In this paper, we present an ultrafast digitizer utilizing the DRS4 switched capacitor array applicationspecific integrated circuit to achieve an ultrafast sampling speed of at most 5 GS/s. We cascaded all eight chann...In this paper, we present an ultrafast digitizer utilizing the DRS4 switched capacitor array applicationspecific integrated circuit to achieve an ultrafast sampling speed of at most 5 GS/s. We cascaded all eight channels(sub-channels) of a single DRS4 chip for increased storage depth. The digitizer contains four DRS4 chips, a quadchannel analog-to-digital converter,a controlling fieldprogrammable gate array, a PXI interface, and an SFP+connector. Consequently, each DRS4 channel has a depth of 8192 points and a vertical resolution of 14 bits. The readout sequences should be broken into several segments and then reordered to obtain the correct sequential data sets, and this offline procedure varies in different readout modes. This paper describes the design and implementation of the hardware;in particular, the respective processing procedures are described in detail. Furthermore, the offset error is calibrated and corrected to improve the precision of the captured waveform in both single-channel and highresolution modes.展开更多
The photoneutron source （PNS, phase 1）, an electron linear accelerator （linac）-based pulsed neutron facility that uses the time-of-flight （TOF） technique, was constructed for the acquisition of nuclear data from...The photoneutron source （PNS, phase 1）, an electron linear accelerator （linac）-based pulsed neutron facility that uses the time-of-flight （TOF） technique, was constructed for the acquisition of nuclear data from the Thorium Molten Salt Reactor （TMSR） at the Shanghai Institute of Applied Physics （SINAP）. The neutron detector signal used for TOF calculation, with information on the pulse arrival time, pulse shape, and pulse height, was recorded by using a waveform digitizer （WFD）. By using the pulse height and pulse-shape discrimination （PSD） analysis to identify neutrons and ＂y-rays, the neutron TOF spectrum was obtained by employing a simple electronic design, and a new WFD-based DAQ system was developed and tested in this commissioning experiment. The DAQ system developed is characterized by a very high efficiency with respect to millisecond neutron TOF spectroscopy.展开更多
RENEWING THE FORBIDDEN CITY’S CENTURY-OLD LEGACY.Oriental Outlook.27 November 2025.At sunrise,the Forbidden City glows under a veil of gold;at night,it retreats into quiet dignity.But the palace never really sleeps.A...RENEWING THE FORBIDDEN CITY’S CENTURY-OLD LEGACY.Oriental Outlook.27 November 2025.At sunrise,the Forbidden City glows under a veil of gold;at night,it retreats into quiet dignity.But the palace never really sleeps.As visitors depart,the“digital relic vault”awakens online,where porcelain,calligraphy,jade and timepieces reveal their beauty in virtual form.History continues to breathe in the data stream.展开更多
A New Chapter of the Century-Old Palace Museum Oriental Outlook Issue 24,2025 The Palace Museum,the imperial palace of the Ming and Qing dynasties(1368-1911),opened to the public in 1925.Rather than a group of static ...A New Chapter of the Century-Old Palace Museum Oriental Outlook Issue 24,2025 The Palace Museum,the imperial palace of the Ming and Qing dynasties(1368-1911),opened to the public in 1925.Rather than a group of static ancient buildings,it stands today as a dynamic cultural organism filled with invaluable collections of cultural relics preserved by generations of artisans and now displayed to the world through digital technology in long-lasting exhibitions.展开更多
Artificial intelligence(AI)is increasingly recognized as a transformative force in the field of solid organ transplantation.From enhancing donor-recipient matching to predicting clinical risks and tailoring immunosupp...Artificial intelligence(AI)is increasingly recognized as a transformative force in the field of solid organ transplantation.From enhancing donor-recipient matching to predicting clinical risks and tailoring immunosuppressive therapy,AI has the potential to improve both operational efficiency and patient outcomes.Despite these advancements,the perspectives of transplant professionals-those at the forefront of critical decision-making-remain insufficiently explored.To address this gap,this study utilizes a multi-round electronic Delphi approach to gather and analyses insights from global experts involved in organ transplantation.Participants are invited to complete structured surveys capturing demographic data,professional roles,institutional practices,and prior exposure to AI technologies.The survey also explores perceptions of AI’s potential benefits.Quantitative responses are analyzed using descriptive statistics,while open-ended qualitative responses undergo thematic analysis.Preliminary findings indicate a generally positive outlook on AI’s role in enhancing transplantation processes,particularly in areas such as donor matching and post-operative care.These mixed views reflect both optimism and caution among professionals tasked with integrating new technologies into high-stakes clinical workflows.By capturing a wide range of expert opinions,the findings will inform future policy development,regulatory considerations,and institutional readiness frameworks for the integration of AI into organ transplantation.展开更多
