In an industrial computer control system, if a communication with a single chip computer built with the aid of serial port I/O ports can be got easily to connect with equipment. Meanwhile, the system reliability would...In an industrial computer control system, if a communication with a single chip computer built with the aid of serial port I/O ports can be got easily to connect with equipment. Meanwhile, the system reliability would be improved and the system cost would be reduced.To save ±15 V power supply and electrical level convert circuit,the author provide a simple interface circuit and operational procedure between PC and the single chip computer in this paper. The application of multithread is introduced and the advantages of data acquisition and processing with multithread are also analyzed.展开更多
As attack techniques evolve and data volumes increase,the integration of artificial intelligence-based security solutions into industrial control systems has become increasingly essential.Artificial intelligence holds...As attack techniques evolve and data volumes increase,the integration of artificial intelligence-based security solutions into industrial control systems has become increasingly essential.Artificial intelligence holds significant potential to improve the operational efficiency and cybersecurity of these systems.However,its dependence on cyber-based infrastructures expands the attack surface and introduces the risk that adversarial manipulations of artificial intelligence models may cause physical harm.To address these concerns,this study presents a comprehensive review of artificial intelligence-driven threat detection methods and adversarial attacks targeting artificial intelligence within industrial control environments,examining both their benefits and associated risks.A systematic literature review was conducted across major scientific databases,including IEEE,Elsevier,Springer Nature,ACM,MDPI,and Wiley,covering peer-reviewed journal and conference papers published between 2017 and 2026.Studies were selected based on predefined inclusion and exclusion criteria following a structured screening process.Based on an analysis of 101 selected studies,this survey categorizes artificial intelligence-based threat detection approaches across the physical,control,and application layers of industrial control systems and examines poisoning,evasion,and extraction attacks targeting industrial artificial intelligence.The findings identify key research trends,highlight unresolved security challenges,and discuss implications for the secure deployment of artificial intelligence-enabled cybersecurity solutions in industrial control systems.展开更多
The 6D pose estimation of objects is of great significance for the intelligent assembly and sorting of industrial parts.In the industrial robot production scenarios,the 6D pose estimation of industrial parts mainly fa...The 6D pose estimation of objects is of great significance for the intelligent assembly and sorting of industrial parts.In the industrial robot production scenarios,the 6D pose estimation of industrial parts mainly faces two challenges:one is the loss of information and interference caused by occlusion and stacking in the sorting scenario,the other is the difficulty of feature extraction due to the weak texture of industrial parts.To address the above problems,this paper proposes an attention-based pixel-level voting network for 6D pose estimation of weakly textured industrial parts,namely CB-PVNet.On the one hand,the voting scheme can predict the keypoints of affected pixels,which improves the accuracy of keypoint localization even in scenarios such as weak texture and partial occlusion.On the other hand,the attention mechanism can extract interesting features of the object while suppressing useless features of surroundings.Extensive comparative experiments were conducted on both public datasets(including LINEMOD,Occlusion LINEMOD and T-LESS datasets)and self-made datasets.The experimental results indicate that the proposed network CB-PVNet can achieve accuracy of ADD(-s)comparable to state-of-the-art using only RGB images while ensuring real-time performance.Additionally,we also conducted robot grasping experiments in the real world.The balance between accuracy and computational efficiency makes the method well-suited for applications in industrial automation.展开更多
The increasing interconnection of modern industrial control systems(ICSs)with the Internet has enhanced operational efficiency,but alsomade these systemsmore vulnerable to cyberattacks.This heightened exposure has dri...The increasing interconnection of modern industrial control systems(ICSs)with the Internet has enhanced operational efficiency,but alsomade these systemsmore vulnerable to cyberattacks.This heightened exposure has driven a growing need for robust ICS security measures.Among the key defences,intrusion detection technology is critical in identifying threats to ICS networks.This paper provides an overview of the distinctive characteristics of ICS network security,highlighting standard attack methods.It then examines various intrusion detection methods,including those based on misuse detection,anomaly detection,machine learning,and specialised requirements.This paper concludes by exploring future directions for developing intrusion detection systems to advance research and ensure the continued security and reliability of ICS operations.展开更多
Modern industrial environments require uninterrupted machinery operation to maintain productivity standards while ensuring safety and minimizing costs.Conventional maintenance methods,such as reactive maintenance(i.e....Modern industrial environments require uninterrupted machinery operation to maintain productivity standards while ensuring safety and minimizing costs.Conventional maintenance methods,such as reactive maintenance(i.e.,run to failure)or time-based preventive maintenance(i.e.,scheduled servicing),prove ineffective for complex systems with many Internet of Things(IoT)devices and sensors because they fall short in detecting faults at early stages when it is most crucial.This paper presents a predictive maintenance framework based on a hybrid deep learning model that integrates the capabilities of Long Short-Term Memory(LSTM)Networks and Convolutional Neural Networks(CNNs).The framework integrates spatial feature extraction and temporal sequence modeling to accurately classify the health state of industrial equipment into three categories,including Normal,Require Maintenance,and Failed.The framework uses a modular pipeline that includes IoT-enabled data collection along with secure transmission methods to manage cloud storage and provide real-time fault classification.The FD004 subset of the NASA C-MAPSS dataset,containing multivariate sensor readings from aircraft engines,serves as the training and evaluation data for the model.Experimental results show that the LSTM-CNN model outperforms baseline models such as LSTM-SVM and LSTM-RNN,achieving an overall average accuracy of 86.66%,precision of 86.00%,recall of 86.33%,and F1-score of 86.33%.Contrary to the previous LSTM-CNN-based predictive maintenance models that either provide a binary classification or rely on synthetically balanced data,our paper provides a three-class maintenance state(i.e.,Normal,Require Maintenance,and Failed)along with threshold-based labeling that retains the true nature of the degradation.In addition,our work also provides an IoT-to-cloud-based modular architecture for deployment.It offers Computerized Maintenance Management System(CMMS)integration,making our proposed solution not only technically sound but also practical and innovative.The solution achieves real-world industrial deployment readiness through its reliable performance alongside its scalable system design.展开更多
