This study explored the role of job crafting and job embeddedness in the relationship between employee strengths use and thriving at work.Participants were 260 nurses from Beijing,China(99.2%female,54.6%aged 26–35 ye...This study explored the role of job crafting and job embeddedness in the relationship between employee strengths use and thriving at work.Participants were 260 nurses from Beijing,China(99.2%female,54.6%aged 26–35 years,and 62%with a bachelor’s degree or above).Data were collected at two different time points,with a two-week interval between them.Regression analysis and path analysis were applied to test the hypotheses.Results showed that strengths use was associated with thriving at work.Job crafting partially mediated this relationship for higher thriving at work.Job embeddedness weakened the relationship between strengths use and job crafting,and also lowered job crafting effects on work thriving.These findings provide insights into the mechanisms by which strengths use influences thriving at work,highlighting the significance of job crafting and job embeddedness.展开更多
Embedded printing is a highly promising approach for creating complex structures within a yield-stress support bath.However,the accurate prediction and control of printability remain fundamental challenges due to the ...Embedded printing is a highly promising approach for creating complex structures within a yield-stress support bath.However,the accurate prediction and control of printability remain fundamental challenges due to the complex interactions between inks and support baths.Here,we present an artificial intelligence(AI)-driven framework that interprets and predicts embedded printability using rheological data.Using a standardized workflow,we extracted 21 rheological descriptors and established 12 indicators to evaluate structural continuity and geometric fidelity.Interpretable machine learning models revealed that direction-dependent defects are governed by the synergistic interplay among ink yield stress,support bath zero shear viscosity,flow behavior index,and time constant.To enable the prediction of printability in a generalizable manner,we further developed a cascaded neural network,which achieved mean relative prediction errors below 15%across all indicators.Experimental validation using three-dimensional(3 D)-printed constructs and micro-computed tomography(μCT)reconstructions confirmed a strong correlation between predicted and actual fidelity.This work establishes a physics-informed,data-driven paradigm for decoding and optimizing embedded printing,offering broad applicability and providing a robust tool for the rapid pairing of suitable printable ink-support bath combinations.展开更多
Unmanned aerial vehicles(UAVs),especially quadcopters,have become indispensable in numerous industrial and scientific applications due to their flexibility,lowcost,and capability to operate in dynamic environments.Thi...Unmanned aerial vehicles(UAVs),especially quadcopters,have become indispensable in numerous industrial and scientific applications due to their flexibility,lowcost,and capability to operate in dynamic environments.This paper presents a complete design and implementation of a compact autonomous quadcopter capable of trajectory tracking,object detection,precision landing,and real-time telemetry via long-range communication protocols.The system integrates an onboard flight controller running real-time sensor fusion algorithms,a vision-based detection system on a companion single-board computer,and a telemetry unit using Long Range(LoRa)communication.Extensive flight tests were conducted to validate the system’s stability,communication range,and autonomous capabilities.Potential applications in law enforcement,agriculture,search and rescue,and environmental monitoring are also discussed.展开更多
To address the challenges of complexity,power consumption,and cost constraints in traditional display driver integrated circuits(DDICs)caused by external NOR Flash and SRAM,this work proposes an embedded resistive ran...To address the challenges of complexity,power consumption,and cost constraints in traditional display driver integrated circuits(DDICs)caused by external NOR Flash and SRAM,this work proposes an embedded resistive random-access memory(RRAM)integration solution based on a 40 nm high-voltage CMOS logic platform.Targeting the yield fluctuations and stability challenges during RRAM mass production,systematic process optimizations are implemented to achieve synergistic improvements in RRAM performance and yield.Through modifications to the film sputtering and pre-deposition treatment,the withinwafer resistance uniformity(RSU)of the oxygen-deficient layer(ODL)thin film is improved from 11%to 8%,while inter-wafer process stability variation reduces from 23%to below 6%.Consequently,the yield of 8 Mb RRAM embedded mass production products increases from 87%to 98.5%.In terms of device performance,the RRAM demonstrates a fast 4.8 ns read speed,exceptional read disturb immunity of 3×10^(8) cycles at 95℃,10^(3) write/erase endurance cycles for the 1 Mb cells,and data retention of 12.5 years at 125℃.Post high-temperature operating life(HTOL)testing exhibits stable high/low resistance window.This study provides process optimization strategies and a reliability assurance framework for the mass production of highly integrated,low-power embedded RRAM display driver IC.展开更多
