Dynamic Change Process Research Articles

Model Predictive Hybrid PID Control and Energy-Saving Performance Analysis of Supercritical Unit

In response to the escalating challenges of rapid load fluctuations and intricate operating environments, supercritical power units demand enhanced control efficiency and adaptability. To this end, this study introduces a novel model predictive hybrid PID control strategy that integrates PID with model predictive control (MPC), leveraging the operational characteristics of multi-loop systems. The proposed strategy adeptly marries the swift response of PID controllers with the foresight and optimization capabilities of MPC. A dynamic model of a supercritical unit is constructed using the subspace identification method. The model’s high precision is confirmed by its alignment with field data. Load change simulations demonstrate that the PID–MPC hybrid controller shows faster response times and more precise tracking capabilities compared to the feedforward-PID strategy. It achieves substantial improvements in the IAE index for three loops, with increases of 29.2%, 54.1%, and 57.3% over the feedforward-PID controller. An energy-saving performance analysis indicates that the proactive control actions of both the PID–MPC and MPC strategies lead to dynamic exergy efficiency and coal consumption rates with a broader range of dynamic process changes. The disturbance scenario simulation regarding the proposed controller achieves faster settling times and minimizes control deviation compared to the traditional controller.

Comprehensive Analysis of Feasibility by Ascending Mining in Coal Mine

In order to study the feasibility of upward mining in a certain coal mine, the mechanical parameters of the coal rock mass were obtained based on on-site investigation and rock mechanics experiments. A numerical model that conforms to the on-site mining layout was established using numerical simulation methods. The stress, displacement, and plastic zone distribution characteristics of the upper coal rock mass at different positions along the X, Y and Z directions after the initial mining of layered coal were analyzed. The critical thickness for tensile failure of the roof during upward mining was calculated using the thick plate theory. A ground penetrating radar was used on site to conduct three-dimensional detection of the fragmentation characteristics of the overlying roof rock. The results show that after the mining of 5# coal, the stress of the overlying roof surrounding rock in the goaf exhibits a dynamic change process of rising peak falling. As the vertical height from the working face increases, the stress in the center of the goaf and around the working face gradually decreases; the displacement distribution extends outwards from the center of the working face, forming a sinking basin with an upward opening in the direction of inclination and direction of the working face. The maximum displacement value is at the bottom of the basin; there is a tensile stress zone above the working face, and the plastic zone has the largest range at the center of the working face direction and inclination. The plastic zone has not evolved to coal 4# and coal 3#; the maximum critical thickness for tensile failure of the roof is 55.4 m, which is much smaller than the actual thickness of 99.82 m on site, and upward mining can be adopted.

Metal welding-inspired phase change self-healing strategy applied to high-modulus hydrogel composites

The self-healing efficiencies of polymers are inversely proportional to their modulus, as the recovery of the polymer network heavily relies on the mobility of polymer chains. Therefore, reinvigorated by the metal welding, we have developed S-PAM-SA-x supercooling hydrogels, consisting of polyacrylamide hydrogel networks and inorganic CH3COONa·3H2O phase change materials. Subsequently, rigid self-healing H-PAM-SA-x composites were achieved via self-actuated crystallization-related phase change from the supersaturated hydrogels, resulting in a significant enhancement in mechanical properties. Notably, the Young’s modulus experienced an astonishing increase from 0.07 to 387.1 MPa. The H-PAM-SA-130 % composites demonstrated satisfactory self-healing performance based on the phase change of melting and crystallization, as the dominant mechanical carrier was found to be the crystal lattice rather than the PAM network. Leveraging the reversible nature of melting and crystallization, the same position can undergo multiple healing cycles without compromising self-healing efficiencies. Moreover, this distinctive dynamic phase change process significantly expands the range of functional applications, encompassing self-healing, adhesion, and patterns’ replication among others.