Industrial Cyber-Physical Systems(ICPSs)play a vital role in modern industries by providing an intellectual foundation for automated operations.With the increasing integration of information-driven processes,ensuring ...Industrial Cyber-Physical Systems(ICPSs)play a vital role in modern industries by providing an intellectual foundation for automated operations.With the increasing integration of information-driven processes,ensuring the security of Industrial Control Production Systems(ICPSs)has become a critical challenge.These systems are highly vulnerable to attacks such as denial-of-service(DoS),eclipse,and Sybil attacks,which can significantly disrupt industrial operations.This work proposes an effective protection strategy using an Artificial Intelligence(AI)-enabled Smart Contract(SC)framework combined with the Heterogeneous Barzilai-Borwein Support Vector(HBBSV)method for industrial-based CPS environments.The approach reduces run time and minimizes the probability of attacks.Initially,secured ICPSs are achieved through a comprehensive exchange of views on production plant strategies for condition monitoring using SC and blockchain(BC)integrated within a BC network.The SC executes the HBBSV strategy to verify the security consensus.The Barzilai-Borwein Support Vectorized algorithm computes abnormal attack occurrence probabilities to ensure that components operate within acceptable production line conditions.When a component remains within these conditions,no security breach occurs.Conversely,if a component does not satisfy the condition boundaries,a security lapse is detected,and those components are isolated.The HBBSV method thus strengthens protection against DoS,eclipse,and Sybil attacks.Experimental results demonstrate that the proposed HBBSV approach significantly improves security by enhancing authentication accuracy while reducing run time and authentication time compared to existing techniques.展开更多
In recent years,against the backdrop of profound geopolitical changes,the European Union(EU)has been deeply mired in an industrial predicament,showing signs of shrinking production,capital outflows,relocation of produ...In recent years,against the backdrop of profound geopolitical changes,the European Union(EU)has been deeply mired in an industrial predicament,showing signs of shrinking production,capital outflows,relocation of production capacity,and lagging development in future industries.The primary causes of this situation include the energy supply crisis stemming from the decoupling from Russian energy,the impact of America's unilateral trade policy,structural flaws within the EU itself,and the intensification of global industrial competition.To overcome these challenges,the EU has introduced a series of new industrial policies,aiming at revitalizing its industries by strengthening support for local manufacturing,enhancing protective mechanisms for its domestic production,building diversified supply chains,and prioritizing the development of military industry.However,due to multiple obstacles such as heavy external dependence,significant funding gaps,internal divisions,and strategic short-sightedness,the EU still faces a long and arduous journey in its industrial revival.展开更多
Industrial operators need reliable communication in high-noise,safety-critical environments where speech or touch input is often impractical.Existing gesture systems either miss real-time deadlines on resourceconstrai...Industrial operators need reliable communication in high-noise,safety-critical environments where speech or touch input is often impractical.Existing gesture systems either miss real-time deadlines on resourceconstrained hardware or lose accuracy under occlusion,vibration,and lighting changes.We introduce Industrial EdgeSign,a dual-path framework that combines hardware-aware neural architecture search(NAS)with large multimodalmodel(LMM)guided semantics to deliver robust,low-latency gesture recognition on edge devices.The searched model uses a truncated ResNet50 front end,a dimensional-reduction network that preserves spatiotemporal structure for tubelet-based attention,and localized Transformer layers tuned for on-device inference.To reduce reliance on gloss annotations and mitigate domain shift,we distill semantics from factory-tuned vision-language models and pre-train with masked language modeling and video-text contrastive objectives,aligning visual features with a shared text space.OnML2HP and SHREC’17,theNAS-derived architecture attains 94.7% accuracywith 86ms inference latency and about 5.9W power on Jetson Nano.Under occlusion,lighting shifts,andmotion blur,accuracy remains above 82%.For safetycritical commands,the emergency-stop gesture achieves 72 ms 99th percentile latency with 99.7% fail-safe triggering.Ablation studies confirm the contribution of the spatiotemporal tubelet extractor and text-side pre-training,and we observe gains in translation quality(BLEU-422.33).These results show that Industrial EdgeSign provides accurate,resource-aware,and safety-aligned gesture recognition suitable for deployment in smart factory settings.展开更多
As the annual production of industrial hemp in China increases and its global market share grows,its multipurpose development has become an important trend for future development.The cellulose mass fraction of industr...As the annual production of industrial hemp in China increases and its global market share grows,its multipurpose development has become an important trend for future development.The cellulose mass fraction of industrial hemp was found to be as high as 59.36%by chemical composition determination,providing a possibility for the production of nanocellulose.To broaden the application field of industrial hemp,the 2,2,6,6-tetramethylpiperidine-1-oxyl radical(TEMPO)-oxidized nanocellulose(TCNF),sulfuric acid hydrolyzed nanocellulose(SCNC),and lignincontaining hydrolyzed nanocellulose(LCNC)were prepared by multi-step chemical purification pretreatment combined with TEMPO oxidation and sulfuric acid hydrolysis,respectively.They were characterized by Fourier transform infrared(FTIR)spectroscopy,X-ray diffraction(XRD),and thermogravimetric analysis(TGA).The effects of the sodium hypochlorite volume,sodium hydroxide mass fraction in the pretreatment process,and acid hydrolysis reaction time on the Zeta potential and particle size of the prepared nanocellulose were investigated.The absolute value of the Zeta potential of SCNC could reach 29.59 mV,and the particle size was small.The suspension could still maintain good dispersion stability after standing for 24.0 h under the same dispersion conditions.The basic functional group composition and crystal morphology of TCNF,SCNC,and LCNC did not change compared with the raw hemp,and the highest crystallinity increased from 24.6%to 68.1%.Due to the introduction of ester and carboxyl groups,the initial degradation temperature and the temperature at the maximum mass loss rate of the nanocellulose were lower than those of the raw hemp,but the nanocellulose still maintained the thermal stability for practical applications.展开更多
In industrial manufacturing,efficient surface defect detection is crucial for ensuring product quality and production safety.Traditional inspectionmethods are often slow,subjective,and prone to errors,while classicalm...In industrial manufacturing,efficient surface defect detection is crucial for ensuring product quality and production safety.Traditional inspectionmethods are often slow,subjective,and prone to errors,while classicalmachine vision techniques strugglewith complex backgrounds and small defects.To address these challenges,this study proposes an improved YOLOv11 model for detecting defects on hot-rolled steel strips using the NEU-DET dataset.Three key improvements are introduced in the proposed model.First,a lightweight Guided Attention Feature Module(GAFM)is incorporated to enhance multi-scale feature fusion,allowing the model to better capture and integrate semantic and spatial information across different layers,which improves its ability to detect defects of varying sizes.Second,an Aggregated Attention(AA)mechanism is employed to strengthen the representation of critical defect features while effectively suppressing irrelevant background information,particularly enhancing the detection of small,low-contrast,or complex defects.Third,Ghost Dynamic Convolution(GDC)is applied to reduce computational cost by generating low-cost ghost features and dynamically reweighting convolutional kernels,enabling faster inference without sacrificing feature quality or detection accuracy.Extensive experiments demonstrate that the proposed model achieves a mean Average Precision(mAP)of 87.2%,compared to 81.5%for the baseline,while lowering computational cost from6.3Giga Floating-point Operations Per Second(GFLOPs)to 5.1 GFLOPs.These results indicate that the improved YOLOv11 is both accurate and computationally efficient,making it suitable for real-time industrial surface defect detection and contributing to the development of practical,high-performance inspection systems.展开更多
