A Discussion on Models of Co-action and Innovation of Government and Enterprises in Agricultural Industrialization——Taking Shandong Fengyu Edible Fungus Co.,Ltd as an Example

The development of agricultural industrialization is an effective way of optimizing rural industrial structure and increasing peasants＇ income. Taking Shandong Fengyu Edible Fungus Co.,Ltd as an example, the paper discusses the development and innovation of edible fungus industry in production models, management system and operational mechanism in Wucheng City. It is expected to be helpful for innovating the development of agricultural industrialization in China.

Intrusion Detection System for Smart Industrial Environments with Ensemble Feature Selection and Deep Convolutional Neural Networks

Smart Industrial environments use the Industrial Internet of Things(IIoT)for their routine operations and transform their industrial operations with intelligent and driven approaches.However,IIoT devices are vulnerable to cyber threats and exploits due to their connectivity with the internet.Traditional signature-based IDS are effective in detecting known attacks,but they are unable to detect unknown emerging attacks.Therefore,there is the need for an IDS which can learn from data and detect new threats.Ensemble Machine Learning(ML)and individual Deep Learning(DL)based IDS have been developed,and these individual models achieved low accuracy;however,their performance can be improved with the ensemble stacking technique.In this paper,we have proposed a Deep Stacked Neural Network(DSNN)based IDS,which consists of two stacked Convolutional Neural Network(CNN)models as base learners and Extreme Gradient Boosting(XGB)as the meta learner.The proposed DSNN model was trained and evaluated with the next-generation dataset,TON_IoT.Several pre-processing techniques were applied to prepare a dataset for the model,including ensemble feature selection and the SMOTE technique.Accuracy,precision,recall,F1-score,and false positive rates were used to evaluate the performance of the proposed ensemble model.Our experimental results showed that the accuracy for binary classification is 99.61%,which is better than in the baseline individual DL and ML models.In addition,the model proposed for IDS has been compared with similar models.The proposed DSNN achieved better performance metrics than the other models.The proposed DSNN model will be used to develop enhanced IDS for threat mitigation in smart industrial environments.

Development and Validation of Integrated Nutrient Management Practices of Industrial Processing Varieties: Asterix and Courage in Bangladesh

An experiment was meticulously conducted at the research field of Bangabandhu Sheikh Mujibur Rahman Agricultural University (BSMRAU), Gazipur, Bangladesh, during the 2011-2012 potato growing season to develop integrated crop management practices for the potato seed production of industrial processing varieties Asterix and Courage. Significantly, higher growth and yield parameters were found in the BADC-recommended practice. Later, another experiment was conducted to validate the BADC practice during the 2013-2014 potato growing season in two locations in Bangladesh. Results showed that the production of tuber per hill, tuber weight per hill as well as gross tuber yield per plot, higher proportion of storable seed tubers, and more quality seed potatoes (A-grade and B-grade) seed tubers were found significantly higher in the “BADC developed practice” compared to other treatments. Viral diseases (PLRV and PVY) prevalence was lower in “BADC developed practice”. Moreover, “BADC developed practice” contributed more economic yield by minimizing input cost compared to “Munshiganj advanced farmers’ practice”. Therefore, the “BADC developed practice” was found “superior” regarding yield, quality, and profitability in seed potato production of industrial varieties—Asterix and Courage in Bangladesh.

The Effect of Key Nodes on theMalware Dynamics in the Industrial Control Network

As industrialization and informatization becomemore deeply intertwined,industrial control networks have entered an era of intelligence.The connection between industrial control networks and the external internet is becoming increasingly close,which leads to frequent security accidents.This paper proposes a model for the industrial control network.It includes a malware containment strategy that integrates intrusion detection,quarantine,and monitoring.Basedonthismodel,the role of keynodes in the spreadofmalware is studied,a comparisonexperiment is conducted to validate the impact of the containment strategy.In addition,the dynamic behavior of the model is analyzed,the basic reproduction number is computed,and the disease-free and endemic equilibrium of the model is also obtained by the basic reproduction number.Moreover,through simulation experiments,the effectiveness of the containment strategy is validated,the influence of the relevant parameters is analyzed,and the containment strategy is optimized.In otherwords,selective immunity to key nodes can effectively suppress the spread ofmalware andmaintain the stability of industrial control systems.The earlier the immunization of key nodes,the better.Once the time exceeds the threshold,immunizing key nodes is almost ineffective.The analysis provides a better way to contain the malware in the industrial control network.

