In rural China,the trend of population aging and family hollowing is becoming increasingly severe.Traditional elderly care methods are no longer adequate to meet the growing demand for elderly care,leading to the emer...In rural China,the trend of population aging and family hollowing is becoming increasingly severe.Traditional elderly care methods are no longer adequate to meet the growing demand for elderly care,leading to the emergence of mutual-support elderly care as a new approach to elderly care.Mutual support has gained widespread practice and has become a vital component of the rural elderly service system.However,rural mutual-support elderly care encounters development bottlenecks,including local cultural resilience,disembedding of social relationships,gaps in policies and regulations,and multiple coordination challenges.Embeddedness theory emphasizes the need for social behavior to be embedded in the network of social connections,providing a valuable theoretical framework for mutual-support elderly care.Drawing on embeddedness theory,this paper investigates the accessibility of mutual-support elderly care in rural areas by examining cognitive embeddedness,relational embeddedness,systemic embeddedness,and structural embeddedness.By addressing the development bottlenecks of mutual-support elderly care in rural China,this paper aims to propose ideas for achieving high-quality development in rural mutual-support elderly care.展开更多
Traceability system has received wide attention in solving food safety issues, via which food information could be tracked back to producer/farmers. Consumers need to obtain this information from producers or social n...Traceability system has received wide attention in solving food safety issues, via which food information could be tracked back to producer/farmers. Consumers need to obtain this information from producers or social networks, trust in the information,and consequently assess perceived risks, especially when food scandals are exposed to the media. In this study, we introduce the social embeddedness theory to understand how consumers’ social activities affect their risk perceptions on traceable food. Specifically, we investigate how risk perceptions are predicted by the interpersonal relationships, organizational level and social-level relationships. Results show that the interpersonal relationships were associated with lower levels of risk perceptions, while organizational and social relationships impacted consumer’s risk perceptions at middle and higher levels,respectively. Results also show that the "ripple effect" extended to effect of risk events with negative information, however,did not exist for the group exposed to positive information. Potential food safety implications have been proposed to identify for effective risk mitigation under media coverages.展开更多
Rapidly emerged creative industries receive increasing attention from a variety of disciplines. However, the space features of creative industries and its association with local socio-cultural contexts have not been f...Rapidly emerged creative industries receive increasing attention from a variety of disciplines. However, the space features of creative industries and its association with local socio-cultural contexts have not been fully understood, especially at a micro-city level. This study attempts to understand the agglomeration of creative industries in Shanghai from the sociology perspective. For this study, this paper utilizes primarily a questionnaire survey to explain the space features of creative industries in Shanghai. The results indicate an extensive socio-cultural embeddedness of the agglomeration of creative industries in Shanghai. First, strong emphasis on face-to-face contacts by creative professionals makes geographical agglomeration necessary for creative industries. Second, the reason why inner city of Shanghai is popular among creative professionals and enterprises lies in the diversity of cultures and special environment of the former colonial zones of Shanghai. Additionally, highly concentrated dining and entertainment facilities in the central city of Shanghai offer creative workers social networking places and nightlife venues. Third, as the educational attainment of local citizens and the protection of intellectual property are highly stressed by creative professionals, research and design specialized creative industries are more likely located near universities and research institutes.展开更多
The current knowledge base lacks evidence about situational-and surface-level personality variables and their impacts on job embeddedness and proclivity to be absent from work.With this recognition,drawing from the hi...The current knowledge base lacks evidence about situational-and surface-level personality variables and their impacts on job embeddedness and proclivity to be absent from work.With this recognition,drawing from the hierarchical personality model and fit theory as well as job embeddedness theory,our paper explores the influences of job resourcefulness(JR)and customer orientation(CO)on job embeddedness and propensity to be absent from work.We tapped time-lagged data gathered from hotel customer-contact employees in the United Arab Emirates to assess the aforementioned linkages via structural equation modeling.CO is a complete mediator between JR and job embeddedness,while job embeddedness completely mediates the linkage between CO and absence intentions.Specifically,hotel employees who can work under a resource-depleted environment are high on CO and therefore display job embeddedness at elevated levels.In addition,customer-oriented hotel employees have higher job embeddedness and therefore exhibit lower absence intentions.展开更多
Organizational learning capability is an important embodiment of the competitive advantage of enterprises in the era of knowledge economy. Based on the embeddedness theory,six factors are discussed that influence orga...Organizational learning capability is an important embodiment of the competitive advantage of enterprises in the era of knowledge economy. Based on the embeddedness theory,six factors are discussed that influence organizational learning capability from the perspective of knowledge embeddedness: employees embeddedness, tools embeddedness, tasks embeddedness,interpersonal relationship embeddedness, organizational culture embeddedness and network environment embeddedness. Combined with the survey data of textile and apparel manufacturing industry,the research proves the important function of knowledge embeddedness in the construction of organizational learning capability, and proposes three research countermeasures for industrial upgrading.展开更多
This paper develops a dynamic theoretical framework for global competitiveness, which describes the relationships among organizations in an industry cluster. The spiral for knowledge transfer, culture variables and em...This paper develops a dynamic theoretical framework for global competitiveness, which describes the relationships among organizations in an industry cluster. The spiral for knowledge transfer, culture variables and embeddedness influence knowledge transfer. Embeddedness and knowledge transfer are the key determinants of industry clusters that lead to global competitiveness. Industry clusters are characterized by external economies, generalized reciprocity and flexible specialization.展开更多