Analysis of lncRNAs and Their Regulatory Network in Skeletal Muscle Development of the Yangtze River Delta White Goat.

lncRNA (long non-coding RNA) has been confirmed to be associated with growth, development, cell proliferation, and other biological processes. This study explored the potential role and dynamic change process of lncRNAs and related ceRNA (competitive endogenous RNA) networks in skeletal muscle development of the Yangtze River Delta White (YDW) goat, and to analyze the differences in muscle fiber characteristics and meat quality levels of goats at different growth stages. In this study, we compared the expression profiles of lncRNAs in the M. Longissimus dorsi of the YDW goats at different stages of growth and development by RNA sequencing. The results revealed that, in terms of muscle fiber characteristics, muscle fiber diameter and muscle fiber area were significantly larger in 6-month-old and 10-month-old goats than those in 2-month-old goats (p < 0.01). In terms of muscle quality, a* and b* values of 6-month-old goats were significantly higher than those of 2-month-old goats (p < 0.01). Additionally, the a*, b*, and L* values of 6-month-old goats were significantly higher than those of 10-month-old goats (p < 0.01). The pH at 45 min post-mortem (pH45min) in 10-month-old goats was significantly higher than that in 2-month-old goats (p = 0.006). However, the pH at 24 h post-mortem (pH24h) in 10-month-old goats was significantly lower than that in both 2-month-old and 6-month-old goats (p < 0.01). Shear force increased gradually with age (p < 0.05), while there was no significant difference in drip loss among the different age groups (p > 0.05). Among the identified lncRNA expression profiles, a total of 3073 lncRNAs were found, including 2676 known lncRNAs and 397 novel lncRNAs. Of these, 110, 93, and 99 lncRNAs were specifically expressed in 2-month-old, 6-month-old, and 10-month-old goats, respectively. The lncRNA target gene enrichment analysis showed that they were mainly involved in actin binding, the actin cytoskeleton, the myocardin complex, as well as the AMPK, FoxO, and GnRH signaling pathways. When constructing the lncRNA-miRNA-mRNA ceRNA network, it was found that the ceRNA networks centered on chi-miR-758 and chi-miR-127-5p were involved in muscle development across all three periods, suggesting that they may play an important role in goat muscle growth and development.

How can sustainable entrepreneurial enterprises escape the "green prison" in the context of environmental dynamism? — An Ecological Niche Enhancement Perspective

The "green prison" refers to the prisoner's dilemma that entrepreneurs face in regard to sustainability, and entrepreneurs tend to escape from the green prison through a series of proactive legitimizing behaviors such as "changing or establishing institutions that create incentives to play the competitive game—norms, property rights, and legislation". However, how sustainable entrepreneurial enterprises (SEEs) escape from the "green prison" under environmental dynamism and the dynamic changes in the legitimacy acquisition process has not yet received adequate attention. This paper introduces ecological niche theory into legitimacy research, interprets the growth of SEE as the process of individual ecological niches realizing ecostate‒ecorole enhancement within population ecological niches, constructs a set of legitimacy scales and an ecostate‒ecorole index system for SEE, and empirically analyzes a sample of 307 SEEs in China. The results show that (1) cognitive legitimacy, normative legitimacy, and regulatory legitimacy play the ecostate‒ecorole enhancement roles for SEEs at low, medium, and high ecological niche levels, respectively; (2) the dynamic change patterns of legitimacy are consistent across the economic, social, and environmental dimensions of the ecological niche of a SEE; (3)environmental dynamism positively moderates the relationship between cognitive legitimacy and the ecological niche situation at a low ecological niche level, as well as between normative legitimacy and the enhancement of the ecological niche situation at a medium ecological niche level, however, it does not moderate the relationship between regulatory legitimacy and the enhancement of the ecological niche situation at a high ecological niche level. This study identifies the paths through which legitimacy changes dynamically along different dimensions and levels of the ecological niche of a SEE, which provides new guidelines on how SEEs can acquire legitimacy under environmental dynamism and expands and enriches the research field of ecological niche theory.