Attributes of Specialized Households'Resilience and Its Impact on Rural Industrial Advancement:A Case Study of National Musical Instrument Production Specialized Households in Lankao County,Henan,China

Specialized households serve as the primary units within specialized villages in China,and their capacity to withstand risks and external influences significantly shapes the future trajectory of specialized villages and the overall vitality of the rural economy.In this study,we established a measurement indicator system based on the definition of specialized households’resilience,elucidating the logical connection between specialized households’resilience and rural industrial development in China.The musical instrument industry in Lankao County,Henan Province of China,was employed as a case;survey data,the entropy method,and an obstacle diagnosis model were used to examine how instrument production specialized households responded to the challenges posed by Corona Virus Disease 2019(COVID-19)and the tightening of national environmental protection policies,yielding the following key findings:1)there exists substantial variation in the comprehensive resilience levels among different specialized households;2)the ability to learn and adapt is the most significant contributor to the overall resilience level of specialized households;3)technological proficiency and access to skilled talent emerge as pivotal factors influencing specialized households’resilience;4)the positioning of specialized households within the industrial supply chain and the stability of their income have a direct bearing on their resilience level.The influence of specialized households’resilience on industrial development primarily manifests in the following ways:stronger resilience correlates with increased stability in production and sales,fostering a more proactive approach to future actions.However,heightened exposure to the external macroeconomic environment can lead to a higher rate of export reduction.To enhance the development resilience of entities like specialized households and family farms,and to invigorate rural economic development,escalating investments in rural science and technology and prioritizing the training of technical talent become imperative.

How can technology and efficiency alleviate the dilemma of economic growth and carbon emissions in China's industrial economy? A metafrontier decoupling decomposition analysis

This paper attempts to explore the decoupling relationship and its drivers between industrial economic increase and energy-related CO_(2) emissions(ICE). Firstly, the decoupling relationship was evaluated by Tapio index. Then, based on the DEA meta-frontier theory framework which taking into account the regional and industrial heterogeneity and index decomposition method, the driving factors of decoupling process were explored mainly from the view of technology and efficiency. The results show that during2000-2019, weak decoupling was the primary state. Investment scale expansion was the largest reason hindering decoupling process of industrial increase from ICE. Both energy saving and production technology achieved significant progress, which facilitated the decoupling process. Simultaneously, the energy technology gap and production technology gap among regions have been narrowed, and played a role in promoting decoupling process. On the contrary, both scale economy efficiency and pure technical efficiency have inhibiting effects on decoupling process. The former indicates that the scale economy of China's industry was not conducive to improve energy efficiency and production efficiency, while the latter indicates that resource misallocation problem may exist in both energy market and product market.

A Deep Learning Approach to Industrial Corrosion Detection

The proposed study focuses on the critical issue of corrosion,which leads to significant economic losses and safety risks worldwide.A key area of emphasis is the accuracy of corrosion detection methods.While recent studies have made progress,a common challenge is the low accuracy of existing detection models.These models often struggle to reliably identify corrosion tendencies,which are crucial for minimizing industrial risks and optimizing resource use.The proposed study introduces an innovative approach that significantly improves the accuracy of corrosion detection using a convolutional neural network(CNN),as well as two pretrained models,namely YOLOv8 and EfficientNetB0.By leveraging advanced technologies and methodologies,we have achieved high accuracies in identifying and managing the hazards associated with corrosion across various industrial settings.This advancement not only supports the overarching goals of enhancing safety and efficiency,but also sets a new benchmark for future research in the field.The results demonstrate a significant improvement in the ability to detect and mitigate corrosion-related concerns,providing a more accurate and comprehensive solution for industries facing these challenges.Both CNN and EfficientNetB0 exhibited 100%accuracy,precision,recall,and F1-score,followed by YOLOv8 with respective metrics of 95%,100%,90%,and 94.74%.Our approach outperformed state-of-the-art with similar datasets and methodologies.