This study analyzes opportunity recognition and development from the perspective of job embeddedness based on entrepreneurial action of tech-entrepreneur. The impact of job embeddedness to entrepreneurial path choice ...This study analyzes opportunity recognition and development from the perspective of job embeddedness based on entrepreneurial action of tech-entrepreneur. The impact of job embeddedness to entrepreneurial path choice of tech-entrepreneur is tested by multi-case study. This paper also provides theoretic evidence to enhance the possibility of success of start-ups for entrepreneurs.展开更多
Against the backdrop of China's socio-economic transition, there is a growing imperative to examine neighborhood renovation initiatives in addressing the emerging needs of residents. Developing Granovetter's c...Against the backdrop of China's socio-economic transition, there is a growing imperative to examine neighborhood renovation initiatives in addressing the emerging needs of residents. Developing Granovetter's classic work on embeddedness, this paper proposes a conceptual framework of spatial embeddedness to understand changes in the physical space brought about by neighborhood renovation, in order to explore how it affects residents' satisfaction in a dynamic temporal and spatial process. It presents whether and why residents' real feelings produced from their interaction with neighborhood renovation are(un)different, and how their feelings are shaped based on six months of fieldwork in a danwei neighborhood in Xi'an, China. The paper conceptualizes the relationship between the neighborhood space and embeddedness by adopting spatial embeddedness to capture the interplay of temporal, spatial, and social factors in the process of danwei neighborhood renovation. This framework not only integrates multiple perspectives and scales, but also reflects different levels of residents' satisfaction, trying to establish a connection between the abstract space and the renovation space. It suggests that spatial embeddedness should be considered as a response to the negative social impacts resulting from changes in the physical space in neighborhood renovation.展开更多
Objective:This study aimed to review the relationship between job embeddedness and turnover intentions among nurses and explore the effects of the Job Embeddedness Scale,number of years in the career,education,and mar...Objective:This study aimed to review the relationship between job embeddedness and turnover intentions among nurses and explore the effects of the Job Embeddedness Scale,number of years in the career,education,and marital status on this relationship.Methods:The review was conducted by searching the China Knowledge Resource Integrated Database(CNKI),Weipu Database(CQVIP),China Biology Medicine(CBM),Wanfang Database,PubMed,Web of Science,Embase,CINAHL,and APA-PsycNet for articles on nurses’job embeddedness and turnover from intention up to March 2024.The research quality was evaluated using the Agency for Healthcare Research and Quality(AHRQ)assessment criteria.The review protocol has been registered on PROSPERO[CRD42023483947].Results:The results of this review included 47 studies consisting of 15,742 nurses from seven countries worldwide.A moderate negative correlation was found between job embeddedness and turnover intention(r=0.487).Furthermore,on-the-job embeddedness(r=0.527)was more negatively associated with turnover intention than off-the-job embeddedness(r=0.234).The highest negative correlation was found between sacrifice and turnover intention(r=0.460),while the lowest was for the link(r=0.185).Furthermore,the relationship between job embeddedness and its dimensions with turnover intention was affected by different job embeddedness scales,number of years in the career,education,and marital status(P<0.05).Conclusion:This systematic review and meta-analysis analyzed the relationships between nurses’job embeddedness,dimensions,and turnover intention.Meanwhile,subgroup analysis and meta-regression explored the factors influencing these relationships.It is an important reference for nurse managers to promote nurse retention.展开更多
Under the current complex and competitive economic environment,more and more firms are embedding themselves into symbiotic networks for value co-creation,since this has become a good strategy to obtain competitive adv...Under the current complex and competitive economic environment,more and more firms are embedding themselves into symbiotic networks for value co-creation,since this has become a good strategy to obtain competitive advantages.Thus,it is important to examine the impacts of firms’embeddedness in symbiotic networks on value co-creation in innovation ecosystems.This study analyzes the mechanisms and contextual factors of firms’dual embeddedness(i.e.,relational and knowledge embeddedness)in symbiotic networks and how each influences value co-creation within innovation ecosystems.Using a sample of 1,972 observations,our findings show,firstly,that firms’dual embeddedness in symbiotic networks positively impacts on value co-creation in innovation ecosystems;secondly,that firms’dual embeddedness in symbiotic networks positively impacts on innovation ecosystem resilience;thirdly,that innovation ecosystem resilience mediates the relationships between firms’dual embeddedness in symbiotic networks and value co-creation in innovation ecosystems;and,fourthly,that innovative ecological environments positively moderate the relationship between firms’dual embeddedness and value co-creation in innovation ecosystems.These results not only enrich the theoretical framework concerning value co-creation within innovation ecosystems but also provide managerial suggestions for firms to efficiently enhance the degree of embeddedness in symbiotic networks and build highly resilient innovation ecosystems,thus promoting value co-creation among innovation ecosystem populations.展开更多
This paper explains the mechanism of R&D network formation based on a game model of network embeddedness.To describe the game relationship between a new member and an original R&D network,this game model is se...This paper explains the mechanism of R&D network formation based on a game model of network embeddedness.To describe the game relationship between a new member and an original R&D network,this game model is set up by introducing three factors:R&D efficiency of the new member,asymmetric information,and trust.By solving the game model,this paper analyzes their impact on the level of embeddedness and transaction cost within the Network.Study results show that,during the formation of an R&D network,low efficiency and asymmetric information will do harm to the level of embeddedness and raise the transaction cost,while trust will have a complicated impact on them because of the probability of misplaced-trust.展开更多
