Industrialism and Pastoral Ideal in Edward Bellamy's Novels

Edward Bellamy's three novels, Six to One, Looking Backward, and Equality, are the expression of his reconciliation between industrialism and pastoral ideal. Six to One represents the writer's early pastoral ideal with its traditional romantic plot of retiring form city life and living on a reclusive island for a while. In Looking Backward, however, Bellamy embraces machine and technology and even considers industrialism to be the panacea for social reform. In Equality, the sequel to Looking Backward, Bellamy tends to reconcile and balance between industrialism and pastoral ideal with his advocacy of decentralized suburbs rather than centralized metropolis in the prequel.

Industrial solid wastes to environmental protection materials for removal of gaseous pollutants:A review

The application of industrial solid wastes as environmentally functional materials for air pollutants control has gained much attention in recent years due to its potential to reduce air pollution in a cost-effective manner.In this review,we investigate the development of industrialwaste-based functional materials for various gas pollutant removal and consider the relevant reaction mechanism according to different types of industrial solid waste.We see a recent effort towards achieving high-performance environmental functional materials via chemical or physical modification,in which the active components,pore size,and phase structure can be altered.The review will discuss the potential of using industrial solid wastes,these modified materials,or synthesized materials from raw waste precursors for the removal of air pollutants,including SO_(2),NO_(x),Hg^(0),H_(2)S,VOCs,and CO_(2).The challenges still need to be addressed to realize this potential and the prospects for future research fully.The suggestions for future directions include determining the optimal composition of these materials,calculating the real reaction rate and turnover frequency,developing effective treatment methods,and establishing chemical component databases of raw industrial solid waste for catalysts/adsorbent preparation.

桥接未来--LCCF库函数的应用

本文探讨了Siemens的LCCF库函数在工业自动化项目中的应用,LCCF库提供了一种软件层面的解决方案,通过库函数替代传统硬件协议网关,实现不同通信协议间的数据交换。介绍了Siemens库函数的分类与功能,阐述了LCCF库的主要组件及其在协议转换中的优势,包括简化配置流程、增强系统兼容性、降低技术门槛等。通过具体的应用实例,展示了LCCF库在SIMATIC控制器与Rockwell及Mitsubishi控制器之间通信的实现方法。此外,文章还对LCom与LCCF两个Siemens通信库进行了比较分析,指出了它们的共同点与不同点。

Digital Economy and Corporate Innovation-Washing--An Empirical Study on How Information Mitigates Policy Distortion

As stated in the Report to the 20th National Congress of the Communist Party of China(CPC),innovation remains at the heart of China’s modernization drive,and it is vital to optimize the allocation of innovation resources,deepen structural scientific and technological reforms,and enhance the overall performance of China’s innovation system.Government incentives have boosted firm R&D and innovation efforts;however,they have also triggered an innovation dilemma where enterprises,capitalizing on their informational advantages,resort to innovation-washing behaviors that undermine the intended purpose of the policies.Based on the information asymmetry theory,this paper conducts an empirical study on how the digital economy affects firms’innovation-washing behavior.The development of the regional digital economy could suppress firm innovation-washing behavior in the region,and such a mitigation effect is primarily caused by an increase in the number of digital industry professionals.According to our heterogeneity analysis,the digital economy has a greater impact on firm innovation-washing behavior for certain types of enterprises,including non-state-owned enterprises(non-SOEs),small and medium-sized enterprises(SMEs),enterprises in less competitive industries,and enterprises in unfavorable business environments.Our mechanism analysis revealed that the digital economy may restrain innovation-washing behavior by reducing information asymmetry between enterprises and external stakeholders.In terms of economic outcomes,the digital economy has the potential to directly influence firm innovation output while also indirectly mitigating the subsequent decline in innovation output by discouraging innovation-washing.This paper enriches the research findings on how the digital economy breaks down“information silos”and offers a potential solution to the“emphasis on input and quantity over quality and efficiency”phenomenon in science and technology innovation practices.