Offshore high-grade limemud resources of west coast of India:Economic potential and industrial applications

Limestone is one of the essential raw materials in the cement,paint,steel,ceramic,glass,chemical,pharmaceutical,paper,and fertilizer industries.In India,only 8%of the limestone resources are placed under the reserve category,of which 97%is of cement grade.Thus,India depends on imports to bridge the demand‐supply gap of steel,blast furnace,and chemical‐grade limestone.Efforts of Geological Survey of India(GSI)to locate alternate sources for limestone led to the discovery of enormous quantities of carbonate minerals called limemud from the continental shelf margin of the west coast of India.GSI carried out systematic studies to explore the nature of the disposition,quality,quantity,and suitability of the offshore limemud for various industrial applications.A preliminary estimate of resources using high‐resolution subbottom profiling and sediment core sample studies established the occurrence of more than 172 billion tonnes of high‐grade(The content of CaCO3 is greater than 80 wt%)limemud in 0.4–28.0m thick stratified sediment layers spread over an area of 18000 km2.Chemical,physical,mineralogical,beneficiation,and agglomeration studies found the offshore limemud as a potential replacement for limestone in the cement,filler,blast furnace,steel melting shop,lime production,paint,and Grade‐I steel industries.An assessment of mining and transportation costs indicates that the offshore limemud(USD 5–6/ton)is more cost‐effective than that imported from other countries(USD16‐18/ton).With several advantageous factors like low impurity,mode of occurrence in overburden‐free stratified form,fine‐grained slurry nature,and shallow water depth,sustainable mining of offshore limemud could be a future reality with controllable technological,economic,and environmental challenges.

Impact of an official accountability audit on industrial structure adjustment:a case study of environmental regulation in China

As a unique environmental regulation in China,the official accountability audit was piloted in 2014.With a focus on prioritizing the ecological environment,officials in pilot districts have implemented economic construction,adjusted industrial structures,and promoted coordinated development between the economy and environment.The effects of implementation have garnered widespread attention from society.However,there is limited research on the impact of an accountability audit on industrial structure adjustments.Using the“Accountability Audit of Officials for Natural Resource Assets(Trial)”released in 2015 as a quasi-natural experiment,this study collected panel data from 279 cities between 2013 and 2017.It then empirically analyzed the impact mechanism and effects of the accountability audit on industrial structure adjustment using the Propensity Score Matching and Difference-in-Differences model.The research findings indicate that the accountability audit directly impacted industrial structure adjustment,promoting the upgrading of the primary industry to the secondary industry and restricting the development of the tertiary industry.In addition,the audit is beneficial for enterprise entry,but not conducive to technological innovation,and has no significant impact on foreign direct investment.This conclusion fills a gap in the existing research and provides valuable insights for policymakers.

A Novel Sensing Imaging Equipment Under Extremely Dim Light for Blast Furnace Burden Surface:Starlight High-Temperature Industrial Endoscope

Blast furnace(BF)burden surface contains the most abundant,intuitive and credible smelting information and acquiring high-definition and high-brightness optical images of which is essential to realize precise material charging control,optimize gas flow distribution and improve ironmaking efficiency.It has been challengeable to obtain high-quality optical burden surface images under high-temperature,high-dust,and extremelydim(less than 0.001 Lux)environment.Based on a novel endoscopic sensing detection idea,a reverse telephoto structure starlight imaging system with large field of view and large aperture is designed.Combined with a water-air dual cooling intelligent self-maintenance protection device and the imaging system,a starlight high-temperature industrial endoscope is developed to obtain clear optical burden surface images stably under the harsh environment.Based on an endoscope imaging area model,a material flow trajectory model and a gas-dust coupling distribution model,an optimal installation position and posture configuration method for the endoscope is proposed,which maximizes the effective imaging area and ensures large-area,safe and stable imaging of the device in a confined space.Industrial experiments and applications indicate that the proposed method obtains clear and reliable large-area optical burden surface images and reveals new BF conditions,providing key data support for green iron smelting.

An Industrial Intrusion Detection Method Based on Hybrid Convolutional Neural Networks with Improved TCN