This paper presents an optimal operation method for embedded DC interconnections based on low-voltage AC/DC distribution areas(EDC-LVDA)under three-phase unbalanced compensation conditions.It can optimally determine t...This paper presents an optimal operation method for embedded DC interconnections based on low-voltage AC/DC distribution areas(EDC-LVDA)under three-phase unbalanced compensation conditions.It can optimally determine the transmission power of the DC and AC paths to simultaneously improve voltage quality and reduce losses.First,considering the embedded interconnected,unbalanced power structure of the distribution area,a power flow calculation method for EDC-LVDA that accounts for three-phase unbalanced compensation is introduced.This method accurately describes the power flow distribution characteristics under both AC and DC power allocation scenarios.Second,an optimization scheduling model for EDC-LVDA under three-phase unbalanced conditions is developed,incorporating network losses,voltage quality,DC link losses,and unbalance levels.The proposed model employs an improved particle swarm optimization(IPSO)two-layer algorithm to autonomously select different power allocation coefficients for the DC link and AC section under various operating conditions.This enables embedded economic optimization scheduling while maintaining compensation for unbalanced conditions.Finally,a case study based on the IEEE 13-node system for EDC-LVDA is conducted and tested.The results show that the proposed optimal operation method achieves a 100%voltage compliance rate and reduces network losses by 13.8%,while ensuring three-phase power balance compensation.This provides a practical solution for the modernization and upgrading of low-voltage power grids.展开更多
Anomaly detection is a vibrant research direction in controller area networks,which provides the fundamental real-time data transmission underpinning in-vehicle data interaction for the internet of vehicles.However,ex...Anomaly detection is a vibrant research direction in controller area networks,which provides the fundamental real-time data transmission underpinning in-vehicle data interaction for the internet of vehicles.However,existing unsupervised learning methods suffer from insufficient temporal and spatial constraints on shallow features,resulting in fragmented feature representations that compromise model stability and accuracy.To improve the extraction of valuable features,this paper investigates the influence of clustering constraints on shallow feature convergence paths at the model level and further proposes an end-to-end intrusion detection system based on efficient deep embedded subspace clustering(EDESC-IDS).Following the standard learning approach,continuous messages are encoded into two-dimensional data frames via a frame builder,which are then input into an extended convolutional autoencoder for extracting shallow features from high-dimensional data.On this basis,the dual constraints of these output features and the embedding clustering module facilitate end-to-end training of the EDESC-IDS in various attack scenarios.Extensive experimental results show that such a system exhibits significant detection performance on four types of attack datasets,including DoS,Gear,Fuzzy,and RPM,with precision,recall,and F1 scores consistently above 97.79%,while maintaining a false negative rate(FNR)and an error rate(ER)below 2.22%.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
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
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
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
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
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
Adaptive optics(AO)has significantly advanced high-resolution solar observations by mitigating atmospheric turbulence.However,traditional post-focal AO systems suffer from external configurations that introduce excess...Adaptive optics(AO)has significantly advanced high-resolution solar observations by mitigating atmospheric turbulence.However,traditional post-focal AO systems suffer from external configurations that introduce excessive optical surfaces,reduced light throughput,and instrumental polarization.To address these limitations,we propose an embedded solar adaptive optics telescope(ESAOT)that intrinsically incorporates the solar AO(SAO)subsystem within the telescope's optical train,featuring a co-designed correction chain with a single Hartmann-Shack full-wavefront sensor(HS f-WFS)and a deformable secondary mirror(DSM).The HS f-WFS uses temporal-spatial hybrid sampling technique to simultane-ously resolve tip-tilt and high-order aberrations,while the DSM performs real-time compensation through adaptive modal optimization.This unified architecture achieves symmetrical polarization suppression and high system throughput by min-imizing optical surfaces.A 600 mm ESAOT prototype incorporating a 12×12 micro-lens array HS f-WFS and 61-actuator piezoelectric DSM has been developed and successfully conducted on-sky photospheric observations.Validations in-cluding turbulence simulations,optical bench testing,and practical observations at the Lijiang observatory collectively confirm the system's capability to maintain aboutλ/10 wavefront error during active region tracking.This architectural breakthrough of the ESAOT addresses long-standing SAO integration challenges in solar astronomy and provides scala-bility analyses confirming direct applicability to the existing and future large solar observation facilities.展开更多