Geographical Indications and Regional Public Brands of the Whole Rice Industry Chain in the Yangtze River Economic Belt

The Yangtze River Economic Belt is the main rice producing area in China.The rice industry chain is the agricultural pillar industry chain of this economic belt and it is the key to ensuring national food security and promoting comprehensive rural revitalization.This study discusses the entire rice industry chain in the Yangtze River Economic Belt from the national rice production functional zones,agricultural product quality and safety,national famous and excellent new agricultural products,national specialty agricultural products,"China s good grain and oil"products,and national advantageous characteristic industrial clusters.Then,it discusses the geographical indications of rice and its products in this economic belt from geographical indication products,geographical indication trademarks,agricultural geographical indications,geographical indication standards,geographical indication special indications,national geographical indication product protection demonstration zones,and Chinese geographical indication products protected by the European Union.In addition,it analyzes the five main problems between geographical indications and public brands,such as the limited use of geographical indication specific signs and the imperfect intellectual property protection system for geographical indications.Finally,it proposes eight strategies,including promoting the high-quality development of the entire rice industry chain,creating a geographical indication regional public brand for rice and its products,and implementing geographical indication protection projects.

Timely Policy Exit:Reducing Over-Investment and Driving High-Quality Firm Performance

Using data from the 11th to 14th Five-Year Plan periods(2006-2025),this study applies a Difference-in-Differences(DID)approach to assess the impact of industrial policy withdrawal.Industries that have faced policy withdrawal for over a decade are categorized as the treatment group,while consistently supported industries form the control group.The analysis examines how withdrawal affects firm total factor productivity(TFP)and investment behavior.The results show that policy withdrawal boosts firm TFP by reducing over-investment and improving the efficiency of R&D spending.This effect is particularly evident in industries with strong,competitive leading firms.Additionally,in regions with lower levels of marketization,timely policy withdrawal plays a key role in curbing over-investment.This study also highlights a dual effect of policy withdrawal:while it fosters corporate social responsibility,it may also encourage financial speculation.These findings suggest that the implementation of industrial policy should provide“timely assistance”over a limited timeframe rather than long-term support to well-established industries.As industries mature,policy support should be gradually reduced or phased out to avoid over-investment and enhance firm efficiency.

Potential industrial applications of photo/electrocatalysis: Recent progress and future challenges

Nowadays,the rapid development of the social economy inevitably leads to global energy and environmental crisis.For this reason,more and more scholars focus on the development of photocatalysis and/or electrocatalysis technology for the advantage in the sustainable production of high-value-added products,and the high efficiency in pollutants remediation.Although there is plenty of outstanding research has been put forward continuously,most of them focuses on catalysis performance and reaction mechanisms in laboratory conditions.Realizing industrial application of photo/electrocatalytic processes is still a challenge that needs to be overcome by social demand.In this regard,this review comprehensively summarized several explorations in thefield of photo/electrocatalytic reduction towards potential industrial applications in recent years.Special attention is paid to the successful attempts and the current status of photo/electrocatalytic water splitting,carbon dioxide conversion,resource utilization from waste,etc.,by using advanced reactors.The key problems and challenges of photo/electrocatalysis in future industrial practice are also discussed,and the possible development directions are also pointed out from the industry view.

Prospects for green steelmaking technology with low carbon emissions in China

The steel industry is a major source of CO_(2) emissions,and thus,the mitigation of carbon emissions is the most pressing challenge in this sector.In this paper,international environmental governance in the steel industry is reviewed,and the current state of development of low-carbon technologies is discussed.Additionally,low-carbon pathways for the steel industry at the current time are proposed,emphasizing prevention and treatment strategies.Furthermore,the prospects of low-carbon technologies are explored from the perspective of transitioning the energy structure to a“carbon-electricity-hydrogen”relationship.Overall,steel enterprises should adopt hydrogen-rich metallurgical technologies that are compatible with current needs and process flows in the short term,based on the carbon substitution with hydrogen(prevention)and the CCU(CO_(2) capture and utilization)concepts(treatment).Additionally,the capture and utilization of CO_(2) for steelmaking,which can assist in achieving short-term emission reduction targets but is not a long-term solution,is discussed.In conclusion,in the long term,the carbon metallurgical process should be gradually supplanted by a hydrogen-electric synergistic approach,thus transforming the energy structure of existing steelmaking processes and attaining near-zero carbon emission steelmaking technology.