Emerging technological advances are reshaping the casting sector in latest decades.Casting technology is evolving towards intelligent casting paradigm that involves automation,greenization and intelligentization,which...Emerging technological advances are reshaping the casting sector in latest decades.Casting technology is evolving towards intelligent casting paradigm that involves automation,greenization and intelligentization,which attracts more and more attention from the academic and industry communities.In this paper,the main features of casting technology were briefly summarized and forecasted,and the recent developments of key technologies and the innovative efforts made in promoting intelligent casting process were discussed.Moreover,the technical visions of intelligent casting process were also put forward.The key technologies for intelligent casting process comprise 3D printing technologies,intelligent mold technologies and intelligent process control technologies.In future,the intelligent mold that derived from mold with sensors,control devices and actuators will probably incorporate the Internet of Things,online inspection,embedded simulation,decision-making and control system,and other technologies to form intelligent cyber-physical casting system,which may pave the way to realize intelligent casting.It is promising that the intelligent casting process will eventually achieve the goal of real-time process optimization and full-scale control,with the defects,microstructure,performance,and service life of the fabricated castings can be accurately predicted and tailored.展开更多
This study introduces a novel method integrating CO_(2)flooding with radial borehole fracturing for enhanced oil recovery and CO_(2)underground storage,a solution to the limited vertical stimulation reservoir volume i...This study introduces a novel method integrating CO_(2)flooding with radial borehole fracturing for enhanced oil recovery and CO_(2)underground storage,a solution to the limited vertical stimulation reservoir volume in horizontal well fracturing.A numerical model is established to investigate the production rate,reservoir pressure field,and CO_(2)saturation distribution corresponding to changing time of CO_(2)flooding with radial borehole fracturing.A sensitivity analysis on the influence of CO_(2)injection location,layer spacing,pressure difference,borehole number,and hydraulic fractures on oil production and CO_(2)storage is conducted.The CO_(2)flooding process is divided into four stages.Reductions in layer spacing will significantly improve oil production rate and gas storage capacity.However,serious gas channeling can occur when the spacing is lower than 20 m.Increasing the pressure difference between the producer and injector,the borehole number,the hydraulic fracture height,and the fracture width can also increase the oil production rate and gas storage rate.Sensitivity analysis shows that layer spacing and fracture height greatly influence gas storage and oil production.Research outcomes are expected to provide a theoretical basis for the efficient development of shale oil reservoirs in the vertical direction.展开更多
Additive manufacturing technology is highly regarded due to its advantages,such as high precision and the ability to address complex geometric challenges.However,the development of additive manufacturing process is co...Additive manufacturing technology is highly regarded due to its advantages,such as high precision and the ability to address complex geometric challenges.However,the development of additive manufacturing process is constrained by issues like unclear fundamental principles,complex experimental cycles,and high costs.Machine learning,as a novel artificial intelligence technology,has the potential to deeply engage in the development of additive manufacturing process,assisting engineers in learning and developing new techniques.This paper provides a comprehensive overview of the research and applications of machine learning in the field of additive manufacturing,particularly in model design and process development.Firstly,it introduces the background and significance of machine learning-assisted design in additive manufacturing process.It then further delves into the application of machine learning in additive manufacturing,focusing on model design and process guidance.Finally,it concludes by summarizing and forecasting the development trends of machine learning technology in the field of additive manufacturing.展开更多
Embedded memory,which heavily relies on the manufacturing process,has been widely adopted in various industrial applications.As the field of embedded memory continues to evolve,innovative strategies are emerging to en...Embedded memory,which heavily relies on the manufacturing process,has been widely adopted in various industrial applications.As the field of embedded memory continues to evolve,innovative strategies are emerging to enhance performance.Among them,resistive random access memory(RRAM)has gained significant attention due to its numerousadvantages over traditional memory devices,including high speed(<1 ns),high density(4 F^(2)·n^(-1)),high scalability(~nm),and low power consumption(~pJ).This review focuses on the recent progress of embedded RRAM in industrial manufacturing and its potentialapplications.It provides a brief introduction to the concepts and advantages of RRAM,discusses the key factors that impact its industrial manufacturing,and presents the commercial progress driven by cutting-edge nanotechnology,which has been pursued by manysemiconductor giants.Additionally,it highlights the adoption of embedded RRAM in emerging applications within the realm of the Internet of Things and future intelligent computing,with a particular emphasis on its role in neuromorphic computing.Finally,the review discusses thecurrent challenges and provides insights into the prospects of embedded RRAM in the era of big data and artificial intelligence.展开更多
Important challenges must be addressed to make wind turbines sustainable renewable energy sources.A typical problem concerns the design of the foundation.If the pile diameter is larger than that of the jacket platform...Important challenges must be addressed to make wind turbines sustainable renewable energy sources.A typical problem concerns the design of the foundation.If the pile diameter is larger than that of the jacket platform,traditional mechanical models cannot be used.In this study,relying on the seabed soil data of an offshore wind farm,the m-method and the equivalent embedded method are used to address the single-pile wind turbine foundation problem for different pile diameters.An approach to determine the equivalent pile length is also proposed accordingly.The results provide evidence for the effectiveness and reliability of the model based on the equivalent embedded method.展开更多