Research on the recycling decision of WEEE in rural China under dual supervision

Against the backdrop of promoting green, low-carbon, and high-quality development, this paper aims to promote efficient recycling of waste electrical and electronic equipment (WEEE) in rural China. In this paper, considering the integrated development of urban and rural areas and the standardization of industrial recycling system, under the joint action of the extension of producer responsibility and “dual regulation” of supply and marketing cooperatives, the evolutionary game model and system dynamics model of three-level recycling network of farmers, supply and marketing cooperatives and retailers are established. The mechanism of the participants to promote the recycling of WEEE in rural areas is discussed and the strategic choices and interactive relationships of various entities in the evolutionary process were used to analyze through the evolutionary game method. Meanwhile, using the theory of system dynamics, the main influencing factors of different evolution stages and the dynamic change process of the system are analyzed. The results show that: (1) supply and marketing cooperatives, retailers, and farmers can initially tend to participate in and supervise the recycling of WEEE; however, (2) they can finally achieve strong supervision, actively undertake and participate in the recycling and stabilization stable strategy of rural WEEE depends on their benefits and cost of expenditure expenditures are reasonable. (3) The strategic choice of supply and marketing cooperatives has the most significant impact on the strategic choice of retailers and the strategic choice of retailers has the most significant impact on the strategic choice of farmers.

Optimal iterative learning PI controller for SISO and MIMO processes with machine learning validation for performance prediction

The multivariable process plays a significant role in industrial applications, and designing a controller for the Multi-Input Multi-Output process is challenging due to dynamic process changes and interactions between system variables. Traditionally, the PI family of controllers has been used for its simple design, easy tuning, and quick deployment. However, these processes require complex control actions due to multiple loops in process plants. Thus, this paper proposes an Iterative Learning Controller Dead-time compensating PI, which utilizes the newly developed hybrid Simulated Annealing-Ant Lion Optimization algorithm for Single-Input Single-Output process simulation and real-time experimentation on the Quadruple Tank System. To validate the effectiveness of the developed controller, Machine Learning techniques such as regression and ensemble trees are used to accurately predict the actual system response using error values from respective processes. The simulation and experimental results demonstrate that the proposed controller achieved better performance. The regression and ensemble tree algorithm models effectively predicted the actual response. The obtained data shows that the proposed controller improved system stability and robustness by minimizing nearly half of the overshoot and improving settling time, with an average of 29.9596% faster than the other controller in the SISO process and 14.6116% in the MIMO process.

Exploring the Innovative Path of Comprehensive Management of Dynamic Online Public Opinion in China Under the Threshold of New Media

Internet public opinion is a dynamic process of change, which is characterised by hiddenness, suddenness, complexity and volatility. The governance of online public opinion is a systematic project that involves network communication, government governance, social organisations, public will and other subjects. Strengthening the comprehensive governance of online public opinion requires innovating governance concepts and mechanisms to solve the problem of online public opinion at source; strengthening institutional construction and collaborative governance to improve the mechanism for managing online public opinion; enhancing professional skills and media literacy to improve the ability to govern online public opinion; and innovating information dissemination means and methods to enhance the dissemination efficacy of online public opinion. By innovating governance concepts and mechanisms, integrating social resources, improving the construction of the network communication system, and enhancing the media literacy and professional skills of netizens, the capacity and level of network public opinion governance will be enhanced.

Research on the relative threshold of sustainable development of the complex system in the Yellow River Basin

As a complex system, the sustainability of basins is crucial for the development and stability of human society. This study creatively combined Otsu algorithm with analytic hierarchy process to determine the relative threshold of sustainable development of the Yellow River basin system, aiming to provide a new perspective for the application of threshold theory to the study of sustainable development. The results showed that among the 24 sustainable development evaluation indicators, the Per Capita Cultivated Area (F24) had the greatest impact, while the Ecological Water use (F2) and Agricultural Water use (F19) indicators had the greatest impact range. For different subsystems, the sustainable development indices of the eco-environment subsystem in the upstream of the Yellow River exhibited more significant changes, while that of the socio-economic subsystem exhibited more prominent changes in the midstream. However, the sustainable development indices of the water-sand subsystems in the upstream, midstream, and downstream fluctuated greatly, with a maximum value occurring downstream. The sustainable development threshold was further determined to be 0.408 for the complex system in the Yellow River Basin. The sustainable development thresholds differed in upstream, midstream, and downstream, which ranged from 0.4201 to 0.4524. Based on the sustainable development threshold, the sustainable development status of the Yellow River Basin had continued to improve since 2017, and a high level of sustainability had been maintained. However, the sustainable status is a dynamic process of change, and changes in natural conditions or policies may affect the state of sustainable development.