Innovation leading development:a glimpse into three-dimensional bioprinting in Israel

Three-dimensional(3D)printing has attracted increasing research interest as an emerging manufacturing technology for devel-oping sophisticated and exquisite architecture through hierarchical printing.It has also been employed in various advanced industrial areas.The development of intelligent biomedical engineering has raised the requirements for 3D printing,such as flexible manufacturing processes and technologies,biocompatible constituents,and alternative bioproducts.However,state-of-the-art 3D printing mainly involves inorganics or polymers and generally focuses on traditional industrial fields,thus severely limiting applications demanding biocompatibility and biodegradability.In this regard,peptide architectonics,which are self-assembled by programmed amino acid sequences that can be flexibly functionalized,have shown promising potential as bioinspired inks for 3D printing.Therefore,the combination of 3D printing and peptide self-assembly poten-tially opens up an alternative avenue of 3D bioprinting for diverse advanced applications.Israel,a small but innovative nation,has significantly contributed to 3D bioprinting in terms of scientific studies,marketization,and peptide architectonics,including modulations and applications,and ranks as a leading area in the 3D bioprinting field.This review summarizes the recent progress in 3D bioprinting in Israel,focusing on scientific studies on printable components,soft devices,and tissue engineering.This paper further delves into the manufacture of industrial products,such as artificial meats and bioinspired supramolecular architectures,and the mechanisms,physicochemical properties,and applications of peptide self-assembly.Undoubtedly,Israel contributes significantly to the field of 3D bioprinting and should thus be appropriately recognized.

Industrial Carbon Emission Distribution and Regional Joint Emission Reduction:A Case Study of Cities in the Pearl River Basin,China

China’s low-carbon development path will make significant contributions to achieving global sustainable development goals.Due to the diverse natural and economic conditions across different regions in China,there exists an imbalance in the distribution of car-bon emissions.Therefore,regional cooperation serves as an effective means to attain low-carbon development.This study examined the pattern of carbon emissions and proposed a potential joint emission reduction strategy by utilizing the industrial carbon emission intens-ity(ICEI)as a crucial factor.We utilized social network analysis and Local Indicators of Spatial Association(LISA)space-time trans-ition matrix to investigate the spatiotemporal connections and discrepancies of ICEI in the cities of the Pearl River Basin(PRB),China from 2010 to 2020.The primary drivers of the ICEI were determined through geographical detectors and multi-scale geographically weighted regression.The results were as follows:1)the overall ICEI in the Pearl River Basin is showing a downward trend,and there is a significant spatial imbalance.2)There are numerous network connections between cities regarding the ICEI,but the network structure is relatively fragile and unstable.3)Economically developed cities such as Guangzhou,Foshan,and Dongguan are in the center of the network while playing an intermediary role.4)Energy consumption,industrialization,per capita GDP,urbanization,science and techno-logy,and productivity are found to be the most influential variables in the spatial differentiation of ICEI,and their combination in-creased the explanatory power of the geographic variation of ICEI.Finally,through the analysis of differences and connections in urban carbon emissions under different economic levels and ICEI,the study suggests joint carbon reduction strategies,which are centered on carbon transfer,financial support,and technological assistance among cities.

Digital Twin Technology of Human-Machine Integration in Cross-Belt Sorting System

The Chinese express delivery industry processes nearly 110 billion items in 2022,averaging an annual growth rate of 200%.Among the various types of sorting systems used for handling express items,cross-belt sorting systems stand out as the most crucial.However,despite their high degree of automation,the workload for operators has intensified owing to the surging volume of express items.In the era of Industry 5.0,it is imperative to adopt new technologies that not only enhance worker welfare but also improve the efficiency of cross-belt systems.Striking a balance between efficiency in handling express items and operator well-being is challenging.Digital twin technology offers a promising solution in this respect.A realization method of a human-machine integrated digital twin is proposed in this study,enabling the interaction of biological human bodies,virtual human bodies,virtual equipment,and logistics equipment in a closed loop,thus setting an operating framework.Key technologies in the proposed framework include a collection of heterogeneous data from multiple sources,construction of the relationship between operator fatigue and operation efficiency based on physiological measurements,virtual model construction,and an online optimization module based on real-time simulation.The feasibility of the proposed method was verified in an express distribution center.

Optimal synthesis of heat-integrated distillation configurations using the two-column superstructure

In the realm of the synthesis of heat-integrated distillation configurations,the conventional approach for exploring more heat integration possibilities typically entails the splitting of a single column into a twocolumn configuration.However,this approach frequently necessitates tedious enumeration procedures,resulting in a considerable computational burden.To surmount this formidable challenge,the present study introduces an innovative remedy:The proposition of a superstructure that encompasses both single-column and multiple two-column configurations.Additionally,a simultaneous optimization algorithm is applied to optimize both the process parameters and heat integration structures of the twocolumn configurations.The effectiveness of this approach is demonstrated through a case study focusing on industrial organosilicon separation.The results underscore that the superstructure methodology not only substantially mitigates computational time compared to exhaustive enumeration but also furnishes solutions that exhibit comparable performance.