With the progress of Industry 4.0,collaborative robots(cobots) have become a key area of innovation.However,safety standards such as ISO/TS 15066 often lag behind rapid technological advances,failing to balance safety...With the progress of Industry 4.0,collaborative robots(cobots) have become a key area of innovation.However,safety standards such as ISO/TS 15066 often lag behind rapid technological advances,failing to balance safety and innovation.This paper analyzes the conflicts between standards and innovation of industrial cobots,including lag,rigidity,and safetyperformance trade-offs.It proposes flexible standards,regulatory sandboxes,and lifecycle safety approaches to align safety with technological progress.展开更多
Industrial waste salts are commonly used to make value-added snow-melting agents to ensure traffic safety in northern China during winter and spring after snowfall.However,heavy metals in industrial waste salts may po...Industrial waste salts are commonly used to make value-added snow-melting agents to ensure traffic safety in northern China during winter and spring after snowfall.However,heavy metals in industrial waste salts may pose certain environmental risks.Snow-melting agents and snow samples were collected and analyzed from highways,arterial roads,footbridges,and other locations in Beijing after the snowstorm in December 2023.It was found that the main component of snow-melting agents was sodium chloride with high concentrations of Cu,Mn,and Zn,which are not regulated in the current policies,despite the recent promotion of environmentally friendly snow-melting agents.The Pb,Zn and Cr contents of some snow samples exceeded the limitation value of surface water quality standards,potentially affecting the soil and water environment near roadsides,although the snow-melting agents comply with relevant standards,which indicates the policy gap in the management of recycled industrial salts.We reviewed and analyzed the relevant standards for snow-melting agents and industrial waste salts proposed nationally and internationally over the past 30 years.Through comparative analysis,we proposed relevant policy recommendations to the existing quality standards of snow-melting agents and the management regulations of industrial waste salts,and the formulation of corresponding usage strategies,aimed at reducing the potential environmental release of heavy metals from the use of snow-melting agents,thereby promoting more sustainable green urban development and environmentally sound waste management.展开更多
Although the effectiveness of a tuned viscous mass damper(TVMD)as an inerter-based device for vibration control in civil structures has been thoroughly investigated,there is a lack of systematic research regarding the...Although the effectiveness of a tuned viscous mass damper(TVMD)as an inerter-based device for vibration control in civil structures has been thoroughly investigated,there is a lack of systematic research regarding the application of TVMDs for seismic response control of industrial buildings coupled with mechanical equipment.Therefore,this study proposes ungrounded and grounded TVMDs to effectively utilize the mass of the mechanical equipment and fully exploit the capabilities of the inerter element.An optimal design methodology is developed by pursuing the maximum effective damping ratio and seeking the most rational TVMD control scheme.Validation of TVMD control performance is conducted through time-history analysis based on 20 real seismic ground motions recommended by ATC-40,and by providing a barrel mixer industrial building as a real-life numerical example.The results show that both an ungrounded and grounded TVMD can effectively mitigate the seismic response of the primary structure.Compared to the traditional tuned mass damper(TMD),TVMDs can obtain improved control performance for a given equipment mass ratio.Moreover,an ungrounded TVMD and a TMD show similar working mechanisms that tend to release the displacement of equipment to keep their optimal state,whereas equipment displacement for a grounded TVMD should be strictly limited to provide sufficient anti-force.展开更多
Soft clay treatment with all industrial by-product(IBP)binder has great economic and environmental benefits,yet its geomechanics and mechanisms still need to be well probed.With the activation by calcium carbide resid...Soft clay treatment with all industrial by-product(IBP)binder has great economic and environmental benefits,yet its geomechanics and mechanisms still need to be well probed.With the activation by calcium carbide residue(CCR)and phosphogypsum(PG),the strength,structure,and mechanisms of soft clay treated by aluminosilicate-rich IBP(AS-IBP,such as ground granulated blast furnace slag(GGBS),fly ash(FA),coal gangue(CG),Bayer red mud(BR),and sintered red mud(SR))are comparatively investigated.The strength characteristics of solidified clay exhibit significant differences as AS-IBP changes.When GGBS is adopted,the strength is sensitive to the change in PG content,while the impact of CCR is insignificant.After 90 d,the strength of the optimal sample(G23)reaches 1.40 MPa,35.9%higher than cement solidified clay(CSC),while that achieved by other AS-IBPs is less than 0.3 MPa.In the compression test,the structure's evolutionary trend of G23 has a sudden change as the strength increases from 1.81 MPa to 2.29 MPa,suggesting the transformation in material properties.Besides,the structure of G23 is stronger than CSC,which contributes more to the compressive performance.The total amount of main products(C-S-H and ettringite)of all-IBP solidified clay determines the strength,and ettringite is only significant when calcium-rich AS-IBP is adopted.The total amount of minor products(C-A-H and C-A-S-H)is similar for different samples,equivalent to 28.9%-46.3%of the main products.The relationship between the strength and the product amount can be presented using an exponential function.展开更多
TheIndustrial Internet of Things(IIoT)has emerged as a cornerstone of Industry 4.0,enabling large-scale automation and data-driven decision-making across factories,supply chains,and critical infrastructures.However,th...TheIndustrial Internet of Things(IIoT)has emerged as a cornerstone of Industry 4.0,enabling large-scale automation and data-driven decision-making across factories,supply chains,and critical infrastructures.However,the massive interconnection of resource-constrained devices also amplifies the risks of eavesdropping,data tampering,and device impersonation.While digital signatures are indispensable for ensuring authenticity and non-repudiation,conventional schemes such as RSA and ECCare vulnerable to quantumalgorithms,jeopardizing long-termtrust in IIoT deployments.This study proposes a lightweight,stateless,hash-based signature scheme that achieves post-quantum security while addressing the stringent efficiency demands of IIoT.The design introduces two key optimizations:(1)Forest ofRandomSubsets(FORS)onDemand,where subset secret keys are generated dynamically via a PseudoRandom Function(PRF),thereby minimizing storage overhead and eliminating key-reuse risks;and(2)Winternitz One-Time Signature Plus(WOTS+)partial hash-chain caching,which precomputes intermediate hash values at edge gateways,reducing device-side computations,latency,and energy consumption.The architecture integrates a multi-layerMerkle authentication tree(Merkle tree)and role-based delegation across sensors,gateways,and a Signature Authority Center(SAC),supporting scalable cross-site deployment and key rotation.Froma theoretical perspective,we establish a formal(Existential Unforgeability under Chosen Message Attack)EUF-CMA security proof using a game-based reduction framework.The proof demonstrates that any successful forgerymust reduce to breaking the underlying assumptions of PRF indistinguishability,(second)preimage resistance,or collision resistance,thus quantifying adversarial advantage and ensuring unforgeability.On the implementation side,our design achieves a balanced trade-off between postquantum security and lightweight performance,offering concrete deployment guidelines for real-time industrial systems.In summary,the proposed method contributes both practical system design and formal security guarantees,providing IIoT with a deployable signature substrate that enhances resilience against quantum-era threats and supports future extensions such as device attestation,group signatures,and anomaly detection.展开更多
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 ...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.展开更多