Security-constrained unit commitment model considering frequency and voltage stabilities with multiresource participation

The rapidly increasing proportion of renewable energy sources has led to a reduction in the relative share of synchronous units, which has resulted in a decline in the inertia of the power system and a decrease in its voltage support capacity. This has led to several issues related to the frequency and voltage stabilities of the power system. To ensure these frequency and voltage stabilities, it is necessary to maintain a number of synchronous units online in the day-ahead generation schedule. First, the dynamic frequency change process after a power system fault is discussed, and a linear expression is derived for the frequency stability constraints involving energy storage systems and wind turbines. Second, the short-circuit capacity of the bus is characterized to describe the strength of voltage support, and the minimum short-circuit capacity requirement of the bus is solved based on the transient voltage recovery problem after clearance of the short-circuit faults. The total short-circuit capacity provided by the unit to the bus is then calculated through the network reactance matrix to establish the voltage stability constraint. Subsequently, the security-constrained unit commitment model considering frequency and voltage stabilities (FVS-SCUC) is established. Finally, the effectiveness of the proposed model is demonstrated through a numerical simulation of the IEEE-39 system comprising storage and wind turbines. The model ensures the frequency and voltage securities of the system, and the renewable energy output is improved upon considering energy storage. Thus, the overall system cost was reduced by nearly 30% by considering the frequency regulation effects of the energy storage system and wind turbine as well as the voltage regulation effects of the energy storage system.

RobotSDF: Implicit Morphology Modeling for the Robotic Arm.

The expression of robot arm morphology is a critical foundation for achieving effective motion planning and collision avoidance in robotic systems. Traditional geometry-based approaches usually suffer from the contradiction between the high demand for computing resources for fine expression and the insufficient detail expression caused by the pursuit of efficiency. The signed distance function addresses these drawbacks due to its ability to handle complex and arbitrary shapes and lower computational requirements. However, conventional robotic morphology methods based on the signed distance function often face challenges when the robot moves dynamically, since robots with different postures are modeled as independent individuals but the postures of robots are infinite. In this paper, we introduce RobotSDF, an implicit morphology modeling approach that can express the robot shape of arbitrary posture precisely. Instead of depicting a whole model of the robot arm, RobotSDF models the robot morphology as integrated implicit joint models driven by joint configurations. In this approach, the dynamic shape change process of the robot is converted into the coordinate transformations of query points within each joint's coordinate system. Experimental results with the Elfin robot demonstrate that RobotSDF can accurately depict robot shapes across different postures up to the millimeter level, which exhibits 38.65% and 66.24% improvement over the Neural-JSDF and configuration space distance field algorithms, respectively, in representing robot morphology. We further verified the efficiency of RobotSDF through collision avoidance in both simulation and actual human-robot collaboration experiments.

Dynamic flood mapping by a normalized probabilistic classification method using satellite radar amplitude time series

ABSTRACT Owing to the vast development of Synthetic Aperture Radar (SAR), especially the improvement of spatio-temporal resolution, observing and quantifying the complex and dynamic flood process becomes increasingly feasible. Utilizing the Sentinel-1 Ground Range Detected (GRD) dataset, we proposed an improved probabilistic flood mapping method combining image Pareto Scaling (PS) normalization and Bayesian probability estimation. We validated our method during a flood event in Xinjiang County, Shaanxi Province of China in October 2021 using a high spatial resolution (0.1 m) Unmanned Aerial Vehicle (UAV) image. The overall reliability of the new method agrees 95% to the UAV measurements and achieves the highest accuracy (85.2%) when compared to the Sentinel-1 dual-polarized water index (SDWI) threshold method and the Z-score method. Our results distinguished four flood stages: flood emergence, peak, receding, and disappearance, which provide valuable insights into the dynamic change process of floods. Notably, we observed that pixels with different flood probabilities exhibited distinct temporal characteristics. The extremely high probability pixel experienced rapid fluctuations, while the medium probability pixel showed more gradual changes over time. We believe our proposed method can enhance our understanding of flood-prone areas and their dynamics so that decision-makers can develop targeted mitigation measures and response plans.