Recent advancements in autonomous vehicle technologies are transforming intelligent transportation systems.Artificial intelligence enables real-time sensing,decision-making,and control on embedded platforms with impro...Recent advancements in autonomous vehicle technologies are transforming intelligent transportation systems.Artificial intelligence enables real-time sensing,decision-making,and control on embedded platforms with improved efficiency.This study presents the design and implementation of an autonomous radio-controlled(RC)vehicle prototype capable of lane line detection,obstacle avoidance,and navigation through dynamic path planning.The system integrates image processing and ultrasonic sensing,utilizing Raspberry Pi for vision-based tasks and ArduinoNano for real-time control.Lane line detection is achieved through conventional image processing techniques,providing the basis for local path generation,while traffic sign classification employs a You Only Look Once(YOLO)model optimized with TensorFlow Lite to support navigation decisions.Images captured by the onboard camera are processed on the Raspberry Pi to extract lane geometry and calculate steering angles,enabling the vehicle to follow the planned path.In addition,ultrasonic sensors placed in three directions at the front of the vehicle detect obstacles and allow real-time path adjustment for safe navigation.Experimental results demonstrate stable performance under controlled conditions,highlighting the system’s potential for scalable autonomous driving applications.This work confirms that deep learning methods can be efficiently deployed on low-power embedded systems,offering a practical framework for navigation,path planning,and intelligent transportation research.展开更多
Battery safety has emerged as a critical challenge for achieving carbon neutrality,driven by the increasing frequency of thermal runaway incidents in electric vehicles(EVs)and stationary energy storage systems(ESSs).C...Battery safety has emerged as a critical challenge for achieving carbon neutrality,driven by the increasing frequency of thermal runaway incidents in electric vehicles(EVs)and stationary energy storage systems(ESSs).Conventional battery monitoring technologies struggle to track multiple physicochemical parameters in real time,hindering early hazard detection.Embedded optical fiber sensors have gained prominence as a transformative solution for next-generation smart battery sensing,owing to their micrometer size,multiplexing capability,and electromagnetic immunity.However,comprehensive reviews focusing on their advancements in operando multi-parameter monitoring remain scarce,despite their critical importance for ensuring battery safety.To address this gap,this review first introduces a classification and the fundamental principles of advanced battery-oriented optical fiber sensors.Subsequently,it summarizes recent developments in single-parameter battery monitoring using optical fiber sensors.Building on this foundation,this review presents the first comprehensive analysis of multifunctional optical fiber sensing platforms capable of simultaneously tracking temperature,strain,pressure,refractive index,and monitoring battery aging.Targeted strategies are proposed to facilitate the practical development of this technology,including optimization of sensor integration techniques,minimizing sensor invasiveness,resolving the cross-sensitivity of fiber Bragg grating(FBG)through structural innovation,enhancing techno-economics,and combining with artificial intelligence(AI).By aligning academic research with industry requirements,this review provides a methodological roadmap for developing robust optical sensing systems to ensure battery safety in decarbonization-driven applications.展开更多