With the continuous advancement and maturation of technologies such as big data,artificial intelligence,virtual reality,robotics,human-machine collaboration,and augmented reality,many enterprises are finding new avenu...With the continuous advancement and maturation of technologies such as big data,artificial intelligence,virtual reality,robotics,human-machine collaboration,and augmented reality,many enterprises are finding new avenues for digital transformation and intelligent upgrading.Industry 5.0,a further extension and development of Industry 4.0,has become an important development trend in industry with more emphasis on human-centered sustainability and flexibility.Accordingly,both the industrial metaverse and digital twins have attracted much attention in this new era.However,the relationship between them is not clear enough.In this paper,a comparison between digital twins and the metaverse in industry is made firstly.Then,we propose the concept and framework of Digital Twin Systems Engineering(DTSE)to demonstrate how digital twins support the industrial metaverse in the era of Industry 5.0 by integrating systems engineering principles.Furthermore,we discuss the key technologies and challenges of DTSE,in particular how artificial intelligence enhances the application of DTSE.Finally,a specific application scenario in the aviation field is presented to illustrate the application prospects of DTSE.展开更多
Promoting the deep integration of advanced manufacturing and producer services is not only a key path for metropolitan to climb the global value chain,but also an important new driving force for optimizing urban spati...Promoting the deep integration of advanced manufacturing and producer services is not only a key path for metropolitan to climb the global value chain,but also an important new driving force for optimizing urban spatial structure.Based on the two dimen-sions of industrial linkage and spatial co-agglomeration from the perspective of industrial integration,taking Beijing,China as a case,using industrial input-output data,micro-enterprise spatial data,and methods such as industrial linkage model,standard deviation el-lipse,and spatial similarity coefficient,this study explores the coupling relationship between industrial linkage and spatial co-agglomer-ation of advanced manufacturing and producer services from 2007 to 2020.The results demonstrate that:1)the industrial linkage between advanced manufacturing and producer services in Beijing has an upward trend,in which the business services have the most significant improvement,in which the business services have the most improvement while the technology services have the most de-crease,but in general,the industrial linkage between the two industries shows a low level.2)Producer services were more spatially clustered than advanced manufacturing,and the degree of spatial co-agglomeration of the two also showed an increasing trend,with strong regional and industrial heterogeneity characteristics,among which the pairing industry involving commerce services and techno-logy services had a more obvious improvement.3)The coupling analysis found that the spatial dependence between advanced manufac-turing and producer services decreased,showing a weak positive correlation and a decreasing trend between industrial linkage and spa-tial co-agglomeration;the heterogeneity among subdivision pairs is prominent,and the strong correlation between industries does not mean that there is an inevitable spatial co-agglomeration.4)Based on the differences in coupling relationships and influence mechan-isms,four coupling modes are identified:H-H type,H-L type,L-L type,and L-H type.Finally,this study proposes three policy implica-tions for the integration of advanced manufacturing and producer services in metropolitan areas.展开更多
Foreign-funded overseas industrial parks(OIPs)are crucial for attracting foreign investment and promoting globalization in developing countries.However,large-scale land acquisition for these parks generates conflicts ...Foreign-funded overseas industrial parks(OIPs)are crucial for attracting foreign investment and promoting globalization in developing countries.However,large-scale land acquisition for these parks generates conflicts between developers and local stakeholders,increasing development costs.A qualitative multicase study was conducted in this study to analyze the land transaction trajectories of China's OIPs.Four OIPs were selected to reveal the underlying mechanisms from the perspectives of institutional arrangements,governance mechanisms,and enterprise heterogeneity.The findings indicate that in host countries with insufficient institutional development,local governments are more inclined to directly engage in OIP land acquisition.High-level intergovernmental mechanisms facilitate land acquisition processes,although their efficacy depends largely on administrative power allocation across parks in host countries.The results also indicate that enterprise characteristics significantly influence land acquisition,where microscale private enterprises lacking political connections often employ low-cost,bottom-up strategies by leveraging international experience.In summary,policy-makers in developing countries should prioritize enhancing OIP governance to mitigate transaction costs,promote diversified land supply,and optimize land allocation.By depicting China's OIP land acquisition processes,this study deepens the academic understanding of OIP governance in developing countries and related international land transactions,offering practical OIP management insights for governments in both host and parent countries.展开更多
Electrical energy can be harvested from the rotational kinetic energy of moving bodies,consisting of both mechanical and kinetic energy as a potential power source through electromagnetic induction,similar to wind ene...Electrical energy can be harvested from the rotational kinetic energy of moving bodies,consisting of both mechanical and kinetic energy as a potential power source through electromagnetic induction,similar to wind energy applications.In industries,rotational bodies are commonly present in operations,yet this kinetic energy remains untapped.This research explores the energy generation characteristics of two rotational body types,disk-shaped and cylinder-shaped under specific experimental setups.The hardware setup included a direct current(DC)motor driver,power supply,DC generator,mechanical support,and load resistance,while the software setup involved automation testing tools and data logging.Electromagnetic induction was used to harvest energy,and experiments were conducted at room temperature(25℃)with controlled variables like speed and friction.Results showed the disk-shaped body exhibited higher energy efficiency than the cylinder-shaped body,largely due to lower mechanical losses.The disk required only two bearings,while the cylinder required four,resulting in lower bearing losses for the disk.Additionally,the disk experienced only air friction,whereas the cylinder encountered friction from a soft,uneven rubber material,increasing surface contact losses.Under a 40 W resistive load,the disk demonstrated a 17.1%energy loss due to mechanical friction,achieving up to 15.55 J of recycled energy.Conversely,the cylinder body experienced a 48.05%energy loss,delivering only 51.95%of energy to the load.These insights suggest significant potential for designing efficient energy recycling systems in industrial settings,particularly in manufacturing and processing industries where rotational machinery is prevalent.Despite its lower energy density,this system could be beneficially integrated with energy storage solutions,enhancing sustainability in industrial practices.展开更多
文摘In an industrial computer control system, if a communication with a single chip computer built with the aid of serial port I/O ports can be got easily to connect with equipment. Meanwhile, the system reliability would be improved and the system cost would be reduced.To save ±15 V power supply and electrical level convert circuit,the author provide a simple interface circuit and operational procedure between PC and the single chip computer in this paper. The application of multithread is introduced and the advantages of data acquisition and processing with multithread are also analyzed.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(RS-2023-00242528,50%)supported by the Korea Internet&Security Agency(KISA)through the Information Security Specialized University Support Project(50%).