Meta: XR-AR-MR and Mirror World Technologies Business Impact of Metaverse

Metaverse offers opportunities for companies to create innovative business models by providing a virtual platform where they can sell products and services and interact with customers in new and unique ways. Extended Reality (XR), Augmented Reality (AR), Mixed Reality (MR) and Mirror World technologies are important technological pathways for the metaverse. The metaverse concept is changing organizational structures with new opportunities and shaping the workforce for the future environment. The purpose of this review article is to discuss the concept of metanomics, the business implications of the metaverse in the context of the economy, business and employee-based value, future workforce, B2B opportunities and new business models. The concept of metaptation was associated with the metaverse in later studies to be conceptualized within the framework of adaptation theory. This review concludes by asserting that as the metaverse continues to evolve, driven by advancements in XR, AR, MR, and Mirror World technologies, it will not only revolutionize traditional business models but also necessitate a new paradigm of metaptation, where businesses must continuously adapt to harness the full potential of the metaverse in the realms of economic growth, innovative B2B opportunities, workforce development, and customer engagement. In order to be successful in this dynamic change process, businesses should adopt a strategic approach to adopting these innovative technologies. These strategic steps of businesses will contribute to gaining competitive advantage by enabling them to make the most of the commercial potential of the Metaverse.

Os protegidos de Ceres: produtores, moageiros e política cerealífera nos Açores (1923-1932)

This article departs from the economic and political context of the transition from the 1920s to the 1930s to study the evolution of the cereal policy in Azores. In this dynamic change process, agriculture, in general, and cereal farming, in particular, have been heavily targeted by public policies and governmental decisions. Our main purposes are the analysis of the organization, relations and implications of the activities of the agents involved in the commodity chain of wheat. It was concluded that the forms of public mobilization and pressure of the economic elites, in this case, the millers and agricultural landowners, on the political instances were not far from what occurred in the continental context, although the state has become the ultimate regulatory element.

Winter Wheat Aboveground-Biomass Estimation and Its Dynamic Variation during Coal Mining—Assessing by Unmanned Aerial Vehicle-Based Remote Sensing

Underground coal mining in coal-grain overlapped areas leads to land subsidence and deformation above the goaf, damaging cultivated land. Understanding the influencing process of coal mining on cultivated land and crops is important for carrying out timely land reclamation and stabilizing crop yield. Research has been carried out by using crop growth parameters to evaluate the damaging degree of cultivated land when the mining subsidence is stable, but few studies focus on the influence of land damage on crop growth when the subsidence is unstable during coal mining. Therefore, this study tracked the three growth stages of winter wheat by using UAV multispectral imagery to explore the dynamic influence of underground mining on winter wheat aboveground biomass (AGB). Firstly, a winter-wheat-AGB estimation model (R2 = 0.89, RMSE = 2.18 t/ha) was developed by using vegetation indexes (VIs), textures, and terrain data extracted from UAV imagery. Secondly, based on the winter-wheat-AGB estimation model, the winter wheat AGB was successfully estimated and mapped at different growth stages. The AGB of winter wheat in the coal mining-affected area was approximately 5.59 t/ha at the reviving stage, 8.2 t/ha at the jointing stage, and 15.6 t/ha at the flowering stage. Finally, combined with the progress of coal mining, the dynamic changing process of crops during underground mining can be inferred by analyzing the spatiotemporal variation in winter wheat AGB. Results showed that, in the dip direction, winter wheat AGB at the flowering stage was the highest at the compression zone, followed by the inner stretch zone, outer stretch zone, and neutral zone. The distance from the waterlogged area and the existence of cracks were found to be the important moderating variables affecting the crop growth status in the mining subsidence area. In the strike direction, there were significant differences in the wheat AGB-affected area as the mining proceeded. Even areas where AGB had previously significantly increased gradually transitioned to significant decreases with the end of mining. The research explores the dynamic changes in winter wheat AGB and land damage status during coal mining. It provides a rapid and non-destructive land-damage-monitoring method to protect cultivated land in mining areas.