Healthy behavior has long been linked to mental health outcomes.However,the role of artificial intelligence(AI)literacy in shaping healthy behaviors and its potential impact on mental health remains underexplored.This...Healthy behavior has long been linked to mental health outcomes.However,the role of artificial intelligence(AI)literacy in shaping healthy behaviors and its potential impact on mental health remains underexplored.This paper presents a scoping review offering a novel perspective on the intersection of healthy behaviors,mental health,and AI literacy.By examining how individuals’understanding of AI influences their choices regarding nutrition and their susceptibility to mental health issues,the current study explores emerging trends in health behavior decision-making.This emphasizes the need for integrating AI literacy into mental health and health behaviors education,as well as the development of AI-driven tools to support healthier behavior choices.It highlights that individuals with low AI literacy may misinterpret or overly depend on AI guidance,resulting in maladaptive health choices,while those with high AI literacy may be more likely to engage reflectively and sustain positive behaviors.The paper outlines the importance of inclusive education,user-centered design,and community-based support systems to enhance AI literacy for digitally marginalized groups.AI literacy may be positioned as a key determinant of health equity,better allowing for interdisciplinary strategies that empower individuals to make informed,autonomous decisions that promote both physical and mental health.展开更多
The increasing global prevalence of mild cognitive impairment(MCI)necessitates a paradigm shift in early detection strategies.Conventional neuropsychological assessment methods,predominantly paper-and-pencil tests suc...The increasing global prevalence of mild cognitive impairment(MCI)necessitates a paradigm shift in early detection strategies.Conventional neuropsychological assessment methods,predominantly paper-and-pencil tests such as the Mini-Mental State Examination and the Montreal Cognitive Assessment,exhibit inherent limitations with respect to accessibility,administration burden,and sensitivity to subtle cognitive decline,particularly among diverse populations.This commentary critically examines a recent study that champions a novel approach:The integration of gait and handwriting kinematic parameters analyzed via machine learning for MCI screening.The present study positions itself within the broader landscape of MCI detection,with a view to comparing its advantages against established neuropsychological batteries,advanced neuroimaging(e.g.,positron emission tomography,magnetic resonance imaging),and emerging fluid biomarkers(e.g.,cerebrospinal fluid,blood-based assays).While the study demonstrates promising accuracy(74.44%area under the curve 0.74 with gait and graphic handwriting)and addresses key unmet needs in accessibility and objectivity,we highlight its cross-sectional nature,limited sample diversity,and lack of dual-task assessment as areas for future refinement.This commentary posits that kinematic biomarkers offer a distinctive,scalable,and ecologically valid approach to widespread MCI screening,thereby complementing existing methods by providing real-world functional insights.Future research should prioritize longitudinal validation,expansion to diverse cohorts,integration with multimodal data including dual-tasking,and the development of highly portable,artificial intelligence-driven solutions to achieve the democratization of early MCI detection and enable timely interventions.展开更多
Metabolic dysfunction-associated steatotic liver disease(MASLD)is an increasingly prevalent condition associated with hepatic complications and cardiovascular and renal events.Given its significant clinical impact,the...Metabolic dysfunction-associated steatotic liver disease(MASLD)is an increasingly prevalent condition associated with hepatic complications and cardiovascular and renal events.Given its significant clinical impact,the development of new strategies for early diagnosis and treatment is essential to improve patient outcomes.Over the past decade,the integration of artificial intelligence(AI)into gastroenterology has led to transformative advancements in medical practice.AI represents a major step towards personalized medicine,offering the potential to enhance diagnostic accuracy,refine prognostic assessments,and optimize treatment strategies.Its applications are rapidly expanding.This article explores the emerging role of AI in the management of MASLD,emphasizing its ability to improve clinical prediction,enhance the diagnostic performance of imaging modalities,and support histopathological confirmation.Additionally,it examines the development of AI-guided personalized treatments,where lifestyle modifications and close monitoring play a pivotal role in achieving therapeutic success.展开更多