Research on the Relationship Between Environmental and Economic Coupling Systems in Bohai Bay Area Based on a Vector Autoregression(VAR)Model

This study analyzed the impact of land-based contaminants and tertiary industrial structure on economic development in the selected Bohai Bay area,China.Based on panel data spanning 2011-2020,a vector autoregressive(VAR)model is used to analyze and forecast the short-run and long-run relationships between three industrial structures,pollutant discharge,and economic development.The results showed that the environmental index had a long-term cointegration relationship with the industrial structure economic index.Per capital chemical oxygen demand(PCOD)and per capita ammonia nitrogen(PNH_(3)N)had a positive impact on delta per capita GDP(dPGDP),while per capita solid waste(PSW),the secondary industry rate(SIR)and delta tertiary industry(dTIR)had a negative impact on dPGDP.The VAR model under this coupling system had stability and credibility.The impulse response results showed that the short-term effect of the coupling system on dPGDP was basically consistent with the Granger causality test results.In addition,variance decomposition was used in this study to predict the long-term impact of the coupling system in the next ten periods(i.e.,ten years).It was found that dTIR had a great impact on dPGDP,with a contribution rate as high as 74.35%in the tenth period,followed by the contribution rate of PCOD up to 3.94%,while the long-term contribution rates of PSW,SIR and PNH3N were all less than 1%.The results show that the government should support the development of the tertiary industry to maintain the vitality of economic development and prevent environmental deterioration.

An Integrated Analysis on the Synergistic Reduction of Carbon and Pollution Emissions from China’s Iron and Steel Industry

Decarbonization and decontamination of the iron and steel industry(ISI),which contributes up to 15%to anthropogenic CO_(2) emissions(or carbon emissions)and significant proportions of air and water pollutant emissions in China,are challenged by the huge demand for steel.Carbon and pollutants often share common emission sources,indicating that emission reduction could be achieved synergistically.Here,we explored the inherent potential of measures to adjust feedstock composition and technological structure and to control the size of the ISI to achieve carbon emission reduction(CER)and pollution emission reduction(PER).We investigated five typical pollutants in this study,namely,petroleum hydrocarbon pollutants and chemical oxygen demand in wastewater,particulate matter,SO_(2),and NO_(x) in off gases,and examined synergies between CER and PER by employing cross elasticity for the period between 2022 and 2035.The results suggest that a reduction of 8.7%-11.7%in carbon emissions and 20%-31%in pollution emissions(except for particulate matter emissions)could be achieved by 2025 under a high steel scrap ratio(SSR)scenario.Here,the SSR and electric arc furnace(EAF)ratio serve critical roles in enhancing synergies between CER and PER(which vary with the type of pollutant).However,subject to a limited volume of steel scrap,a focused increase in the EAF ratio with neglection of the available supply of steel scrap to EAF facilities would lead to an increase carbon and pollution emissions.Although CER can be achieved through SSR and EAF ratio optimization,only when the crude steel production growth rate remains below 2.2%can these optimization measures maintain the emissions in 2030 at a similar level to that in 2021.Therefore,the synergistic effects between PER and CER should be considered when formulating a development route for the ISI in the future.

Significant contributions of the petroleum industry to volatile organic compounds and ozone pollution:Insights from year-long observations in the Yellow River Delta

The petroleum industry is a significant source of anthropogenic volatile organic compounds(VOCs),but up to now,its exact impact on urban VOCs and ozone(O_(3))remains unclear.This study conducted year-long VOC ob-servations in Dongying,China,a petroleum industrial region.The VOCs from the petroleum industry(oil and gas volatilization and petrochemical production)were identified by employing the positive matrix factorization model,and their contribution to O_(3) formation was quantitatively evaluated using an observation-based chemical box model.The observed annual average concentration of VOCs was 68.6±63.5 ppbv,with a maximum daily av-erage of 335.3 ppbv.The petroleum industry accounted for 66.5%of total VOCs,contributing 54.9%from oil and gas evaporation and 11.6%from petrochemical production.Model results indicated that VOCs from the petroleum industry contributed to 31%of net O_(3) production,with 21.3%and 34.2%contributions to HO_(2)+NO and RO_(2)+NO pathways,respectively.The larger impact on the RO_(2) pathway is primarily due to the fact that OH+VOCs ac-count for 86.9%of the primary source of RO_(2).This study highlights the critical role of controlling VOCs from the petroleum industry in urban O_(3) pollution,especially those from previously overlooked low-reactivity alkanes.