Neural organoids and confocal microscopy have the potential to play an important role in microconnectome research to understand neural patterns.We present PLayer,a plug-and-play embedded neural system,which demonstrat...Neural organoids and confocal microscopy have the potential to play an important role in microconnectome research to understand neural patterns.We present PLayer,a plug-and-play embedded neural system,which demonstrates the utilization of sparse confocal microscopy layers to interpolate continuous axial resolution.With an embedded system focused on neural network pruning,image scaling,and post-processing,PLayer achieves high-performance metrics with an average structural similarity index of 0.9217 and a peak signal-to-noise ratio of 27.75 dB,all within 20 s.This represents a significant time saving of 85.71%with simplified image processing.By harnessing statistical map estimation in interpolation and incorporating the Vision Transformer–based Restorer,PLayer ensures 2D layer consistency while mitigating heavy computational dependence.As such,PLayer can reconstruct 3D neural organoid confocal data continuously under limited computational power for the wide acceptance of fundamental connectomics and pattern-related research with embedded devices.展开更多
Edge defects significantly impact the forming quality of Mg/Al composite plates during the rolling process.This study aims to develop an effective rolling technique to suppress these defects.First,an enhanced Lemaitre...Edge defects significantly impact the forming quality of Mg/Al composite plates during the rolling process.This study aims to develop an effective rolling technique to suppress these defects.First,an enhanced Lemaitre damage model with a generalized stress state damage prediction mechanism was used to evaluate the key mechanical factors contributing to defect formation.Based on this evaluation,an embedded composite rolling technique was proposed.Subsequently,comparative validation was conducted at 350℃ with a 50% reduction ratio.Results showed that the plates rolled using the embedded composite rolling technique had smooth surfaces and edges,with no macroscopic cracks observed.Numerical simulation indicated that,compared to conventional processes,the proposed technique reduced the maximum edge stress triaxiality of the plates from-0.02 to-1.56,significantly enhancing the triaxial compressive stress effect at the edges,which suppressed void nucleation and growth,leading to a 96%reduction in damage values.Mechanical property evaluations demonstrated that,compared to the conventional rolling process,the proposed technique improved edge bonding strength and tensile strength by approximately 67.7%and 118%,respectively.Further microstructural characterization revealed that the proposed technique,influenced by the restriction of deformation along the transverse direction(TD),weakened the plastic flow in the TD and enhanced plastic flow along the rolling direction(RD),resulting in higher grain boundary density and stronger basal texture.This,in turn,improved the toughness and transverse homogeneity of the plates.In summary,the embedded composite rolling technique provides crucial technical guidance for the preparation of Mg-based composite plates.展开更多
In this study,a new linear friction welding(LFW)process,embedded LFW process,was put forward,which was mainly applied to combination manufacturing of long or overlong loadcarrying titanium alloy structural components ...In this study,a new linear friction welding(LFW)process,embedded LFW process,was put forward,which was mainly applied to combination manufacturing of long or overlong loadcarrying titanium alloy structural components in aircraft.The interfacial plastic flow behavior and bonding mechanism of this process were investigated by a developed coupling EulerianLagrangian numerical model using software ABAQUS and a novel thermo-physical simulation method with designed embedded hot compression specimen.In addition,the formation mechanism and control method of welding defects caused by uneven plastic flow were discussed.The results reveal that the plastic flow along oscillating direction of this process is even and sufficient.In the direction perpendicular to oscillation,thermo-plastic metals mainly flow downward along welding interface under coupling of shear stress and interfacial pressure,resulting in the interfacial plastic zone shown as an inverted“V”shape.The upward plastic flow in this direction is relatively weak,and only a small amount of flash is extruded from top of joint.Moreover,the wedge block and welding components at top of joint are always in un-steady friction stage,leading to nonuniform temperature field distribution and un-welded defects.According to the results of numerical simulation,high oscillating frequency combined with low pressure and small amplitude is considered as appropriate parameter selection scheme to improve the upward interfacial plastic flow at top of joint and suppress the un-welded defects.The results of thermo-physical simulation illustrate that continuous dynamic recrystallization(CDRX)induces the bonding of interface,accompanying by intense dislocation movement and creation of many low-angle grain boundaries.In the interfacial bonding area,grain orientation is random with relatively low texture density(5.0 mud)owing to CDRX.展开更多
基金This study received funding from the Youth Project of Humanities and Social Sciences Research at Guizhou University(No.GDQN2022010)the Zhiyuan Science Foundation at Beijing Institute of Petrochemical Technology(No.BIPTCSF-2023012)the URT Program for Undergraduate Research and Training at Beijing Institute of Petrochemical Technology(No.2024J00263).