文摘As attack techniques evolve and data volumes increase,the integration of artificial intelligence-based security solutions into industrial control systems has become increasingly essential.Artificial intelligence holds significant potential to improve the operational efficiency and cybersecurity of these systems.However,its dependence on cyber-based infrastructures expands the attack surface and introduces the risk that adversarial manipulations of artificial intelligence models may cause physical harm.To address these concerns,this study presents a comprehensive review of artificial intelligence-driven threat detection methods and adversarial attacks targeting artificial intelligence within industrial control environments,examining both their benefits and associated risks.A systematic literature review was conducted across major scientific databases,including IEEE,Elsevier,Springer Nature,ACM,MDPI,and Wiley,covering peer-reviewed journal and conference papers published between 2017 and 2026.Studies were selected based on predefined inclusion and exclusion criteria following a structured screening process.Based on an analysis of 101 selected studies,this survey categorizes artificial intelligence-based threat detection approaches across the physical,control,and application layers of industrial control systems and examines poisoning,evasion,and extraction attacks targeting industrial artificial intelligence.The findings identify key research trends,highlight unresolved security challenges,and discuss implications for the secure deployment of artificial intelligence-enabled cybersecurity solutions in industrial control systems.
基金supported by the Knowledge Innovation Program of Wuhan-Shuguang Project(Grant No.2023010201020443)the School-Level Scientific Research Project Funding Program of Jianghan University(Grant No.2022XKZX33)the Natural Science Foundation of Hubei Province(Grant No.2024AFB466).
文摘The 6D pose estimation of objects is of great significance for the intelligent assembly and sorting of industrial parts.In the industrial robot production scenarios,the 6D pose estimation of industrial parts mainly faces two challenges:one is the loss of information and interference caused by occlusion and stacking in the sorting scenario,the other is the difficulty of feature extraction due to the weak texture of industrial parts.To address the above problems,this paper proposes an attention-based pixel-level voting network for 6D pose estimation of weakly textured industrial parts,namely CB-PVNet.On the one hand,the voting scheme can predict the keypoints of affected pixels,which improves the accuracy of keypoint localization even in scenarios such as weak texture and partial occlusion.On the other hand,the attention mechanism can extract interesting features of the object while suppressing useless features of surroundings.Extensive comparative experiments were conducted on both public datasets(including LINEMOD,Occlusion LINEMOD and T-LESS datasets)and self-made datasets.The experimental results indicate that the proposed network CB-PVNet can achieve accuracy of ADD(-s)comparable to state-of-the-art using only RGB images while ensuring real-time performance.Additionally,we also conducted robot grasping experiments in the real world.The balance between accuracy and computational efficiency makes the method well-suited for applications in industrial automation.
文摘The increasing interconnection of modern industrial control systems(ICSs)with the Internet has enhanced operational efficiency,but alsomade these systemsmore vulnerable to cyberattacks.This heightened exposure has driven a growing need for robust ICS security measures.Among the key defences,intrusion detection technology is critical in identifying threats to ICS networks.This paper provides an overview of the distinctive characteristics of ICS network security,highlighting standard attack methods.It then examines various intrusion detection methods,including those based on misuse detection,anomaly detection,machine learning,and specialised requirements.This paper concludes by exploring future directions for developing intrusion detection systems to advance research and ensure the continued security and reliability of ICS operations.
文摘Modern industrial environments require uninterrupted machinery operation to maintain productivity standards while ensuring safety and minimizing costs.Conventional maintenance methods,such as reactive maintenance(i.e.,run to failure)or time-based preventive maintenance(i.e.,scheduled servicing),prove ineffective for complex systems with many Internet of Things(IoT)devices and sensors because they fall short in detecting faults at early stages when it is most crucial.This paper presents a predictive maintenance framework based on a hybrid deep learning model that integrates the capabilities of Long Short-Term Memory(LSTM)Networks and Convolutional Neural Networks(CNNs).The framework integrates spatial feature extraction and temporal sequence modeling to accurately classify the health state of industrial equipment into three categories,including Normal,Require Maintenance,and Failed.The framework uses a modular pipeline that includes IoT-enabled data collection along with secure transmission methods to manage cloud storage and provide real-time fault classification.The FD004 subset of the NASA C-MAPSS dataset,containing multivariate sensor readings from aircraft engines,serves as the training and evaluation data for the model.Experimental results show that the LSTM-CNN model outperforms baseline models such as LSTM-SVM and LSTM-RNN,achieving an overall average accuracy of 86.66%,precision of 86.00%,recall of 86.33%,and F1-score of 86.33%.Contrary to the previous LSTM-CNN-based predictive maintenance models that either provide a binary classification or rely on synthetically balanced data,our paper provides a three-class maintenance state(i.e.,Normal,Require Maintenance,and Failed)along with threshold-based labeling that retains the true nature of the degradation.In addition,our work also provides an IoT-to-cloud-based modular architecture for deployment.It offers Computerized Maintenance Management System(CMMS)integration,making our proposed solution not only technically sound but also practical and innovative.The solution achieves real-world industrial deployment readiness through its reliable performance alongside its scalable system design.