This paper presents a comprehensive exploration into the integration of Internet of Things(IoT),big data analysis,cloud computing,and Artificial Intelligence(AI),which has led to an unprecedented era of connectivity.W...This paper presents a comprehensive exploration into the integration of Internet of Things(IoT),big data analysis,cloud computing,and Artificial Intelligence(AI),which has led to an unprecedented era of connectivity.We delve into the emerging trend of machine learning on embedded devices,enabling tasks in resource-limited environ-ments.However,the widespread adoption of machine learning raises significant privacy concerns,necessitating the development of privacy-preserving techniques.One such technique,secure multi-party computation(MPC),allows collaborative computations without exposing private inputs.Despite its potential,complex protocols and communication interactions hinder performance,especially on resource-constrained devices.Efforts to enhance efficiency have been made,but scalability remains a challenge.Given the success of GPUs in deep learning,lever-aging embedded GPUs,such as those offered by NVIDIA,emerges as a promising solution.Therefore,we propose an Embedded GPU-based Secure Two-party Computation(EG-STC)framework for Artificial Intelligence(AI)systems.To the best of our knowledge,this work represents the first endeavor to fully implement machine learning model training based on secure two-party computing on the Embedded GPU platform.Our experimental results demonstrate the effectiveness of EG-STC.On an embedded GPU with a power draw of 5 W,our implementation achieved a secure two-party matrix multiplication throughput of 5881.5 kilo-operations per millisecond(kops/ms),with an energy efficiency ratio of 1176.3 kops/ms/W.Furthermore,leveraging our EG-STC framework,we achieved an overall time acceleration ratio of 5–6 times compared to solutions running on server-grade CPUs.Our solution also exhibited a reduced runtime,requiring only 60%to 70%of the runtime of previously best-known methods on the same platform.In summary,our research contributes to the advancement of secure and efficient machine learning implementations on resource-constrained embedded devices,paving the way for broader adoption of AI technologies in various applications.展开更多
The battery technology progress has been a contradictory process in which performance improvement and hidden risks coexist.Now the battery is still a“black box”,thus requiring a deep understanding of its internal st...The battery technology progress has been a contradictory process in which performance improvement and hidden risks coexist.Now the battery is still a“black box”,thus requiring a deep understanding of its internal state.The battery should“sense its internal physical/chemical conditions”,which puts strict requirements on embedded sensing parts.This paper summarizes the application of advanced optical fiber sensors in lithium-ion batteries and energy storage technologies that may be mass deployed,focuses on the insights of advanced optical fiber sensors into the processes of one-dimensional nano-micro-level battery material structural phase transition,electrolyte degradation,electrode-electrolyte interface dynamics to three-dimensional macro-safety evolution.The paper contributes to understanding how to use optical fiber sensors to achieve“real”and“embedded”monitoring.Through the inherent advantages of the advanced optical fiber sensor,it helps clarify the battery internal state and reaction mechanism,aiding in the establishment of more detailed models.These advancements can promote the development of smart batteries,with significant importance lying in essentially promoting the improvement of system consistency.Furthermore,with the help of smart batteries in the future,the importance of consistency can be weakened or even eliminated.The application of advanced optical fiber sensors helps comprehensively improve the battery quality,reliability,and life.展开更多
Continental shale oil reservoirs,characterized by numerous bedding planes and micro-nano scale pores,feature significantly higher stress sensitivity compared to other types of reservoirs.However,research on suitable s...Continental shale oil reservoirs,characterized by numerous bedding planes and micro-nano scale pores,feature significantly higher stress sensitivity compared to other types of reservoirs.However,research on suitable stress sensitivity characterization models is still limited.In this study,three commonly used stress sensitivity models for shale oil reservoirs were considered,and experiments on representative core samples were conducted.By fitting and comparing the data,the“exponential model”was identified as a characterization model that accurately represents stress sensitivity in continental shale oil reservoirs.To validate the accuracy of the model,a two-phase seepage mathematical model for shale oil reservoirs coupled with the exponential model was introduced.The model was discretely solved using the finite volume method,and its accuracy was verified through the commercial simulator CMG.The study evaluated the productivity of a typical horizontal well under different engineering,geological,and fracture conditions.The results indicate that considering stress sensitivity leads to a 13.57%reduction in production for the same matrix permeability.Additionally,as the fracture half-length and the number of fractures increase,and the bottomhole flowing pressure decreases,the reservoir stress sensitivity becomes higher.展开更多
Being different from testing for popular GUI software, the “instruction-category” approach is proposed for testing embedded system. This approach is constructed by three steps including refining items, drawing instr...Being different from testing for popular GUI software, the “instruction-category” approach is proposed for testing embedded system. This approach is constructed by three steps including refining items, drawing instruction-brief and instruction-category, and constructing test suite. Consequently, this approach is adopted to test oven embedded system, and detail process is deeply discussed. As a result, the factual result indicates that the “instruction-category” approach can be effectively applied in embedded system testing as a black-box method for conformity testing.展开更多
基金supported by the General Project of National Social Sciences Fund of China (No.20BZZ042)Heilongjiang Province Philosophy and Social Science Research Program (No.23RKD136)。
文摘In rural China,the trend of population aging and family hollowing is becoming increasingly severe.Traditional elderly care methods are no longer adequate to meet the growing demand for elderly care,leading to the emergence of mutual-support elderly care as a new approach to elderly care.Mutual support has gained widespread practice and has become a vital component of the rural elderly service system.However,rural mutual-support elderly care encounters development bottlenecks,including local cultural resilience,disembedding of social relationships,gaps in policies and regulations,and multiple coordination challenges.Embeddedness theory emphasizes the need for social behavior to be embedded in the network of social connections,providing a valuable theoretical framework for mutual-support elderly care.Drawing on embeddedness theory,this paper investigates the accessibility of mutual-support elderly care in rural areas by examining cognitive embeddedness,relational embeddedness,systemic embeddedness,and structural embeddedness.By addressing the development bottlenecks of mutual-support elderly care in rural China,this paper aims to propose ideas for achieving high-quality development in rural mutual-support elderly care.