文摘This study explored the role of job crafting and job embeddedness in the relationship between employee strengths use and thriving at work.Participants were 260 nurses from Beijing,China(99.2%female,54.6%aged 26–35 years,and 62%with a bachelor’s degree or above).Data were collected at two different time points,with a two-week interval between them.Regression analysis and path analysis were applied to test the hypotheses.Results showed that strengths use was associated with thriving at work.Job crafting partially mediated this relationship for higher thriving at work.Job embeddedness weakened the relationship between strengths use and job crafting,and also lowered job crafting effects on work thriving.These findings provide insights into the mechanisms by which strengths use influences thriving at work,highlighting the significance of job crafting and job embeddedness.
基金supported by the National Natural Science Foundation of China(Nos.52305314 and U21A20394)the Beijing Natural Science Foundation(Nos.7252285 and L246001)the National Key Research and Development Program of China(No.2023YFB4605800)。
文摘Embedded printing is a highly promising approach for creating complex structures within a yield-stress support bath.However,the accurate prediction and control of printability remain fundamental challenges due to the complex interactions between inks and support baths.Here,we present an artificial intelligence(AI)-driven framework that interprets and predicts embedded printability using rheological data.Using a standardized workflow,we extracted 21 rheological descriptors and established 12 indicators to evaluate structural continuity and geometric fidelity.Interpretable machine learning models revealed that direction-dependent defects are governed by the synergistic interplay among ink yield stress,support bath zero shear viscosity,flow behavior index,and time constant.To enable the prediction of printability in a generalizable manner,we further developed a cascaded neural network,which achieved mean relative prediction errors below 15%across all indicators.Experimental validation using three-dimensional(3 D)-printed constructs and micro-computed tomography(μCT)reconstructions confirmed a strong correlation between predicted and actual fidelity.This work establishes a physics-informed,data-driven paradigm for decoding and optimizing embedded printing,offering broad applicability and providing a robust tool for the rapid pairing of suitable printable ink-support bath combinations.
文摘Unmanned aerial vehicles(UAVs),especially quadcopters,have become indispensable in numerous industrial and scientific applications due to their flexibility,lowcost,and capability to operate in dynamic environments.This paper presents a complete design and implementation of a compact autonomous quadcopter capable of trajectory tracking,object detection,precision landing,and real-time telemetry via long-range communication protocols.The system integrates an onboard flight controller running real-time sensor fusion algorithms,a vision-based detection system on a companion single-board computer,and a telemetry unit using Long Range(LoRa)communication.Extensive flight tests were conducted to validate the system’s stability,communication range,and autonomous capabilities.Potential applications in law enforcement,agriculture,search and rescue,and environmental monitoring are also discussed.
文摘To address the challenges of complexity,power consumption,and cost constraints in traditional display driver integrated circuits(DDICs)caused by external NOR Flash and SRAM,this work proposes an embedded resistive random-access memory(RRAM)integration solution based on a 40 nm high-voltage CMOS logic platform.Targeting the yield fluctuations and stability challenges during RRAM mass production,systematic process optimizations are implemented to achieve synergistic improvements in RRAM performance and yield.Through modifications to the film sputtering and pre-deposition treatment,the withinwafer resistance uniformity(RSU)of the oxygen-deficient layer(ODL)thin film is improved from 11%to 8%,while inter-wafer process stability variation reduces from 23%to below 6%.Consequently,the yield of 8 Mb RRAM embedded mass production products increases from 87%to 98.5%.In terms of device performance,the RRAM demonstrates a fast 4.8 ns read speed,exceptional read disturb immunity of 3×10^(8) cycles at 95℃,10^(3) write/erase endurance cycles for the 1 Mb cells,and data retention of 12.5 years at 125℃.Post high-temperature operating life(HTOL)testing exhibits stable high/low resistance window.This study provides process optimization strategies and a reliability assurance framework for the mass production of highly integrated,low-power embedded RRAM display driver IC.