Network intrusion detection systems(NIDS)based on deep learning have continued to make significant advances.However,the following challenges remain:on the one hand,simply applying only Temporal Convolutional Networks(TCNs)can lead to models that ignore the impact of network traffic features at different scales on the detection performance.On the other hand,some intrusion detection methods considermulti-scale information of traffic data,but considering only forward network traffic information can lead to deficiencies in capturing multi-scale temporal features.To address both of these issues,we propose a hybrid Convolutional Neural Network that supports a multi-output strategy(BONUS)for industrial internet intrusion detection.First,we create a multiscale Temporal Convolutional Network by stacking TCN of different scales to capture the multiscale information of network traffic.Meanwhile,we propose a bi-directional structure and dynamically set the weights to fuse the forward and backward contextual information of network traffic at each scale to enhance the model’s performance in capturing the multi-scale temporal features of network traffic.In addition,we introduce a gated network for each of the two branches in the proposed method to assist the model in learning the feature representation of each branch.Extensive experiments reveal the effectiveness of the proposed approach on two publicly available traffic intrusion detection datasets named UNSW-NB15 and NSL-KDD with F1 score of 85.03% and 99.31%,respectively,which also validates the effectiveness of enhancing the model’s ability to capture multi-scale temporal features of traffic data on detection performance.

Exploring the Dynamics of Industrial Convergence Among RCEP Member Countries: An Empirical Study

The evolving dynamics of industrial convergence among the member countries of the Regional Comprehensive Economic Partnership(RCEP)framework have emerged as a significant subject that merits in-depth consideration and analysis.This study initially employs multi-regional input-output(MRIO)data and the social network analysis(SNA)method to delineate the levels and variation trends of this industrial convergence across the RCEP member countries.It then delves into the positive effects of this convergence phenomenon on the trade and investment fields of the member countries.The research findings indicate:(a)In 2006 and 2015,before the implementation of the RCEP,the RCEP member countries displayed a relatively close industrial convergence.The convergence levels exhibited a general upward trend on both the supply and the demand sides,but there were significant disparities in the levels of industrial convergence among the member countries.Furthermore,while the convergence in the three economic sectors showed an increasing trend,the development was uneven across the board.(b)Since the implementation of the RCEP,the trade ties among the member countries within the region have strengthened significantly,and the interplay between the countries’industrial and supply chains has been characterized by high-quality collaboration and demonstrated remarkable resilience.In addition,the convergence in the investment fields of the RCEP member countries and their respective industries has unleashed a wave of positive synergies.These findings offer valuable insights that can serve as a robust foundation for formulating effective policies to advance the growth and prosperity of the RCEP region.

A compatible carbon efficiency information service framework based on the industrial internet identification

Green and low-carbon is a new development model that seeks balance between environmental sustainability and high economic growth.If explainable and available carbon emission data can be accurately obtained,it will help policy regulators and enterprise managers to more accurately implement this development strategy.A lot of research has been carried out,but it is still a difficult problem that how to accommodate and adapt the complex carbon emission data computing models and factor libraries developed by different regions,different industries and different enterprises.Meanwhile,with the rapid development of the Industrial Internet,it has not only been used for the supply chain optimization and intelligent scheduling of the manufacturing industry,but also been used by more and more industries as an important way of digital transformation.Especially in China,the Industrial Internet identification and resolution system is becoming an important digital infrastructure to uniquely identify objects and share data.Hence,a compatible carbon efficiency information service framework based on the Industrial Internet Identification is proposed in this paper to address the problem of computing and querying multi-source heterogeneous carbon emission data.We have defined a multi cooperation carbon emission data interaction model consisting of three roles and three basic operations.Further,the implementation of the framework includes carbon emission data identification,modeling,calculation,query and sharing.The practice results show that its capability and effectiveness in improving the responsiveness,accuracy,and credibility of compatible carbon efficiency data query and sharing services.

Effects of acid-rock reaction on physical properties during CO_(2)-rich industrial waste gas(CO_(2)-rich IWG)injection in shale reservoirs