基金support from the National Natural Science Foundation of China (71773109, 71703150 and 71633002)the support from the Fundamental Research Funds for the Central Universities, China
文摘Traceability system has received wide attention in solving food safety issues, via which food information could be tracked back to producer/farmers. Consumers need to obtain this information from producers or social networks, trust in the information,and consequently assess perceived risks, especially when food scandals are exposed to the media. In this study, we introduce the social embeddedness theory to understand how consumers’ social activities affect their risk perceptions on traceable food. Specifically, we investigate how risk perceptions are predicted by the interpersonal relationships, organizational level and social-level relationships. Results show that the interpersonal relationships were associated with lower levels of risk perceptions, while organizational and social relationships impacted consumer’s risk perceptions at middle and higher levels,respectively. Results also show that the "ripple effect" extended to effect of risk events with negative information, however,did not exist for the group exposed to positive information. Potential food safety implications have been proposed to identify for effective risk mitigation under media coverages.
文摘Rapidly emerged creative industries receive increasing attention from a variety of disciplines. However, the space features of creative industries and its association with local socio-cultural contexts have not been fully understood, especially at a micro-city level. This study attempts to understand the agglomeration of creative industries in Shanghai from the sociology perspective. For this study, this paper utilizes primarily a questionnaire survey to explain the space features of creative industries in Shanghai. The results indicate an extensive socio-cultural embeddedness of the agglomeration of creative industries in Shanghai. First, strong emphasis on face-to-face contacts by creative professionals makes geographical agglomeration necessary for creative industries. Second, the reason why inner city of Shanghai is popular among creative professionals and enterprises lies in the diversity of cultures and special environment of the former colonial zones of Shanghai. Additionally, highly concentrated dining and entertainment facilities in the central city of Shanghai offer creative workers social networking places and nightlife venues. Third, as the educational attainment of local citizens and the protection of intellectual property are highly stressed by creative professionals, research and design specialized creative industries are more likely located near universities and research institutes.
文摘The current knowledge base lacks evidence about situational-and surface-level personality variables and their impacts on job embeddedness and proclivity to be absent from work.With this recognition,drawing from the hierarchical personality model and fit theory as well as job embeddedness theory,our paper explores the influences of job resourcefulness(JR)and customer orientation(CO)on job embeddedness and propensity to be absent from work.We tapped time-lagged data gathered from hotel customer-contact employees in the United Arab Emirates to assess the aforementioned linkages via structural equation modeling.CO is a complete mediator between JR and job embeddedness,while job embeddedness completely mediates the linkage between CO and absence intentions.Specifically,hotel employees who can work under a resource-depleted environment are high on CO and therefore display job embeddedness at elevated levels.In addition,customer-oriented hotel employees have higher job embeddedness and therefore exhibit lower absence intentions.
基金the Fundamental Research Funds for the Central Universities,China(No.17D111004)
文摘Organizational learning capability is an important embodiment of the competitive advantage of enterprises in the era of knowledge economy. Based on the embeddedness theory,six factors are discussed that influence organizational learning capability from the perspective of knowledge embeddedness: employees embeddedness, tools embeddedness, tasks embeddedness,interpersonal relationship embeddedness, organizational culture embeddedness and network environment embeddedness. Combined with the survey data of textile and apparel manufacturing industry,the research proves the important function of knowledge embeddedness in the construction of organizational learning capability, and proposes three research countermeasures for industrial upgrading.
文摘This paper develops a dynamic theoretical framework for global competitiveness, which describes the relationships among organizations in an industry cluster. The spiral for knowledge transfer, culture variables and embeddedness influence knowledge transfer. Embeddedness and knowledge transfer are the key determinants of industry clusters that lead to global competitiveness. Industry clusters are characterized by external economies, generalized reciprocity and flexible specialization.
基金supported by SHANNXI Social Science Foundation(10Q067)Ministry of Education Social Science and Humanities Foundation(12YJA630187)High Education Research Fund of Northwestern Polytechnical University(2014)
文摘This study analyzes opportunity recognition and development from the perspective of job embeddedness based on entrepreneurial action of tech-entrepreneur. The impact of job embeddedness to entrepreneurial path choice of tech-entrepreneur is tested by multi-case study. This paper also provides theoretic evidence to enhance the possibility of success of start-ups for entrepreneurs.