The evolution of cities into digitally managed environments requires computational systems that can operate in real time while supporting predictive and adaptive infrastructure management.Earlier approaches have often...The evolution of cities into digitally managed environments requires computational systems that can operate in real time while supporting predictive and adaptive infrastructure management.Earlier approaches have often advanced one dimension—such as Internet of Things(IoT)-based data acquisition,Artificial Intelligence(AI)-driven analytics,or digital twin visualization—without fully integrating these strands into a single operational loop.As a result,many existing solutions encounter bottlenecks in responsiveness,interoperability,and scalability,while also leaving concerns about data privacy unresolved.This research introduces a hybrid AI–IoT–Digital Twin framework that combines continuous sensing,distributed intelligence,and simulation-based decision support.The design incorporates multi-source sensor data,lightweight edge inference through Convolutional Neural Networks(CNN)and Long ShortTerm Memory(LSTM)models,and federated learning enhanced with secure aggregation and differential privacy to maintain confidentiality.A digital twin layer extends these capabilities by simulating city assets such as traffic flows and water networks,generating what-if scenarios,and issuing actionable control signals.Complementary modules,including model compression and synchronization protocols,are embedded to ensure reliability in bandwidth-constrained and heterogeneous urban environments.The framework is validated in two urban domains:traffic management,where it adapts signal cycles based on real-time congestion patterns,and pipeline monitoring,where it anticipates leaks through pressure and vibration data.Experimental results show a 28%reduction in response time,a 35%decrease in maintenance costs,and a marked reduction in false positives relative to conventional baselines.The architecture also demonstrates stability across 50+edge devices under federated training and resilience to uneven node participation.The proposed system provides a scalable and privacy-aware foundation for predictive urban infrastructure management.By closing the loop between sensing,learning,and control,it reduces operator dependence,enhances resource efficiency,and supports transparent governance models for emerging smart cities.展开更多
Deep tight reservoirs exhibit complex stress and seepage fields due to varying pore structures,thus the seepage characteristics are significant for enhancing oil production.This study conducted triaxial compression an...Deep tight reservoirs exhibit complex stress and seepage fields due to varying pore structures,thus the seepage characteristics are significant for enhancing oil production.This study conducted triaxial compression and permeability tests to investigate the mechanical and seepage properties of tight sandstone.A digital core of tight sandstone was built using Computed Tomography(CT)scanning,which was divided into matrix and pore phases by a pore equivalent diameter threshold.A fluid-solid coupling model was established to investigate the seepage characteristics at micro-scale.The results showed that increasing the confining pressure decreased porosity,permeability,and flow velocity,with the pore phase becoming the dominant seepage channel.Cracks and large pores closed first under increasing pressure,resulted in a steep drop in permeability.However,permeability slightly decreased under high confining pressure,which followed a first-order exponential function.Flow velocity increased with seepage pressure.And the damage mainly occurred in stress-concentration regions under low seepage pressure.Seepage behavior followed linear Darcy flow,the damage emerged at seepage entrances under high pressure,which decreased rock elastic modulus and significantly increased permeability.展开更多
With the continuous advancement and maturation of technologies such as big data,artificial intelligence,virtual reality,robotics,human-machine collaboration,and augmented reality,many enterprises are finding new avenu...With the continuous advancement and maturation of technologies such as big data,artificial intelligence,virtual reality,robotics,human-machine collaboration,and augmented reality,many enterprises are finding new avenues for digital transformation and intelligent upgrading.Industry 5.0,a further extension and development of Industry 4.0,has become an important development trend in industry with more emphasis on human-centered sustainability and flexibility.Accordingly,both the industrial metaverse and digital twins have attracted much attention in this new era.However,the relationship between them is not clear enough.In this paper,a comparison between digital twins and the metaverse in industry is made firstly.Then,we propose the concept and framework of Digital Twin Systems Engineering(DTSE)to demonstrate how digital twins support the industrial metaverse in the era of Industry 5.0 by integrating systems engineering principles.Furthermore,we discuss the key technologies and challenges of DTSE,in particular how artificial intelligence enhances the application of DTSE.Finally,a specific application scenario in the aviation field is presented to illustrate the application prospects of DTSE.展开更多