文摘Industrial Cyber-Physical Systems(ICPSs)play a vital role in modern industries by providing an intellectual foundation for automated operations.With the increasing integration of information-driven processes,ensuring the security of Industrial Control Production Systems(ICPSs)has become a critical challenge.These systems are highly vulnerable to attacks such as denial-of-service(DoS),eclipse,and Sybil attacks,which can significantly disrupt industrial operations.This work proposes an effective protection strategy using an Artificial Intelligence(AI)-enabled Smart Contract(SC)framework combined with the Heterogeneous Barzilai-Borwein Support Vector(HBBSV)method for industrial-based CPS environments.The approach reduces run time and minimizes the probability of attacks.Initially,secured ICPSs are achieved through a comprehensive exchange of views on production plant strategies for condition monitoring using SC and blockchain(BC)integrated within a BC network.The SC executes the HBBSV strategy to verify the security consensus.The Barzilai-Borwein Support Vectorized algorithm computes abnormal attack occurrence probabilities to ensure that components operate within acceptable production line conditions.When a component remains within these conditions,no security breach occurs.Conversely,if a component does not satisfy the condition boundaries,a security lapse is detected,and those components are isolated.The HBBSV method thus strengthens protection against DoS,eclipse,and Sybil attacks.Experimental results demonstrate that the proposed HBBSV approach significantly improves security by enhancing authentication accuracy while reducing run time and authentication time compared to existing techniques.
文摘In recent years,against the backdrop of profound geopolitical changes,the European Union(EU)has been deeply mired in an industrial predicament,showing signs of shrinking production,capital outflows,relocation of production capacity,and lagging development in future industries.The primary causes of this situation include the energy supply crisis stemming from the decoupling from Russian energy,the impact of America's unilateral trade policy,structural flaws within the EU itself,and the intensification of global industrial competition.To overcome these challenges,the EU has introduced a series of new industrial policies,aiming at revitalizing its industries by strengthening support for local manufacturing,enhancing protective mechanisms for its domestic production,building diversified supply chains,and prioritizing the development of military industry.However,due to multiple obstacles such as heavy external dependence,significant funding gaps,internal divisions,and strategic short-sightedness,the EU still faces a long and arduous journey in its industrial revival.
文摘Industrial operators need reliable communication in high-noise,safety-critical environments where speech or touch input is often impractical.Existing gesture systems either miss real-time deadlines on resourceconstrained hardware or lose accuracy under occlusion,vibration,and lighting changes.We introduce Industrial EdgeSign,a dual-path framework that combines hardware-aware neural architecture search(NAS)with large multimodalmodel(LMM)guided semantics to deliver robust,low-latency gesture recognition on edge devices.The searched model uses a truncated ResNet50 front end,a dimensional-reduction network that preserves spatiotemporal structure for tubelet-based attention,and localized Transformer layers tuned for on-device inference.To reduce reliance on gloss annotations and mitigate domain shift,we distill semantics from factory-tuned vision-language models and pre-train with masked language modeling and video-text contrastive objectives,aligning visual features with a shared text space.OnML2HP and SHREC’17,theNAS-derived architecture attains 94.7% accuracywith 86ms inference latency and about 5.9W power on Jetson Nano.Under occlusion,lighting shifts,andmotion blur,accuracy remains above 82%.For safetycritical commands,the emergency-stop gesture achieves 72 ms 99th percentile latency with 99.7% fail-safe triggering.Ablation studies confirm the contribution of the spatiotemporal tubelet extractor and text-side pre-training,and we observe gains in translation quality(BLEU-422.33).These results show that Industrial EdgeSign provides accurate,resource-aware,and safety-aligned gesture recognition suitable for deployment in smart factory settings.
基金Fundamental Research Funds for the Central Universities of China(No.2232024G-01)Textile Vision Basic Research Program,China(No.J202305)。
文摘As the annual production of industrial hemp in China increases and its global market share grows,its multipurpose development has become an important trend for future development.The cellulose mass fraction of industrial hemp was found to be as high as 59.36%by chemical composition determination,providing a possibility for the production of nanocellulose.To broaden the application field of industrial hemp,the 2,2,6,6-tetramethylpiperidine-1-oxyl radical(TEMPO)-oxidized nanocellulose(TCNF),sulfuric acid hydrolyzed nanocellulose(SCNC),and lignincontaining hydrolyzed nanocellulose(LCNC)were prepared by multi-step chemical purification pretreatment combined with TEMPO oxidation and sulfuric acid hydrolysis,respectively.They were characterized by Fourier transform infrared(FTIR)spectroscopy,X-ray diffraction(XRD),and thermogravimetric analysis(TGA).The effects of the sodium hypochlorite volume,sodium hydroxide mass fraction in the pretreatment process,and acid hydrolysis reaction time on the Zeta potential and particle size of the prepared nanocellulose were investigated.The absolute value of the Zeta potential of SCNC could reach 29.59 mV,and the particle size was small.The suspension could still maintain good dispersion stability after standing for 24.0 h under the same dispersion conditions.The basic functional group composition and crystal morphology of TCNF,SCNC,and LCNC did not change compared with the raw hemp,and the highest crystallinity increased from 24.6%to 68.1%.Due to the introduction of ester and carboxyl groups,the initial degradation temperature and the temperature at the maximum mass loss rate of the nanocellulose were lower than those of the raw hemp,but the nanocellulose still maintained the thermal stability for practical applications.
基金supported in part by the National Natural Science Foundation of China(Grant No.62071123)in part by the Natural Science Foundation of Fujian Province(Grant Nos.2024J01971,2022J05202)in part by the Young and Middle-Aged Teacher Education Research Project of Fujian Province(Grant No.JAT210370).
文摘In industrial manufacturing,efficient surface defect detection is crucial for ensuring product quality and production safety.Traditional inspectionmethods are often slow,subjective,and prone to errors,while classicalmachine vision techniques strugglewith complex backgrounds and small defects.To address these challenges,this study proposes an improved YOLOv11 model for detecting defects on hot-rolled steel strips using the NEU-DET dataset.Three key improvements are introduced in the proposed model.First,a lightweight Guided Attention Feature Module(GAFM)is incorporated to enhance multi-scale feature fusion,allowing the model to better capture and integrate semantic and spatial information across different layers,which improves its ability to detect defects of varying sizes.Second,an Aggregated Attention(AA)mechanism is employed to strengthen the representation of critical defect features while effectively suppressing irrelevant background information,particularly enhancing the detection of small,low-contrast,or complex defects.Third,Ghost Dynamic Convolution(GDC)is applied to reduce computational cost by generating low-cost ghost features and dynamically reweighting convolutional kernels,enabling faster inference without sacrificing feature quality or detection accuracy.Extensive experiments demonstrate that the proposed model achieves a mean Average Precision(mAP)of 87.2%,compared to 81.5%for the baseline,while lowering computational cost from6.3Giga Floating-point Operations Per Second(GFLOPs)to 5.1 GFLOPs.These results indicate that the improved YOLOv11 is both accurate and computationally efficient,making it suitable for real-time industrial surface defect detection and contributing to the development of practical,high-performance inspection systems.