基金supported by the National Natural Science Foundation of China (Nos. 7227419742371238)。
文摘Against the backdrop of China's socio-economic transition, there is a growing imperative to examine neighborhood renovation initiatives in addressing the emerging needs of residents. Developing Granovetter's classic work on embeddedness, this paper proposes a conceptual framework of spatial embeddedness to understand changes in the physical space brought about by neighborhood renovation, in order to explore how it affects residents' satisfaction in a dynamic temporal and spatial process. It presents whether and why residents' real feelings produced from their interaction with neighborhood renovation are(un)different, and how their feelings are shaped based on six months of fieldwork in a danwei neighborhood in Xi'an, China. The paper conceptualizes the relationship between the neighborhood space and embeddedness by adopting spatial embeddedness to capture the interplay of temporal, spatial, and social factors in the process of danwei neighborhood renovation. This framework not only integrates multiple perspectives and scales, but also reflects different levels of residents' satisfaction, trying to establish a connection between the abstract space and the renovation space. It suggests that spatial embeddedness should be considered as a response to the negative social impacts resulting from changes in the physical space in neighborhood renovation.
基金sponsor from the Academic Research Funding of Macao Polytechnic University(Grant number RP/AE-06/2022).
文摘Objective:This study aimed to review the relationship between job embeddedness and turnover intentions among nurses and explore the effects of the Job Embeddedness Scale,number of years in the career,education,and marital status on this relationship.Methods:The review was conducted by searching the China Knowledge Resource Integrated Database(CNKI),Weipu Database(CQVIP),China Biology Medicine(CBM),Wanfang Database,PubMed,Web of Science,Embase,CINAHL,and APA-PsycNet for articles on nurses’job embeddedness and turnover from intention up to March 2024.The research quality was evaluated using the Agency for Healthcare Research and Quality(AHRQ)assessment criteria.The review protocol has been registered on PROSPERO[CRD42023483947].Results:The results of this review included 47 studies consisting of 15,742 nurses from seven countries worldwide.A moderate negative correlation was found between job embeddedness and turnover intention(r=0.487).Furthermore,on-the-job embeddedness(r=0.527)was more negatively associated with turnover intention than off-the-job embeddedness(r=0.234).The highest negative correlation was found between sacrifice and turnover intention(r=0.460),while the lowest was for the link(r=0.185).Furthermore,the relationship between job embeddedness and its dimensions with turnover intention was affected by different job embeddedness scales,number of years in the career,education,and marital status(P<0.05).Conclusion:This systematic review and meta-analysis analyzed the relationships between nurses’job embeddedness,dimensions,and turnover intention.Meanwhile,subgroup analysis and meta-regression explored the factors influencing these relationships.It is an important reference for nurse managers to promote nurse retention.
基金supported by the Major Project of National Social Science Fund of China(grant number:20&ZD059)
文摘Under the current complex and competitive economic environment,more and more firms are embedding themselves into symbiotic networks for value co-creation,since this has become a good strategy to obtain competitive advantages.Thus,it is important to examine the impacts of firms’embeddedness in symbiotic networks on value co-creation in innovation ecosystems.This study analyzes the mechanisms and contextual factors of firms’dual embeddedness(i.e.,relational and knowledge embeddedness)in symbiotic networks and how each influences value co-creation within innovation ecosystems.Using a sample of 1,972 observations,our findings show,firstly,that firms’dual embeddedness in symbiotic networks positively impacts on value co-creation in innovation ecosystems;secondly,that firms’dual embeddedness in symbiotic networks positively impacts on innovation ecosystem resilience;thirdly,that innovation ecosystem resilience mediates the relationships between firms’dual embeddedness in symbiotic networks and value co-creation in innovation ecosystems;and,fourthly,that innovative ecological environments positively moderate the relationship between firms’dual embeddedness and value co-creation in innovation ecosystems.These results not only enrich the theoretical framework concerning value co-creation within innovation ecosystems but also provide managerial suggestions for firms to efficiently enhance the degree of embeddedness in symbiotic networks and build highly resilient innovation ecosystems,thus promoting value co-creation among innovation ecosystem populations.
基金This work was supported by National Natural Science Foundation of China[grant number 71132006].
文摘This paper explains the mechanism of R&D network formation based on a game model of network embeddedness.To describe the game relationship between a new member and an original R&D network,this game model is set up by introducing three factors:R&D efficiency of the new member,asymmetric information,and trust.By solving the game model,this paper analyzes their impact on the level of embeddedness and transaction cost within the Network.Study results show that,during the formation of an R&D network,low efficiency and asymmetric information will do harm to the level of embeddedness and raise the transaction cost,while trust will have a complicated impact on them because of the probability of misplaced-trust.
基金funded by the Beijing Natural Science Foundation-Haidian Original Innovation Joint Fund(L212002)the Tsinghua-Toyota Joint Research Fund(20223930096)the Guangdong Provincial Key Area Research and Development Program(2022B0909070001).