基金supported by the key technology project of China Southern Power Grid Corporation(GZKJXM20220041)partly by the National Key Research and Development Plan(2022YFE0205300).
文摘This paper presents an optimal operation method for embedded DC interconnections based on low-voltage AC/DC distribution areas(EDC-LVDA)under three-phase unbalanced compensation conditions.It can optimally determine the transmission power of the DC and AC paths to simultaneously improve voltage quality and reduce losses.First,considering the embedded interconnected,unbalanced power structure of the distribution area,a power flow calculation method for EDC-LVDA that accounts for three-phase unbalanced compensation is introduced.This method accurately describes the power flow distribution characteristics under both AC and DC power allocation scenarios.Second,an optimization scheduling model for EDC-LVDA under three-phase unbalanced conditions is developed,incorporating network losses,voltage quality,DC link losses,and unbalance levels.The proposed model employs an improved particle swarm optimization(IPSO)two-layer algorithm to autonomously select different power allocation coefficients for the DC link and AC section under various operating conditions.This enables embedded economic optimization scheduling while maintaining compensation for unbalanced conditions.Finally,a case study based on the IEEE 13-node system for EDC-LVDA is conducted and tested.The results show that the proposed optimal operation method achieves a 100%voltage compliance rate and reduces network losses by 13.8%,while ensuring three-phase power balance compensation.This provides a practical solution for the modernization and upgrading of low-voltage power grids.
基金supported by the National Natural Science Foundation of China(Grant No.62172292).
文摘Anomaly detection is a vibrant research direction in controller area networks,which provides the fundamental real-time data transmission underpinning in-vehicle data interaction for the internet of vehicles.However,existing unsupervised learning methods suffer from insufficient temporal and spatial constraints on shallow features,resulting in fragmented feature representations that compromise model stability and accuracy.To improve the extraction of valuable features,this paper investigates the influence of clustering constraints on shallow feature convergence paths at the model level and further proposes an end-to-end intrusion detection system based on efficient deep embedded subspace clustering(EDESC-IDS).Following the standard learning approach,continuous messages are encoded into two-dimensional data frames via a frame builder,which are then input into an extended convolutional autoencoder for extracting shallow features from high-dimensional data.On this basis,the dual constraints of these output features and the embedding clustering module facilitate end-to-end training of the EDESC-IDS in various attack scenarios.Extensive experimental results show that such a system exhibits significant detection performance on four types of attack datasets,including DoS,Gear,Fuzzy,and RPM,with precision,recall,and F1 scores consistently above 97.79%,while maintaining a false negative rate(FNR)and an error rate(ER)below 2.22%.
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.
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.
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support from the National Science Foundation of China(NSFC)(Grants No.12293031 and No.61905252)the National Science Foundation for Distinguished Young Scholars(Grant No.12022308)the National Key R&D Program of China(Grants No.2021YFC2202200 and No.2021YFC2202204).
文摘Adaptive optics(AO)has significantly advanced high-resolution solar observations by mitigating atmospheric turbulence.However,traditional post-focal AO systems suffer from external configurations that introduce excessive optical surfaces,reduced light throughput,and instrumental polarization.To address these limitations,we propose an embedded solar adaptive optics telescope(ESAOT)that intrinsically incorporates the solar AO(SAO)subsystem within the telescope's optical train,featuring a co-designed correction chain with a single Hartmann-Shack full-wavefront sensor(HS f-WFS)and a deformable secondary mirror(DSM).The HS f-WFS uses temporal-spatial hybrid sampling technique to simultane-ously resolve tip-tilt and high-order aberrations,while the DSM performs real-time compensation through adaptive modal optimization.This unified architecture achieves symmetrical polarization suppression and high system throughput by min-imizing optical surfaces.A 600 mm ESAOT prototype incorporating a 12×12 micro-lens array HS f-WFS and 61-actuator piezoelectric DSM has been developed and successfully conducted on-sky photospheric observations.Validations in-cluding turbulence simulations,optical bench testing,and practical observations at the Lijiang observatory collectively confirm the system's capability to maintain aboutλ/10 wavefront error during active region tracking.This architectural breakthrough of the ESAOT addresses long-standing SAO integration challenges in solar astronomy and provides scala-bility analyses confirming direct applicability to the existing and future large solar observation facilities.