In the wave of digital and intelligent applications,artificial intelligence(AI)is transforming the development trajectories of industries across the globe.Traditional Chinese medicine(TCM),as a cultural treasure of th...In the wave of digital and intelligent applications,artificial intelligence(AI)is transforming the development trajectories of industries across the globe.Traditional Chinese medicine(TCM),as a cultural treasure of the Chinese nation,carries thousands of years of wisdom and practical experience.However,in the context of the rapid advancements in modern medicine and technology,TCM faces dual challenges:preserving its heritage while innovating.DeepSeek,a major achievement in the field of AI,offers a new opportunity for the development of TCM with its powerful technological capabilities.Exploring the integration of DeepSeek with TCM not only helps modernize the practice but also promises unique contributions to global health.展开更多
The integration of the digital economy with the traditional sales industry has prompted the robust growth of e-commerce.Live-streaming e-commerce,as a novel business model,has gained immense popularity.However,is⁃sues...The integration of the digital economy with the traditional sales industry has prompted the robust growth of e-commerce.Live-streaming e-commerce,as a novel business model,has gained immense popularity.However,is⁃sues of regulatory loopholes and inefficacy continue to surface.In live-streaming e-commerce,the head anchor,as host of the live-streaming rooms,wields significant influence in determining the goods to be showcased and marketed.Such influence expands risks such as infringement of intellectual property rights.Yet the uncertainty in law concerning the identity of head anchors results in a lack of accountability.Current norms are inadequate in constraining the group of head anchors.Drawing on the principles of risk control,the alignment between benefit and risk,and the theory of so⁃cial cost control,this paper argues that it is both justifiable and feasible to impose a duty to exercise reasonable care on head anchors.To effectively enshrine this duty in law,it is of great importance to redefine the mechanism of identifying the duty of care of head anchors in live-streaming e-commerce.In particular,the contents of the duty of care under⁃taken by head anchors and the consequences of breaching such a duty of care should be clarified.展开更多
In the context of the digital transformation of vocational education,a quality evaluation index system has been constructed.Based on a questionnaire survey conducted among higher vocational colleges and enterprises in...In the context of the digital transformation of vocational education,a quality evaluation index system has been constructed.Based on a questionnaire survey conducted among higher vocational colleges and enterprises in Hainan Province,it has been found that the quality of vocational education generally depends on the talent training program and professional construction at the macro level.At the meso level,the teacher level and teaching environment are critical,while at the micro level,the evaluation of talent training quality cannot be underestimated.Strategies for quality improvement in vocational education are proposed from the perspectives of talent training programs,major construction,teacher development,teaching environment,and talent training quality,all under the lens of digital transformation.展开更多
文摘In this paper, we present an ultrafast digitizer utilizing the DRS4 switched capacitor array applicationspecific integrated circuit to achieve an ultrafast sampling speed of at most 5 GS/s. We cascaded all eight channels(sub-channels) of a single DRS4 chip for increased storage depth. The digitizer contains four DRS4 chips, a quadchannel analog-to-digital converter,a controlling fieldprogrammable gate array, a PXI interface, and an SFP+connector. Consequently, each DRS4 channel has a depth of 8192 points and a vertical resolution of 14 bits. The readout sequences should be broken into several segments and then reordered to obtain the correct sequential data sets, and this offline procedure varies in different readout modes. This paper describes the design and implementation of the hardware;in particular, the respective processing procedures are described in detail. Furthermore, the offset error is calibrated and corrected to improve the precision of the captured waveform in both single-channel and highresolution modes.