文摘Emerging technological advances are reshaping the casting sector in latest decades.Casting technology is evolving towards intelligent casting paradigm that involves automation,greenization and intelligentization,which attracts more and more attention from the academic and industry communities.In this paper,the main features of casting technology were briefly summarized and forecasted,and the recent developments of key technologies and the innovative efforts made in promoting intelligent casting process were discussed.Moreover,the technical visions of intelligent casting process were also put forward.The key technologies for intelligent casting process comprise 3D printing technologies,intelligent mold technologies and intelligent process control technologies.In future,the intelligent mold that derived from mold with sensors,control devices and actuators will probably incorporate the Internet of Things,online inspection,embedded simulation,decision-making and control system,and other technologies to form intelligent cyber-physical casting system,which may pave the way to realize intelligent casting.It is promising that the intelligent casting process will eventually achieve the goal of real-time process optimization and full-scale control,with the defects,microstructure,performance,and service life of the fabricated castings can be accurately predicted and tailored.
基金This study has been funded by the National Science Fund for Distinguished Young Scholars(No.52204063)Science Foundation of China University of Petroleum,Beijing(No.2462023BJRC025).Moreover,we would like to express our heartfelt appreciation to the Computational Geosciences group in the Department of Mathematics and Cybernetics at SINTEF Digital for developing and providing the free open-source MATLAB Reservoir Simulation Toolbox(MRST)used in this research.
文摘This study introduces a novel method integrating CO_(2)flooding with radial borehole fracturing for enhanced oil recovery and CO_(2)underground storage,a solution to the limited vertical stimulation reservoir volume in horizontal well fracturing.A numerical model is established to investigate the production rate,reservoir pressure field,and CO_(2)saturation distribution corresponding to changing time of CO_(2)flooding with radial borehole fracturing.A sensitivity analysis on the influence of CO_(2)injection location,layer spacing,pressure difference,borehole number,and hydraulic fractures on oil production and CO_(2)storage is conducted.The CO_(2)flooding process is divided into four stages.Reductions in layer spacing will significantly improve oil production rate and gas storage capacity.However,serious gas channeling can occur when the spacing is lower than 20 m.Increasing the pressure difference between the producer and injector,the borehole number,the hydraulic fracture height,and the fracture width can also increase the oil production rate and gas storage rate.Sensitivity analysis shows that layer spacing and fracture height greatly influence gas storage and oil production.Research outcomes are expected to provide a theoretical basis for the efficient development of shale oil reservoirs in the vertical direction.
基金financially supported by the Technology Development Fund of China Academy of Machinery Science and Technology(No.170221ZY01)。
文摘Additive manufacturing technology is highly regarded due to its advantages,such as high precision and the ability to address complex geometric challenges.However,the development of additive manufacturing process is constrained by issues like unclear fundamental principles,complex experimental cycles,and high costs.Machine learning,as a novel artificial intelligence technology,has the potential to deeply engage in the development of additive manufacturing process,assisting engineers in learning and developing new techniques.This paper provides a comprehensive overview of the research and applications of machine learning in the field of additive manufacturing,particularly in model design and process development.Firstly,it introduces the background and significance of machine learning-assisted design in additive manufacturing process.It then further delves into the application of machine learning in additive manufacturing,focusing on model design and process guidance.Finally,it concludes by summarizing and forecasting the development trends of machine learning technology in the field of additive manufacturing.
基金supported by the Key-Area Research and Development Program of Guangdong Province(Grant No.2021B0909060002)National Natural Science Foundation of China(Grant Nos.62204219,62204140)+1 种基金Major Program of Natural Science Foundation of Zhejiang Province(Grant No.LDT23F0401)Thanks to Professor Zhang Yishu from Zhejiang University,Professor Gao Xu from Soochow University,and Professor Zhong Shuai from Guangdong Institute of Intelligence Science and Technology for their support。
文摘Embedded memory,which heavily relies on the manufacturing process,has been widely adopted in various industrial applications.As the field of embedded memory continues to evolve,innovative strategies are emerging to enhance performance.Among them,resistive random access memory(RRAM)has gained significant attention due to its numerousadvantages over traditional memory devices,including high speed(<1 ns),high density(4 F^(2)·n^(-1)),high scalability(~nm),and low power consumption(~pJ).This review focuses on the recent progress of embedded RRAM in industrial manufacturing and its potentialapplications.It provides a brief introduction to the concepts and advantages of RRAM,discusses the key factors that impact its industrial manufacturing,and presents the commercial progress driven by cutting-edge nanotechnology,which has been pursued by manysemiconductor giants.Additionally,it highlights the adoption of embedded RRAM in emerging applications within the realm of the Internet of Things and future intelligent computing,with a particular emphasis on its role in neuromorphic computing.Finally,the review discusses thecurrent challenges and provides insights into the prospects of embedded RRAM in the era of big data and artificial intelligence.
基金supported by the National Natural Science Foundation of China (52071055)the Fundamental Research Funds for the Central Universities (Grant No.DUT22QN237).
文摘Important challenges must be addressed to make wind turbines sustainable renewable energy sources.A typical problem concerns the design of the foundation.If the pile diameter is larger than that of the jacket platform,traditional mechanical models cannot be used.In this study,relying on the seabed soil data of an offshore wind farm,the m-method and the equivalent embedded method are used to address the single-pile wind turbine foundation problem for different pile diameters.An approach to determine the equivalent pile length is also proposed accordingly.The results provide evidence for the effectiveness and reliability of the model based on the equivalent embedded method.