Association of bioimpedance analysis parameters trajectories with clinical outcomes in neurocritical patients

Background and objectiveNeurocritical patients often experience uncontrolled high catabolic metabolism state during the acuta phase of the disease. The complex interactions of neuroendocrine, inflammation, and immune system lead to massive protein breakdown and changes in body composition. Bioelectrical impedance analysis (BIA) evaluates the content and proportions of body components based on the principles of bioelectricity. Its parameters reflect the overall health status of the body and the integrity of cellular structure and function, playing an important role in assessing the disease status and predicting prognosis of such patients. This study explored the association of BIA parameters trajectories with clinical outcomes in neurocritical patients. MethodsThis study prospectively collected BIA parameters of 127 neurocritical patients in the Department of Neurology admitted to the NICU for the first 1–7 days. All these patients were adults (≥18 years old) experiencing their first onset of illness and were in the acute phase of the disease. The group-based trajectory modeling (GBTM), which aims to identify individuals following similar developmental trajectories, was used to identify potential subgroups of individuals based on BIA parameters. The short-term prognosis of patients in each trajectory group with variations in phase angle (PA) and extracellular water/total body water (ECW/TBW) over time was differentially analyzed, and the logistic regression model was used to analyze the relationship between potential trajectory groups of PA and ECW/TBW and the short-term prognosis of neurocritical patients. The outcome was Glasgow Outcome Scale (GOS) score at discharge. ResultsFour PA trajectories and four ECW/TBW trajectories were detected respectively in neurocritical patients. Among them, compared with the other latent subgroups, the “Low PA rapidly decreasing subgroup” and the “High ECW/TBW slowly rising subgroup” had higher incidences of adverse outcomes at discharge (GOS:1–3), in-hospital mortality, and length of neurology intensive care unit stay (all P < 0.05). After correcting for potential confounders, compared with the “Low PA rapidly decreasing subgroup”, the risk of adverse outcome (GOS:1–3) was lower in the other three PA trajectories, with OR values of 0.0003, 0.0004, and 0.003 respectively (all P < 0.05). Compared with the “High ECW/TBW slowly rising subgroup”, the risk of adverse outcome (GOS:1–3) was lower in the other three ECW/TBW trajectories, with OR values of 0.013, 0.035 and 0.038 respectively (all P < 0.05). ConclusionLatent PA trajectories and latent ECW/TBW trajectories during 1–7 days after admission were associated with the clinical outcomes of neurocritical patients. The risk of adverse outcomes was highest in the “Low PA rapidly decreasing subgroup” and the “High ECW/TBW slowly rising subgroup”. These results reflected the overall health status and nutritional condition of neurocritical patients at the onset of the disease, and demonstrated the dynamic change process in body composition caused by the inflammatory response during the acute phase of the disease. This provided a reference basis for the observation and prognostic evaluation of such patients.

The influence of dynamic pitching on the aerodynamic performance of large horizontal axis wind turbines

To delve into the aerodynamic changes of wind turbines during pitching, this study employs the user-defined function (UDF) and dynamic mesh technique. The dynamic aerodynamic performance of a 3.3 MW turbine blade during variable pitch is investigated via numerical simulation. The results show that the optimal pitch angle increases with increasing incoming wind speed. At the initial and final stages of pitch change, the wind turbine experiences the influence of impact loads, leading to minor fluctuations in torque and thrust coefficients. Within the dynamic pitch change process, the pitch angle notably affects the aerodynamic performance of airfoils at blade x/ c = 0~0.6 c cross sections. The primary stress area of the airfoil contracts, with the blade root experiencing comparatively less impact. In the constant-wind-speed pitching scenario, the low-speed region in the immediate wake of the wind turbine diminishes, resulting in a 10.7% enhancement in the average wind speed at 2.5D wake.