基金Supported by Strategic Priority Research Program of the Chinese Academy of Science(TMSR)(XDA02010100)National Natural Science Foundation of China(NSFC)(11475245,No.11305239)Shanghai Key Laboratory of Particle Physics and Cosmology(11DZ2260700)
文摘The photoneutron source （PNS, phase 1）, an electron linear accelerator （linac）-based pulsed neutron facility that uses the time-of-flight （TOF） technique, was constructed for the acquisition of nuclear data from the Thorium Molten Salt Reactor （TMSR） at the Shanghai Institute of Applied Physics （SINAP）. The neutron detector signal used for TOF calculation, with information on the pulse arrival time, pulse shape, and pulse height, was recorded by using a waveform digitizer （WFD）. By using the pulse height and pulse-shape discrimination （PSD） analysis to identify neutrons and ＂y-rays, the neutron TOF spectrum was obtained by employing a simple electronic design, and a new WFD-based DAQ system was developed and tested in this commissioning experiment. The DAQ system developed is characterized by a very high efficiency with respect to millisecond neutron TOF spectroscopy.
文摘RENEWING THE FORBIDDEN CITY’S CENTURY-OLD LEGACY.Oriental Outlook.27 November 2025.At sunrise,the Forbidden City glows under a veil of gold;at night,it retreats into quiet dignity.But the palace never really sleeps.As visitors depart,the“digital relic vault”awakens online,where porcelain,calligraphy,jade and timepieces reveal their beauty in virtual form.History continues to breathe in the data stream.
文摘A New Chapter of the Century-Old Palace Museum Oriental Outlook Issue 24,2025 The Palace Museum,the imperial palace of the Ming and Qing dynasties(1368-1911),opened to the public in 1925.Rather than a group of static ancient buildings,it stands today as a dynamic cultural organism filled with invaluable collections of cultural relics preserved by generations of artisans and now displayed to the world through digital technology in long-lasting exhibitions.
文摘Artificial intelligence(AI)is increasingly recognized as a transformative force in the field of solid organ transplantation.From enhancing donor-recipient matching to predicting clinical risks and tailoring immunosuppressive therapy,AI has the potential to improve both operational efficiency and patient outcomes.Despite these advancements,the perspectives of transplant professionals-those at the forefront of critical decision-making-remain insufficiently explored.To address this gap,this study utilizes a multi-round electronic Delphi approach to gather and analyses insights from global experts involved in organ transplantation.Participants are invited to complete structured surveys capturing demographic data,professional roles,institutional practices,and prior exposure to AI technologies.The survey also explores perceptions of AI’s potential benefits.Quantitative responses are analyzed using descriptive statistics,while open-ended qualitative responses undergo thematic analysis.Preliminary findings indicate a generally positive outlook on AI’s role in enhancing transplantation processes,particularly in areas such as donor matching and post-operative care.These mixed views reflect both optimism and caution among professionals tasked with integrating new technologies into high-stakes clinical workflows.By capturing a wide range of expert opinions,the findings will inform future policy development,regulatory considerations,and institutional readiness frameworks for the integration of AI into organ transplantation.
文摘Healthy behavior has long been linked to mental health outcomes.However,the role of artificial intelligence(AI)literacy in shaping healthy behaviors and its potential impact on mental health remains underexplored.This paper presents a scoping review offering a novel perspective on the intersection of healthy behaviors,mental health,and AI literacy.By examining how individuals’understanding of AI influences their choices regarding nutrition and their susceptibility to mental health issues,the current study explores emerging trends in health behavior decision-making.This emphasizes the need for integrating AI literacy into mental health and health behaviors education,as well as the development of AI-driven tools to support healthier behavior choices.It highlights that individuals with low AI literacy may misinterpret or overly depend on AI guidance,resulting in maladaptive health choices,while those with high AI literacy may be more likely to engage reflectively and sustain positive behaviors.The paper outlines the importance of inclusive education,user-centered design,and community-based support systems to enhance AI literacy for digitally marginalized groups.AI literacy may be positioned as a key determinant of health equity,better allowing for interdisciplinary strategies that empower individuals to make informed,autonomous decisions that promote both physical and mental health.