文摘Recent advancements in autonomous vehicle technologies are transforming intelligent transportation systems.Artificial intelligence enables real-time sensing,decision-making,and control on embedded platforms with improved efficiency.This study presents the design and implementation of an autonomous radio-controlled(RC)vehicle prototype capable of lane line detection,obstacle avoidance,and navigation through dynamic path planning.The system integrates image processing and ultrasonic sensing,utilizing Raspberry Pi for vision-based tasks and ArduinoNano for real-time control.Lane line detection is achieved through conventional image processing techniques,providing the basis for local path generation,while traffic sign classification employs a You Only Look Once(YOLO)model optimized with TensorFlow Lite to support navigation decisions.Images captured by the onboard camera are processed on the Raspberry Pi to extract lane geometry and calculate steering angles,enabling the vehicle to follow the planned path.In addition,ultrasonic sensors placed in three directions at the front of the vehicle detect obstacles and allow real-time path adjustment for safe navigation.Experimental results demonstrate stable performance under controlled conditions,highlighting the system’s potential for scalable autonomous driving applications.This work confirms that deep learning methods can be efficiently deployed on low-power embedded systems,offering a practical framework for navigation,path planning,and intelligent transportation research.
基金the financial supports of the National Natural Science Foundation of China(No.52372200)a project supported by the State Key Laboratory of Mechanics and Control for Aerospace Structures(No.MCAS-S-0324G01)。
文摘Battery safety has emerged as a critical challenge for achieving carbon neutrality,driven by the increasing frequency of thermal runaway incidents in electric vehicles(EVs)and stationary energy storage systems(ESSs).Conventional battery monitoring technologies struggle to track multiple physicochemical parameters in real time,hindering early hazard detection.Embedded optical fiber sensors have gained prominence as a transformative solution for next-generation smart battery sensing,owing to their micrometer size,multiplexing capability,and electromagnetic immunity.However,comprehensive reviews focusing on their advancements in operando multi-parameter monitoring remain scarce,despite their critical importance for ensuring battery safety.To address this gap,this review first introduces a classification and the fundamental principles of advanced battery-oriented optical fiber sensors.Subsequently,it summarizes recent developments in single-parameter battery monitoring using optical fiber sensors.Building on this foundation,this review presents the first comprehensive analysis of multifunctional optical fiber sensing platforms capable of simultaneously tracking temperature,strain,pressure,refractive index,and monitoring battery aging.Targeted strategies are proposed to facilitate the practical development of this technology,including optimization of sensor integration techniques,minimizing sensor invasiveness,resolving the cross-sensitivity of fiber Bragg grating(FBG)through structural innovation,enhancing techno-economics,and combining with artificial intelligence(AI).By aligning academic research with industry requirements,this review provides a methodological roadmap for developing robust optical sensing systems to ensure battery safety in decarbonization-driven applications.
基金supported by the National Key R&D Program of China(Grant No.2021YFA1001000)the National Natural Science Foundation of China(Grant Nos.82111530212,U23A20282,and 61971255)+2 种基金the Natural Science Founda-tion of Guangdong Province(Grant No.2021B1515020092)the Shenzhen Bay Laboratory Fund(Grant No.SZBL2020090501014)the Shenzhen Science,Technology and Innovation Commission(Grant Nos.KJZD20231023094659002,JCYJ20220530142809022,and WDZC20220811170401001).
