluation are not suitable nor intended to uncover the many translation errors and quality deficiencies that still persist. Furthermore, the quality of standard reference translations is commonly questioned and comparable quality levels have been reached by MT alone in several language pairs. Navigating further research in these high-resource settings is thus difficult. In this paper, we propose a methodology for creating more reliable document-level human reference translations, called “optimal reference translations,” with the simple aim to raise the bar of what should be deemed “human translation quality.” We evaluate the obtained document-level optimal reference translations in comparison with “standard” ones, confirming a significant quality increase and also documenting the relationship between evaluation and translation editing.

Quantitative 1H NMR Spectroscopy Method for Determination of Anthraquinone Derivatives in Extracts from Rubia tinctorum L. Roots and Rhizomes

Quantitative 1H NMR Spectroscopy Method for Determination of Anthraquinone Derivatives in Extracts from Rubia tinctorum L. Roots and Rhizomes

Adaptive reinforcement learning-based control using proximal policy optimization and slime mould algorithm with experimental tower crane system validation

This paper presents a novel optimal reference tracking control approach resulted from the combination of a popular policy gradient Reinforcement Learning (RL) algorithm, namely Proximal Policy Optimization (PPO), and a metaheuristic Slime Mould Algorithm (SMA). One of the most important parameters in the PPO-based RL process is the learning rate, which has a big impact on how the parameters of the actor neural network (NN) are iteratively updated. In every episode of the RL process, the weights and the biases of the actor NN are multiplied with the learning rate, determining how much the learning agent will step into a certain direction computed based on previous experiences. The classical PPO algorithm usually relies on fixed values for the learning rates which rarely change, or not at all, during the learning process. However, its main drawback is that the learning agent cannot take advantage of positive momentum in the learning process by accelerating towards good learning experiences or slow down and quickly change the direction in the case of consecutive negative learning experiences. The main objective of the combination proposed in this paper is to create an adaptive SMA-based PPO approach applied to control systems, which instead of using fixed learning rate values, it uses the SMA to compute optimal values of the learning rates in each time step of the learning process based on the progress of the learning agent. This paper investigates if the adaptive SMA-based PPO control approach can be considered as an alternative to the classical PPO version, which employs fixed values of the learning rate. A comparison is carried out using control system performance indices gathered while performing an optimal reference tracking control task on tower crane system laboratory equipment.

FTIR determination of the degree of molar substitution for hydroxypropyl chitosan

We developed and validated a novel Fourier transform infrared (FTIR) method to determine the degree of molar substitution (MS) for hydroxypropyl chitosan (HPCS) using nuclear magnetic resonance (1H NMR) as a reference, and investigated the factors influencing the MS assay. Through extensive screening of integration methods for candidate bands in the FTIR spectrum of HPCS using 20 HPCS samples with degrees of acetylation (DA) ranging from 0.003 to 0.139, we found that when using band area at 2970 cm−1 as a probe integral, the MS values obtained via the 1H NMR method exhibited linear correlations (R2 > 0.98) with at least 16 integral ratios derived from their FTIR spectra. The optimal reference bands with high reliability are located at 3440 cm−1 and 1415 cm−1, with R2 exceeding 0.99 and a MS range of 0.17–1.92. The band at 2875 cm−1 is less affected by the trace moisture present in HPCS samples than the others. The results of the method validation demonstrated a mean recovery of 98.9 ± 2.8 % and an RSD below 10 %, suggesting a simple, robust, and highly accurate and precise method. This method could be extendable for the determination of the MS of insoluble HPCS derivatives and other hydroxypropylated polysaccharides.

An optimal decision for fresh products' cold chain considering freshness and carbon emission reduction

PurposeThe aim of this study was to analyze the effects of carbon reduction efforts and preservation efforts on system benefits in the cold chain industry of fresh products.Design/methodology/approachThis study develops an optimal decision game model for the fresh products in the cold chain, incorporating the retailer's preservation effort and the supplier's carbon emission reduction effort. It quantifies the relationship between carbon emission reduction effort, preservation effort and system profit. The model considers parameters like carbon trading price, consumer low-carbon preference and consumer freshness preference, reflecting real-world conditions and market trends. Numerical simulations are conducted by varying these parameters to observe their impact on system profit.FindingsUnder the carbon cap-and-trade policy, the profit of the fresh cold chain system is higher than that of the fresh cold chain system without carbon constraints, and the profit of the supplier under decentralized decision-making is increased by nine times in the simulation results. The increase in carbon trading prices can effectively improve the freshness level of fresh products cold chain, carbon emission reduction level and system profit.Originality/valueThis study comprehensively considers the factors of freshness and carbon emission reduction, provides the optimal low-carbon production decision-making reference for the fresh food cold chain and promotes the sustainable development of the fresh food cold chain.

Robot obstacle avoidance optimization by A* and DWA fusion algorithm.

The current robot path planning methods only use global or local methods, which is difficult to meet the real-time and integrity requirements, and can not avoid dynamic obstacles. Based on this, this study will use the improved A-star global planning algorithm to design a hybrid robot obstacle avoidance path planning algorithm that integrates sliding window local planning methods to solve related problems. Specifically, A-star is optimized by evaluation function, sub node selection mode and path smoothness, and fuzzy control is introduced to optimize the sliding window algorithm. The study conducted algorithm validation on the TurtleBot3 mobile robot, with data sourced from experimental data from a certain college. The results showed that hybrid algorithm enabled the planned path to effectively navigate around dynamic obstacles and reach the target point accurately. When compared with traditional methods, path length reduced by 9.6%, path planning time decreased by 29% with an approximate 26.7% increase in the average speed of the robot. Compared with the traditional methods, the research algorithm has greatly improved in avoiding dynamic obstacles, path planning efficiency, model adaptability and so on, which has important value for relevant research. It can be seen that the algorithm proposed in the study has performance advantages, demonstrating the effectiveness and advantages of robot path planning, and can provide reference for robot obstacle avoidance optimization. Research can complete tasks for robots in practical environments, which has certain reference value for the research of robots in path planning and the development of path obstacle avoidance planning.