基金supported in part by Major Science and Technology Demonstration Project of Jiangsu Provincial Key R&D Program under Grant No.BE2023025in part by the National Natural Science Foundation of China under Grant No.62302238+2 种基金in part by the Natural Science Foundation of Jiangsu Province under Grant No.BK20220388in part by the Natural Science Research Project of Colleges and Universities in Jiangsu Province under Grant No.22KJB520004in part by the China Postdoctoral Science Foundation under Grant No.2022M711689.
文摘This paper presents a comprehensive exploration into the integration of Internet of Things(IoT),big data analysis,cloud computing,and Artificial Intelligence(AI),which has led to an unprecedented era of connectivity.We delve into the emerging trend of machine learning on embedded devices,enabling tasks in resource-limited environ-ments.However,the widespread adoption of machine learning raises significant privacy concerns,necessitating the development of privacy-preserving techniques.One such technique,secure multi-party computation(MPC),allows collaborative computations without exposing private inputs.Despite its potential,complex protocols and communication interactions hinder performance,especially on resource-constrained devices.Efforts to enhance efficiency have been made,but scalability remains a challenge.Given the success of GPUs in deep learning,lever-aging embedded GPUs,such as those offered by NVIDIA,emerges as a promising solution.Therefore,we propose an Embedded GPU-based Secure Two-party Computation(EG-STC)framework for Artificial Intelligence(AI)systems.To the best of our knowledge,this work represents the first endeavor to fully implement machine learning model training based on secure two-party computing on the Embedded GPU platform.Our experimental results demonstrate the effectiveness of EG-STC.On an embedded GPU with a power draw of 5 W,our implementation achieved a secure two-party matrix multiplication throughput of 5881.5 kilo-operations per millisecond(kops/ms),with an energy efficiency ratio of 1176.3 kops/ms/W.Furthermore,leveraging our EG-STC framework,we achieved an overall time acceleration ratio of 5–6 times compared to solutions running on server-grade CPUs.Our solution also exhibited a reduced runtime,requiring only 60%to 70%of the runtime of previously best-known methods on the same platform.In summary,our research contributes to the advancement of secure and efficient machine learning implementations on resource-constrained embedded devices,paving the way for broader adoption of AI technologies in various applications.
基金the National Natural Science Foundation of China(No.52307245[Y.D.Li],No.U21A20170[X.He],22279070[L.Wang],and 52206263[Y.Song])the China Postdoctoral Science Foundation(No.2022M721820[Y.D.Li])the Ministry of Science and Technology of China(No.2019YFA0705703[L.Wang])。
文摘The battery technology progress has been a contradictory process in which performance improvement and hidden risks coexist.Now the battery is still a“black box”,thus requiring a deep understanding of its internal state.The battery should“sense its internal physical/chemical conditions”,which puts strict requirements on embedded sensing parts.This paper summarizes the application of advanced optical fiber sensors in lithium-ion batteries and energy storage technologies that may be mass deployed,focuses on the insights of advanced optical fiber sensors into the processes of one-dimensional nano-micro-level battery material structural phase transition,electrolyte degradation,electrode-electrolyte interface dynamics to three-dimensional macro-safety evolution.The paper contributes to understanding how to use optical fiber sensors to achieve“real”and“embedded”monitoring.Through the inherent advantages of the advanced optical fiber sensor,it helps clarify the battery internal state and reaction mechanism,aiding in the establishment of more detailed models.These advancements can promote the development of smart batteries,with significant importance lying in essentially promoting the improvement of system consistency.Furthermore,with the help of smart batteries in the future,the importance of consistency can be weakened or even eliminated.The application of advanced optical fiber sensors helps comprehensively improve the battery quality,reliability,and life.
基金supported by the China Postdoctoral Science Foundation(2021M702304)Natural Science Foundation of Shandong Province(ZR2021QE260).
文摘Continental shale oil reservoirs,characterized by numerous bedding planes and micro-nano scale pores,feature significantly higher stress sensitivity compared to other types of reservoirs.However,research on suitable stress sensitivity characterization models is still limited.In this study,three commonly used stress sensitivity models for shale oil reservoirs were considered,and experiments on representative core samples were conducted.By fitting and comparing the data,the“exponential model”was identified as a characterization model that accurately represents stress sensitivity in continental shale oil reservoirs.To validate the accuracy of the model,a two-phase seepage mathematical model for shale oil reservoirs coupled with the exponential model was introduced.The model was discretely solved using the finite volume method,and its accuracy was verified through the commercial simulator CMG.The study evaluated the productivity of a typical horizontal well under different engineering,geological,and fracture conditions.The results indicate that considering stress sensitivity leads to a 13.57%reduction in production for the same matrix permeability.Additionally,as the fracture half-length and the number of fractures increase,and the bottomhole flowing pressure decreases,the reservoir stress sensitivity becomes higher.
文摘Being different from testing for popular GUI software, the “instruction-category” approach is proposed for testing embedded system. This approach is constructed by three steps including refining items, drawing instruction-brief and instruction-category, and constructing test suite. Consequently, this approach is adopted to test oven embedded system, and detail process is deeply discussed. As a result, the factual result indicates that the “instruction-category” approach can be effectively applied in embedded system testing as a black-box method for conformity testing.