"Carbon peaking and carbon neutrality"is an essential national strategy,and the geological storage and utilization of CO_(2)is a hot issue today.However,due to the scarcity of pure CO_(2)gas sources in China and the high cost of CO_(2)capture,CO_(2)-rich industrial waste gas(CO_(2)-rich IWG)is gradually emerging into the public's gaze.CO_(2)has good adsorption properties on shale surfaces,but acidic gases can react with shale,so the mechanism of the CO_(2)-rich IWG-water-shale reaction and the change in reservoir properties will determine the stability of geological storage.Therefore,based on the mineral composition of the Longmaxi Formation shale,this study constructs a thermodynamic equilibrium model of water-rock reactions and simulates the regularity of reactions between CO_(2)-rich IWG and shale minerals.The results indicate that CO_(2)consumed 12%after reaction,and impurity gases in the CO_(2)-rich IWG can be dissolved entirely,thus demonstrating the feasibility of treating IWG through water-rock reactions.Since IWG inhibits the dissolution of CO_(2),the optimal composition of CO_(2)-rich IWG is 95%CO_(2)and 5%IWG when CO_(2)geological storage is the main goal.In contrast,when the main goal is the geological storage of total CO_(2)-rich IWG or impurity gas,the optimal CO_(2)-rich IWG composition is 50%CO_(2)and 50%IWG.In the CO_(2)-rich IWG-water-shale reaction,temperature has less influence on the water-rock reaction,while pressure is the most important parameter.SO2 has the greatest impact on water-rock reaction in gas.For minerals,clay minerals such as illite and montmorillonite had a significant effect on water-rock reaction.The overall reaction is dominated by precipitation and the volume of the rock skeleton has increased by 0.74 cm3,resulting in a decrease in shale porosity,which enhances the stability of CO_(2)geological storage to some extent.During the reaction between CO_(2)-rich IWG-water-shale at simulated temperatures and pressures,precipitation is the main reaction,and shale porosity decreases.However,as the reservoir water content increases,the reaction will first dissolve and then precipitate before dissolving again.When the water content is less than 0.0005 kg or greater than 0.4 kg,it will lead to an increase in reservoir porosity,which ultimately reduces the long-term geological storage stability of CO_(2)-rich IWG.

Training Mode of Design Talents under the Concept of Regional Revitalization and Industrial Upgrading

Based on the background of the revitalization of Northeast China and industrial transformation,with the goal of serving society with design,leading the future with design,and revitalizing the economy with design,we adhere to the innovative,comprehensive and cultural design talent cultivation concept,fully practice the“student-centered,output-oriented,continuously-improving”educational philosophy taking quality as the first priority,and continuously improve the theoretical system and implementation path for cultivation of postgraduate talents in design science,hoping to optimize the entire process of talent cultivation.Meanwhile,on the basis of“fostering character and civic virtue,cultivating people in a three-all manner,and cultivating people from five aspects simultaneously”,we cultivate high-quality design talents with brand-new models and ideas,through a series of educational reform measures,such as strategic cooperation,resource integration,systematic sorting,quality improvement,standard formulation,strengthening characteristics,platform construction,so that the quality of talents and social development can be perfectly integrated and mutually assist each other to achieve a win-win effect,and the training of design talents can be implemented and serve the society.

A Double-Timescale Reinforcement Learning Based Cloud-Edge Collaborative Framework for Decomposable Intelligent Services in Industrial Internet of Things

With the proportion of intelligent services in the industrial internet of things(IIoT)rising rapidly,its data dependency and decomposability increase the difficulty of scheduling computing resources.In this paper,we propose an intelligent service computing framework.In the framework,we take the long-term rewards of its important participants,edge service providers,as the optimization goal,which is related to service delay and computing cost.Considering the different update frequencies of data deployment and service offloading,double-timescale reinforcement learning is utilized in the framework.In the small-scale strategy,the frequent concurrency of services and the difference in service time lead to the fuzzy relationship between reward and action.To solve the fuzzy reward problem,a reward mapping-based reinforcement learning(RMRL)algorithm is proposed,which enables the agent to learn the relationship between reward and action more clearly.The large time scale strategy adopts the improved Monte Carlo tree search(MCTS)algorithm to improve the learning speed.The simulation results show that the strategy is superior to popular reinforcement learning algorithms such as double Q-learning(DDQN)and dueling Q-learning(dueling-DQN)in learning speed,and the reward is also increased by 14%.

Tackling the proton limit under industrial electrochemical CO_(2)reduction by a local proton shuttle

Industrial CO_(2)electroreduction has received tremendous attentions for resolution of the current energy and environmental crisis,but its performance is greatly limited by mass transport at high current density.In this work,an ion‐polymer‐modified gas‐diffusion electrode is used to tackle this proton limit.It is found that gas diffusion electrode‐Nafion shows an impressive performance of 75.2%Faradaic efficiency in multicarbon products at an industrial current density of 1.16 A/cm^(2).Significantly,in‐depth electrochemical characterizations combined with in situ Raman have been used to determine the full workflow of protons,and it is found that HCO_(3)^(−)acts as a proton pool near the reaction environment,and HCO_(3)^(−)and H_(3)O^(+)are local proton donors that interact with the proton shuttle−SO_(3)^(−)from Nafion.With rich proton hopping sites that decrease the activation energy,a“Grotthuss”mechanism for proton transport in the above system has been identified rather than the“Vehicle”mechanism with a higher energy barrier.Therefore,this work could be very useful in terms of the achievement of industrial CO_(2)reduction fundamentally and practically.