A Review of Hybrid Cyber Threats Modelling and Detection Using Artificial Intelligence in IIoT

The Industrial Internet of Things(IIoT)has brought numerous benefits,such as improved efficiency,smart analytics,and increased automation.However,it also exposes connected devices,users,applications,and data generated to cyber security threats that need to be addressed.This work investigates hybrid cyber threats(HCTs),which are now working on an entirely new level with the increasingly adopted IIoT.This work focuses on emerging methods to model,detect,and defend against hybrid cyber attacks using machine learning(ML)techniques.Specifically,a novel ML-based HCT modelling and analysis framework was proposed,in which L1 regularisation and Random Forest were used to cluster features and analyse the importance and impact of each feature in both individual threats and HCTs.A grey relation analysis-based model was employed to construct the correlation between IIoT components and different threats.

Research Progress and Prospects of Total Factor Productivity in the Construction Industry

The high-quality development of the construction industry fundamentally stems from the significant improvement of total factor productivity.Therefore,it is of crucial significance for promoting the development of the construction industry to a higher level by scientifically and accurately measuring the total factor productivity of the construction industry and deeply analyzing the influencing factors behind it.Based on a comprehensive consideration of research methods and influencing factors,this paper systematically reviews the existing relevant literature on total factor productivity in the construction industry,aiming to reveal the current research development trend in this field and point out potential problems.This effort aims to provide a solid theoretical foundation and valuable reference for further in-depth research,and jointly promote the continuous progress and development of total factor productivity research in the construction industry.

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.

Can Industrial Structure Upgrading Restrain Industrial Land Expansion?Evidence from China

China has made great achievements in industrial development and is transforming into a powerful manufacturing country.Meanwhile,the industrial land scale is also expanding.However,whether industrial structure upgrading achieves the purpose of restraining industrial land expansion remains unanswered.By calculating the industrial land structure index(ILSI)and industrial land expansion scale(ILES),this study analyzed their temporal and spatial distribution characteristics at both regional and city levels from 2007to 2020 in China.Results show that industrial land expansion presents a different trend in the four regions,the ILES in the eastern region is the largest,and the speed of industrial land expansion has declined since 2013,but it has gradually increased since 2016.The ILSI of the eastern and central regions is higher than that of the western and northeastern regions.Furthermore,a spatial Durbin model(SDM)has been established to estimate the spatial effect of industrial structure upgrading on industrial land expansion from 2007 to2020.Notably,industrial structure upgrading has not slowed industrial land expansion.The eastern and western regions require a greater amount of industrial land while upgrading the industrial structure.The improvement of the infrastructure level and international trade level has promoted industrial land expansion.

Spatial Patterns and Drivers of Intelligent Manufacturing from a‘Glob-allocal'Perspective:A Study of China's Industrial Robotics

The advancement of the intelligent manufacturing industry(IMI)represents the future direction for the world's manufactur-ing sector,offering a promising avenue to bolster national competitiveness and enhance industrial manufacturing efficiency.In this study,we took the industrial robot industry(IRI)as a case study to elucidate the spatial distribution and interconnections of IMI from a geographical perspective,and the modified diamond model(DM)was used to analyze the influencing factors.Results show that:1)the spatial pattern of IRI with various investment attributes in different industrial chain links is generally similar,centered in the southeast.Key investment areas are in the east and south.The spatial distribution of China's IRI covers a multitude of provinces and obtains differ-ent scales of investment in different countries(regions).2)The spatial correlation between foreign investors and China's provincial-level administrative regions(PARs)forms a network,and the network of foreign-invested enterprises is more stable.Different countries(regions)have distinct location preferences in China,with significant spatial differences in correlation degrees.3)Overall,the interac-tion of these factors shapes the location decisions and correlation patterns of industrial robot enterprises.This study not only contributes to our theoretical knowledge of the industrial spatial structure and industrial economy but also offers valuable references and sugges-tions for national IMI planning and relevant industry investors.