Identification of NOx emissions and source characteristics by TROPOMI observations – A case study in north-central Henan, China

With the development of industries, air pollution in north-central Henan is becoming increasingly severe. The TROPOspheric Monitoring Instrument (TROPOMI) provides nitrogen dioxide (NO2) column densities with high spatial resolution. Based on TROPOMI, in this study, the nitrogen oxides (NOx) emissions in north-central Henan are derived and the emission hotspots are identified with the flux divergence method (FDM) from May to September 2021. The results indicate that Zhengzhou has the highest NOx emissions in north-central Henan. The most prominent hotspots are in Guancheng Huizu District (Zhengzhou) and Yindu District (Anyang), with emissions of 448.4 g/s and 300.3 g/s, respectively. The Gaussian Mixture Model (GMM) is applied to quantify the characteristics of emission hotspots, including the diameter, eccentricity, and tilt angle, among which the tilt angle provides a novel metric for identifying the spatial distribution of pollution sources. Furthermore, the results are compared with the CAMS global anthropogenic emissions (CAMS-GLOB-ANT) and Multi-resolution Emission Inventory model for Climate and air pollution research (MEIC), and they are generally in good agreement. However, some point sources, such as power plants, may be missed by both inventories. It is also found that for emission hotspots near transportation hubs, CAMS-GLOB-ANT may not have fully considered the actual traffic flow, leading to an underestimation of transportation emissions. These findings provide key information for the accurate implementation of pollution prevention and control measures, as well as references for future optimization of emission inventories. Consequently, deriving NOx emissions from space, quantifying the characteristics of emission hotspots, and combining them with bottom-up inventories can provide valuable insights for targeted emission control.

Exploring the filtration performance and usage cost of commercial fiber air filters for capturing moxa smoke aerosols

Traditional moxibustion treatments plays a role in preventing and treating COVID-19 while aggravating indoor air pollution. Therefore, commercial fiber air filters (CFAF) are widely used to improve indoor air quality to reduce the risk of people being exposed to moxa smoke aerosols (MSA). Considering that there were few reports on the performance of CFAF for capturing MSA, we explored in detail the effects of face velocity and MSA particle size on the filtration performance of CFAF to fill this gap. Then, we analyzed the deposition characteristics of MSA on fibers in combination with SEM images. In addition, the long-term stability, cleaning performance and MSA holding capacity of the CFAF were further characterized by tests of continuous operation, clean air delivery rate (CADR) and MSA loading. The results indicated that the CFAF had the potential to efficiently capture MSA in indoor air at an acceptable annual usage cost (AUC). Specifically, the pristine CFAF had high classification counting efficiency (CCE) (99.1 %-100 %), medium pressure drop (150.3 Pa), and low quality factor (0.04 Pa−1) at the face velocity of 0.3 m·s−1. Note that increasing face velocity not only decreased CCE and quality factor but also significantly increased pressure drop. Furthermore, the CFAF maintained excellent CCE (99.5 %-100 %) after 24-h of continuous operation at high concentrations of MSA (100 mg·m−3), while the pressure drop increased to 203.7 Pa. Obviously, the deposited MSA severely clogged the inter-fiber pores, which explained the fact of the rapid increase in the pressure drop of the CFAF. Of course, the high CADR value (66.6 m3·h−1) also demonstrated that the CFAF had the ability to efficiently remove MSA from confined place. Moreover, a total of 216.3 g MSA can be captured by the CFAF when the final pressure drop reached 300 Pa, which meant that further increasing the MSA holding capacity would be the focus of future research by filter media manufacturers. Finally, through the established mathematical model, we successfully predicted the service life (86 days) and the total AUC (276 $·year−1) of using the CFAF to capture MSA. This work is expected to provide a useful reference for routine maintenance and design optimization of existing CFAF.

Valuing and integrating soil roles in assessing the capital dimension of soil security: An Australian case study

The crucial role of soil in global food production and its multifaceted contributions to ecosystem services underscore the need for a comprehensive evaluation framework. This study presents a novel approach to soil evaluation by integrating the assessment of soil functions, services, and threats into a unified metric which quantifies the capital dimension which is termed "soil management capital". To achieve this, we focused on three key roles: a threat, evaluated by the pH regulation costs, factoring in different buffering capacities and liming/sulphuring treatments to attain an optimal reference pH, a function, representing soil's role as a reservoir and regulator of nutrients; and a service, considering available water holding capacity (AWC) for water security. Integrating these activities culminates in a soil capital metric, providing a comprehensive understanding of the soil's economic value in US$/ha units on a pixel-by-pixel basis across Australia. To achieve this, we analysed spatial information from the Soil and Landscape Grid of Australia (SLGA) with Google Earth Engine (GEE). Our study generated detailed maps illustrating pH regulation costs, OC, nutrients (N, P, K), and AWC across Australia. The integration of these roles revealed regions of large soil capital in the Australian eastern coast and Tasmania.