CO_(2) mineralization by typical industrial solid wastes for preparing ultrafine CaCO_(3): A review

Mineral carbonation is a promising CO_(2) sequestration strategy that can utilize industrial wastes to convert CO_(2) into high-value CaCO_(3).This review summarizes the advancements in CO_(2) mineralization using typical industrial wastes to prepare ultrafine CaCO_(3).This work surveys the mechanisms of CO_(2) mineralization using these wastes and its capacities to synthesize CaCO_(3),evaluates the effects of carbonation pathways and operating parameters on the preparation of CaCO_(3),analyzes the current industrial application status and economics of this technology.Due to the large amount of impurities in solid wastes,the purity of CaCO_(3) prepared by indirect methods is greater than that prepared by direct methods.Crystalline CaCO_(3) includes three polymorphs.The polymorph of CaCO_(3) synthesized by carbonation process is determined the combined effects of various factors.These parameters essentially impact the nucleation and growth of CaCO_(3) by altering the CO_(2) supersaturation in the reaction system and the surface energy of CaCO_(3) grains.Increasing the initial pH of the solution and the CO_(2)flow rate favors the formation of vaterite,but calcite is formed under excessively high pH.Vaterite formation is favored at lower temperatures and residence time.With increased temperature and prolonged residence time,it passes through aragonite metastable phase and eventually transforms into calcite.Moreover,polymorph modifiers can decrease the surface energy of CaCO_(3) grains,facilitating the synthesis of vaterite.However,the large-scale application of this technology still faces many problems,including high costs,high energy consumption,low calcium leaching rate,low carbonation efficiency,and low product yield.Therefore,it is necessary to investigate ways to accelerate carbonation,optimize operating parameters,develop cost-effective agents,and understand the kinetics of CaCO_(3) nucleation and crystallization to obtain products with specific crystal forms.Furthermore,more studies on life cycle assessment(LCA)should be conducted to fully confirm the feasibility of the developed technologies.

A general Boolean semantic modelling approach for complex and intelligent industrial systems in the framework of DES

Discrete event system(DES)models promote system engineering,including system design,verification,and assessment.The advancement in manufacturing technology has endowed us to fabricate complex industrial systems.Consequently,the adoption of advanced modeling methodologies adept at handling complexity and scalability is imperative.Moreover,industrial systems are no longer quiescent,thus the intelligent operations of the systems should be dynamically specified in the model.In this paper,the composition of the subsystem behaviors is studied to generate the complexity and scalability of the global system model,and a Boolean semantic specifying algorithm is proposed for generating dynamic intelligent operations in the model.In traditional modeling approaches,the change or addition of specifications always necessitates the complete resubmission of the system model,a resource-consuming and error-prone process.Compared with traditional approaches,our approach has three remarkable advantages:(i)an established Boolean semantic can be fitful for all kinds of systems;(ii)there is no need to resubmit the system model whenever there is a change or addition of the operations;(iii)multiple specifying tasks can be easily achieved by continuously adding a new semantic.Thus,this general modeling approach has wide potential for future complex and intelligent industrial systems.

Rationale and Pathway for New Industrialization in the Context of Chinese Modernization

The concepts of modernization and industrialization have different connotations that are specific to their historical backgrounds,and their theoretical innovation and development may benefit from China’s experiences.Industrialization is the cornerstone of modernization,and holds the key to its success.China’s experiences in blazing a new trail of industrialization are challenging the traditional Western theory of industrialization and deepening the connotations of Chinese modernization.New industrialization is a key entry point for steering China’s modernization drive and theoretical innovations.This paper offers an overview of the theory of Chinese modernization and its evolving trend along China’s socialist industrialization path,as well as the rationale and pathway for new industrialization in the context of Chinese modernization.As our findings suggest,the new industrialization concept has taken hold in every key aspect of Chinese modernization.When combined with the theory of Chinese modernization,the theoretical implications of new industrialization play a crucial role in propelling Chinese modernization forward along a new journey in the new era.