文摘Neural organoids and confocal microscopy have the potential to play an important role in microconnectome research to understand neural patterns.We present PLayer,a plug-and-play embedded neural system,which demonstrates the utilization of sparse confocal microscopy layers to interpolate continuous axial resolution.With an embedded system focused on neural network pruning,image scaling,and post-processing,PLayer achieves high-performance metrics with an average structural similarity index of 0.9217 and a peak signal-to-noise ratio of 27.75 dB,all within 20 s.This represents a significant time saving of 85.71%with simplified image processing.By harnessing statistical map estimation in interpolation and incorporating the Vision Transformer–based Restorer,PLayer ensures 2D layer consistency while mitigating heavy computational dependence.As such,PLayer can reconstruct 3D neural organoid confocal data continuously under limited computational power for the wide acceptance of fundamental connectomics and pattern-related research with embedded devices.
基金supported by National Key Research and Development Program(2018YFA0707300)Major Program of National Natural Science Foundation of China(U22A20188).
文摘Edge defects significantly impact the forming quality of Mg/Al composite plates during the rolling process.This study aims to develop an effective rolling technique to suppress these defects.First,an enhanced Lemaitre damage model with a generalized stress state damage prediction mechanism was used to evaluate the key mechanical factors contributing to defect formation.Based on this evaluation,an embedded composite rolling technique was proposed.Subsequently,comparative validation was conducted at 350℃ with a 50% reduction ratio.Results showed that the plates rolled using the embedded composite rolling technique had smooth surfaces and edges,with no macroscopic cracks observed.Numerical simulation indicated that,compared to conventional processes,the proposed technique reduced the maximum edge stress triaxiality of the plates from-0.02 to-1.56,significantly enhancing the triaxial compressive stress effect at the edges,which suppressed void nucleation and growth,leading to a 96%reduction in damage values.Mechanical property evaluations demonstrated that,compared to the conventional rolling process,the proposed technique improved edge bonding strength and tensile strength by approximately 67.7%and 118%,respectively.Further microstructural characterization revealed that the proposed technique,influenced by the restriction of deformation along the transverse direction(TD),weakened the plastic flow in the TD and enhanced plastic flow along the rolling direction(RD),resulting in higher grain boundary density and stronger basal texture.This,in turn,improved the toughness and transverse homogeneity of the plates.In summary,the embedded composite rolling technique provides crucial technical guidance for the preparation of Mg-based composite plates.
基金co-supported by the National Natural Science Foundation of China(Nos.52105411,52105400and 52305420)the China Postdoctoral Science Foundation(No.2023M742830)Innovation Foundation for Doctor Dissertation of Northwestern Polytechnical University(No.CX2023008).
文摘In this study,a new linear friction welding(LFW)process,embedded LFW process,was put forward,which was mainly applied to combination manufacturing of long or overlong loadcarrying titanium alloy structural components in aircraft.The interfacial plastic flow behavior and bonding mechanism of this process were investigated by a developed coupling EulerianLagrangian numerical model using software ABAQUS and a novel thermo-physical simulation method with designed embedded hot compression specimen.In addition,the formation mechanism and control method of welding defects caused by uneven plastic flow were discussed.The results reveal that the plastic flow along oscillating direction of this process is even and sufficient.In the direction perpendicular to oscillation,thermo-plastic metals mainly flow downward along welding interface under coupling of shear stress and interfacial pressure,resulting in the interfacial plastic zone shown as an inverted“V”shape.The upward plastic flow in this direction is relatively weak,and only a small amount of flash is extruded from top of joint.Moreover,the wedge block and welding components at top of joint are always in un-steady friction stage,leading to nonuniform temperature field distribution and un-welded defects.According to the results of numerical simulation,high oscillating frequency combined with low pressure and small amplitude is considered as appropriate parameter selection scheme to improve the upward interfacial plastic flow at top of joint and suppress the un-welded defects.The results of thermo-physical simulation illustrate that continuous dynamic recrystallization(CDRX)induces the bonding of interface,accompanying by intense dislocation movement and creation of many low-angle grain boundaries.In the interfacial bonding area,grain orientation is random with relatively low texture density(5.0 mud)owing to CDRX.