文摘With the progress of Industry 4.0,collaborative robots(cobots) have become a key area of innovation.However,safety standards such as ISO/TS 15066 often lag behind rapid technological advances,failing to balance safety and innovation.This paper analyzes the conflicts between standards and innovation of industrial cobots,including lag,rigidity,and safetyperformance trade-offs.It proposes flexible standards,regulatory sandboxes,and lifecycle safety approaches to align safety with technological progress.
基金supported by the National Natural Science Foundation of China(No.22176200)the Industrial Innovation Entrepreneurial Team Project of Ordos 2021.
文摘Industrial waste salts are commonly used to make value-added snow-melting agents to ensure traffic safety in northern China during winter and spring after snowfall.However,heavy metals in industrial waste salts may pose certain environmental risks.Snow-melting agents and snow samples were collected and analyzed from highways,arterial roads,footbridges,and other locations in Beijing after the snowstorm in December 2023.It was found that the main component of snow-melting agents was sodium chloride with high concentrations of Cu,Mn,and Zn,which are not regulated in the current policies,despite the recent promotion of environmentally friendly snow-melting agents.The Pb,Zn and Cr contents of some snow samples exceeded the limitation value of surface water quality standards,potentially affecting the soil and water environment near roadsides,although the snow-melting agents comply with relevant standards,which indicates the policy gap in the management of recycled industrial salts.We reviewed and analyzed the relevant standards for snow-melting agents and industrial waste salts proposed nationally and internationally over the past 30 years.Through comparative analysis,we proposed relevant policy recommendations to the existing quality standards of snow-melting agents and the management regulations of industrial waste salts,and the formulation of corresponding usage strategies,aimed at reducing the potential environmental release of heavy metals from the use of snow-melting agents,thereby promoting more sustainable green urban development and environmentally sound waste management.
基金National Natural Science Foundation of China under Grant Nos.52408327 and 52278306Key Research and Development Program of Hunan Province,China under Grant No.2022SK2096+3 种基金Science and Technology Progress and Innovation Project of the Department of Transportation of Hunan Province,China under Grant No.201912Natural Science Foundation of Hunan Province,China under Grant No.2024JJ6198Scientific Research Project of the Education Department of Hunan Province,China under Grant No.25A0645Emergency Management Science and Technology Project of the Emergency Management Department of Hunan Province,China under Grant No.yjtkjxm_202406。
文摘Although the effectiveness of a tuned viscous mass damper(TVMD)as an inerter-based device for vibration control in civil structures has been thoroughly investigated,there is a lack of systematic research regarding the application of TVMDs for seismic response control of industrial buildings coupled with mechanical equipment.Therefore,this study proposes ungrounded and grounded TVMDs to effectively utilize the mass of the mechanical equipment and fully exploit the capabilities of the inerter element.An optimal design methodology is developed by pursuing the maximum effective damping ratio and seeking the most rational TVMD control scheme.Validation of TVMD control performance is conducted through time-history analysis based on 20 real seismic ground motions recommended by ATC-40,and by providing a barrel mixer industrial building as a real-life numerical example.The results show that both an ungrounded and grounded TVMD can effectively mitigate the seismic response of the primary structure.Compared to the traditional tuned mass damper(TMD),TVMDs can obtain improved control performance for a given equipment mass ratio.Moreover,an ungrounded TVMD and a TMD show similar working mechanisms that tend to release the displacement of equipment to keep their optimal state,whereas equipment displacement for a grounded TVMD should be strictly limited to provide sufficient anti-force.
基金supported by the National Natural Science Foundation of China(Grant No.U24A20183)Natural Science Fund for Distinguished Young Scholars of Hubei Province,China(Grant No.2024AFA051)Youth Science Fund(A-class)of Hunan Natural Science Foundation of China(Grant No.2025JJ20049).
文摘Soft clay treatment with all industrial by-product(IBP)binder has great economic and environmental benefits,yet its geomechanics and mechanisms still need to be well probed.With the activation by calcium carbide residue(CCR)and phosphogypsum(PG),the strength,structure,and mechanisms of soft clay treated by aluminosilicate-rich IBP(AS-IBP,such as ground granulated blast furnace slag(GGBS),fly ash(FA),coal gangue(CG),Bayer red mud(BR),and sintered red mud(SR))are comparatively investigated.The strength characteristics of solidified clay exhibit significant differences as AS-IBP changes.When GGBS is adopted,the strength is sensitive to the change in PG content,while the impact of CCR is insignificant.After 90 d,the strength of the optimal sample(G23)reaches 1.40 MPa,35.9%higher than cement solidified clay(CSC),while that achieved by other AS-IBPs is less than 0.3 MPa.In the compression test,the structure's evolutionary trend of G23 has a sudden change as the strength increases from 1.81 MPa to 2.29 MPa,suggesting the transformation in material properties.Besides,the structure of G23 is stronger than CSC,which contributes more to the compressive performance.The total amount of main products(C-S-H and ettringite)of all-IBP solidified clay determines the strength,and ettringite is only significant when calcium-rich AS-IBP is adopted.The total amount of minor products(C-A-H and C-A-S-H)is similar for different samples,equivalent to 28.9%-46.3%of the main products.The relationship between the strength and the product amount can be presented using an exponential function.
文摘TheIndustrial Internet of Things(IIoT)has emerged as a cornerstone of Industry 4.0,enabling large-scale automation and data-driven decision-making across factories,supply chains,and critical infrastructures.However,the massive interconnection of resource-constrained devices also amplifies the risks of eavesdropping,data tampering,and device impersonation.While digital signatures are indispensable for ensuring authenticity and non-repudiation,conventional schemes such as RSA and ECCare vulnerable to quantumalgorithms,jeopardizing long-termtrust in IIoT deployments.This study proposes a lightweight,stateless,hash-based signature scheme that achieves post-quantum security while addressing the stringent efficiency demands of IIoT.The design introduces two key optimizations:(1)Forest ofRandomSubsets(FORS)onDemand,where subset secret keys are generated dynamically via a PseudoRandom Function(PRF),thereby minimizing storage overhead and eliminating key-reuse risks;and(2)Winternitz One-Time Signature Plus(WOTS+)partial hash-chain caching,which precomputes intermediate hash values at edge gateways,reducing device-side computations,latency,and energy consumption.The architecture integrates a multi-layerMerkle authentication tree(Merkle tree)and role-based delegation across sensors,gateways,and a Signature Authority Center(SAC),supporting scalable cross-site deployment and key rotation.Froma theoretical perspective,we establish a formal(Existential Unforgeability under Chosen Message Attack)EUF-CMA security proof using a game-based reduction framework.The proof demonstrates that any successful forgerymust reduce to breaking the underlying assumptions of PRF indistinguishability,(second)preimage resistance,or collision resistance,thus quantifying adversarial advantage and ensuring unforgeability.On the implementation side,our design achieves a balanced trade-off between postquantum security and lightweight performance,offering concrete deployment guidelines for real-time industrial systems.In summary,the proposed method contributes both practical system design and formal security guarantees,providing IIoT with a deployable signature substrate that enhances resilience against quantum-era threats and supports future extensions such as device attestation,group signatures,and anomaly detection.