文摘The increasing global prevalence of mild cognitive impairment(MCI)necessitates a paradigm shift in early detection strategies.Conventional neuropsychological assessment methods,predominantly paper-and-pencil tests such as the Mini-Mental State Examination and the Montreal Cognitive Assessment,exhibit inherent limitations with respect to accessibility,administration burden,and sensitivity to subtle cognitive decline,particularly among diverse populations.This commentary critically examines a recent study that champions a novel approach:The integration of gait and handwriting kinematic parameters analyzed via machine learning for MCI screening.The present study positions itself within the broader landscape of MCI detection,with a view to comparing its advantages against established neuropsychological batteries,advanced neuroimaging(e.g.,positron emission tomography,magnetic resonance imaging),and emerging fluid biomarkers(e.g.,cerebrospinal fluid,blood-based assays).While the study demonstrates promising accuracy(74.44%area under the curve 0.74 with gait and graphic handwriting)and addresses key unmet needs in accessibility and objectivity,we highlight its cross-sectional nature,limited sample diversity,and lack of dual-task assessment as areas for future refinement.This commentary posits that kinematic biomarkers offer a distinctive,scalable,and ecologically valid approach to widespread MCI screening,thereby complementing existing methods by providing real-world functional insights.Future research should prioritize longitudinal validation,expansion to diverse cohorts,integration with multimodal data including dual-tasking,and the development of highly portable,artificial intelligence-driven solutions to achieve the democratization of early MCI detection and enable timely interventions.
文摘Metabolic dysfunction-associated steatotic liver disease(MASLD)is an increasingly prevalent condition associated with hepatic complications and cardiovascular and renal events.Given its significant clinical impact,the development of new strategies for early diagnosis and treatment is essential to improve patient outcomes.Over the past decade,the integration of artificial intelligence(AI)into gastroenterology has led to transformative advancements in medical practice.AI represents a major step towards personalized medicine,offering the potential to enhance diagnostic accuracy,refine prognostic assessments,and optimize treatment strategies.Its applications are rapidly expanding.This article explores the emerging role of AI in the management of MASLD,emphasizing its ability to improve clinical prediction,enhance the diagnostic performance of imaging modalities,and support histopathological confirmation.Additionally,it examines the development of AI-guided personalized treatments,where lifestyle modifications and close monitoring play a pivotal role in achieving therapeutic success.
基金The researchers would like to thank the Deanship of Graduate Studies and Scientific Research at Qassim University for financial support(QU-APC-2025)。
文摘The evolution of cities into digitally managed environments requires computational systems that can operate in real time while supporting predictive and adaptive infrastructure management.Earlier approaches have often advanced one dimension—such as Internet of Things(IoT)-based data acquisition,Artificial Intelligence(AI)-driven analytics,or digital twin visualization—without fully integrating these strands into a single operational loop.As a result,many existing solutions encounter bottlenecks in responsiveness,interoperability,and scalability,while also leaving concerns about data privacy unresolved.This research introduces a hybrid AI–IoT–Digital Twin framework that combines continuous sensing,distributed intelligence,and simulation-based decision support.The design incorporates multi-source sensor data,lightweight edge inference through Convolutional Neural Networks(CNN)and Long ShortTerm Memory(LSTM)models,and federated learning enhanced with secure aggregation and differential privacy to maintain confidentiality.A digital twin layer extends these capabilities by simulating city assets such as traffic flows and water networks,generating what-if scenarios,and issuing actionable control signals.Complementary modules,including model compression and synchronization protocols,are embedded to ensure reliability in bandwidth-constrained and heterogeneous urban environments.The framework is validated in two urban domains:traffic management,where it adapts signal cycles based on real-time congestion patterns,and pipeline monitoring,where it anticipates leaks through pressure and vibration data.Experimental results show a 28%reduction in response time,a 35%decrease in maintenance costs,and a marked reduction in false positives relative to conventional baselines.The architecture also demonstrates stability across 50+edge devices under federated training and resilience to uneven node participation.The proposed system provides a scalable and privacy-aware foundation for predictive urban infrastructure management.By closing the loop between sensing,learning,and control,it reduces operator dependence,enhances resource efficiency,and supports transparent governance models for emerging smart cities.
基金financially supported by the National Natural Science Foundation of China(Nos.42272153 and 42472195)the Research Fund of PetroChina Tarim Oilfield Company(No.671023060003)the Research Fund of China National Petroleum Corporation Limited(No.2023ZZ16YJ04).