The Impact of the Industrial Internet on the Innovation and Development Level of China’s Manufacturing Industry: Under the Perspective of Government Incentives

In the era of the digital economy, it has become an inevitable trend for manufacturing enterprises to establish industrial Internet platforms toward achieving transformation and innovative development. However, the current development model of industrial Internet platforms is still imperfect, wherein the application scenario is complex, the investment cost is too high, the return-on-investment cycle is too long, and other factors have hindered the willingness of manufacturing enterprises to employ cloud services and capital investment. For this reason, governments have introduced a series of relevant incentive policies to promote the development of industrial Internet platforms and the transformation and upgrading of manufacturing enterprises. Considering the role of government incentives, this study first constructs an evolutionary game model with local governments, manufacturing enterprises, and industrial Internet platforms as the main players. Then, the dynamic change process of each game player’s strategy choice and the stable state of the system evolution under multiple scenarios are analyzed, and the validity of the conclusions is verified through a numerical simulation analysis. Finally, the statistical data of 28 provinces in China from 2018 to 2020 are used to conduct an empirical test to explore the impact of the industrial Internet on the transformation and innovation development of the manufacturing industry and the role of government incentives. The results show that the development of the industrial Internet has a significant role in promoting the innovation and development of the manufacturing industry; government incentives can promote the innovation and development of the industrial Internet and manufacturing industry, but incentives should not be too generous; and the impact of developing the industrial Internet on the level of innovation input/output of the manufacturing industry shows obvious regional differences. This study takes the local government as an independent game participant into consideration, which enriches the research field of combining evolutionary game theory with the transformation and innovative development of the manufacturing industry. In addition, this study provides theoretical guidance and practical references for the government to formulate incentive policies to promote the development of industrial Internet platforms and for manufacturing enterprises to utilize these platforms to carry out innovation and perform upgrades.

The migration process and temperature effect of aqueous solutions contaminated by heavy metal ions in unsaturated silty soils

Adsorption-desorption experiments of three heavy metal ions (i.e., lead, copper, cadmium) in silty soil were carried out at different temperatures, and the microscopic characteristics of silty soil loaded with the three heavy metal ions were analyzed. A one-dimensional soil column was used to discuss the influences of heavy metal ion types and concentrations on the soil moisture distribution and the migration level of different heavy metal ions, especially during the dynamic change process from an unsaturated state to a saturated state. Studies show that the adsorption of heavy metal ions onto silty soil is closely related to the mineral composition and functional groups in silty soil. In addition to physical adsorption, the adsorption of heavy metal ions is closely related to the hydrolysis reaction of mineral components such as kaolinite, calcite, dolomite, plagioclase and quartz. Under constant temperature, the types and concentrations of heavy metal ions play an important role in the moisture migration of unsaturated soil. In the presence of heavy metal ions, the penetration of lead ions is the greatest, followed by copper ions and then cadmium ions. The greater the ion concentration is, the stronger the penetration of heavy metal ions in silty soils.

Characterization of rutting damage based on two-dimensional image analysis of changes in mesoscopic aggregate properties of asphalt mixtures

Accurately predicting the rutting development law of asphalt pavement is of great significance for preventing and controlling pavement diseases. The aggregate skeleton of the asphalt mixture is the main load-bearing part and plays an important role in its anti-rutting performance. However, quantitative and mesoscopic evaluation indicators and standards for aggregate skeletons have not been established. This study aims to reveal the relationship between the mesostructured characteristics of asphalt mixtures and rutting damage. This paper uses two-dimensional image technology to analyze the dynamic change process of internal skeleton information of two graded asphalt mixtures under cyclic wheel load. According to the fractal theory, the fractal dimension and multifractal spectrum of the full-depth aggregate were calculated. The results indicate that the linear regression model between the mesoscopic skeleton information of asphalt mixture and the average rutting depth during the rutting test can be used to quantify the rutting performance. There is an obvious correlation between the fractal dimension of the section aggregate and the loading times, and there is a certain linear relationship between the multifractal spectrum indexes and the loading times. It indicates that the fractal theory index of aggregate can reflect the change of the macro performance of loading times.