基金supported by National Natural Science Foundation of China(Grant No.52270106 and 22266021)Yunnan Major Scientific and Technological Projects(grant No.202202AG050005)Yunnan Fundamental Research Projects(grant No.202201AT070116).
文摘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.
基金Supported by Beijing Municipal Natural Science Foundation of China(Grant No.24JL002)China Postdoctoral Science Foundation(Grant No.2024M754054)+2 种基金National Natural Science Foundation of China(Grant No.52120105008)Beijing Municipal Outstanding Young Scientis Program of Chinathe New Cornerstone Science Foundation through the XPLORER PRIZE。
文摘With the continuous advancement and maturation of technologies such as big data,artificial intelligence,virtual reality,robotics,human-machine collaboration,and augmented reality,many enterprises are finding new avenues for digital transformation and intelligent upgrading.Industry 5.0,a further extension and development of Industry 4.0,has become an important development trend in industry with more emphasis on human-centered sustainability and flexibility.Accordingly,both the industrial metaverse and digital twins have attracted much attention in this new era.However,the relationship between them is not clear enough.In this paper,a comparison between digital twins and the metaverse in industry is made firstly.Then,we propose the concept and framework of Digital Twin Systems Engineering(DTSE)to demonstrate how digital twins support the industrial metaverse in the era of Industry 5.0 by integrating systems engineering principles.Furthermore,we discuss the key technologies and challenges of DTSE,in particular how artificial intelligence enhances the application of DTSE.Finally,a specific application scenario in the aviation field is presented to illustrate the application prospects of DTSE.
基金Under the auspices of National Natural Science Foundation of China(No.42371181)。
文摘Promoting the deep integration of advanced manufacturing and producer services is not only a key path for metropolitan to climb the global value chain,but also an important new driving force for optimizing urban spatial structure.Based on the two dimen-sions of industrial linkage and spatial co-agglomeration from the perspective of industrial integration,taking Beijing,China as a case,using industrial input-output data,micro-enterprise spatial data,and methods such as industrial linkage model,standard deviation el-lipse,and spatial similarity coefficient,this study explores the coupling relationship between industrial linkage and spatial co-agglomer-ation of advanced manufacturing and producer services from 2007 to 2020.The results demonstrate that:1)the industrial linkage between advanced manufacturing and producer services in Beijing has an upward trend,in which the business services have the most significant improvement,in which the business services have the most improvement while the technology services have the most de-crease,but in general,the industrial linkage between the two industries shows a low level.2)Producer services were more spatially clustered than advanced manufacturing,and the degree of spatial co-agglomeration of the two also showed an increasing trend,with strong regional and industrial heterogeneity characteristics,among which the pairing industry involving commerce services and techno-logy services had a more obvious improvement.3)The coupling analysis found that the spatial dependence between advanced manufac-turing and producer services decreased,showing a weak positive correlation and a decreasing trend between industrial linkage and spa-tial co-agglomeration;the heterogeneity among subdivision pairs is prominent,and the strong correlation between industries does not mean that there is an inevitable spatial co-agglomeration.4)Based on the differences in coupling relationships and influence mechan-isms,four coupling modes are identified:H-H type,H-L type,L-L type,and L-H type.Finally,this study proposes three policy implica-tions for the integration of advanced manufacturing and producer services in metropolitan areas.
基金Philosophy and Social Science Planning Projects in Yunnan Province,No.QN202428China Postdoctoral Science Foundation,No.2024M752918。
文摘Foreign-funded overseas industrial parks(OIPs)are crucial for attracting foreign investment and promoting globalization in developing countries.However,large-scale land acquisition for these parks generates conflicts between developers and local stakeholders,increasing development costs.A qualitative multicase study was conducted in this study to analyze the land transaction trajectories of China's OIPs.Four OIPs were selected to reveal the underlying mechanisms from the perspectives of institutional arrangements,governance mechanisms,and enterprise heterogeneity.The findings indicate that in host countries with insufficient institutional development,local governments are more inclined to directly engage in OIP land acquisition.High-level intergovernmental mechanisms facilitate land acquisition processes,although their efficacy depends largely on administrative power allocation across parks in host countries.The results also indicate that enterprise characteristics significantly influence land acquisition,where microscale private enterprises lacking political connections often employ low-cost,bottom-up strategies by leveraging international experience.In summary,policy-makers in developing countries should prioritize enhancing OIP governance to mitigate transaction costs,promote diversified land supply,and optimize land allocation.By depicting China's OIP land acquisition processes,this study deepens the academic understanding of OIP governance in developing countries and related international land transactions,offering practical OIP management insights for governments in both host and parent countries.
基金The APC was funded by Research Management Center, Multimedia University, Malaysia.
文摘Electrical energy can be harvested from the rotational kinetic energy of moving bodies,consisting of both mechanical and kinetic energy as a potential power source through electromagnetic induction,similar to wind energy applications.In industries,rotational bodies are commonly present in operations,yet this kinetic energy remains untapped.This research explores the energy generation characteristics of two rotational body types,disk-shaped and cylinder-shaped under specific experimental setups.The hardware setup included a direct current(DC)motor driver,power supply,DC generator,mechanical support,and load resistance,while the software setup involved automation testing tools and data logging.Electromagnetic induction was used to harvest energy,and experiments were conducted at room temperature(25℃)with controlled variables like speed and friction.Results showed the disk-shaped body exhibited higher energy efficiency than the cylinder-shaped body,largely due to lower mechanical losses.The disk required only two bearings,while the cylinder required four,resulting in lower bearing losses for the disk.Additionally,the disk experienced only air friction,whereas the cylinder encountered friction from a soft,uneven rubber material,increasing surface contact losses.Under a 40 W resistive load,the disk demonstrated a 17.1%energy loss due to mechanical friction,achieving up to 15.55 J of recycled energy.Conversely,the cylinder body experienced a 48.05%energy loss,delivering only 51.95%of energy to the load.These insights suggest significant potential for designing efficient energy recycling systems in industrial settings,particularly in manufacturing and processing industries where rotational machinery is prevalent.Despite its lower energy density,this system could be beneficially integrated with energy storage solutions,enhancing sustainability in industrial practices.