文摘Deep tight reservoirs exhibit complex stress and seepage fields due to varying pore structures,thus the seepage characteristics are significant for enhancing oil production.This study conducted triaxial compression and permeability tests to investigate the mechanical and seepage properties of tight sandstone.A digital core of tight sandstone was built using Computed Tomography(CT)scanning,which was divided into matrix and pore phases by a pore equivalent diameter threshold.A fluid-solid coupling model was established to investigate the seepage characteristics at micro-scale.The results showed that increasing the confining pressure decreased porosity,permeability,and flow velocity,with the pore phase becoming the dominant seepage channel.Cracks and large pores closed first under increasing pressure,resulted in a steep drop in permeability.However,permeability slightly decreased under high confining pressure,which followed a first-order exponential function.Flow velocity increased with seepage pressure.And the damage mainly occurred in stress-concentration regions under low seepage pressure.Seepage behavior followed linear Darcy flow,the damage emerged at seepage entrances under high pressure,which decreased rock elastic modulus and significantly increased permeability.
基金Supported by Beijing Municipal Natural Science Foundation of China(Grant No.24JL002)China Postdoctoral Science Foundation(Grant No.2024M754054)+2 种基金National Natural Science Foundation of China(Grant No.52120105008)Beijing Municipal Outstanding Young Scientis Program of Chinathe New Cornerstone Science Foundation through the XPLORER PRIZE。
文摘With the continuous advancement and maturation of technologies such as big data,artificial intelligence,virtual reality,robotics,human-machine collaboration,and augmented reality,many enterprises are finding new avenues for digital transformation and intelligent upgrading.Industry 5.0,a further extension and development of Industry 4.0,has become an important development trend in industry with more emphasis on human-centered sustainability and flexibility.Accordingly,both the industrial metaverse and digital twins have attracted much attention in this new era.However,the relationship between them is not clear enough.In this paper,a comparison between digital twins and the metaverse in industry is made firstly.Then,we propose the concept and framework of Digital Twin Systems Engineering(DTSE)to demonstrate how digital twins support the industrial metaverse in the era of Industry 5.0 by integrating systems engineering principles.Furthermore,we discuss the key technologies and challenges of DTSE,in particular how artificial intelligence enhances the application of DTSE.Finally,a specific application scenario in the aviation field is presented to illustrate the application prospects of DTSE.
文摘In the wave of digital and intelligent applications,artificial intelligence(AI)is transforming the development trajectories of industries across the globe.Traditional Chinese medicine(TCM),as a cultural treasure of the Chinese nation,carries thousands of years of wisdom and practical experience.However,in the context of the rapid advancements in modern medicine and technology,TCM faces dual challenges:preserving its heritage while innovating.DeepSeek,a major achievement in the field of AI,offers a new opportunity for the development of TCM with its powerful technological capabilities.Exploring the integration of DeepSeek with TCM not only helps modernize the practice but also promises unique contributions to global health.
文摘The integration of the digital economy with the traditional sales industry has prompted the robust growth of e-commerce.Live-streaming e-commerce,as a novel business model,has gained immense popularity.However,is⁃sues of regulatory loopholes and inefficacy continue to surface.In live-streaming e-commerce,the head anchor,as host of the live-streaming rooms,wields significant influence in determining the goods to be showcased and marketed.Such influence expands risks such as infringement of intellectual property rights.Yet the uncertainty in law concerning the identity of head anchors results in a lack of accountability.Current norms are inadequate in constraining the group of head anchors.Drawing on the principles of risk control,the alignment between benefit and risk,and the theory of so⁃cial cost control,this paper argues that it is both justifiable and feasible to impose a duty to exercise reasonable care on head anchors.To effectively enshrine this duty in law,it is of great importance to redefine the mechanism of identifying the duty of care of head anchors in live-streaming e-commerce.In particular,the contents of the duty of care under⁃taken by head anchors and the consequences of breaching such a duty of care should be clarified.
文摘In the context of the digital transformation of vocational education,a quality evaluation index system has been constructed.Based on a questionnaire survey conducted among higher vocational colleges and enterprises in Hainan Province,it has been found that the quality of vocational education generally depends on the talent training program and professional construction at the macro level.At the meso level,the teacher level and teaching environment are critical,while at the micro level,the evaluation of talent training quality cannot be underestimated.Strategies for quality improvement in vocational education are proposed from the perspectives of talent training programs,major construction,teacher development,teaching environment,and talent training quality,all under the lens of digital transformation.
